electronics & biomedical engineering

1

Syllabus S5 & S6 (Electronics & Biomedical Engineering )

Semester 5

Core Courses

Minor Courses

CourseNo. Courses Page No

Basket I (Biomedical Signal & Image Processing)

EBT381 BIOMEDICAL SIGNAL PROCESSING 42

Basket II(Biomedical Instrumentation)

EBT383 PRINCIPLES OF BIOMEDICAL IMAGING 50

Basket III (Computing in Biomedical Engineering)

EBT385 ARTIFICIAL INTELLIGENCE & MACHINE LEARNING TECHNIQUES 57

Honours Courses


Group I

EBT393 SPEECH & AUDIO SIGNAL PROCESSING 64

Group II

EBT395 ANALOG INTEGRATED CIRCUIT DESIGN 70

Group III

EBT397 MATHEMATICAL METHODS IN BIOMEDICAL ENGINEERING 77

CourseNo. Courses Page No.

EBT301 ANALYTICAL & DIAGNOSTIC EQUIPMENTS 4

EBT303 HOSPITAL ENGINEERING 12

EBT305 MEDICAL IMAGING TECHNIQUES 20

EBT307 INTRODUCTION TO BIOMEDICAL SIGNAL PROCESSING 28

EBL331 MEDICAL ELECTRONICS LAB 35

EBL333 BIOMEDICAL SIGNAL PROCESSING LAB 39

ELECTRONICS & BIOMEDICAL ENGINEERING

2

Semester 6

CourseNo. Courses Page No:

EBT302 MEDICAL IMAGE PROCESSING 87

EBT304 THERAPEUTIC EQUIPMENTS 94

EBT306 ARTIFICIAL NEURAL NETWORKS & APPLICATIONS 101

EBT308 COMPREHENSIVE COURSE WORK 108

EBL332 BIOENGINEERING LAB 114

EBD334 MINI PROJECT 117

Program Electives I


EBT312 ELECTRICAL NETWORKS & ANALYSIS 120

EBT322 MEDICAL INFORMATICS 128

EBT332 ADVANCED MICROPROCESSORS & MICROCONTROLLERS 135

EBT342 DESIGN OF BIOMEDICAL DEVICES 142

EBT352 BIOSTATISTICS 149

EBT362 BIOMEDICAL SIGNAL PROCESSING & APPLICATIONS 156

EBT372 COMMUNICATION TECHNIQUES 162

Minor Courses


Basket I (Biomedical Signal & Image Processing)

EBT382 BIOMEDICAL IMAGE PROCESSING 169

Basket II (Biomedical Instrumentation)

EBT384 THERAPEUTIC DEVICES 176

Basket III (Computing in Biomedical Engineering)

EBT386 PHYSIOLOGICAL SYSTEM MODELLING 184


3

Honours Courses

Course No. Courses Page No

Group I

EBT394 ADAPTIVE SIGNAL PROCESSING 191

Group II

EBT396 DIGITAL INTEGRATED CIRCUITS 198

Group III

EBT398 STATISTICAL METHODS IN BIOMEDICAL ENGINEERING 204


SEMESTER V


4

EBT301 ANALYTICAL &

DIAGNOSTIC EQUIPMENTS

CATEGORY L T P CREDIT

PCC 4 0 0 4

Preamble: This course describes the basic principles of different analytical and diagnostic equipment used in clinical environments.

Prerequisite: Basic knowledge about the anatomy and physiology of human body, understanding of different types of sensors and transducers used for body parameter measurement is desirable.

Course Outcomes: After the completion of the course the student will be able to

CO 1 Familiarise the instrumentation of various analytical equipment used in clinical laboratory.

CO 2 Recognize the principles and applications of biochemistry equipment used in clinical environment.

CO 3 Analyse the instrumentation of bioelectric devices.

CO 4 Analyse the impedance measurement concepts and related measurements.

CO 5 Interpret the principles related to respiratory, blood flow and audiometric measurements.

Mapping of course outcomes with program outcomes

PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12

CO 1 3 1 1 1 1 CO 2 2 2 1 1 1 CO 3 3 2 2 1 1 CO 4 3 2 2 1 1 CO 5 3 2 2 1 1

Assessment Pattern

Bloom’s Category Continuous Assessment Tests End Semester Examination

1 2

Remember 10% 10% 10% Understand 30% 30% 30% Apply 30% 30% 30% Analyse 30% 30% 30%


5

Mark distribution

Total Marks CIE ESE ESE Duration

150 50 100 3 hours

Continuous Internal Evaluation Pattern:

Attendance : 10 marks Continuous Assessment Test (2 numbers) : 25 marks Assignment/Quiz/Course project : 15 marks End Semester Examination Pattern: There will be two parts; Part A and Part B. Part A contain 10 questions with 2 questions from each module, having 3 marks for each question. Students should answer all questions. Part B contains 2 questions from each module of which student should answer any one. Each question can have maximum 2 sub-divisions and carry 14 marks.

Course Outcome 1 (CO1): Familiarise the instrumentation of various analytical equipment used in clinical laboratory.

1. With respect to visible Spectrophotometers, describe single beam photometers. 2. Explain the concept of solid-state ISE electrolyte analyser. 3. With the help of a block diagram explain a IR spectrophotometer.

Course Outcome 2 (CO2) Recognize the principles and applications of biochemistry equipment used in clinical environment.

1. What is the principle of electrophoresis? 2. Explain high pressure liquid chromatography. 3. Describe the concept of ELISA test. What are its applications.

Course Outcome 3(CO3): Analyse the instrumentation of bioelectric devices,

1. With the help of a block diagram analyse the instrumentation of a single channel ECG machine

2. What is polysomnography. What are the different types of sleep disorders? 3. Explain the instrumentation of an ambulatory recorder.

Course Outcome 4 (CO4): Analyse the impedance measurement concepts and related measurements.

1. Draw bipolar and tetra polar circuits for impedance based respiratory measurements. 2. Analyse different types of cardiac output measurement methods? 3. What are apnoea monitors?


6

Course Outcome 5 (CO5): Interpret the principles related to respiratory, blood flow and audiometric measurement.

1. What are impedance audiometers? 2. With the help of a schematic diagram explain the principle of Coulter counter 3. What are the different types of sensors used in wearable health monitors?

Model Question paper

SET 1 Total Pages:

Reg No.:_______________ Name:__________________________

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY FIFTH SEMESTER B. TECH DEGREE EXAMINATION, DECEMBER 2022

Course Code: EBT301

Course Name: ANALYTICAL & DIAGNOSTIC EQUIPMENTS

Max. Marks: 100 Duration: 3 Hours

PART A

Answer all questions (3 marks). Marks

1 State Beer Lambert’s Law. (3)

2 What is the basic principle of measurement of UV spectrometer? (3)

3 Compare paper electrophoresis and gel electrophoresis (3)

4 List the applications of radioimmunoassay. (3)

5 What are arrhythmias? (3)

6 What are the basic parameters monitored in central station patient monitoring systems?

(3)

7 Compare invasive and non-invasive methods of BP measurement. (3)

8 What the difference between functional and fractional oxygen saturation.

(3)

9 What are spirometers? (3)

10 State the principle of Electromagnetic Flow meters (3)

PART B

Answer any one full question, carrying 14 marks.

11 a) The linearity of the Beer-Lambert's law is limited by chemical and (7)


7

instrumental factor, what can be the causes for non-linearity.

b) Explain the instrumentation of IR spectrophotometer. (7)

OR

12 a) What are applications of electrolyte analysers? (9)

b) Explain the working of automated clinical analysers. (5)

13 a) With a block diagram explain a high-pressure liquid chromatography in detail.

(7)

b) State the principle of RIA. What are the tracers used in this RIA process?

(7)

OR

14 a) Explain the working of a flow cytometer with the help of a schematic diagram.

(7)

b) State the principle of electrophoresis. Prove that the electrophoretic mobility is proportional to charge on the molecules and inversely proportional to the radius of the molecules.

(7)

15 a) How cardiac stress testing is done. Give an account of ST analysis (7)

b) What is phonocardiograph? Discuss the microphones used in phonocardiograph.

(7)

OR

16 a) Discuss the essential components in an ECG machine with necessary diagrams.

(7)

b) With the help of a block diagram explain how EEG signals can be used for BCI applications.

(7)

17 a) Explain the doppler method used for cardiac output measurement. (7)

b) Describe the pulse oximetry measurement in detail. (7)

OR

18 a) Interpret the detection of respiratory activity using impedance technique

(7)

b) Illustrate invasive and non-invasive blood pressure measurements (7)

19 a) Explain the principle of ultrasonic blood flow meters. (6)


8

b) Define the respiratory terms i) Total Lung Capacity ii ) Forced Inspiration iii) vital capacity

(8)

OR

20 a) Explain in detail about wearable devices and its applications. (7)

b) Explain the principle of working of pure tone audiometers. (7)

Syllabus

Module 1

Introduction to medical equipment, Analytical equipment used in the clinical environment Beer-Lambert's Law, Colorimeters, Spectrophotometers: Instrumentation - Filters-Monochromators -Detectors -UV &Visible, IR Spectrophotometer – Instrumentation- Radiation Source -Monochromators & Detectors-Applications, Electrolyte Analysers-Measurement methods -Ion selective electrode method (ISE) -Solid state ISE -Ion‐Selective Optodes. (Assignment topics:Lab on a Chip (LOC) biochemical sensor,Miniaturized Systems for (Bio)Chemical analysis and synthesis- glucometer-Point of Care Test equipment (POCT))

Module 2

Biochemistry Equipment: Automated clinical analysers-Biochemistry analysers, Blood Culture Equipment, Antibody based analytical techniques-Radioimmunoassay (RIA) -Enzyme Linked Immuno Sorbent Assay (ELISA/CLIA) -Applications, Immunoprecipitation- Immunofluorescence- Polymerase Chain Reaction (PCR)- RT-PCR instrumentation, Electrophoresis- Principles ,Chromatography – Gas- high-pressure liquid and paper chromatography - principle and applications, Flow Cytometry-Applications ,Blood cell counters- Coulter Counters, Blood Gas Analysers.

Module 3

Bioelectric Devices: Electro cardiograph- Pre-amplifiers- Filters- Isolation circuits- RL driven circuit- protection circuits-Power amplifiers -Recorders, Phonocardiograph–Instrumentation, Cardiac stress testing, Patient monitoring systems -ECG-NIBP-PPG-Temperature measurements, Arrhythmia monitors, Ambulatory recorders-Holter monitors, Electroencephalography– Instrumentation, Evoked potential measurement systems-applications, Sleep Studies-Polysomnography, Sleep apnoea monitors.


9

Module 4

Impedance Techniques: Bipolar and tetrapolar circuits-detection of physiological activities using impedance techniques - respiratory activity- Impedance Cardiography- Impedance Plethysmography, Pulse Oximeter Instrumentation, Cardiac output measurement- Fick method -Dilution Methods-Doppler method, Blood pressure monitors-invasive and non-invasive methods.

Module 5

Audiometers – Pure tone - speech audiometers and impedance audiometry. Respiratory measurements: Spirometry – Basic system and applications- Pulmonary function measurements: Respiratory volumes, lung capacity -different volume measurement. Blood flowmeters - Electromagnetic – Ultrasonic Doppler blood flowmeters. Introduction to wearable health monitors. Text Books

1. Mahin Basha - Analytical Techniques in Biochemistry-Springer US_Humana (2020) 2. RüdigerKramme, Heike Kramme, Springer Handbook of Medical Technology,

Springer-Verlag Berlin Heidelberg, Year: 2011 3. Webb, Andrew G. Principles of biomedical instrumentation. Cambridge University

Press, 2018. 4. Chan, Anthony YK. Biomedical device technology: principles and design. Charles C

Thomas Publisher, 2016. 5. Khandpur R S, Handbook of Bio-Medical Instrumentation, Tata McGraw Hill, 2nd

Ed., 2003 6. Skoog A Dogulas, F. James Holler, Stanley R Crouch, Principles of Instrumental

Analysis, 6th Edition.2014. 7. Joseph D. Bronzino, The Biomedical Engineering Handbook, CRC Press, 1995

Reference Books

1. Geddes, Leslie Alexander, and Lee Edward Baker. Principles of applied biomedical instrumentation. John Wiley & Sons, 1975.

2. John G. Webster: Medical Instrumentation - Application and Design; Houghton Mifflin Co., Boston.1992

3. John G. Webster, Encyclopaedia of Medical Devices and Instrumentation, 2nd Ed., Wiley Interscience, 2006

4. Richard Aston, Principles of Biomedical Instrumentation and Measurements, Merril Publishing Co., 1990.

5. Myer Kutz, Standard Handbook of Biomedical Engineering and Design, McGraw Hill, 1993.


10

Course Contents and Lecture Schedule

No Topic No. of Lectures

1 Module 1

1.1 Introduction to medical equipment, Analytical equipment used in the clinical environment Beer-Lambert's Law-Deviation, Colorimeters-Single beam & Double beam instruments.

2

1.2 Spectrophotometers: Instrumentation - Filters-Monochromators -Detectors -UV & Visible -IR Spectrophotometer – Instrumentation- Radiation Source -Monochromators & Detectors-Applications

3

1.3 Electrolyte Analysers-Measurement methods -Ion selective electrode method(ISE) -Solid state ISE Ion‐Selective Optodes, 2

1.4 LabOn a Chip (LOC) biochemical sensor,Miniaturized Systems for (Bio)Chemical analysis and synthesis- glucometer-Point Of Care Test equipment (POCT ) (Assignment topics)

1

2 Module 2

2.1 Automated clinical analysers-Semi & Automated, Biochemistry analysers, Blood Culture Equipment 2

2.2 Antibody based analytical techniques-Radioimmunoassay (RIA) -Enzyme Linked Immuno Sorbent Assay (ELISA/CLIA)-Applications 2

2.3 Immunoprecipitation- Immunofluorescence- Polymerase Chain Reaction (PCR)- RT-PCR instrumentation 2

2.3 Electrophoresis -Different Techniques-Principles, Chromatography – Gas- high-pressure liquid and paper chromatography - principle and applications

2

2.4 Flow Cytometry-Block Diagram-Applications, Blood cell counters- Coulter Counters, Blood Gas Analyzers-Instrumentation 2

3 Module 3

3.1 Electro cardiograph- Pre-amplifiers- Filters- Isolation circuits- RL driven circuit- protection circuits-Power Amplifiers-Recorders 2

3.2 Phonocardiograph–Instrumentation, Cardiac stress testing , Patient monitoring systems -ECG-NIBP-PPG-Temperature 2

3.3 Arrhythmia monitors-Block Diagram, Ambulatory recorders-Holter monitors. 2

3.4 Electroencephalography– Instrumentation, Evoked potential measurement systems-applications 2


11

3.5 Sleep studies-Polysomnography, Sleep apnoea monitors 1

4 Module 4

4.1 Impedance Techniques: Bipolar and tetrapolar circuits-detection of physiological activities using impedance techniques - respiratory activity- Impedance Cardiography- Impedance Plethysmography

3

4.2 Pulse Oximeter Instrumentation, Cardiac output measurement- Fick method Dilution Methods-Doppler method, 2

4.3 Blood pressure monitors-invasive and non-invasive methods 2

5 Module 5

5.1 Audiometers – pure tone, speech audiometers and impedance audiometry 2

5.2 Spirometry – Basic system and applications- Pulmonary function measurements: Respiratory volumes, -different volume measurement, 2

5.3 Blood flowmeters - Electromagnetic – Ultrasonic Doppler blood flowmeters 2

5.4 Introduction to wearable health monitors. 1


12

EBT 303 HOSPITAL ENGINEERING CATEGORY L T P CREDIT

PCC 3 1 0 4

Preamble:This subject is intended for understanding the engineering systems in hospitals and the role and responsibilities of engineers, in health care sector. Helps students to understand how engineering and technology are essential and how they can be better organized for efficient healthcare delivery in hospitals.

Prerequisite: Nil


CO 1 Recognize the role of a biomedical engineer in hospitals and healthcare.

CO 2 Describe hospital electrical systems and safety standards.

CO 3 Analyse the centralized medical gas supply and sterilization systems in hospitals

CO 4 Understand the technology management systems currently used in hospitals

CO 5 Explore the role of clinical engineering in disaster preparedness and management



CO 1 3 3 2 3 2 1 2 2 2

CO 2 3 2 3 2 2 2

CO 3 3 2 3 3 1 2 2

CO 4 3 2 3 1 3 2

CO 5 3 2 3 1 2 2 2

Assessment Pattern

Bloom’s Category Continuous Assessment Tests End Semester

Examination 1 2

Remember 20% 20% 20%

Understand 40% 40% 40%

Apply 40% 40% 40%


13

Mark distribution


150 50 100 3 hours



Course Level Assessment Questions

Course Outcome 1 (CO1): Recognize the role of a biomedical engineer in hospitals and healthcare.

1. How does a biomedical engineer contribute to patient care 2. Distinguish between the functions of Biomedical engineer clinical engineer and

bioengineer. 3. How scalable architecture helps in optimization of space in hospitals?

Course Outcome 2 (CO2): Describe hospital electrical systems and safety standards.

1. What are the essential components of a substation for hospitals 2. Distinguish between micro and macro shock 3. What are the methods to measure leakage currents? Course Outcome 3(CO3): Analyse the centralized medical gas supply and sterilization

systems in hospitals

1. Explain the working of an autoclave 2. Give a method of chemical sterilization 3. Explain the methods for disinfection in hospitals Course Outcome 4 (CO4): Understand technology management systems currently

used in hospitals 1. Explain how RFID tracking can be used for asset tracking 2. What are the steps involved in procurement of a medical equipment? 3. What is the advantage of PACS in hospitals?


14

Course Outcome 5 (CO5): Explore the role of clinical engineering in disaster preparedness and management

1. List the technological recommendations for disaster management 2. How does ITIL frame work is useful in disaster management? 3. What is the role of a clinical engineer in disaster preparedness and management?


Reg No.:_______________ Name:__________________________

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY FIFTH SEMESTER B. TECH DEGREE EXAMINATION, ____________ 20__

Course Code: EBT 303 Course Name: Hospital Engineering


PART A Answer any all questions. Each carry 3 marks. Marks

1 How a scientist in Bioengineering can contribute to patient care? (3)

2 Distinguish between micro and macro shock (3)

3 Why doesn’t a patient get shock from ESU currents? (3)

4 Identify two methods which helped to meet and master the challenges

raised by the covid-19 pandemic (3)

5 Identify any two steps a biomedical engineer in a hospital can take to

face the unexpected flood occurred in the locality (3)

6 Which are the commonly used gases in hospitals? (3)

7 Explain a method for real time localisation of assets in hospitals (3)

8 Explain the significance of preventive maintenance programs in hospitals?

(3)

9 What is the purpose of bus bars used in substations? (3)

10 What is the advantage of integrating RIS and HIS? (3)

PART B

Answer any one full question from each module. Each carry 14 marks.

MODULE 1

11 a) Explain how a Biomedical Engineer and a bioengineer can

contribute to patient care (7)

b) Explain the concept of smart hospitals (7)


15

OR

12

a) Explain the main aspects to be emphasized while planning a

(i) Radiology department

(ii) ICU

(8)

b) What are the architectural features of a smart hospital? (6)

MODULE 2

13

a) What is the principle of working of an EMI filter (8)

b) Briefly explain any three radiation protection methods (6)

OR

14 a) Explain the main subunits of a substation (9)

b) What are the essential components of a UPS? (5)

MODULE 3

15

a) Explain the working of a steam sterilization unit? (6)

b) Explain a centralised gas supply system for the distribution for i) Oxygen ii) Vacuum iii) Nitrous oxide

(9)

OR

16 a) What are disinfection methods employed in hospital ICUs (7)

b) With a block diagram explain a EO sterilization unit (7)

MODULE 4

17 a) Briefly explain the procurement procedure for a medical

equipment

(8)

b) Explain the need for preventive maintenance in hospitals (6)

OR

18 a) What are the essential components of a PACS in a University

hospital?

(6)

b) Explain how RFID tracking of assets can be useful in hospitals (8)

MODULE 5

19 a) Briefly enumerate the technological and organizational

recommendations that help clinical engineers to use their expertise for disaster preparedness and management

(14)

OR


16

20

a) What do you mean by ITIL frame work? How it is necessary in disaster management?

(7)

b) What do you mean by dual use infrastructure? How is it useful in disaster management

(7)

Syllabus Module 1

Role of Engineering in healthcare sector: Definition: Bio-Engineering, Biomedical Engineering, Clinical engineering & Hospital engineering. Role & responsibilities. Concept of smart hospital- Increasing staff productivity-optimizing cost efficiencies- Improving patient outcomes- Integrated building management platform- Architecture- Regulations- Planning and design of various departments. (Radiology Dept, Nuclear Medicine, ICU, Central Sterilization and Operation theatres) – Smart hospitals -case study

Module 2

Power systems in Hospitals: Electrical power systems in hospitals –Design of sub stations- Stabilized and uninterrupted power supply systems. Protective systems: Over voltage and over current protectors, circuit breakers, Surge protectors, EMI filters. Introduction to hospital electrical safety andits ISO standards- Safety measures & standards for radiation rooms-planning & installation. Patient safety – electrical shocks and hazards – micro and macro shocks – effects of electrical current on human body – leakage currents – types & measurements

Module 3

Centralized medical gas supply and sterilization systems in hospital: Hospital gas supply systems - Centralized supply of air, nitrous oxide, vacuum & oxygen - principle of production of liquid oxygen. Air quality in hospital environment – Heating, Ventilation and Air Conditioning (HVAC) - Basic concepts and standards in different hospital areas - Refrigeration systems, Air changes, filtering & sterility. Sterilization systems in hospitals: Principles and techniques of sterilization - Steam & EO sterilization. Autoclaves, Incinerators. Hospital seamless flooring and antibacterial painting, Biomedical waste management and solutions.

Module 4

Healthcare technology management: Medical Equipment Planning in healthcare - purchase & contract procedures (CMC and AMC) - selection, testing and calibration, installation of equipment. Training of medical staff. Repair & maintenance of medical equipment, Preventive maintenance. Healthcare technology management with RFID system-based asset tracking-medical equipment IT networking and communication with Hospital Information


17

Systems (HIS)/Radiology Information System (RIS)/ Picture Archival and Communication System (PACS).

Module 5

Medical preparedness for disaster management: Principles of hospital disaster planning- Emergency medical services-Role of clinical and biomedical engineers in disaster preparedness and management-organizational, technological and professional recommendations. Training and medical preparedness-Role of communication and information technology tools for disaster response and management- Smart design requirements-ITIL framework-dual use infra-structure-research and rapid deployment technologies for disaster management-Identify new treatment modalities-establish link to monitoring centres.

Text Books

1. Azzam Taktak, Paul Ganney, David Long and Paul White (Eds.), A Handbook for Clinical and Biomedical Engineers, Academic press,2010.

2. Roberto Miniati, Ernesto Iadanza, Fabrizio Dori, Clinical EngineeringFrom Devices to Systems, Elsevier,2005.

3. F. Hosea,Emerging Horizons of Clinical Engineering in Disaster preparedness and Management: Proposal for an expanded professional identity, Global Clinical Engineering Journal,2020.

4. Arora Rajesh, Arora Preeti Disaster Management: Medical Preparedness, Response and Homeland Security. Oxfordshire: 2013.

Reference Books 1. H. Al Nahas and J. S. Deogun, "Radio frequency identification applications in smart

hospitals", the Proceedings of IEEE International Symposium on Computer-Based Medical Systems, pp. 337-342, 2007.

2. Anantha Narayanan, Basic Refrigeration and Air Conditioning, , 2nd edition, TMH 1996. Switzerland 2015A. LNCS 8700, pp. 1–20, 2015.DOI: 10.1007/978-3-319-16226-3_

3. KutzMyer, Standard Handbook of Biomedical Engineering &Design, McGraw Hill 4. B. N. Feinberg, Handbook of Clinical Engineering, CRC Press, 1980. 5. Richard L. Miller, Earl S. Swensson, Hospital and Healthcare Facility Design, W.

W. Norton & Company; 2nd edition 2002 6. John Douglas McDonald, Electric Power Substations Engineering, CRC Press, 2003 7. Andreas Holzinger1, Carsten Röcker1,2, and Martina Ziefle3 , From Smart Health to

Smart Hospitals, Springer International Publishing 8. Hogan, David E., and Jonathan L. Burstein, eds. Disaster medicine. Lippincott

Williams & Wilkins, 2007.


18



1 Module 1

1.1 Definition: Bio-Engineering, Biomedical Engineering, Clinical engineering & Hospital engineering. Role & responsibilities 1

1.2 Concept of smart hospital- Increasing staff productivity-optimizing cost efficiencies- Improving patient outcomes- Integrated building management platform- regulations.

3

1.3 Hospital Architecture – Planning and design of various departments. (Radiology Dept., Nuclear Medicine, ICU, Central Sterilization and Operation Theaters). Space distribution in a hospital building.

3

1.4 Smart hospitals-Case study 2 2 Module 2

2.1 Electrical power systems in hospitals -Design of sub stations- wiring in hospitals

2

2.2 Stabilized and uninterrupted power supply systems. 1

2.3 Protective systems: Over voltage and over current protectors, circuit breakers, Surge protectors, EMI filters.

2

2.4 Patient safety – electrical shocks and hazards – micro and macro shocks- effects of electrical current on human body – leakage currents – types & measurements

3

2.5 Introduction to hospital electrical safety and its ISO standards- Safety measures & standards for radiation, Rooms-planning & installation.

2

3 Module 3

3.1 Hospital gas supply systems - Centralized supply of air, nitrous oxide, vacuum & oxygen - principle of production of liquid oxygen. 2

3.2 Air quality in hospital environment - Heating, Ventilation and Air Conditioning (HVAC) - Basic concepts and standards in different hospital areas.

3

3.3 Refrigeration systems, Sterilization systems in hospitals: Principles and techniques of sterilization - Steam & EO sterilization. Autoclaves. 2

3.4 Incinerators, Hospital seamless flooring and antibacterial painting, Biomedical waste management and solutions.

2

4 Module 4

4.1 Medical Equipment Planning in healthcare - purchase & contract procedures (CMC and AMC) - selection, testing and calibration, installation of equipment.

3

4.2 Training of medical staff. Repair & maintenance of medical equipment, 2


19

Preventive maintenance.

4.3 Healthcare technology management with RFID system-based asset tracking- 1

4.4 Medical equipment IT networking and communication with Hospital Information Systems (HIS)/Radiology Information System (RIS)/ Picture Archival and Communication System (PACS.

3

5 Module 5 5.1 Principles of hospital disaster planning- Emergency medical services- 1

5.2 Role of clinical and biomedical engineers in disaster preparedness and management-organizational, technological and professional recommendations.

2

5.3 Training and medical preparedness-Role of communication and information technology tools for disaster response and management- Smart design requirements-ITIL framework

3

5.4 Dual use infra-structure-research and rapid deployment technologies for disaster management-Identify new treatment modalities-establish link to monitoring centres

2


20

EBT305 MEDICAL IMAGING TECHNIQUES


PCC 4 0 0 4

Preamble:

This subject is intended to understand the physical principles of imaging and image reconstruction methods with respect to Ultrasound imaging, Computed Tomography, Magnetic resonance imaging- Radionuclide imaging and Intra operative imaging.

Prerequisite: NIL


CO 1 Understand the principles of diagnostic Ultrasound imaging.

CO 2 Analyse the imaging methods used in Computed tomography.

CO 3 Apply the principles of Nuclear Magnetic Resonance in medical imaging.

CO 4 Analyse the use of radio nuclides in medical imaging.

CO 5 Understand the technology and applications of intraoperative imaging



CO 1 3 3 1 1 1 3 CO 2 3 3 1 1 1 3 CO 3 3 3 1 1 3 CO 4 3 3 1 1 3 CO 5 3 3 1 1 3

Assessment Pattern

Bloom’s Category Continuous Assessment

Tests End Semester Examination 1 2

Remember Understand 20% 20% 20% Apply 40% 40% 40% Analyse 40% 40% 40%

Mark distribution


150 50 100 3 hours


21




Course Outcome 1 (CO1): Appreciate the principles of Ultrasound imaging

1. What is the principle of generation of medical Ultrasound? 2. What is the principle of image formation in diagnostic ultrasound? 3. Give one application each for A-mode, B-mode, M-mode ultrasound scan

Course Outcome 2 (CO2): Analyse the imaging methods used in computed tomography

1. What is the difference between conventional radiograph and CT image? 2. What is CT number? 3. Identify the steps involved in algebraic reconstruction technique used in CT

imaging.

Course Outcome 3 (CO3): Apply the principles of nuclear magnetic resonance in medical imaging

1. What is free induction decay? 2. Analyse any two fast pulse sequences. 3. Differentiate spatial and temporal resolution in fMRI

Course Outcome 4 (CO4): Analyse the use of radionuclides in medical imaging

1. Illustrate the components of Anger camera 2. How does nuclear imaging incorporate functional aspects of the organ considered. 3. Compare MRI-PET and CT-SPECT.

Course Outcome 5 (CO5): Understand the technology and applications of intraoperative imaging

1. Explain ultrasound technique in intra operative imaging. 2. What is photoacoustic imaging? 3 Explain how echo planar imaging is suitable for real time intra operative imaging.


22


Reg No.:_______________ Name:__________________________

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY FIFTH SEMESTER B. TECH DEGREE EXAMINATION, ____________ 20__

Course Code: EBT305 Course Name: MEDICAL IMAGING TECHNIQUES



1 What is the relation between depth of penetration and frequency of US

used?

(3)

2 What is the difference between specular and non-specular reflection? (3)

3 Define CT number. (3)

4 In what respect a CT image is superior to a radiographic image. (3)

5 What is free induction decay? (3)

6 What gives contrast in functional MRI? (3)

7 Why spatial resolution of PET image is inferior compared to CT images? (3)

8 Name any two radioisotopes used in SPECT imaging. (3)

9 Give any one typical applications of ultrasound guided surgery (3)

10 What is echo planar imaging? (3)

PART B Answer any one full question from each module. Each carry 14 marks.

MODULE I

11 a) What is the principle of working of an A-mode scanner? (7)

b) Give an example of an A-mode US instrument. (7)

OR

12

a) Explain the principle of working of a phased array system of

ultrasound transducers

(7)

b) What is the difference between 3 D and 2 D ultrasound scans? (7)

MODULE II

13

a) With the help of a block diagram explain the working of a CT scanner.

(8)

b) Briefly explain the features of an X-ray tube used for CT application. (6)


23

OR

14

a) Explain filtered back projection technique used in CT image reconstruction.

(10)

b) Define Radon transform (4)

MODULE III

15

a) With the help of a block diagram explain the working of an MRI scanner.

(10)

b) What do you understand by k-space in MRI imaging? (4)

OR

16 a) What is the purpose of gradient coils used in MRI imaging? (10)

b) Explain the concept of fMRI. (4)

MODULE IV

17

a) With the help of a block diagram explain the principle of working of a Gamma-camera.

(10)

b) Name any two radiation detectors used in PET imaging. (4)

OR

18

a) With the help of a block diagram explain the working of a PET scanner.

(10)

b) How functional information is encoded in a MRI-PET image? (4)

MODULE V

19

a) Give any one application where ultrasound guided surgery is suitable. Explain the setup for that.

(10)

b) Give any one typical application of CMUT in interventional imaging. (4)

OR

20

a) Explain how photoacoustic imaging supplement the other imaging modalities

(7)

b) How echo planar imaging is suitable in real-time interactive imaging?

(7)


24

Syllabus

Module 1

Ultrasound imaging: Fundamentals of acoustical Propagation: Reflection and Refraction, Attenuation, Absorption and Scattering, Doppler effect. Principle of image formation- constructional details of US probes- Transducer Design – Considerations- Beam forming- Array Beam forming, -Scattering from Tissue and Tissue Characterization, Modes of scanning-A mode-B mode-M mode- Duplex scanning-applications of each. Principles of 3D/4D ultrasound Functional Ultrasound Imaging, Clinical applications.

Module 2

Computed Tomography: Principle of Computed Tomography, Scanner configurations Different Geometries, Multislice CT Scanners: CT Scanning in Spiral-Helical Geometry, Fifth-Generation Scanners, Sixth-Generation Scanners: The Dual-Source CT Scanner, Seventh-Generation Scanners: Flat-Panel CT Scanners, Slip-Ring Technology, System components: Gantry, Collimation. X-ray tubes for CT applications-pencil beam and cone beam projections- CT Detector Technology, Multi row / Multi slice Detectors, Area Detectors. Image reconstruction algorithms, Image characteristics: Image matrix, CT numbers, Spatial resolution, System noise, Image Artifacts.

Module 3

Magnetic Resonance Imaging Principles of Nuclear Magnetic Resonance. Nuclear spin, Precession, Spins in an External Magnetic Field., RF Excitation, Relaxation-T1 & T2 relaxation measurements, The Bloch Equations, Spin Echoes and T2*, Inversion Recovery, Image Reconstruction, Gradients -Slice Selection – Frequency and Phase Encoding, Gradient and Spin-echo Pulse Sequences, spatial encoding in k-space. MRI contrast mechanisms, Rapid MR Imaging -Gradient-Echo Imaging, Echo-Planar Imaging Fast Spin-Echo Imaging Partial k-Space Acquisition MR Instrumentation, Functional MRI- BOLD Hemodynamic Response Spatial and temporal Resolution of fMRI.

Module 4

Radionuclide Imaging Radio-isotope in medical diagnosis, Interaction of Nuclear particles with Matter. Radionuclide generators, Nuclear Radiation Detectors, Rectilinear Scanner, Gamma camera, Single Photon Emission Computed Tomography, Positron Emission Tomography, Biological Effects. Hybrid Imaging Instrumentation MR-PET Instrumentation-Mutual Interference Between MR and PET, MR Compatible PET Detector Technology, MR-PET System Architecture. PET-CT, SPECT-CT.

Module 5

Intraoperative imaging Intraoperative imaging and image guided therapy-X-Ray Hybrid Modalities for Image Guidance-Technology of Ultrasound-Guided Therapy-Innovations in


25

Ultrasound Instrumentation for Image Guidance-CT-Guided Interventions: Current Practice and Future Directions-Real-Time and Interactive MRI.

Text Books

1. Hoskins, Peter R., Kevin Martin, and Abigail Thrush, eds. Diagnostic ultrasound: physics and equipment. CRC Press, 2019.

2. Szabo, Thomas L. Diagnostic ultrasound imaging: inside out. Academic Press, 2004. 3. M Flower ,Webb’s Physics of Medical Imaging, Taylor & Francis, 2016. 4. Shah, N. Jon, ed. Hybrid MR-PET Imaging: Systems, Methods and Applications.

Royal Society of Chemistry, 2018. 5. Seeram, Euclid. Computed Tomography-E-Book: Physical Principles, Clinical

Applications, and Quality Control. Elsevier Health Sciences, 2015. 6. Ferenc A. Jolesz Editor, Intraoperative Imaging and Image-Guide Therapy,

Springer,2008 7. Weishaupt, Dominik, Köchli, Victor D, Marincek, Borut, How does MRI work? An

Introduction to the Physics and Function of Magnetic Resonance Imaging, Springer, 2006.

Reference Books

1. Avinash C Kak, Malcolm Slaney ,Principles of Computerized Tomographic Imaging 2001

2. Hans H Schild ,MRI made easy, 2003. 3. Fenster, Aaron, and James C. Lacefield, eds. Ultrasound imaging and therapy.

Taylor & Francis, 2015 4. DuccioVolterraniPaola Anna ErbaIgnasiCarrióH. William Strauss Giuliano Mariani

Editors, Nuclear Medicine Te x t b o o k, Methodology and Clinical Applications, Springer, 2019.

5. Christian, Paul E., and Kristen M. Waterstram-Rich, eds. Nuclear medicine and PET/CT: technology and techniques. Mosby/Elsevier, 2007.



1 Module 1`

1.1 Fundamentals of acoustical Propagation: Reflection and Refraction, Attenuation, Absorption and Scattering, Doppler effect

1

1.2 Acoustic characteristics of US- frequency, wavelength, velocity, characteristic impedance.

1

1.3 Principle of image formation 1

1.4 Constructional details of US probe- Transducer Design Beamforming Array Beamforming, Scattering from Tissue and Tissue Characterization

3


26

1.5 Modes of scanning-A mode-B mode-M mode- Duplex scanning-applications of each- Principles of 3D/4D ultrasound Functional Ultrasound Imaging

3

2 Module 2

2.1 Principle of Computed Tomography-:Data acquisition concepts, Geometries First,Second, Third,Fourth generation Scanners. Multislice CT Scanners

2

2.2

CT Scanning in Spiral-Helical Geometry Fifth-Generation Scanners, Sixth-Generation Scanners: The Dual-Source CT Scanner, Seventh-Generation Scanners: Flat-Panel CT Scanners, Slip-Ring Technology-Design and Power Supply-Advantages

2

2.3 System components: Gantry, Collimation. X-ray tubes for CT applications

1

2.4 Image reconstruction algorithms- pencil beam and cone beam projections

2

2.5 CT Detector Technology, Multirow/Multislice Detectors, Area Detectors 1

2.6 Image characteristics: Image matrix, CT numbers, Spatial resolution, System noise, Image Artifacts. 2

3 Module 3

3.1 Principles of Nuclear Magnetic Resonance. Nuclear spin, Precession, Spins in an External Magnetic Field, RF Excitation, Relaxation mechanisms

2

3.2 The Bloch Equations, Spin Echoes and T2*, Inversion Recovery, Image Reconstruction

1

3.3 Image acquisition methods- Gradients-Slice Selection –Frequency and Phase Encoding, Spatial encoding in k-space. Pulse sequences (Gradient and spin echo)

2

3.4 Echo-Planar Imaging - Fast Spin-Echo Imaging - Partial k-Space acquisition - MR Instrumentation-Magnet-Gradient coils-RF system

2

3.5 Functional MRI- BOLD Hemodynamic Response, Spatial and temporal Resolution of fMRI 2

4 Module 4

4.1 Radio-isotopes in medical diagnosis, Interaction of Nuclear particles with matter.

1

4.2 Radionuclide generators, Nuclear Radiation Detectors 1 4.3 Rectilinear Scanner, Gamma camera 1

4.4 Single Photon Emission Computed Tomography, Positron Emission Tomography- Biological effects of radionuclides

2

4.5 Hybrid Imaging instrumentation – MR-PET Instrumentation-Mutual Interference Between MR and PET, MR Compatible PET Detector 4


27

Technology, MR-PET System Architecture - PET-CT, SPECT-CT

5 Module 5

5.1 Intraoperative imaging and image guided therapy-X-Ray Hybrid Modalities for Image Guidance

1

5.2 Technology of Ultrasound-Guided Therapy-Innovations in Ultrasound Instrumentation for Image Guidance

2

5.3 CT-Guided Interventions: Current Practice and Future Directions 2 5.4 Real-Time and Interactive MRI. 2


28

EBT307 INTRODUCTION TO

BIOMEDICAL SIGNAL PROCESSING


PCC 3 1 0 4

Preamble: This course makes students familiarized with basics of digital signal processing, concepts of digital filters & its design and applications of biomedical signal processing. Prerequisite: Basic understanding of biomedical signals. Course Outcomes: After the completion of the course the student will be able to

CO 1 Analyse the basics of discrete time signals &systems and their time domain processing techniques with specific reference to biomedical signals.

CO 2 Apply the different methods of analysing digital signals using frequency domain analysis.

CO 3 Analyse the discrete time system using Z Transform.

CO 4 Design of different types of digital filters such as FIR &IIR filters.

CO 5 Apply various signal processing techniques in biomedical applications.

Mapping of course outcomes with program outcomes PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12

CO 1 3 2 2

CO 2 3 2 2

CO 3 3 2 1 2

CO 4 3 3 1 1 2 1

CO 5 3 3 1 1 2 1

Assessment Pattern




Mark distribution


150 50 100 3 hours


29

Continuous Internal Evaluation Pattern: Attendance : 10 marks Continuous Assessment Test (2 numbers) : 25 marks Assignment/Quiz/Course project : 15 marks It is mandatory that at least one assignment should be a Course Project. The course project can be a simulation of biomedical signal processing technique. End Semester Examination Pattern: There will be two parts; Part A and Part B. Part A contain 10 questions with 2 questions from each module, having 3 marks for each question. Students should answer all questions. Part B contains 2 questions from each module of which student should answer any one. Each question can have maximum 2 sub-divisions and carry 14 marks.

Course Outcome 1 (CO1): Analyse the basics of discrete time signals &systems and their time domain processing techniques with specific reference to biomedical signals.

1. Determine the following system is linear or not y(n)=5 x(n)+ 100

𝑥𝑥(𝑛𝑛)

2. Find the convolution between two sequences x1(n)= 4 n u(n) and x2(n)= (1/8) n u(n) 3. Determine the homogeneous solution of the difference equation

y(n)=58 y(n-1) - 1

8 y(n-2) +x(n)

Course Outcome 2 (CO2): Apply the different methods of analysing digital signals using frequency domain analysis

1. State and prove time reversal property of DFT 2. Determine the DFT of the sequence x(n)= 5n u(n)-u (n-4) 3. Determine the IDFT of the given sequence X(k)= 1, -2-j, 0, -2+j

Course Outcome 3 (CO3): Analyse the discrete time system using Z Transform 1. Determine the Z transform and ROC of cos ωon u(n) 2. What is the Z transform of the sequence x(n)= n an u(n) ? 3. State & prove correlation property of Z transform

Course Outcome 4 (CO4): Design of different types of digital filters such as FIR &IIR filters

1. What are the desirable characteristics of window? 2. Determine the order of filter using Chebyshev approximations if αp=3dB; αs=16dB;

fp=1KHz and fs=2 KHz. 3. Find the stable poles of Butterworth filter of order 4

Course Outcome 5 (CO5): Apply various signal processing techniques in biomedical applications.

1. Explain the process of synchronised averaging to remove random noise. 2. Design the filtering method to remove low frequency artefacts. 3. Explain the correlation-based method for EEG waves detection.


30


Total Pages:

Reg No.: _______________ Name: __________________________

FIFTH SEMESTER B. TECH DEGREE EXAMINATION

Course Code: EBT307 Course Name: INTRODUCTION TO BIOMEDICAL SIGNAL PROCESSING

Max. Marks: 100 Duration: 3 Hours PART A

Answer full questions, each carry 3 marks. (3)

1 What is a shift invariant system? give an example. (3)

2 Check the given signal is energy or power signal x(n)=10u(n) (3)

3 Compute N point DFT of the sequence x(n)=e j2πnko/N (3)

4 Find the circular convolution of two sequences x1(n)= 2,1, 2, 1 &x2(n)=

1,2,3,4 (3)

5 What are the features of parametric spectrum estimation? (3)

6 Find the inverse Z transform using convolution method X(Z)= 11−3z−1+2z−2 (3)

7 Determine the order of Butterworth filter that has 2 dB attenuation at 500Hz and

an attenuation of 30 dB at 1000Hz. (3)

8 What is the need for employing window technique for FIR filter design? (3)

9 Illustrate time domain method to remove base line drift in PPG signal. (3)

10 Identify at least three potential sources of physiological artifacts in recording.

PART B Answer any one question, each carry 14 marks.

11 a) Determine the response y(n), n≥0 of the system described by second order

difference equation 2y(n)- y(n-1) +8y(n-2) =2x(n)-2x(n-1), when the input

is x(n)= (2)n u(n) and initial conditions are

y (-1) =y (-2) =1

(7)

b) (i)Determine the response of the relaxed system characterised by the

impulse response h(n)=(α)n u(n) to the input signalx(n)=(α-10) n u(n)

(ii)Define linear system, Give an example of linear system.

(4)

(3)

OR

12 a) Determine whether the given systems are causal, linear, dynamic, time (10)


31

invariant and stable.

(i) y(n)= ∑ x(k)nk=n−5

(ii) y(n)=sin (n x(n)+ x(n-1))

b) Determine the correlation between the signals x1(n)=1; n=-2,0,1 =2; n= -1 =0 elsewhere x2(n)=δ(n)-δ(n-1) +δ(n-2) +δ(n-3)

(4)

13 a) Compute 8-point FFT of the sequence x(n)= 1,2,4,6,1 ,2,4,6 using DIT

algorithm. (10)

b) State and prove circular frequency shift property of DFT. (4)

OR

14 a) Compute IDFT of the sequence, X(k)= 6, -2-2j, 2, -2+2j. (6)

b) Find the DFT of the following signals

(i)x(n)= (1/2) n for N=16

(ii)x(n)=δ(n-n0)

(8)

15 a) State and prove the convolution theorem of Z transform with example. (7)

b) Find the Z transform of the following

(i)x(n)=αn cos ωon u(n)

(ii)x(n)=rncos[(n+1)ω]cosω

(7)

OR

16 a) Find the inverse Z transform of X(Z)= z2+Zz2−4Z+3

(7)

b) Illustrate the periodogram method of power spectrum estimation, what are

the drawbacks of periodogram method? (7)

17 a) Design an approximation to ideal lowpass filter using Hanning window

with magnitude response

Hd(ejω) =1 for −π8

≤ω≤π8

=0 for π8<|ω| ≤π

(10)

b) What is Gibb’s phenomenon? (4)

OR

18 a) Design a Chebyshev filter with maximum passband attenuation of 2dB at

Ωp=10 rad/sec and the stopband attenuation of 20 dB at Ωs=40 rad/sec. (9)


32

b) Design a digital filter equivalent of the given analog filter, H(s)= 10s2+7s+10

using impulse invariant method. (5)

19 a) Explain how you would apply synchronized averaging to remove noise in ECG signal.

(7)

b) Describe the time domain signal processing method to detect dicrotic

notch. (7)

OR 20 a) What are the steps in Pan Tompkins algorithm for QRS detection? (7)

b) Illustrate time domain method to detect the presence of α rhythm in EEG signal.

(7)

Syllabus

Module 1

Basics of biomedical signal processing: Introduction & relevance of biomedical signal processing. Biomedical signals –ECG, EMG, EEG, PCG, VAG, carotid pulse, speech signal, concurrent signals. Signal representation, Aliasing-Sampling theorem. Elementary signals. Classification of discrete signals - Energy and Power signals – periodic and aperiodic, even and odd signals. Discrete time systems - Properties of discrete systems. LTI system-Impulse Response of a Linear Time-Invariant System -convolution- correlation - difference equation representation of discrete systems

Module 2

Fourier Analysis: Fourier Analysis for Continuous Time Processes-Synthesis of an ECG signal using pure sinusoid. Frequency Domain Analysis of discrete time signals: Discrete Fourier series - Discrete Time Fourier Transform- Discrete Fourier Transform-properties - Fast Fourier Transform- FFT algorithms (Radix 2)- decimation in - time - decimation in - frequency.

Module 3

Spectrum analysis & Z Transform: Spectrum analysis of bio signals – Introduction to parametric &non parametric methods. Z transform – ROC, properties of ROC, Properties of Z transform: Linearity, Time shifting, Scaling, Time reversal, Differentiation in Z domain, Convolution, Correlation, Multiplication, Parseval’s relation, initial value theorem- rational Z transform-poles &zeros-LTI system function - inverse Z transform-long division-partial fraction expansion method-residue method-convolution method.

Module 4

Digital filters: Concept of digital filtering, types of digital filters. Comparison with analog filters. FIR filter design using Fourier series - use of window functions, IIR Digital Filters -


33

Analog filter approximations - Butterworth approximation - Frequency transformation techniques - impulse invariant transformation -Matched Z transform technique- bilinear transformation

Module 5

Applications of biomedical signal processing: Filtering: Noises in biomedical recording-Time domain filters- synchronised averaging -random noise removal, moving averaging- high frequency noise removal in ECG, derivative based operators-removal of base line wander. Event detection: QRS detection-derivative based method-Pan Tompkins algorithm- dicrotic notch detection - Heart sound detection- EEG rhythm detection -correlation based method

Text Books:

1. John G Proakis& Dimitris G Manolakis, Digital Signal Processing-Principles, Algorithms and Applications, PHI, 4 th Edition, 2016

2. Alan V Oppenheim, Alan S Willsky, Signals and Systems. Prentice Hall India, 2ndEdition, 2014.

3. P. Ramesh Babu: Digital Signal Processing, Scitech Publications, India, 6th Edition, 2014.

4. Rangaraj M Rangayyan: Biomedical Signal Analysis, John Wiley, 2 nd Edition, 2015. 5. Suresh R Devasahayam , Signals & Systems in Biomedical Engineering , Springer

2 nd Edition, 2013 References

1. Andreas Antonion: Digital Filters Analysis & Design, Prentice Hall of India, 2018 2. Andreas Antoniou: Digital Signal Processing, Prentice Hall of India.4 th Edition,

2006 3. R Rabiner& B. Gold: Theory & Application of Digital Signal processing, PHI, 3 rd

Edition, 2000 4. Steven W. Smith, Digital Signal Processing – A Practical Guide for Engineers and

Scientists, Elsevier India Pvt Ltd., 2006. 5. Sanjit K. Mithra, Digital Signal Processing, Tata McGraw Hill, 4th Edition, 2013



1 Module 1

1.1 Introduction & relevance of biomedical signal processing- Introduction to biomedical signals –ECG, EMG, EEG, PCG, VAG, carotid pulse, speech signal, concurrent signals

1

1.2 Continuous time and discrete time signal representation 1 1.3 Aliasing-Sampling theorem. 1 1.4 Introduction to elementary signals. Classification of discrete signals - 1


34

Energy and Power signals - periodic, even and odd signals 1.5 Discrete time systems - Properties of discrete systems. 2 1.6 LTI system-Impulse Response of a Linear Time-Invariant System -

convolution- correlation 2

1.7 Difference equation representation of discrete systems 2

2 Module 2

2.1 Fourier Analysis for Continuous Time Processes-Synthesis of an ECG signal using pure sinusoid.

1

2.2 Frequency Domain Analysis of discrete time signals: Discrete Fourier series

2

2.3 Discrete Time Fourier Transform 1 2.4 Discrete Fourier Transform-properties 2 2.5 Fast Fourier Transform- FFT algorithms (Radix 2)- decimation in - time

- decimation in - frequency 3

3 Module 3

3.1 Spectrum analysis of bio signals – Introduction to parametric &non parametric methods.

3

3.2 The Z transform 1 3.3 Properties of Z transform 2 3.4 Inverse Z transform 1

4 Module 4

4.1 Concept of digital filtering, types of digital filters. Comparison with analog filters

1

4.2 FIR filter design using Fourier series 1 4.3 Use of window functions like rectangular, raised Cosine, Kaiser,

Triangular 2

4.4 IIR Digital Filters - Analog filter approximations - Butterworth and approximations

3

4.5 Frequency transformation techniques - impulse invariant transformation Matched Z transform technique -bilinear transformation

3

5 Module 5

5.1 Filtering: Noises &artefacts in biomedical recording 1 5.2 Time domain filters- synchronised averaging -random noise removal 1 5.3 Moving averaging- high frequency noise removal in ECG 1 5.4 Derivative based operators-removal of base line wander 1 5.5 Event detection: QRS detection-derivative based method-Pan Tompkins

algorithm 2

5.6 Dicrotic notch detection 1 5.7 Heart sound detection- EEG rhythm detection -correlation based

method 2


35

EBL331 MEDICAL

ELECTRONICS LAB


PCC 0 0 3 2

Preamble: This lab course makes the student capable of the designing and implementing of instrumentation for medical equipment using Op-amp, specific sensors and specialized ICs Prerequisite: Basic knowledge about electronic circuits.


CO 1 Design and implement circuits for biomedical applications using Op amp

CO 2 Design the circuits using transducers for biosignal acquisition

CO 3 Develop circuits using specialized ICs for biomedical applications

CO 4 Describe operating procedures of medical equipment.


PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 CO 1 3 1 3 3 3 1 1 3 3 2 CO 2 3 1 3 3 3 1 1 3 3 2 CO 3 3 2 3 3 3 1 1 3 3 2 CO 4 3 2 3 3 3 1 1 3 3 2

Mark Distribution


150 75 75 2.5 hours


Attendance : 15 marks Continuous Assessment : 30 marks Internal Test (Immediately before the second series test) : 30 marks


36

End Semester Examination Pattern: The following guidelines should be followed regarding award of marks

(a) Preliminary work : 15 Marks (b) Implementing the work/Conducting the experiment : 10 Marks (c) Performance, result and inference (usage of equipment and troubleshooting) : 25 Marks (d) Viva voce : 20 marks (e) Record : 5 Marks

General instructions: Practical examination to be conducted immediately after the second series test covering the entire syllabus given below. Evaluation is a serious process that is to be conducted under the equal responsibility of both the internal and external examiners. The number of candidates evaluated per day should not exceed 20. Students shall be allowed for the University examination only on submitting the duly certified record. The external examiner shall endorse the record.


Course Outcome 1 (CO1) Design and implement circuits for biomedical applications

1. Design and setup a UJT relaxation oscillator

2. Set up a real time ECG acquisition circuit. Simulate the circuit and compare the performance with the obtained result.

3. Implement DC power control using SCR and observe their performances

Course Outcome 2 (CO2) Design the circuits using transducers for biosignal acquisition

1. Design circuit to observe thermistor characteristics. Simulate the circuit and compare the performance with the obtained result.

2. Implement LDR circuit & stud its characteristics.

Course Outcome 3 (CO3) Develop circuits using specialized ICs for biomedical applications

1. Design a circuit for ECG acquisition and heart rate measurement using BIOPAC

2. Study the data sheet of 4046 and Set up a biotelemetry circuit using IC 4046

Course Outcome 4 (CO4) Describe operating procedures of medical equipment.

1. Study to operate ECG and Sphygmomanometer

2. Demonstration of operation of analytical equipment such as colorimeter, pH meter,


37

HB meter

List of Exercises/ Experiments (Minimum of 10 mandatory) GROUP 1

1. Study of temperature transducer ICs

2. Sample and hold circuit ‘

3. Real time ECG acquisition circuit

4. DC power control using SCR.

5. UJT relaxation oscillator

GROUP 2

1. Study of PLL IC 565

2. ECG acquisition and heart rate measurement using BIOPAC

3. Design of pacemaker circuits &characteristics

a. Fixed type

b. Demand type

4. Thermistor characteristics

5. Measurement of skin contact impedance.

6. Study of LDR & its characteristics

GROUP 3

1. Determination of alpha waves using EEG module

2. Basic principle of biotelemetry using IC 4046. (Transmitting ECG signals).

3. Study of medical equipment- a. ECG Machine b. EEG Machine c. Spirometer d. Bedside monitor

4. Study of Sphygmomanometer- manual and automated

5. Study of analytical equipment such as colorimeter, pH meter, HB meter

(Include one open ended experiment from each group to the students to make them understand the concepts learned)


38

Reference Books

1. R E Boylstead and L Nashelsky: Electronic Devices and Circuit Theory, 9/e, Pearson Education.

2. Allan Mottershead, Electronic Devices & Circuits, Prentice Hall of India, NewDelhi, 2003.

3. Millman and Taub, Pulse, digital and Switching Waveforms, Tata McGrawHill, 2007.

4. R S Khandpur Handbook of Biomedical Instrumentation, Second Edition

5. Dr. John G. Webster Encyclopedia of Medical Devices and Instrumentation, 2nd Edition


39

EBL333 BIOMEDICAL SIGNAL PROCESSING LAB


PCC 0 0 3 2 Preamble: This course makes students develop and implement algorithms for analysis &

processing of biomedical signals

Prerequisite: Thorough knowledge about Biomedical signal processing techniques.

Course Outcomes:After the completion of the course the student will be able to

CO 1 Implement basic signal processing operations in Qt-octave & Python CO 2 Implement FIR and IIR filters CO 3 Develop algorithms to extract features of normal biomedical signals CO 4 Develop algorithm to analyse biomedical signal and detect abnormalities



CO 1 3 2 3 3 2 1 CO 2 3 2 2 2 3 3 2 1 CO 3 3 2 3 3 3 3 2 1 CO 4 3 2 2 3 3 3 2 1

Mark distribution


150 75 75 2.5 hours


Attendance : 15 marks Continuous Assessment : 30 marks Internal Test (Immediately before the second series test) : 30 marks End Semester Examination Pattern: The following guidelines should be followed regarding award of marks. (a) Preliminary work : 15 Marks (b) Implementing the work/Conducting the experiment : 10 Marks (c) Performance, result and inference

(usage of equipment and troubleshooting) : 25 Marks (d) Viva voce : 20 Marks (e) Record : 5 Marks


40

General instructions: Practical examination to be conducted immediately after the second series test covering the entire syllabus given below. Evaluation is a serious process that is to be conducted under the equal responsibility of both the internal and external examiners. The number of candidates evaluated per day should not exceed 20. Students shall be allowed for the University examination only on submitting the duly certified record. The external examiner shall endorse the record.


Course Outcome 1 (CO 1): Implement basic signal processing operations in Qt-octave & Python

1. Obtain the response of a system whose impulse response and input signal are given.

2. Find the autocorrelation function of the given sequence using python.

3. Write a function to obtain Discrete Fourier transform

Course Outcome 2 (CO2): Implement FIR and IIR filters 1. Write a program to eliminate baseline wander in ECG data.

2. Implement a program to remove powerline interference.

3. Write a program to extract specific bands from EEG data.

Course Outcome 3(CO3): Develop algorithms to extract features of normal biomedical signals

1. Write a program to identify presence and absence of dicrotic in PPG data

2. Calculate QRS wave frequency using time domain and frequency domain analysis.

3. Calculate pulse transit time using concurrent PPG & ECG analysis

Course Outcome 4 (CO4): Develop algorithm to analyse biomedical signal and detect

abnormalities

1. Write a program to classify given EEG data into normal, tachycardia & bradycardia

classes using time domain analysis.

2. Calculate respiratory rate using frequency domain analysis of respiratory signal.

3. Write a program to identify premature ventricular contraction.

LIST OF EXPERIMENTS (10 Mandatory) 1. Familiarization of QT-Octave

2. Familiarization of python programming

Programs in python

3. Processing of ECG signals for acquiring parameters - heart rate, amplitude & time

interval calculation of QRS complex, P wave & T wave


41

4. Processing and estimation of respiratory rate from respiratory signal using python.

5. Analysis of plethysmography signal and calculation of pulse rate

6. Time & frequency domain analysis of HRV signal

7. Analysing biomedical signals using toolbox in python (biosppy,neurokit2 etc)

8. Exploratory data analysis (EDA) using python toolbox.

Programs in QT Octave

9. Time domain Filtering to remove baseline drift & high frequency artefacts in ECG

signal.

10. Powerline interference rejection from ECG signals

11. Arrhythmia analysis

12. Detection of Premature Ventricular Contraction in ECG

13. Estimation of dicrotic notch from PPG signal

14. Detection of respiratory signal from PPG signal

15. PCG Segmentation into systolic & Diastolic phases and identification of heart

sounds

16. Event detection in EEG signal

17. Spectral analysis of ECG signal

18. Spectral analysis of EEG & EMG signal

19. Concurrent signal analysis with ECG, PPG and PCG

20. Signal classification using Neural network toolbox

(Include one open ended experiment from each group to the students to make them

understand the concepts learned)

Reference Books

1. Rangaraj M Rangayyan: Biomedical Signal Analysis, John Wiley, 2 nd Edition, 2015.

2. Suresh R Devasahayam, Signals & Systems in Biomedical Engineering, Springer 2nd Edition, 2013

3. AbdulhamitSubasi,Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques, Academic Press,1st Edition, 2019


SEMESTER V MINOR


42

Preamble: This course aims to introduce the students to filtering and other signal processing techniques used for biomedical signals to gather clinical information related to diagnosis as well as therapeutic efficacy. Prerequisite: Basic understanding about the characteristics of Biomedical signals.


CO 1 Apply pre-processing using FIR filter to remove artifact from ECG. CO 2 Choose appropriate IIR filter for removal of artifacts from bio signals. CO 3 Design suitable signal processing algorithms to extract clinical information related to

diagnosis and therapeutic efficacy from bio signals. CO 4 Detect abnormal events from the acquired bio signal. CO 5 Implement the algorithms for bio signal processing on any programming language.



CO 1 2 1 1 1 1 CO 2 2 1 1 1 1 CO 3 2 1 1 1 1 1 CO 4 2 1 1 1 1 1 CO 5 1 1 1 1 3 1

Assessment Pattern



Understand 10% 10% 10% Apply 50% 50% 50% Analyse 40% 40% 40%

Mark distribution

Total Marks

CIE ESE ESE Duration

150 50 100 3 hours

EBT381 BIOMEDICAL SIGNAL PROCESSING


VAC 4 0 0 4


43


Attendance : 10 marks

Continuous Assessment Test (2 numbers) : 25 marks Assignment/Quiz/Course project : 15 marks

End Semester Examination Pattern: There will be two parts; Part A and Part B. Part A contain 10 questions with 2 questions from each module, having 3 marks for each question. Students should answer all questions. Part B contains 2 questions from each module of which student should answer any one. Each question can have maximum 2 sub-divisions and carry 14 marks.


Course Outcome 1 (CO1): Apply pre-processing using FIR filter to remove artifact from ECG.

1. Design an FIR linear phase, digital filter approximating the ideal response

2. Design an FIR filter to remove artifact (Base line wander) from ECG.

3. Identify the major artifacts associated with ECG monitoring.

Course Outcome 2 (CO2): Choose appropriate IIR filter for removal of artifacts from biosignals.

1. Given the specifications αp = 3 dB; αs =16 dB; fp=1 KHz and fs =2 KHz. Determine the order of the filter using Chebyshev approximation.

2. Select an IIR filter to remove the stationary power-line interference from Bio signals. 3. Design a lowpass digital Butterworth filter with a sampling rate of 10 kHz, a passband

up to 1.0 kHz, and a stopband starting at 1.5 kHz. A maximum passband attenuation of 0.5 dB in the passband and a minimum stopband attenuation of 10 dB in the stopband are allowed using bilinear transformation.

Course Outcome 3(CO3):Design suitable signal processing algorithms to extract clinical information related to diagnosis and therapeutic efficacy from biosignals.

1. Analyse the ECG signal to derive diagnostic information about Heart Rate Variability.

2. Choose a spectral estimation technique to analyse Auditory Evoked Potential. 3. Detect dicrotic notch in PPG signal to extract clinical information.

Course Outcome 4 (CO4): Detect abnormal events from the acquired biosignal.


44

1. Design an algorithm to detect QRS complex from ECG. 2. Detect abnormal heart rate from ECG data. 3. Extract the diastolic heart sounds from PCG signal.

Course Outcome 5 (CO5): Implement the algorithms for biosignal processing on any programming language.

1. Implement an algorithm to remove 50 Hz power line interference from biosignals. 2. Implement an algorithm to detect QRS complex from ECG. 3. Implement an algorithm to segment PCG into systolic and diastolic parts.

Model Question Paper

Total Pages: 2

Reg No.:_______________ Name:__________________________

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY FIFTH SEMESTER B.TECH DEGREE EXAMINATION

Course Code: EBT381 Course Name: Biomedical Signal Processing


PART A Answer all questions, each carries 3 marks. 10x3=30marks

1 Draw the direct form realization of a linear phase FIR system for N even. (3)

2 What is the need of employing window technique for FIR filter design? (3)

3 Illustrate the parallel form structures for realization of IIR filters. (3)

4 How a digital IIR filter is designed? (3)

5 What are the changes made in the Bartlett method to form the Welch

method of power spectrum estimation? (3)

6 What is the advantage of implementing Bartlett method of spectral

estimation? (3)

7 Describe in what ways the parametric spectral estimation is different

from non-parametric techniques. (3)

8 Differentiate AR and ARMA models. (3)

9 Why the derivative-based method is superior for detecting QRS complex

in ECG? (3)

10 Identify the importance of different heart sounds in PCG. (3)

PART B 5x14=70marks


45

Answer five full questions, each carries 14 marks. 11 a) Draw direct form-I structures for each of the following LTI systems with

input node x(n) and output node y(n). 1. y(n) = x(n) + 2 x(n − 1) + 3x(n − 2) 2.

(8)

b) Design a lowpass FIR filter using Hamming window satisfying the following requirements: a passband frequency of 500 Hz with a maximum passband attenuation of 0.2 dB, a stopband frequency of 600 Hz with a minimum stopband attenuation of 40 dB, and a sampling rate of 4 kHz.

(6)

OR 12. a) An FIR filter is described by the difference equation

Determine and draw the block diagrams of the following structures. 1. Direct form 2. Linear-phase form 3. Cascade form

(9)

b) Realize the following system function using minimum number of multipliers

(5)

13 a) Design a lowpass Butterworth filter satisfying the following requirements: a passband frequency of 200 Hz with a maximum passband attenuation of 0.5 dB, a stopband frequency of 400 Hz with a minimum stopband attenuation of 20 dB, and a sampling frequency of 2 KHz.

(8)

b) Determine the order of Butterworth Filter if pass band attenuation is -2 dB at Ωp=10 rad/sec and stop band attenuation is -20 dB at Ωs=40 rad/sec. (6)

OR 14 a) Design a Butterworth high pass filter with a rate of 10 kHz, a passband

starting at 1.5 kHz, and a stopband up to 1 kHz. A maximum passband attenuation of 0.5 dB in the passband and a minimum stopband

(8)


46

attenuation of 10 dB in the stopband are allowed using bilinear transformation.

b) Design a digital filter equivalent to an analog filter with transfer function

using impulse invariant method.

(6)

15 a) Define periodogram. Justify the following statement, ‘Periodogram is not a consistent estimate of true power density spectrum’. (6)

b) Apply the Bartlett's method for Periodogram Averaging. (8) OR

16 a) Compare the performance of Welch and Blackman Tukey methods. (8) b) Propose a method to obtain spectral estimation of Auditory Evoked

Potential. (6)

17 a) What are the limitations of non-parametric methods for power spectrum estimation? (8)

b) How can the ARMA model be used for PSD estimation. (6) OR

18 a) Establish the relationship between the autocorrelation and the AR model parameters. (8)

b) Analyse the diastolic heart sounds using the AR moving average modelling.

(6)

19 a) Design a derivative based algorithm to extract QRS complex from ECG. (6) b) How can the heart rate variability be analysed using frequency domain

methods? (8)

OR 20 a) Analyse the Pan Tompkins Algorithm for QRS Detection. (7) b) Design an algorithm to do the segmentation of PCG into systolic and

diastolic parts. (7)


47

Syllabus

Module 1

FIR Digital Filters- Basic structures-direct and cascade forms, linear phase. Design of FIR Digital Filters: Use of window functions like Rectangular, Hanning, Hamming, Bartlett and Kaiser. Applications of FIR filter in artifact removal: Artifacts associated with ECG monitoring- Base line wander, motion artifact and power line interference. Artifact removal (Base line wander) by FIR filter.

Module 2

IIR digital Filters- Basic structures- direct, cascade and parallel forms. Design of an IIR Digital Filter from an Analog Filter: Impulse invariant and Bilinear Transformations. Characteristics of filters - Butterworth approximations. Application of IIR filter to remove the stationary power-line interference from Bio signals.

Module 3

Spectral Estimation Techniques: The Periodogram, Bartlett, Welch, Blackman and Tukey Methods, Analysis of Heart Rate Variability and Analysis of Auditory Evoked Potential (AEPs) using the Periodogram.

Module 4

Parametric Modelling Methods: Auto regressive (AR)- The Autocorrelation (Yule-Walker) Method, Moving average (MA) and Autoregressive moving average (ARMA) models. Application of A R Modelling of Seizure EEG, A R Modelling of Surface EMG, AR Moving Average Modelling of Diastolic Heart Sounds.

Module 5

Event Detection: P, QRS and T wave detection from ECG, Derivative based Approaches for QRS detection, Pan Tompkins Algorithm for QRS Detection and heart rate measurement. Analysis of heart rate variability - time domain method and frequency domain methods. Dicrotic Notch Detection, Segmentation of PCG into systolic and diastolic parts.

(One of the assignments may be the implementation of the filtering and processing techniques on biosignals using any of the programming languages.)

Text Books

1. Biomedical Signal Analysis, Second Edition. By Rangaraj M. Rangayyan, The Institute of Electrical and Electronics Engineers, Inc., 2015.

2. Biomedical Signal Processing: MetinAkay, Academic Press 1994. 3. Digital Signal Processing Using MATLAB, Vinay K. Ingle John G. Proakis, Fourth

Edition, 2016.

Reference Books 1. Biomedical Signal Processing: Principles and Techniques, D C Reddy, Tata


48

McGrawHill Publishing Co. Ltd, 2005. 2. Biomedical Signal Processing and Signal Modelling, Eugene N. Bruce, Wiley,

2009 3. Biomedical Signal Processing, Advances in Theory, Algorithms and

ApplicationsGanesh Naik, Springer,2020. 4. Signals and Systems in Biomedical Engineering, Suresh R. Devasahayam, Third

Edition Springer Science Business Media, LLC, 2019. 5. Biomedical Signal Processing and Artificial Intelligence in Healthcare, Edited by

Dr.Walid Zgallai Series Editor Dr. Dennis Fitzpatrick, Academic Press, 2020. 6. Digital Signal Processing – Principles, Algorithms and Applications, John G

Proakis& Dimitris G Manolakis, Prentice Hall of India, Fourth Edition, 2014



1 Module 1 1.1 Basic structures of FIR filters-direct and cascade forms, linear phase. 2

1.2 Design of FIR Digital Filters: Use of window functions like Rectangular, Hanning, Hamming, Bartlett and Kaiser. 3

1.3 Applications of FIR filter in artifact removal: Artifacts associated with ECG monitoring- Base line wander, motion artifact and power line interference.

2

1.4 Artifact removal (Base line wander) by Moving average/ FIR filter. 2

2 Module 2

2.1 Basic structures- direct, cascade and parallel forms. 2

2.2 Design of an IIR Digital Filter from an Analog Filter: Impulse invariant and Bilinear Transformations 3

2.3 Characteristics of filters - Butterworth approximations. 2

2.4 Application of IIR filter to remove the stationary power-line interference from Bio signals. 2

3 Module 3 3.1 The Periodogram, Bartlett, Welch methods 3 3.2 Blackman-Tukey Method. 2 3.3 Analysis of Heart Rate Variability using spectral estimation techniques. 2

3.4 Analysis of Auditory Evoked Potential (AEPs) using spectral estimation techniques. 2

4 Module 4 4.1 Auto Regressive (AR)- The Autocorrelation (Yule-Walker) Method. 2

4.2 Moving average (MA) and Autoregressive Moving Average (ARMA) models. 3


49

4.3 Application of A R Modelling of Seizure EEG and Surface EMG. 2 4.4 AR Moving Average Modelling of Diastolic Heart Sounds. 2 5 Module 5

5.1 P, QRS and T wave detection from ECG, Derivative based Approaches for QRS detection, 3

5.2 Pan Tompkins Algorithm for QRS Detection and heart rate measurement 2

5.3 Analysis of heart rate variability - time domain method and frequency domain methods. 2

5.4 Dicrotic Notch Detection, Segmentation of PCG into systolic and diastolic parts. 2


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EBT383 PRINCIPLES OF BIOMEDICAL IMAGING


VAC 4 0 0 4

Preamble: This course aims to introduce the students to the physical principles underlying X-ray, Computed Tomography, Nuclear Magnetic Resonance and Intraoperative imaging techniques that are useful in diagnosis. Prerequisite: NIL Course Outcomes: After the completion of the course the student will be able to

CO 1 Explain the concepts of X-radiography CO 2 Analyse the physics of Computed tomography and Nuclear medicine imaging. CO 3 Interpret the physical principle behind the formation of Ultrasound medical images. CO 4 Describe the principle of nuclear magnetic resonance imaging. CO 5 Identify various intraoperative imaging methods and their applications



CO 1 3 2 1 1 1 1 CO 2 3 2 1 1 1 1 CO 3 3 2 1 1 1 1 CO 4 3 2 1 1 1 1 CO 5 3 2 1 1 1 1

Assessment Pattern




Mark distribution


150 50 100 3 hours




51

Continuous Assessment Test (2 numbers) : 25 marks Assignment/Quiz/Course project : 15 marks End Semester Examination Pattern: There will be two parts; Part A and Part B. Part A contain 10 questions with 2 questions from each module, having 3 marks for each question. Students should answer all questions. Part B contains 2 questions from each module of which student should answer any one. Each question can have maximum 2 sub-divisions and carry 14 marks.


Course Outcome 1 (CO1): Review the concepts of X-radiography

1. Summarize the principle of image formation in conventional planar radiography. 2. List the interactive processes between X-ray and body tissues. 3. Identify the essential components of a digital radiographic system

Course Outcome 2 (CO2): Analyse the physics Computed tomography and nuclear medicine imaging.

1. How nuclear imaging can be complementary to conventional imaging? 2. Differentiate tomographic imaging from conventional radiography. 3. Compare PET and SPECT.

Course Outcome 3(CO3):Interpret the physical principle behind the origination of

Ultrasound medical images.

1. What is the principle of diagnostic imaging using ultrasound? 2. How do you choose US transducer frequency for various depth of penetration? 3. Identify the components of an Ultrasound imaging system.

Course Outcome 4 (CO4): Review the principle of nuclear magnetic resonance

imaging.

1. Elaborate the physics of image formation in MRI. 2. Summarize the components of MRI instrumentation. 3. Identify the contrast giving mechanisms available in MRI.

Course Outcome 5 (CO5): Identify various intraoperative imaging methods and their

applications

1. Explain ultrasound technique in intra operative imaging 2. What is photo acoustic imaging? 3. Explain how echo planar imaging is suitable for real time intra operative imaging


52


Total Pages: 2 Reg No.:_______________ Name:__________________________

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY FIFTH SEMESTER B.TECH DEGREE EXAMINATION,

Course Code: EBT 383 Course Name: Principles of Biomedical Imaging


PART A Answer all questions, each carries 3 marks. 10x3=30marks 1 Draw the energy spectrum of a beam emitted from an X-ray source. (3) 2 Differentiate between line spectra and characteristic spectra (3) 3 What is CT number? (3) 4 Find two applications of SPECT imaging in medicine. (3) 5 Differentiate A mode and B mode display formats. (3) 6 State the Doppler principle and find its application in ultrasound

imaging. (3)

7 What is the use of gradient coils in MRI? (3) 8 List two important clinical applications of MRI (3) 9 Give any one typical applications of ultrasound guided surgery (3) 10 What is echo planar imaging? (3)

PART B Answer five full questions, each carries 14 marks.

11 a) Identify the major interactive processes between the X-rays and body tissues. (7)

b) With the help of a diagram explain the working of a Coolidge tube (7)

OR

12. a) Explain the set up for a digital radiography system. (7)

b) With help of a block diagram explain the set up for a digital fluoroscopic system. (7)

13 a) Demonstrate physics of a nuclear medicine imaging system with suitable schematics. (10)

b) List any two applications of PET. (4)


53

OR

14 a) Discuss various generations of CT scanners and illustrate how image quality has been enhanced through generations (7)

b) Analyse the working of a Gamma camera. (7)

15 a) Identify the physical principles and theory of image generation in Ultrasound imaging. (8)

b) Summarize the important modes of image display in Ultrasound. (6)

OR

16 a) Describe the important parameters related to ultrasound transducers and describe it’s working. (8)

b) Explain the relationship between the depth of penetration and frequency of ultrasound (6)

17 a) List the contrast mechanisms commonly employed in MRI imaging (6)

b) Differentiate T1 and T2 relaxations in MRI. (8)

OR

18 a) Explain any two fast pulse sequences used in MRI (8)

b) Characterize the properties of magnets used in MRI. (6)

19 a) Explain how echo planar imaging is suitable for real time intraoperative imaging (8)

b) Explain how photo acoustic imaging supplement the other imaging modalities (6)

OR

20 a) Give any one application where ultrasound guided surgery is suitable. Explain the setup for that

(10)

b) Give any one typical application of CMUT in interventional imaging

(4)


54

Syllabus

Module 1:

X-ray imaging – Production of X-rays-Coolidge tube-discharge tube- diagnostic X-ray-line spectrum-Bremsstrahlung radiation-Principle of image formation- interactions of X-rays with the body- photoelectric attenuation, Compton scattering, attenuation coefficients -absorbed dose, X-ray detectors- X-ray films- Instrumentation of radiographic equipment (block diagram)- Digital radiography, Fluoroscopy and image intensifier systems, DigitalSubtraction Angiography, Digital Mammography.

Module 2:

Computed Tomography - X-ray Computed Tomography (CT): Principles of CT Imaging- Source–Detector Geometries-Generations of scanners-CT scanner (block level description)-CT number- pencil beam, fan beam projections- image reconstruction –clinical applications-Radioactive nuclide imaging-Principle of image formation-PET-SPECT scanner (block level description)- Gamma Camera-Clinical applications of nuclear medicine imaging.

Module 3:

Ultrasound Imaging: Diagnostic Ultrasound –principle of image formation- wave characteristics- intensity, velocity. Attenuation of ultrasound -reflection, refraction, absorption, Ultrasound transducers:Principle of production-constructional details of ultrasound transducer- phased array system- modes of image display A-mode-B- Mode-M-Mode- Doppler Effect-Principle of Doppler imaging-duplex scanners - 3D/4D ultrasound scanners- Typical clinical applications of Ultrasound imaging.

Module 4:

Magnetic Resonance Imaging: Physics of nuclear magnetic resonance – Free Induction Decay (FID) -principle of image formation- instrumentation of MRI Scanner (block level) - Magnet(superconducting) -RF coils-gradient coils (concept of frequency encoding, space encoding) - pulse sequences - partial saturation recovery-inversion recovery –spin echo- fast pulse sequences- contrast mechanisms-Proton density-relaxation time T1 and T2 – flow-diffusion.

Module 5:

Intraoperative Imaging: Intraoperative imaging and image guided therapy-X-Ray Hybrid Modalities for Image Guidance-Technology of Ultrasound-Guided Therapy-Innovations in Ultrasound Instrumentation for Image Guidance-CT-Guided Interventions: Current Practice and Future Directions-Real-Time and Interactive MRI.


55

Text Books

1. Hoskins, Peter R., Kevin Martin, and Abigail Thrush, eds. Diagnostic ultrasound: physics and equipment. CRC Press, 2019.

2. Szabo, Thomas L. Diagnostic ultrasound imaging: inside out. Academic Press, 2004. 3. M Flower ,Webb’s Physics of Medical Imaging, Taylor & Francis, 2016. 4. Shah, N. Jon, ed. Hybrid MR-PET Imaging: Systems, Methods and Applications.


Applications, and Quality Control. Elsevier Health Sciences, 2015. 6. Ferenc A. Jolesz Editor, Intraoperative Imaging and Image-Guided therapy,

Springer,2008 7. Weishaupt, Dominik, Köchli, Victor D, Marincek, Borut, How does MRI work? An

Introduction to the Physics and Function of Magnetic Resonance Imaging, Springer, 2006.

Reference Books 1. Avinash C Kak, Malcolm Slaney ,Principles of Computerized Tomographic Imaging

2001 2. Hans H Schild ,MRI made easy, 2003. 3. Fenster, Aaron, and James C. Lacefield, eds. Ultrasound imaging and therapy. Taylor

& Francis, 2015 4. DuccioVolterraniPaola Anna ErbaIgnasiCarrióH. William Strauss Giuliano Mariani

Editors, Nuclear Medicine Text book, Methodology and Clinical Applications, Springer, 2019.

5. Christian, Paul E., and Kristen M. Waterstram-Rich, eds. Nuclear medicine and PET/CT: technology and techniques. Mosby/Elsevier, 2007



1 Module 1

1.1 Production of X-rays-Coolidge tube-discharge tube- diagnostic X-ray-line spectrum-Bremsstrahlung radiation-Principle of image formation 2

1.2 Interactions of X-rays with the body- photoelectric attenuation, Compton scattering, attenuation coefficients -absorbed dose 2

1.3 X-ray detectors- X-ray films 1

1.4 Instrumentation of radiographic equipment (block diagram) 1

Digital radiography, Fluoroscopy and image intensifier systems- Digital Subtraction Angiography- Digital Mammography. 3

2 Module 2


56

2.1 X-ray Computed Tomography (CT): Principles of CT Imaging- Source–Detector Geometries-Generations of scanners 3

2.2 CT scanner (block level description)-CT number 1

2.3 Pencil beam, fan beam projections- image reconstruction –clinical applications 3

2.4 Radioactive nuclide imaging-Principle of image formation-PET-SPECT scanner( block level description) 2

2.5 Gamma Camera-Clinical applications of nuclear medicine imaging. 1 3 Module 3

3.1 DiagnosticUltrasound –principle of image formation- wave characteristics- intensity, velocity. Attenuation of ultrasound -reflection, refraction, absorption.

2

3.2 Ultrasound transducers:Principle of production-constructional details of ultrasound transducer -phased array system. 3

3.3 Modes of image display A-mode-B- Mode-M-Mode- clinical applications

2

3.4 Doppler effect-Principle of Doppler imaging-duplex scanners 1

3.5 3D/4D ultrasound scanners 1

4 Module 4

4.1 Physics of nuclear magnetic resonance- FID- principle of image formation.

2

4.2 MRI instrumentation (block level) – Magnet (superconducting) -RF coils-gradient coils (concept of frequency encoding, space encoding). 3

4.3 Pulse sequences - partial saturation recovery-inversion recovery –spin echo- fast pulse sequences. 2

4.4 Contrast mechanisms-Proton density-relaxation time T1 and T2 – flow-diffusion.

2

5 Module 5

5.1 Intraoperative imaging and image guided therapy-X-Ray Hybrid Modalities for Image Guidance 3

5.2 Technology of Ultrasound-Guided Therapy-Innovations in Ultrasound Instrumentation for Image Guidance 2

5.3 CT-Guided Interventions: Current Practice and Future Directions 2

5.4 Current Practice and Future Directions-Real-Time and Interactive MRI. 2


57

EBT385 ARTIFICIAL INTELLIGENCE &

MACHINE LEARNING TECHNIQUES


VAC 4 0 0 4

Preamble: This course introduces the students about the concepts of artificial neural networks and enables to use them for different applications in Biomedical field

Prerequisite: NIL


CO 1 Examine the basic concepts of artificial intelligence, machine learning and deep

learning.

CO 2 Solve different single layer/multiple layer networks

CO 3 Develop networks to understand the concepts of associative networks and SOM

CO 4 Evaluate the concept of support vector machines

CO 5 Understand the concepts of convolutional neural networks



CO 1 3 1 1 2 CO 2 3 2 2 2 3 1 1 2 CO 3 3 2 2 1 3 1 1 2 CO 4 3 2 2 2 3 1 1 3 CO 5 3 2 2 2 3 1 1 3

Assessment Pattern

Bloom’s Category Continuous Assessment Tests End Semester Examination 1 2

Remember 10% 10% 10% Understand 20% 20% 20% Apply 30% 30% 30% Analyse 20% 20% 20% Evaluate 20% 20% 20%

Mark distribution


150 50 100 3 hours


58




Course Outcome 1 (CO1):Examine the basic concepts of artificial intelligence, machine learning and deep learning.

1. Difference between artificial intelligence and machine learning. 2. What are the different types of learning in neural networks 3 Compare different activation functions

Course Outcome 2 (CO2): Develop different single layer/multiple layer networks

1. Compare linear and logistic regression methods 2. Gradient decent algorithm and its derivation. 3. Architecture and training algorithms for perceptron networks

Course Outcome 3 (CO3):Develop networks to understand the concepts of associative

networks and SOM 1. What are associative networks. Give applications. 2. Explain the concept of Kohonen learning in self-organising maps 3. What are self-organizing maps. Explain its properties in terms of the topologies

used, selection of neighbourhood, best matching unit (BMU).

Course Outcome 4 (CO4): Evaluate the concept of support vector machines 1. Explain the concept of feature engineering in SVM 2. Different types of Kernels used in SVM 3. Applications of SVM in Biomedical field

Course Outcome 5 (CO5): Understand the concepts of deep learning networks

1. Explain the architecture of Convolutional neural networks 2. What are the advantages of using convolutional layers instead of fully connected

networks 3. What are the advantages of Adversarial Generative Networks


59


Reg No.:_______________ Name:__________________________

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY ____________SEMESTER B. TECH DEGREE EXAMINATION, ____________ 20__

Course Code: EBT385 Course Name: ARTIFICIAL INTELLIGENCE & MACHINE LEARNING

TECHNIQUES



1 Compare the supervised and unsupervised learning used in neural

networks? (3)

2 What are the different health data types (3)

3 Draw McCulloch pit neuron model for AND logic. (3)

4 What are the limitations of the “Perceptron” model? (3)

5 How energy function is calculated in Bidirectional associative networks. (3)

6 Give an application of SOM in Biomedical Engineering. (3)

7 List the different types of Kernels used in SVM (3)

8 What are support vectors in support vector machines (3)

9 Why does a Convolutional Neural Network (CNN) work better with image data?

(3)

10 4. List the supervised and unsupervised tasks in Deep Learning. (3)

PART B


MODULE 1

11 a) Differentiate AI, Machine learning and Deep learning (7)

b) Compare static learning and dynamic learning (7)

12

a) With mathematical expressions discuss the different activation

functions used in neural networks

(7)

b) Classify neural networks based on architecture and learning rules (7)

MODULE 2

13 a) Derive Gradient decent algorithm used in supervised networks (8)


60

b) What are the issues with single layer perceptron networks? How this is rectified in multi-layer networks

(6)

14

a) Using back-propagation network, find the new weights for the network shown in the following figure. The network is presented with the input pattern [2, 3] and target output 1. Use learning rate of α = 0.6 and bipolar sigmoidal activation function. Bias inputs(b1,b2,b3) to hidden layer neurons and output neuron is 1. Update the weights of the network for one epoch

(8)

b) Explain the architecture of multilayer perceptron network. (6)

MODULE 3

15

a) What are the differences between auto associative network and hetero associative network.

(5)

b) Consider a Kohonen self-organizing map with six cluster units and six input units Using squared Euclidean distance find the cluster unit closer to the input vector [0.1 0 0.3 0.6 0.2 0.3] The initial weights associated with the cluster units are

⎣⎢⎢⎢⎢⎡0.1 0.2 0.3 0.4 0.6 0.70.3 0.3 0.1 0.2 0.2 0.40 0.2 0.3 0.4 0.6 0.7

0.3 0 0 0.2 0.2 0.40.2 0.2 0.3 0.5 0 0.80.4 0.3 0.2 0.3 0.1 0.1⎦

⎥⎥⎥⎥⎤

Each row of the weight matrix corresponds to weights of each input unit to six cluster units. Using a learning rate 0.6 update the weights associated with winning cluster unit. Update the weights of the neighbourhood of radius 1.

(9)

16

a) Explain the architecture and learning in BAM network. (7)

b) What are self-organizing maps. Explain its properties in terms of the topologies used, selection of neighbourhood, best matching unit (BMU).

(7)

MODULE 4


61

17 a) What’s the “kernel trick” in SVM and how is it useful? (7)

b) What is the difference between hard margin and soft margin SVM (7)

18 a) Give an application of SVM (7)

b) What is the role of C in SVM? How does it affect the bias/variance trade-off?

(7)

MODULE 5

19

a) Explain the architecture of Convolutional neural networks (7)

b) What are the advantages of using convolutional layers instead of fully connected networks

(7)

20 a) Compare LSTM and GRU networks (4)

b) Explain the concept of deep unsupervised networks. (10)

Syllabus

Module1 Introductionto AI and Machine Learning: Definition Artificial intelligence, Machine learning, Deep learning, AI tools and learning models Types of Machine Learning - Supervised learning , Unsupervised learning Reinforcement learning, Static learning , dynamic learning, Dimensionality, Health data types Elements of AI- activation functions, Software architectures- Neural networks and fully connected networks Convolutional neural networks Clinical applications Module2 Machine learning : Linear methods, linear regression, logistic regression, k-Nearest Neighbor (KNN) Algorithm Characteristics- learning methods Evolution of neural networks- McCulloch-Pitts neuron -linear separability - Hebb network - supervised learning network: perceptron networks – Gradient descent algorithm, Back propagation- multilayer perceptron network Case studies on biomedical applications Module3 Types of Neural Networks Associative memory network: auto-associative memory network, hetero-associative memory network, BAM, Hopfield networks, Kohonen self-organizing maps, Case studies on biomedical applications Module4 Support vector machines:Support vector machines: hard-margin and soft-margin SVMs, concepts of kernels and feature spaces, basics of optimization and quadratic programming Applications in Biomedical Engineering


62

Module5: Deep learning:Convolutional Neural Networks Architectures, convolution / pooling layers, Introduction to Deep Unsupervised Learning: Autoencoders, Variational Autoencoders, Generative adversarial networks, Deep learning for image analysis,DL and Wearable Device Technology, Introduction to Recurrent Neural Networks Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU), Encoder Decoder architectures (Assignment can be implementation of Machine learning/AI/Deep learning algorithm for medical application) TextBooks:

1. TomMMitchell,―MachineLearning‖,FirstEdition,McGrawHillEducationIndiaLtd,2013.

2. Fausett, Laurene V. Fundamentals of neural networks: architectures, algorithms and applications. Pearson Education India, 2006.

3. Dash, Sujata, Biswa Ranjan Acharya, Mamta Mittal, Ajith Abraham, and Arpad G. Kelemen, eds. Deep learning techniques for biomedical and health informatics. Cham: Springer, 2020.

4. Joshi, Ameet V. Machine learning and artificial intelligence. Springer, 2020.

ReferenceBooks: 1. StephenMarsland,“MachineLearning:AnAlgorithmicPerspective”,CRCPress,2015. 2. TonJ.Cleophas,AeilkoH.Zwinderman,“MachineLearninginMedicine”,Springer,Revis

edEdition2, 2015. 3. Santosh, K. C., Sameer Antani, Devanur S. Guru, and Nilanjan Dey, eds. Medical

Imaging: Artificial Intelligence, Image Recognition, and Machine Learning Techniques. CRC Press, 2019.

4. Xing, Lei, Maryellen L. Giger, and James K. Min, eds. Artificial intelligence in medicine: technical basis and clinical applications. Academic Press, 2020.

5. Rothman, Denis. Artificial Intelligence By Example: Acquire advanced AI, machine learning, and deep learning design skills. Packt Publishing Limited, 2020.

6. Nagy, Zsolt. Artificial Intelligence and Machine Learning Fundamentals: Develop real-world applications powered by the latest AI advances. Packt Publishing Ltd, 2018.



1 Module 1 1.1 Definition Artificial intelligence, Machine learning, Deep learning, AI

tools and learning models Types of Machine Learning - Supervised learning, Unsupervised learning Reinforcement learning

3

1.2 Static learning, dynamic learning, Dimensionality, Health data types Elements of AI- activation functions

2


https://www.amazon.com/s/ref%3Ddp_byline_sr_book_1?ie=UTF8&text=Ton%2BJ.%2BCleophas&search-alias=books&field-author=Ton%2BJ.%2BCleophas&sort=relevancerank


63

1.3 Software architectures- Neural networks and fully connected networks Convolutional neural networks

2

1.4 Clinical applications of neural networks 1

2 Module 2 2.1 Linear methods, linear regression, logistic regression, k-Nearest

Neighbor (KNN) Algorithm Characteristics- learning methods 2

2.2 Evolution of neural networks- McCulloch-Pitts neuron -linear separability - Hebb network

2

2.3 Perceptron networks – Gradient descent algorithm 2

2.4 Back propagation- multilayer perceptron network Case studies on biomedical applications

2

3 Module 3 3.1 Associativememorynetwork:auto-associativememorynetwork,hetero-

associativememorynetwork 2

3.2 BAM, Energy Function. Problems 2

3.3 Hopfield networksKohonen self-organizing maps 2

3.4 Case studies on biomedical applications 2

4 Module 4 4.1 Support vector machines: hard-margin and soft-margin SVM 2

4.2 Concepts of kernels and feature spaces 2

4.3 Basics of optimization and quadratic programming 2

4.4 Applications in Biomedical Engineering 2

5 Module 5 5.1 Convolutional Neural Networks Architectures, convolution / pooling

layers 2

5.2 Introduction to Deep Unsupervised Learning: Autoencoders, Variational Autoencoders, U-Nets and V-Nets, Dense Nets

2

5.3 Generative adversarial networks, Deep learning for image analysisDL and Wearable Device Technology

2

5.4 Introduction to Recurrent Neural Networks Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU), Encoder Decoder architectures

2

5.5 Applications in Biomedical Engineering (just an overview of different applications)

2


SEMESTER V HONOURS


64

EBT393 SPEECH & AUDIO SIGNAL PROCESSING


VAC 3 1 0 4

Preamble : The students will be able to analyse speech signals to extract the characteristics and implement algorithms for processing speech and audio signals considering the properties of acoustic signals and human hearing.

Prerequisite: Thorough knowledge of biomedical signal processing concepts Course Outcomes: After the completion of the course the student will be able to CO 1 Familiarize the basic speech production and audio perception mechanism

CO 2 Implement different methods of processing speech and audio signals using time & transform domain techniques

CO 3 Analyse the methods of parametric representation of speech signals

CO 4 Apply the concepts of speech coding

CO 5 Apply various speech and audio signal processing techniques in biomedical applications

Mapping of course outcomes with program outcomes PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO1

0 PO1

1 PO1

2 CO 1 3 3 3 2 1 1 CO 2 3 3 2 2 3 1 1 1 2 2 1 CO 3 3 3 2 2 1 1 CO 4 3 3 3 1 1 1 CO 5 3 2 3 3 1 1

Assessment Pattern




Mark distribution

Total Marks CIE ESE ESE Duration 150 50 100 3 hours


65

Continuous Internal Evaluation Pattern: Attendance : 10 marks Continuous Assessment Test (2 numbers) : 25 marks Assignment/Quiz/Course project : 15 marks End Semester Examination Pattern: There will be two parts; Part A and Part B. Part A contain 10 questions with 2 questions from each module, having 3 marks for each question. Students should answer all questions. Part B contains 2 questions from each module of which student should answer anyone. Each question can have a maximum 2 subdivisions and carry 14 marks.

Course Outcome 1 (CO1): Familiarize the basic speech production and audio perception mechanism

1. What are the characteristics of vowels? Explain the vowel sound production mechanism.

2. How a lossless tube model is related to digital filters. 3. Describe the mechanisms of Vowel Perception.

Course Outcome 2 (CO2): Implement different methods of processing speech and audio signals using time & transform domain techniques

1. How the formant frequencies are estimated in speech signal 2. With related equations explain STFT 3. Explain the procedure of calculation of MFCC.

Course Outcome 3 (CO3): Analyse the methods of parametric representation of speech signals

1. State the advantage of using LPC parameters for format analysis. 2. Derive the covariance matrix of LPC analysis. 3. Describe Sinusoidal Model of speech

Course Outcome 4 (CO4): Apply the concepts of speech coding

1. Describe any one vocoder based on the CELP algorithm. 2. Draw and explain the structure of a perceptual sub band speech coder. 3. Explain harmonic coders.

Course Outcome 5 (CO5): Apply various speech and audio signal processing techniques in biomedical applications

1. Explain the speech processing steps in emotion recognition. 2. What are neurodegenerative disorders?


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3. Explain how the speech signal processing techniques are used for detection of Alzheimer's disease.


Total Pages:

Reg No.:_______________ Name:__________________________

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY SEMESTER V B. TECH DEGREE EXAMINATION

Course Code: EBT393

Course Name: SPEECH & AUDIO SIGNAL PROCESSING


Answer full questions, each carries 3 marks. 1 What is articulatory phonetics? (3) 2 What is the formant structure of speech? (3) 3 What are critical band phenomena in hearing? (3) 4 What is the relation between sound pressure level and loudness? (3) 5 Why is short time analysis carried out in processing speech signals? (3) 6 With related equations explain the terms, short time average magnitude and

short time zero crossing rate (3)

7 Differentiate between AR, MA & ARMA models (3) 8 What is HMM? Draw the state diagram of HMM. (3) 9 Distinguish between adaptive transform coders and harmonic coders (3) 10 What are the components of analysis by synthesis speech coders (3)

PART B Answer any one question, each carries 14 marks.

11 a) What is the significance of the speech production model? Analyse the acoustic modelling of the vocal tract in speech processing

(9)

b) Explain voice and unvoiced speech signals? (5)

OR 12 a) What is Pitch of aspeech signal? What are formant frequencies in speech

signal (6)

b) Explain the anatomy & physiology of speech production (8)

13 a) Distinguish between simultaneous masking & temporal masking in audio signals

(6)

b) What are auditory filter banks? Explain how human cochlea act as a frequency encoder.

(8)

OR


67

14 a) What are the stages of speech perception & Explain the speech perception model

(9)

b) What reason can you give to explain why a low-frequency tone is better able to mask a tone of higher frequency than vice versa?

(5)

15 a) Explain how cepstral analysis is used in speech signal processing, with relevant block diagram

(8)

b) Differentiate between narrow band and wideband spectrogram (6)

OR 16 a) Describe the use of autocorrelation function & short-term energy in time

domain analysis of speech signals (7)

b) Explain the frequency domain analysis of speech signals using filter banks. (7) 17 a) Explain the steps of Levinson Durbin algorithm with suitable example (8) b) Derive the expression for autocorrelation matrix in linear prediction

analysis of speech signals (6)

OR 18 a) Derive the solutions for LPC using covariance method (9) b) Explain the application of LPC parameters for pitch detection (5) 19 a) Explain how Adaptive Transform Coding is performed in speech coding (7) b) Explain in detail speaker verification system (7)

OR 20 a) Illustrate the significance of Code-Excited LPC (CELP) in speech coding (7) b) Explain how the speech signal processing techniques are used for detection

of Parkinson’s disease (7)

Syllabus

Module 1

Speech Production: - Anatomy & physiology of speech production. Speech Fundamentals: Articulatory Phonetics – Production and Classification of Speech Sounds; Articulation, Voicing, Articulatory model. Acoustic Phonetics – acoustics of speech production; Acoustic theory of speech production-Excitation,Vocal tract model, Formant structure, Pitch.

Module 2

Audio Perception: Basic anatomy of hearing System. Psycho-acoustic analysis: Sound pressure level & loudness, Auditory Filter Banks, Critical Band Structure, Absolute Threshold of Hearing, Simultaneous Masking, Temporal Masking. Speech perception: Vowel Perception

Module 3

Time and frequency domain methods for speech and audio processing Speech Analysis: - Short-Time Speech Analysis, Time domain analysis- Short time energy, short time average


68

magnitude, short time zero crossing rate, short time ACF. Frequency domain analysis- Filter Banks, STFT, Spectrogram, Formant Estimation & Analysis, Cepstral Analysis-MFCC

Module 4

Parametric representation of speech: - AR Model, ARMA model. LPC Analysis- LPC model, Auto correlation method, Covariance method. Levinson-Durbin Algorithm, Sinusoidal Model, HMM. Applications of LPC parameters as pitch detection and formant analysis.

Module 5

Speech coding: - Phase Vocoder, LPC, Sub-band coding, Adaptive Transform Coding, Harmonic Coding, Vector Quantization based Coders, CELP.Biomedical applications of speech signal processing: - Detection of neurodegenerative diseases, emotion recognition, Speaker Verification.

Textbooks

1. Thomas F. Quatieri, Discrete-Time Speech Signal Processing: Principles and Practice, Prentice Hall; ISBN: 013242942X; 1stEdition, 2001

2. Rabiner and Schafer, Digital Processing of Speech Signals, Prentice Hall,2 nd Edition 3. Deller J. R. Proakis J. G. and Hanson J. H, Discrete Time Processing of Speech

Signals, Wiley Inter science, 2010 4. Nelson Morgan and Ben Gold, Speech and Audio Signal Processing: Processing and

Perception of Speech and Music, John Wiley & Sons, ISBN: 0471351547, 2nd Edition, 2011

Reference

1. Douglas O’Shaughnessy, Speech Communications: Human & Machine, IEEE Press, 2nd Edition, 1999; ISBN: 0780334493.

2. Donald G. Childers, Speech Processing and Synthesis Toolboxes, John Wiley & Sons, September 1999; ISBN: 0471349593

3. Rabiner and Juang, Fundamentals of Speech Recognition, Prentice Hall,1st Edition, 1994ISBN-10 -0130151572


No Topic No. of

Lectures 1 Module 1

1.1 Speech Production: - Anatomy & physiology of speech production 1 1.2 Speech Fundamentals: Articulatory Phonetics – Production and

Classification of Speech Sounds 2

1.3 Articulation, Voicing, Articulatory model 1


69

1.4 Acoustic Phonetics – acoustics of speech production; Acoustic theory of speech production-Excitation

2

1.5 Vocal tract model, Formant structure, Pitch 2

2 Module 2 2.1 Audio Perception: Basic anatomy of hearing System 1 2.2 Psycho-acoustic analysis: Sound pressure level & loudness 1 2.3 Auditory Filter Banks, Critical Band Structure, Absolute Threshold of

Hearing 2

2.4 Simultaneous Masking, Temporal Masking 2 2.5 Speech perception: Vowel Perception 2 3 Module 3

3.1 Speech Analysis: - Short-Time Speech Analysis: Time domain analysis- Short time energy, short time average magnitude

1

3.2 Short time zero crossing rate, short time AC 2 3.3 Frequency domain analysis- Filter Banks 2 3.4 STFT, Spectrogram 2 3.5 Formant Estimation & Analysis, Cepstral Analysis-MFCC 3 4 Module 4

4.1 Parametric representation of speech: - AR Model, ARMA model 2 4.2 LPC Analysis- LPC model, Auto correlation method, Covariance

method 2

4.3 Levinson-Durbin Algorithm 2 4.4 Sinusoidal Model, HMM 2

4.5 Applications of LPC parameters as pitch detection and formant analysis 2

5 Module 5 5.1 Speech coding: - Phase Vocoder, LPC, Sub-band coding 2 5.2 Adaptive Transform Coding, Harmonic Coding 2 5.3 Vector Quantization based Coders, CELP 2

5.4 Biomedical applications of speech signal processing: - Detection of neurodegenerative diseases

1

5.5 Emotion recognition, Speaker Verification 2


70

EBT395 ANALOG INTEGRATED CIRCUIT DESIGN


VAC 4 0 0 4

Preamble: The Course builds the basic concepts and the design of advanced CMOS analog Integrated Circuit and focuses on the concepts of MOSFETs.The course is designed, considering the need of VLSI technology in the healthcare field.

Prerequisite: Through knowledge about solid state electronic devices.


CO 1 Develop MOS circuit model by formulating its operation.

CO 2 Analyse the large signal and small signal characteristics of MOS amplifiers.

CO 3 Examine the operation of MOS Differential Amplifiers.

CO 4 Illustrate the operation of current mirrors.

CO 5 Analyse the operation of CMOS operational amplifiers.



CO 1 3 3 1 1 1 1 CO 2 3 3 1 1 1 CO 3 3 3 1 1 1 CO 4 3 3 2 1 CO 5 3 3 2 2 3 1

Assessment Pattern




Apply 30% 30% 30%

Analyse 30% 30% 30%

Mark distribution


150 50 100 3 hours


71


Attendance : 10 marks Continuous Assessment Test (2 numbers) : 25 marks Assignment/Quiz/Course project : 15 marks (50% of the assignment shall be of circuit simulations using any of the open source tools.) End Semester Examination Pattern: There will be two parts; Part A and Part B. Part A contain 10 questions with 2 questions from each module, having 3 marks for each question. Students should answer all questions. Part B contains 2 questions from each module of which student should answer any one. Each question can have a maximum 2 sub-divisions and carry 14 marks.


Course Outcome 1 (CO1): Develop MOS circuit model by formulating its operation

1. Describe channel length modulation in MOSFET .

2. Plot ID/VDS characteristics of a MOSFET

3. Write notes on MOS capacitances.

Course Outcome 2 (CO2) :Analyse the large signal and small signal characteristics of MOS amplifiers

1. Draw the small signal equivalent circuit of a MOS Cascode stage.

2. Discuss the large signal behaviour of a common gate amplifier.

3. How the body affect the input impedance of a common gate stage?

Course Outcome 3(CO3):Analyse the operation of MOS Differential amplifiers

1. Draw the input and output characteristics of a MOS differential pair.

2. What is the small signal gain of a MOS differential pair?

3. Discuss the common mode behaviour of a MOS differential pair.

Course Outcome 4 (CO4): Design and analyse current mirrors

1. Describe the basic principle of operation of MOS current mirrors.

2. How a MOSFET is biased so as to operate as a stable current source?

3. What are the applications of MOS current mirrors?

Course Outcome 5 (CO5): Analysis of CMOS operational amplifiers.

1. Write notes on the performance parameters of CMOS operational amplifiers.

2. Discuss the design of two stage MOS op amps.


72

3. Draw and explain the operation of a single ended MOS op amp.


SET1 Total Pages: Reg No.:______________ Name:__________________________

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY FIFTH SEMESTER B.TECH DEGREE EXAMINATION

Course Code: EBT395 Course Name: ANALOG INTEGRATED CIRCUIT DESIGN


PART A Answer all questions. Each carries 3 marks

1 Draw the symbols of PMOS and NMOS. (3)

2 List out the second order effects in MOSFET? (3)

3 What is a MOS cascode stage amplifier? (3)

4 Draw the small signal model of the Common Source amplifier. (3)

5 Illustrate the circuit of a basic CMOS differential pair. (3)

6 What is the allowable value of common mode input voltage in a CMOS differential amplifier?

(3)

7 What is a MOS current mirror? (3)

8 List out the applications of MOS current mirrors in analog circuits. (3)

9 What are the drawbacks of single stage CMOS op amps? (3)

10 Draw the circuit of a folded cascade CMOS op amp. (3)

PART B

11 a) Discuss the structure of a MOSFET with necessary diagrams. (8)

b) Explain the MOS subthreshold characteristics. (6)

OR

12 a) Describe the body effect in MOS structure. (7)

b) Derive the expression for gmro in terms of ID and W/L. (7)

13 a) Plot and explain the I-O characteristics of a Common Source amplifier. (8)

b) Discuss the operation of Source follower stage and plot the I-O characteristics (6)

OR


73

14 a) How the voltage gain of a Common Source stage can be maximised? (8)

b) Describe the allowable voltages in a MOS cascode stage. (6)

15 a) Discuss the differential mode behaviour of a CMOS differential amplifier. (7)

b) Derive the differential gain of a CMOS differential pair. (7)

OR

16 a) Sketch the small signal differential gain of a CMOS differential pair. (6)

b) Discuss the common mode behaviour of a CMOS differential pair. (8)

17 a) Discuss the application of current mirrors used to bias a CMOS differential amplifier.

(7)

b) Explain the operation of a MOS cascode current mirror. (7)

OR

18 a) How a MOSFET is biased so as to operate as a stable current source? (5)

b) Explain the operation of a basic MOS current mirror. (9)

19 a) Explain the following design parameters of a CMOS op amp i)gain ii)small signal bandwidth ii)supply rejection

(9)

b) Explain the operation of a single ended CMOS op amp. (5)

OR

20 a) Calculate the input common mode voltage range and the closed loop output impedance of a unity gain CMOS op amp.

(8)

b) Explain the characteristics of CMOS op amp. (6)


74

Syllabus

Module 1

MOSFET: Structure, I-V characteristics - threshold voltage, derivation of I-V characteristics, second order effect - body effect, channel length modulation, subthreshold conduction, MOS device model - MOS capacitance, small signal model - derivation of output resistance ro and trans conductance gm.

Module 2

Single stage amplifiers: Common source amplifier - with resistive load, with diode connected load, Source follower, common gate amplifier, Cascode amplifier . (Derivation of voltage gain, input and output impedance).

Module 3

CMOS Differential amplifiers: Basic differential amplifier, qualitative analysis -differential and common mode behaviour, quantitative analysis - variation of ID and Gm with input voltage, common mode response - common mode gain, differential pair with MOS load - diode connected load, current source load, Cascode differential pair.

Module 4

Current mirrors: Basic current mirror - design, biasing the current mirror - using a MOSFET only reference circuit, power supply independent biasing, Wilson current mirror - small signal equivalent, operation of Cascode current mirror.

Module 5 CMOS Operational amplifiers:Performance parameters, CMOS single stage op amps, two stage single ended output op amps - offset voltage, low frequency small signal voltage gains of telescopic Cascode op amp, folded Cascode op amp, current mirror op amp, introduction to MCP606 CMOS op amp.CMOS IC design for healthcare – fundamentals of wireless capsule endoscope.

Text Books:

1. Behzad Razavi, “Design of Analog CMOS Integrated Circuits”, McGraw Hill Education, 2002.

2. Behzad Razavi, “Fundamentals of Microelectronics”, Wiley, 2nd edition 2013. 3. Paul R. Gray, Paul J. Hurst, S. Lewis and R. G. Meyer, “Analysis and Design of

Analog Integrated Circuits”, Wiley India, 5th Edition, 2010. 4. Jacob Baker, “CMOS Circuit Design Layout and Simulation”, Wiley-IEEE Press,

3rd edition, 2010. 5. Rasoul Dehghani, “Design of CMOS Operational Amplifiers”, Artech House, 2013.


75

6. Franco Maloberti, “Analog design for CMOS VLSI Systems, Kluwer Academic Publishers, 2001. (Current mirrors)

7. Zhihua Wang, ‎Hanjun Jiang, ‎Hong Chen, “CMOS IC Design for wireless Medical and Healthcare”, Springer, 2014.

References:

1. David A. Johns, Ken Martin, “Analog Integrated Circuit Design”, Wiley Student Edition, 2013.

2. Philip E. Allen and Douglas R. Holberg, “CMOS Analog Circuit Design”, Oxford University Press, International 2nd Edition/Indian Edition, 2010.



1 Module 1 1.1 Structure, I-V characteristics - threshold voltage, derivation of I-V

characteristics 3

1.2 Second order effect - body effect, channel length modulation, subthreshold conduction

3

1.3 MOS device models-MOS capacitance, small signal model-derivation of output resistance ro and trans conductance gm.

3

2 Module 2 2.1 Common Source amplifier- with resistive load, with diode connected

load- derivation of voltage gain , input and output impedance 3

2.2 Source follower- derivation of voltage gain , input and output impedance 2 2.3 Common Gate amplifier- derivation of voltage gain , input and output

impedance 2

2.4 Cascode amplifier- derivation of voltage gain , input and output impedance

2

3 Module 3 3.1 Basic differential amplifier, qualitative analysis-differential and

common mode behaviour 2

3.2 quantitative analysis-variation of ID and Gm with input voltage 2 3.3 common mode response-common mode gain 2 3.4 differential pair with MOS load-diode connected load, current source

load, cascode differential pair 4

4 Module 4 4.1 Basic current mirror- design 2 4.2 Biasing the current mirror- using a MOSFET only reference circuit,

power supply independent biasing 3

4.3 Simple Cascode current mirror 3 5 Module 5


76

5.1 Performance parameters, CMOS single-stage op amps 2 5.2 Two-stage single ended output op amps-offset voltage 3 5.3 Low frequency small signal voltage gains of telescopic Cascode op

amp, folded-Cascode op amp, current mirror op amp. 3

5.4 Introduction to MCP606 CMOS op amp. CMOS IC design for healthcare- fundamentals of wireless capsule endoscope

1


77

EBT397

MATHEMATICAL METHODS IN BIOMEDICAL ENGINEERING


VAC 4 0 0 4

Preamble: This course enables the student to understand different mathematical approaches in Biomedical Engineering

Prerequisite: Thorough understanding linear, nonlinear, ODE, PDE solutions using analytical and numerical methods.

Course Outcomes: After the completion of the course the student will be able to CO 1 Formulate ODE for applications in Biomedical Engineering

CO 2 Solve PDE for thermal, electrical and chemical transport mechanisms

CO 3 Find solutions for one dimensional wave equations

CO 4 Examine analytical solution for diffusion process using Bessel functions

CO 5 Analyse the nonlinear characteristics of coupled ODE’s


CO 1 3 3 2 2 2 1 1 2 CO 2 3 3 3 2 1 1 1 2 CO 3 3 3 3 2 2 1 1 2 CO 4 3 3 2 2 1 1 1 2 CO 5 3 3 3 3 2 1 1 2

Assessment Pattern



Remember 10% 10% 10% Understand 15% 15% 15% Apply 15% 15% 15% Analyse 40% 40% 40% Evaluate 20% 20% 20% Mark distribution

Total Marks CIE ESE ESE Duration 150 50 100 3 hours


78

Continuous Internal Evaluation Pattern: Attendance : 10 marks Continuous Assessment Test (2 numbers) : 25 marks Assignment/Quiz/Course project : 15 marks End Semester Examination Pattern: There will be two parts; Part A and Part B. Part A contain 10 questions with 2 questions from each module, having 3 marks for each question. Students should answer all questions. Part B contains 2 questions from each module of which student should answer any one. Each question can have maximum 2 sub-divisions and carry 14 marks.

Course Level Assessment Questions Course Outcome 1 (CO1): Formulate ODE for applications in Biomedical Engineering

1. Consider a two-segment lumped model of diffusion along a passive cable of length

L, with line resistivity r and line capacitance c, and with zero-voltage bound conditions on both ends, as shown below. The length of each of the two segments is Δx = L/2.

Write the ordinary differential equation governing the dynamics of the voltage v1(t) at the

centre of the cable. 2. What are the methods to solve ODE?

Course Outcome 2 (CO2): Solve PDE for thermal, electrical and chemical transport mechanisms

1. Formulate equations for the transport of ions across the cell membrane. 2. State the governing equation for one dimensional heat equation and necessary

conditions to solve the problem. 3. The ends A and B of a rod of length 10cm long have their temperature distribution

kept at 20oC and 70oC. Find the steady state temperature distribution of the rod

Course Outcome 3 (CO3):Find solutions for one dimensional wave equations 1. Write the boundary condition and initial conditions for solving the vibration of string

equation, if the string is subjected to initial displacement f(x) and initial velocity g(x).

2. Test Stokes’ theorem using 𝑢𝑢 = −y𝑖𝑖 + x𝑗𝑗 for a hemisphere of radius R with z>0 bounded by a circle of radius R lying in the x-y plane with centre at the origin.

Write the boundary condition and initial conditions for solving the vibration of string equation, if the string is subjected to initial displacement f(x) and initial velocity g(x).


79

Course Outcome 4 (CO4): Examine analytical solution for diffusion process using Bessel functions

1. Define the orthogonality of Bessel functions 2. Use the derivative identities of Bessel functions and integration by parts to show that

3. Expand f(x) = 1 for 0 < x < 1 in a Fourier-Bessel series of the form

Course Outcome 5 (CO5): Analyse the nonlinear characteristics of coupled ODE’s 1. Analyse the phase plane plots of coupled ODE’s 2. Plot the nullclines for Fitzhugh Nagumo neuron model 3. Explain limit cycle oscillations and stability in system of coupled ODE’s

Model Question paper Reg No.:_______________ Name:__________________________


Course Code: EBT 397

Course Name: MATHEMATICAL METHODS IN BIOMEDICAL ENGINEERING


PART A . Answer any all questions. Each carry 3 marks Marks

1 What is the difference between ordinary differential equation and

homogeneous differential equation?

(3)

2 What are the methods to solve ODE? (3)

3

Is 1-D diffusion over a bounded interval [0, L] linear space-invariant

(LSI)?

(3)

4 Find the nature of PDE

(3)

5 State the governing equation for one dimensional heat equation and

necessary conditions to solve the problem.

(3)


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6 Write the boundary condition and initial conditions for solving the

vibration of string equation, if the string is subjected to initial

displacement f(x) and initial velocity g(x).

(3)

7 In the study of forced vibrating membranes, list the conditions for

different solutions (3)

8 Define the orthogonality of Bessel functions (3) 9 What are limit cycle oscillations (3) 10 In phase plane analysis how the direction of vector field is plotted (3)


MODULE I

11

a) Solve the non-linear first-order ODE

(7)

b) Consider a two-segment lumped model of diffusion along a passive cable of length L, with line resistivity r and line capacitance c, and with zero-voltage boundary conditions on both ends, as shown below. The length of each of the two segments is Δx = L/2.

Write the ordinary differential equation governing the dynamics of the voltage v1(t) at the centre of the cable.

(7)

12

a) The rise and fall of a single bacterial population x(t) and a single nutrient y(t) in a petri dish over time t are modelled by the following set of ordinary differential equations

Where g is the intrinsic bacterial growth rate, c is the nutrition induced bacterial growth rate, d is the intrinsic nutrient decay rate, e is the nutrient consumption rate, and q(t) is the spontaneous nutrient source generation over time. At time t = 0 the nutrient is fully depleted and the bacterial population is at an initial level x0. Find the Laplace transform of the solution for the bacterial population x(t) from the initial conditions. Under what condition on the parameters g; c; d; and e is the bacteria-nutrient

(8)


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system stable? b) Consider an electrically excitable cell as shown below. The cell has

membrane capacitance Cm and leak conductance gi. The extracellular space has leak conductance ge. Both intracellular and extracellular potentials are initially zero. At time zero, a constant current electrode current Ielect(t) = I0 is injected into the extracellular space.

Write the differential equations and initial conditions governing the dynamics of the intracellular and extracellular potentials, Vi(t) and Ve(t).

(6)

MODULE II

13

a) An electrode in contact with electrolyte in tissue is modelled by the electrical circuit given below, with series resistance Rs, double-layer resistance Rd, and double-layer capacitance Cd. Initially the electrode is fully discharged, with zero voltage across the double-layer capacitance. At time zero a step voltage V (t) = V0 is applied across the electrode in order to stimulate the tissue.

Write the differential equation and initial condition governing the dynamics of the double-layer voltage Vd(t) as a function of the voltage V(t) applied across the electrode. Find the current I(t) flowing through the electrode over time.

(9)

b) What conditions are assumed in deriving the one-dimensional wave equation?

(5)

14

a) The ends A and B of a rod of length 10cm long have their temperature distribution kept at 20oC and 70oC. Find the steady state temperature distribution of the rod

(9)

b) An athlete initially at rest starts to exercise. The body is covered with thermally insulating material. Underneath the skin (x = 0) is muscle tissue of thickness L, interfacing on the other end (x = L) with vasculature. The thermal conductivity of the muscle tissue is K0, and the vasculature

(5)


82

conducts heat to maintain the tissue interface at a constant temperature T0. Specific heat of the muscle tissue is c, and mass density is ρ. Once starting to exercise (t ≥ 0), the athlete burns calories (Joules) uniformly in the muscle tissue at constant rate, with heat generation Q(x, t) = Q0. Write the partial differential equation governing temperature u(x,t) in the muscle tissue. Express initial and boundary conditions.

MODULE 3

15

a) Consider the wave equation with following boundary and initial conditions:

What is missing in this problem statement to determine a unique solution in u(x,t).

(7)

b) Let r(x,y,z)=xi+yj+zkbe the position vector field on R3 Then ∥r(x,y,z)∥2=r⋅r=x2+y2+z2 is a real-valued function. Find

a. the gradient of ∥r∥2 b. the divergence of r c. the curl of r d. the Laplacian of ∥r∥2

(7)

16

a) A system of electric charges has a charge density ρ(x,y,z) and produces an electrostatic field E(x,y,z) at points (x,y,z) in space. Gauss’ Law states that

∬E⋅dσ=4π∭ρdV

for any closed surface which encloses the charges Show that ∇⋅E=4πρ

(7)

b) Test Stokes’ theorem using 𝑢𝑢 = −y𝑖𝑖 + x𝑗𝑗 for a hemisphere of radius R with z>0 bounded by a circle of radius R lying in the x-y plane with centre at the origin.

(7)

MODULE 4

17

a) Explain how Bessel functions can be used to solve heat equation in polar coordinates

(6)

b) Use the derivative identities of Bessel functions and integration by parts to show that

(8)

18 a) Expand f(x) = 1 for 0 < x < 1 in a Fourier-Bessel series of the form

(8)


83

b) How Bessel function can be used to obtain solution of diffusion equations in cylindrical coordinate system

(6)

MODULE 5

19

a) For the following first-order ordinary differential equations, sketch solution curves y (t) by first plotting the tangent vectors specified by the differential equations.

(7)

b) Construct a Phase-Plane diagram to explain neuron dynamics using a suitable model

(7)

20

a) Sketch the nullclines in the xy phase plane, identify steady states, and draw directions of arrows on the nullclines for the following systems of first-order equations:

(8)

b) Give an example of nonlinear control system in Bioengineering (6)

Syllabus

Module 1

Introduction to Ordinary differential equations (ODEs), and initial and boundary conditions. Solution of homogeneous and inhomogeneous ODEs. Analytical and numerical techniques for solving ODEs. Introduction to Matlab/Python for ODEs

Module 2

Introduction to PDEs. One-dimensional heat equation, and its equivalents in electrical and chemical transport with applications to biomedical engineering. Flux through membranes. One-dimensional wave equation in an electrical transmission line, with open and short circuit termination. Finite difference PDE approximations.Solutions to PDEs over bounded and unbounded domains. Separation of variables. Boundary value problem and solution of the x dependent equation. Product solution of the PDEs with specified boundary conditions. Solutions over infinite domains using Fourier transforms.

Module 3

The one-dimensional wave equation. The vibrating string as a boundary value problem. Vibrating string clamped at both ends. Standing waves and summation of traveling waves.


84

Sound, and transmission of waves in gases.Review of vector calculus. Gradients, divergence, curl, and Laplacian. Transformation between Cartesian, cylindrical, and radial coordinates. Fields and potentials. Divergence theorem, and Stokes’s theorem

Module 4

Diffusion in polar and cylindrical coordinates. Analytical solution using Bessel functions. Value and flux boundary conditions in terms of roots and extrema of Bessel functions. Fourier-Bessel series expansion of initial conditions.

Module 5

Systems of coupled ODE’s Phase-Plane Methods and Qualitative Solutions Phase plane analysis of coupled ODE’s Direction Field Nullclines: Phase-Plane Diagrams of Linear Systems, Classifying Stability Characteristics Constructing a Phase-Plane Diagram for neuron dynamics-The Nullclines Steady States Limit cycle oscillations, stability Introduction to linear and nonlinear control systems in bioengineering.

Text Books:

1. Logan, J. David. Applied partial differential equations. Springer, 2014. 2. Bourne, Donald Edward. Vector analysis and Cartesian tensors. CRC Press, 2018 3. Glantz, Stanton A. Mathematics for biomedical applications. University of California

Press, 2020. 4. Edelstein-Keshet, Leah. Mathematical models in biology. Society for Industrial and

Applied Mathematics, 2005. 5. Izhikevich, Eugene M. Dynamical systems in neuroscience. MIT press, 2007. 6. Peattie, Robert A., Robert J. Fisher, Joseph D. Bronzino, and Donald R. Peterson,

eds. Transport phenomena in biomedical engineering: principles and practices. CRC Press, 2012

Reference Texts

1. Schiesser, William E. Differential Equation Analysis in Biomedical Science and Engineering: Ordinary Differential Equation Applications with R. John Wiley & Sons, 2014.

2. Schiesser, William E. Method of lines PDE analysis in biomedical science and engineering. Wiley, 2016

3. Epstein, Marcelo. Partial Differential Equations: Mathematical Techniques for Engineers. Springer, 2017.

4. Strauss, Walter A. Partial differential equations: An introduction. John Wiley & Sons, 2007.

5. Schey, Harry Moritz, and Harry M. Schey. Div, grad, curl, and all that: an informal text on vector calculus. New York: WW Norton, 2005.

6. Johnson, Christopher R. "Numerical methods for bio-electric field problems." The biomedical engineering handbook (1995).

7. Ockendon, John R., Sam Howison, Andrew Lacey, and Alexander Movchan. Applied partial differential equations. Oxford University Press on Demand, 2003.


85

8. Dunn, Stanley, AlkisConstantinides, and Prabhas V. Moghe. Numerical methods in biomedical engineering. Elsevier, 2005.

9. Logan, J. David, and William Wolesensky. Mathematical methods in biology. Vol. 96. John Wiley & Sons, 2009



1 Module 1

1.1 ODEs initial and boundary conditions. Solution of homogeneous and inhomogeneous

2

1.2 Analytical and numerical techniques for solving ODEs 3 1.3 Applications of ODE in Bioengineering 2 1.4 Introduction to Matlab/Python for ODE 2 2 Module 2

2.1 One-dimensional heat equation, and its equivalents in electrical and chemical transport with applications to biomedical engineering

2

2.2 Flux through membranes. One-dimensional wave equation in an electrical transmission line, with open and short circuit termination.

2

2.3 Solutions to PDEs over bounded and unbounded domains. Separation of variables. Boundary value problem and solution of the x dependent equation.

2

2.4 Product solution of the PDEs with specified boundary conditions. 2 2.5 Solutions over infinite domains using Fourier transforms. 1

3 Module 3 3.1 The vibrating string as a boundary value problem. Vibrating string

clamped at both ends 2

3.2 Standing waves and summation of traveling waves. Sound, and transmission of waves in gases.

2

3.3 Review of vector calculus. Gradients, divergence, curl, and Laplacian. Transformation between Cartesian, cylindrical, and radial coordinates.

3

3.4 Fields and potentials. Divergence theorem, and Stokes’s theorem 2

4 Module 4 4.1 Analytical solution using Bessel functions. 2 4.2 Value and flux boundary conditions in terms of roots and extrema of

Bessel functions. 2

4.3 Fourier-Bessel series expansion of initial conditions. 2 4.4 Applications in Biomedical Engineering 2 5 Module 5

5.1 Phase plane analysis of coupled ODE’s Direction Field Nullclines: 2 5.2 Phase-Plane Diagrams of Linear Systems, Classifying Stability 2


86

Characteristics 5.3 Constructing a Phase-Plane Diagram for a neuron dynamics-The

Nullclines Steady States Limit cycle oscillations, stability 3

5.4 Introduction to linear and nonlinear control systems in bioengineering. 2


SEMESTER VI


87

EBT302 MEDICAL IMAGE PROCESSING CATEGORY L T P CREDIT

PCC 3 1 0 4 Preamble: This course aims to provide an overview of the techniques used for medical image processing and analysis. Prerequisite: Nil Course Outcomes: After the completion of the course the student will be able to CO 1 Infer the nature of processes involved in human visual image perception. CO 2 Interpret the steps in digitization of images and the important transforms used in

image processing. CO 3 Apply methods of image enhancement both in time and transform domains. CO 4 Analyse the techniques for feature extraction, image segmentation and image

restoration. CO 5 Apply machine and deep learning algorithms for medical image analysis.



CO 1 3 - - - - - - - - 1 CO 2 3 2 - 1 - - - - - 1 CO 3 3 2 2 2 1 - - - 1 - - 2 CO 4 2 2 2 2 1 - - - 1 - - 2 CO 5 2 2 2 2 2 - - - 1 - - 2

Assessment Pattern



Remember Understand 20% 20% 20% Apply 40% 40% 40% Analyse 40% 40% 40%

Mark distribution


150 50 100 3 hours


88


Attendance : 10 marks Continuous Assessment Test (2 numbers) : 25 marks Assignment/Quiz/Course project : 15 marks End Semester Examination Pattern: There will be two parts; Part A and Part B. Part A contain 10 questions with 2 questions from each module, having 3 marks for each question. Students should answer all questions. Part B contains 2 questions from each module of which student should answer any one. Each question can have maximum 2 sub-divisions and carry 14 marks. Course Level Assessment Questions

Course Outcome 1 (CO1): Infer the nature of processes involved in human visual image perception.

1. Comment on Mach band effect, Impulse response and lateral inhibition associated with human visual system.

2. Can two monochromatic sources with different wavelengths be perceived to have the same colour?

3. How the impulse response of HVS is calculated from the Mach Band Effect. Course Outcome 2 (CO2): Interpret the steps in digitization of images and the important transforms used in image processing.

1. The image f (x, y) = 4 cos4πx cos 6πy is sampled with ∆x = ∆y = 0.5 and ∆x = ∆y = 0.2. The reconstruction filter is an ideal low-pass filter with bandwidths (∆x/2. ∆y/2). What is the reconstructed image in each case?

2. Draw the sampled spectrum of an image. Demonstrate the importance of Nyquist criterion based on the spectrum.

3. Write the mathematical expressions for the forward and inverse 2D- DFTand explain any three of its properties.

Course Outcome 3(CO3): Apply methods of image enhancement both in time and transform domains.

1. Analyse the use of interpolation in medical image enhancement. 2. Design a filter to remove high frequency noise from medical images. 3. Select an enhancement operation to remove artifacts on medical images.

Course Outcome 4 (CO4): Analyse the techniques for feature extraction, image segmentation and image restoration.

1. Choose a filter to remove the degradation caused by motion blur. 2. Select an edge detection method for boundary extraction in medical images. a. Compare region growing and region merging techniques for medical image

segmentation.


89

Course Outcome 5 (CO5): Apply machine and deep learning algorithms for medical image analysis.

1. Identify the role of deep learning methods in medical image analysis. 2. Elaborate the Convolutional Neural Network architecture. 3. Apply Convolutional Neural Network for Pancreas Segmentation in CT and MRI

images.


Total Pages: 2

Reg No.:_______________ Name:__________________________

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY SIXTH SEMESTER B.TECH DEGREE EXAMINATION

Course Code: EBT302 Course Name: MEDICAL IMAGE PROCESSING


PART A Answer all questions, each carries 3 marks. 10x3=30marks

1 Draw a monochrome vision model for Human eye and interpret the properties of

the different components of HVS in arriving at such a model.

2 How does the separability property of a two-dimensional unitary transform help

in reducing the order of computations?

3 Compare the clipping and thresholding operations for medical image

enhancement.

4 Select a suitable mask for image smoothing and explain the enhancement

operation using that.

5 Choose an appropriate filter to restore medical images.

6 Identify any two operators used for edge detection in medical images.

7 Mention any three of the spatial features used in medical image analysis.

8 Compare supervised and unsupervised classification algorithms.

9 Identify the role of Convolutional Neural Network in image analysis.

10 Analyse the importance of fusion in hybrid imaging.

PART B 5x14=70marks Answer five full questions, each carries 14 marks.

11 a) Write the mathematical expressions for the forward and inverse 2D- DFT

and explain any three of its properties.

(8)


90

b) Identify the importance and principle ofimage sampling and quantization

in medical image processing.

(6)

OR 12.

a) Elaborate three important properties and the main application of DCT in

medical image processing.

(8)

b) Draw the sampled spectrum of an image. Demonstrate the importance of

Nyquist criterion in 2-D sampling based on the spectrum.

(6)

13 a) Select a suitable mask for image smoothing and explain the enhancement

operation using that.

(8)

b) Compare the clipping and thresholding operations for medical image

enhancement.

(6)

OR 14 a) Summarize the process of histogram equalization for medical image

enhancement.

(8)

b) Design a sharpening filter to pre-process a medical image. (6)

15 a) Analyse the thresholding-based medical image segmentation. (5)

b) Suggest a method so that an image restoration problem can be solved. (9)

OR

16 a) Draw an image observation model and explain the reasons for

degradations in the observed image.

(8)

b) Compare the two region-based segmentation methods for medical

images.

(6)

17 a) Analyse the working of an unsupervised classifier for medical image

classification.

(8)

b) Describe the principle of k-nearest-Neighbor (k-NN) classifier. (6)

OR

18 a) When is the Linear Discriminant Analysis used for classification? (6)

b) Identify the role of supervised learning in medical image classification. (8)

19 a) Analyse the technique of deep learning in medical image analysis. (6)


91

b) Analyse a hybrid PET/MRI system and find the importance of image

fusion.

(8)

OR 20 a) Identify the importance of fusion in super resolution imaging. (7)

b) Apply the Convolutional Neural Network for Pancreas Segmentation in

CT and MRI images.

(7)

Syllabus

Module 1

Image perception -MTF of the visual system –monochrome vision models - color vision model. Image sampling and quantization: Two-dimensional sampling theory, Image quantization - uniform quantizer.Image transforms -Two dimensional orthogonal and unitary transforms - properties of unitary transforms, 2D DFT, Cosine, Hadamard, Haar, KL transforms.

Module 2

Image enhancement: contrast enhancement, clipping and thresholding - digital negative, intensity level slicing - bit extraction. Histogram processing, Magnification and interpolation. Image Enhancement in Spatial domain: Smoothing and sharpening operations in time domain, Filtering in frequency domain: Smoothing and sharpening frequency domain filters, Homomorphic filtering.

Module 3

Image restoration, Image degradation, Noise, Blurring, Modelling image degradation, Inverse filtering, Wiener filtering. Image segmentation- Thresholding- optimal, adaptive, Region-based methods- region growing and region merging, Boundary-based methods- edge detection and linking, boundary tracking.

Module 4

Feature recognition and classification: Features - describing the contents and the shape of objects. Object recognition and classification- discriminant analysis, k-nearest-Neighbor (k-NN) classifier. Unsupervised- k-means clustering. Supervised learning.

Module 5

Fusion of multi-modal images for Hybrid Imaging: Hybrid PET/CT Systems, PET/MRI Systems. Super resolution imaging. Deep Learning for Medical Image Analysis: Convolutional Neural Networks, Convolutional Neural Network for Pancreas Segmentation in CT and MRI images.


92

Text Books 1. Jain Anil K: Fundamentals of Digital Image Processing-, Prentice Hall of India. 1989 2. Digital Image Processing for Medical Applications, Geoff Dougherty, Cambridge

University Press, 2007. 3. Hybrid Image Processing Methods for Medical Image Examination, Venkatesan

Rajinikanth, E. Priya, Hong Lin, and Fuhua Lin, CRC PRESS, First Edition, 2021.

Reference Books 1. Digital Image Processing, Gonzalez Rafel C, Fourth Edition, 2018. 2. Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical

Informatics, Le Lu Xiaosong Wang Gustavo Carneiro Lin Yang Editors. 3. Deep Learning for Medical Image Analysis, Edited by S. Kevin Zhou Hayit

Greenspan Ding gang Shen, Academic Press, Elsevier, Ist Edition, 2017.



1 Module 1

1.1 Image perception -MTF of the visual system, Mach band effect, Monochrome vision models and colour vision model.

2

1.2 Image sampling and quantization -Two-dimensional sampling theory - Image quantization.

3

1.3 Two dimensional orthogonal and unitary transforms - properties of unitary transforms.

2

1.4 2D DFT- Cosine, Hadamard, Haar, KL transforms. 3

2 Module 2

2.1 Contrast enhancement, clipping and thresholding, digital negative, intensity level slicing, bit extraction.

2

2.2 Histogram processing, Magnification and interpolation. 2

2.3 Image Enhancement in Spatial domain: Smoothing and sharpening operations in time domain.

2

2.4 Filtering in frequency domain: Smoothing and sharpening frequency domain filters, Homomorphic filtering.

3

3 Module 3

3.1 Restoration: Image degradation, Noise, Blurring, Modelling image degradation, Inverse filtering, Wiener filtering

3

3.2 Segmentation: Thresholding- optimal, adaptive, Region-based methods- region growing and region merging.

3

3.3 Boundary-based methods- edge detection and linking, boundary tracking. 3

4 Module 4


93

4.1 Features - describing the contents and the shape of objects. 2

4.2 Object recognition and classification- discriminant analysis, k-nearest-Neighbor (k-NN) classifier.

3

4.3 Unsupervised- k-means clustering. Supervised learning. 3

5 Module 5

5.1 Hybrid PET/CT Systems, PET/MRI Systems. 3

5.2 Super resolution imaging. 2

5.3 Deep Learning for Medical Image Analysis: Convolutional Neural Networks.

2

5.4 Convolutional Neural Network for Pancreas Segmentation in CT and MRI images.

2


94

EBT304 THERAPEUTIC EQUIPMENTS


PCC 4 0 0 4

Preamble: This course describes the basic principles of different therapeutic equipment used in clinical environments.

Prerequisite: NIL


CO 1 Recognise the design concepts of cardiac pacemakers and defibrillators.

CO 2 Analyse the working principles of ventilators, heart lung machines and anaesthetic machines.

CO 3 Examine the therapeutic applications of electric current

CO 4 Explain the working principle of drug delivery devices.

CO 5 Identify the components of endoscopes used for different applications.



CO 1 3 2 2 2 - - CO 2 3 3 1 2 - - CO 3 3 2 2 2 - - CO 4 3 2 1 2 - - CO 5 3 2 1 2 - -

Assessment Pattern


Examination 1 2


Mark distribution


150 50 100 3 hours


95



Continuous Assessment Test (2 numbers) : 25 marks

Assignment/Quiz/Course project : 15 marks



Course Outcome 1 (CO1): Understand the design concepts of cardiac pacemakers and defibrillators.

1. With the help of a block diagram explain the principle of operation of a atrial sensed

ventricular trigged pacemaker. 2. Draw the block diagram of synchronized defibrillator and explain its working? 3. With the help of a diagram, explain the Lithium iodide battery for pacemakers.

Course Outcome 2 (CO2) : Analyse the working principles of ventilators heart lung machines and anaesthetic machines

1. Analyse the importance for oxygenators in heart lung machine 2. What are the major components of anaesthetic devices? 3. Illustrate a positive pressure ventilator

Course Outcome 3(CO3): Examine the therapeutic applications of electric current

1. What is short wave diathermy 2. What is principle of production of microwaves in diathermy 3. Examine different types of electrosurgery techniques with waveforms and output

power requirements

Course Outcome 4 (CO4): Explain the working principle of drug delivery devices and dialysis machines.

1. Explain the principle of operation of an infusion pump 2. With the help of a block diagram explain the basic functions of a hemodialysis

machine. 3. What are elastomeric infusers.

Course Outcome 5 (CO5): Identify the components of endoscopes used for different applications

1. Analyse the working principle of a basic endoscopic system?


96

2 Explain the principle of operation of a stroboscope. . 3. With the help of a block diagram explain Extracorporeal shock wave lithotripsy


SET Total Pages:

Reg No.:_______________ Name:__________________________

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY

SIXTH SEMESTER B. TECH DEGREE EXAMINATION, DECEMBER 2022

Course Code: EBT304

Course Name: THERAPEUTIC EQUIPMENTS


PART A

Answer all questions(3 marks). Marks

1 Classify the defibrillator based on the output waveforms. (3)

2 List the requirements for an implantable pacemaker. (3)

3 Which ventilator parameters need to be adjusted to maintain optimum minute ventilation? How is it calculated? (3)

4 List down the criteria that blood pumps must follow when used with heart lung machine. (3)

5 Describe an ultrasonic stimulator? (3)

6 How Microwaves are produced in microwave diathermy. (3)

7 What are the limitations in traditional intravenous infusion system? (3)

8 What are the different types of ultrafiltration membranes used in dialysis unit. (3)

9 Identify the components of capsule endoscopy. (3)

10 What are the applications of Cryosurgery. (3)

PART B


11 a) What are the different power sources for cardiac pacemaker (7)

b) What are current limited and voltage limited pacemakers (7)

OR


97

12 a) Write short notes on defibrillator analysers (9)

b) How synchronized mode of defibrillator is different from emergency mode.

(5)

13 a) Illustrate and explain the anaesthesia machine and breathing circuit (10)

b) What are the different methods for monitoring the depth of anaesthesia. (4)

OR

14 a) Explain the different types of gas exchange systems found in Heart lung machines

(8)

b) How CPAP differ from BiPAP (6)

15 a) With the help of a block diagram explain the principle of operation of a surgical diathermy unit.

(9)

b) What are the applications of lasers in ophthalmology? (5)

OR

16 a) How TENS is used for pain relief. With the help of a block explain a basic TENS unit.

(10)

b) What are the applications of DBS in neurological disorders? (4)

17 a) What is the working principle of an implantable infusion pump system (7)

b) How peritoneal dialysis is done. What are its limitations. (7)

OR

18 a) Explain the recent developments in drug infusion systems (7)

b) With the help of a block diagram explain the principle of operation of hemodialysis unit.

(7)

19 a) Explain the commonly used acoustic shock wave sources and the focusing methods in a lithotripter

(7)

b) Explain the technical characteristics and the components of flexible fibre optic endoscopic equipment incorporated with imaging techniques, using necessary diagrams.

(7)

OR 20 a) Write notes on (i) Bronchoscope (ii) Laparoscope (9)

b) Explain the limitations of cryosurgery. (5)


98

Syllabus

Module 1

Cardiac pacemakers: different modes of operation, external and implantable pacemakers, pacemaker standard codes. Need for cardiac pacemaker. Defibrillators: AC and DC defibrillator – Need for defibrillator – basic principle. Cardioverter defibrillator – block diagram, Implantable defibrillator and automated external defibrillator (AED)– functional block diagram. defibrillator analysers. Catheterization - IABP, Stents.

Module 2

Ventilators: Basic concepts: - Mechanics of ventilation Work of breathing Block diagram, ventilator settings, types of ventilators, Modes of ventilation - Non-Invasive, CPAP, BiPAP, Invasive modes - Controlled, Assisted, SIMV, APRV, Pressure Support, Flow sensors and FiO2 sensor. Heart lung machine (HLM) – principle of operation-functional block diagram - types of oxygenators. Extracorporeal membrane oxygenation (ECMO) machine. Anesthetic machines: Block diagram and working Gas blending and vaporizers, Anesthesia delivery system, breathing circuit. Computer aided anesthesia control

Module 3

Surgical diathermy -Basic principle and working,Electrodes and safety aspects in electrosurgical units, Electro-surgical analyzers, Neuro drills, Neuro navigation systems, Intra operative nerve monitors, Deep brain simulators. Laser surgery and its applications in ophthalmology, Short-wave diathermy, Ultrasonic therapy, Interferential current therapy, Transcutaneous electrical nerve stimulation (TENS) - applications. Transcranial magnetic stimulation (TMS) - applications Photo therapy unit

Module 4

Drug delivery systems – Different approaches for drug delivery, Drug infusion devices - Gravity Drip Systems, Infusion pump, Syringe pump, Implantable pumps, Patient Controlled Analgesia (PCA) Pumps, Elastomeric Infusers. Recent developments in drug infusion systems. Dialysis machine – haemodialysis unit Block diagram and working

Module 5

Endoscopy – Principles, types & applications. Block diagram of a fibre optic endoscope with integral TV cameras.Laparoscopes,Gastroendoscope, Bronchoscope, Stroboscope, Capsule endoscopy, Cryo-surgery techniques and application. Operating microscope, arthroscopy. Modern lithotripter systems, Extracorporeal shock wave lithotripsy (ESWL). Text Books

1. Bronzino, Joseph D and Donald R. Peterson. Biomedical engineering fundamentals. CRC press, 2014.


99

2. Kramme, Rüdiger, Klaus-Peter Hoffmann, and Robert Steven Pozos, eds. Springer handbook of medical technology. Springer Science & Business Media, 2011.

3. Lei, Yuan. Medical Ventilator System Basics: A Clinical Guide. Oxford University Press, 2017.

4. Khandpur, Raghbir Singh. Handbook of biomedical instrumentation. McGraw-Hill Education, 2004

5. Christe, Barbara L. Introduction to biomedical instrumentation: The technology of patient care. Cambridge University Press, 2017.

6. Webster, John G. Encyclopedia of medical devices and instrumentation. Vol. 4. Wiley-Interscience, 1988.

Reference Books

1. Webster, John G., ed. Medical instrumentation: application and design. John Wiley & Sons, 2009.

2. Mushin, William Woolf. "Automatic ventilation of the lungs." (1980). 3. Joseph J. Carr, John M. Brown, Introduction to Biomedical Equipment Technology,

Pearson Education (Singapore) Pvt. Ltd., 2001. 4. Geddes & Baker, Principles of Applied Biomedical Instrumentation Wiley, 1989

Biomedical Engineering Handbook, CRC Press, 1995



1 Module 1

1.1 Cardiac pacemakers: . Need for cardiac pacemaker ,different modes of operation, external and implantable pacemakers, pacemaker standard codes 2

1.2 External and internal pacemakers - programmable pacemakers – power sources 2

1.3 AC and DC defibrillator – Need for defibrillator – basic principle. Cardioverter defibrillator – block diagram, 2

1.4 Implantable defibrillator and automated external defibrillator (AED)–functional block diagram. defibrillator analysers 2

1.5 Catheterization - IABP, Stents 1

2 Module 2

2.1 Ventilators: Basic concepts: - Mechanics of ventilation Work of breathing Block diagram, ventilator settings, types of ventilators, 2

2.2 Modes of ventilation - Non-Invasive, CPAP, BiPAP, Invasive modes - Controlled, Assisted, SIMV, APRV, Pressure Support, Flow sensors and FiO2 sensor.

2

2.3 Heart lung machine (HLM) – principle of operation-functional block diagram - types of oxygenators. Extracorporeal membrane oxygenation (ECMO) machine.

3


100

2.4 Anesthetic machines: Block diagram and working Gas blending and vaporizers, Anesthesia delivery system, breathing circuit. Computer aided anesthesia control

2

3 Module 3

3.1 Surgical diathermy -Basic principle and working, Electrodes and safety aspects in electrosurgical units, Electro-surgical analyzers, 2

3.2 Neuro drills, Neuro navigation systems, Intra operative nerve monitors, Deep brain simulators 2

3.3 Laser surgery and its applications in ophthalmology, Short-wave diathermy, Ultrasonic therapy 2

3.4 Interferential current therapy, Transcutaneous electrical nerve stimulation (TENS) - applications. Transcranial magnetic stimulation (TMS) - applications Photo therapy unit

3

4 Module 4

4.1 Drug delivery systems – Different approaches for drug delivery, Drug infusion devices - 3

4.2 Gravity Drip Systems, Infusion pump, Syringe pump, Implantable pumps

2

4.3 Patient Controlled Analgesia (PCA) Pumps, Elastomeric Infusers. Recent developments in drug infusion systems 2

4.4 Dialysis machine – haemodialysis unit Block diagram and working 2

5 Module 5

5.1 Endoscopy – Principles, types & applications. Block diagram of a fibre optic endoscope with integral TV cameras. 3

5.2 Laparoscopes, Gastroendoscope, Bronchoscope, Stroboscope, Capsule endoscopy 2

5.3 Operating microscope, arthroscopy. Cryo-surgery techniques and application. 2

5.4 Modern lithotripter systems, Extracorporeal shock wave lithotripsy (ESWL). 2


101

EBT306 ARTIFICIAL NEURAL NETWORKS & APPLICATIONS


PCC 3 1 0 4

Preamble: This course enables the student to understand the basic concepts of different types of neural networks and to apply the knowledge gained to implement machine learning concepts to applications in Biomedical field.

Prerequisite: NIL


CO 1 Examine the basic concepts of machine learning algorithms, neural network architectures and its applications.

CO 2 Develop different single layer/multiple layer networks

CO 3 Develop networks to understand the concepts of ART and SOM

CO 4 Evaluate the concept of associative networks and support vector machine

CO 5 Implement algorithms for convolutional neural networks



CO 1 3 3 1 1 1 1 1 1 CO 2 3 2 2 2 3 1 1 1 CO 3 3 2 2 2 3 1 1 2 CO 4 3 2 2 1 3 2 1 2 CO 5 3 2 2 2 3 2 1 3

Assessment Pattern


Remember Understand 20% 20% 20% Apply 40% 40% 40% Analyse 20% 20% 20% Evaluate 20% 20% 20%

Mark distribution


150 50 100 3 hours



102

Attendance : 10 marks Continuous Assessment Test (2 numbers) : 25 marks Assignment/Quiz/Course project : 15 marks



Course Outcome 1 (CO1): Understand the basic concepts of machine learning algorithms, neural network architectures and its applications

1. Difference between Biological networks and neural networks

2. Classify neural networks based on network architecture

3 Compare different activation functions

Course Outcome 2 (CO2): Develop different single layer/multiple layer networks

1. Different types of single layer networks

2. Gradient decent algorithm and its derivation

3. Architecture and training algorithms for multilayer networks

Course Outcome 3 (CO3): Develop networks to understand the concepts of ART and SOM networks

1. Stability plasticity dilemma in networks and how it’s solved in adaptive resonance networks.

2. Explain the concept of Kohonen learning and self-organising maps 3. What are self-organizing maps. Explain its properties in terms of the topologies

used, selection of neighbourhood, best matching unit (BMU).

Course Outcome 4 (CO4): Evaluate the concept of associative networks and support vector machine

1. What are hetero associative networks 2. Explain the concept of energy function in associative networks 3. What is the difference between hard margin and soft margin SVM. 4. Analyse different types of Kernels used in SVM

Course Outcome 5 (CO5): Construct algorithms for convolutional neural networks

1. Explain the architecture of Convolutional neural networks 2. What are the advantages of using convolutional layers instead of fully connected

networks 3. What are the advantages of Adversarial Generative Networks


103


Reg No.:_______________ Name:__________________________


Course Code: EBT306 Course Name: ARTIFICIAL NEURAL NETWORKS & APPLICATIONS


Answer any all questions. Each carry 3 marks. Marks

1 Compare the various learning rules used in neural networks? (3)

2 Write the differences between Single Layer Perceptron (SLP) and Multilayer Perceptron (MLP).

(3)

3 What do you mean by Linear Separability? (3)

4 What are the limitations of the “Perceptron” model? (3)

5 What are the different activation functions used in back propagation network?

(3)

6 Elucidate the effect of vigilance parameter in ART network. (3)

7 What’s role of energy function in Bidirectional associative networks. (3)

8 What are Support Vectors and Hyperplanes in support vector machines (3)

9 Why does a Convolutional Neural Network (CNN) work better with image data?

(3)

10 List the supervised and unsupervised tasks in Deep Learning. (3)


MODULE I

11 a) Differentiate supervised, unsupervised and reinforcement learning

methods (7)

b) Compare Biological neuron with an artificial neuron used in neural networks

(7)

12 a) With mathematical expressions discuss the different activation

functions used in neural networks (7)

b) Classify neural networks based on architecture and learning rules (7)

MODULE 2

13 a) Derive Gradient decent algorithm used in supervised networks (9)

b) What are the issues with single layer perceptron networks? How this is rectified in multi-layer networks

(5)

14 a) Using back-propagation network, find the new weights for the network shown in the following figure. The network is presented

(9)


104

with the input pattern [2, 3] and target output 1. Use learning rate of α = 0.6 and bipolar sigmoidal activation function. Bias inputs(b1,b2,b3) to hidden layer neurons and output neuron is 1. Update the weights of the network for one epoch

b) Explain the architecture of forward only counter propagation network.

(5)

MODULE 3

15

a) What are the differences between ART1 and ART2 (4)

b) Consider a Kohonen self-organizing map with six cluster units and six input units Using squared Euclidean distance find the cluster unit closer to the input vector [0.1 0 0.3 0.6 0.2 0.3] The initial weights associated with the cluster units are similar with value 0.1 Each row of the weight matrix corresponds to weights of each input unit to six cluster units. Using a learning rate 0.6 update the weights associated with winning cluster unit. Update the weights of the neighbourhood of radius 1.

(10)

16

a) With a schematic diagram explain the F1 layer of ART2 architecture

(7)

b) What are self-organizing maps. Explain its properties in terms of the topologies used, selection of neighbourhood, best matching unit (BMU).

(7)

MODULE 4

17

a) A hetero associative net is trained by Hebb outer product rule for the input row vectors S=(x1, x2,x3,x4) to output row vectors t = (t1, t2) .Find the weight matrix

S1 = (1 1 0 0) t1(1 0) S2 = (1 1 1 0) t1(0 1) S3 = (0 0 1 1) t1(1 0) S4 = (0 1 0 0 t1(1 0)

(7)

b) What is the difference between hard margin and soft margin SVM (7)

18

a) Give an application of SVM (7)

b) Design an auto associative network to store the vectors (1 1 -1 -1),( 1 -1 1 -1), (1 -1 1 -1). Test whether the system recognises the stored vectors.

(7)

MODULE 5

19 a) Explain the architecture of Convolutional neural networks (7)

b) What are the advantages of using convolutional layers instead of fully connected networks

(7)

20 a) Compare LSTM and GRU networks (5)

b) Explain the concept of deep unsupervised networks. (9)


105

Syllabus Module 1

Fundamental Concepts of Artificial Neural Networks :Structure of biological neurons relevant to ANNs– Comparison Basic building blocks of ANN. Activation functions, McCulloch-Pitts Neuron Model Learning Rules-Hebbian Learning Rules, Perceptron, Delta, Competitive learning

Module 2

Single layer and Multilayer networks :Perceptron networks- single layer, multilayer, Gradient descent method, Back Propagation, algorithm Learning Rule, Architecture, training algorithm. Problems Counter Propagation Network: Full CPN, Forward only CPN, architecture, training and testing phases.

Module 3

Adaptive Resonance Theory (ART) & Self Organising feature Map (SOM) Networks Adaptive resonance Theory, Architecture ART 1 and ART 2 Learning, stability plasticity concept. Problems, Self-Organising feature maps, Kohonen network, SOM learningApplications in Biomedical Engineering

Module 4

Associative memory networks: Algorithms for pattern association Hetero associative networks, Auto associative memory networks Bidirectional associative memory networks Energy Function. Problems. Support vector machines: hard-margin and soft-margin SVMs, concepts of kernels and feature spaces, basics of optimization and quadratic programmingApplications in Biomedical Engineering

Module 5

Deep learning Networks: Convolutional Neural Networks Architectures, convolution / pooling layers, Introduction to Recurrent Neural Networks Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU), Encoder Decoder architectures Introduction to Deep Unsupervised Learning: Autoencoders, Variational Autoencoders, Adversarial Generative networks, applications in biomedical engineering. TextBooks:

1. TomMMitchell,―MachineLearning‖,FirstEdition,McGrawHillEducationIndiaLtd,2013.

2. Fausett, Laurene V. Fundamentals of neural networks: architectures, algorithms and applications. Pearson Education India, 2006.

3. Dash, Sujata, Biswa Ranjan Acharya, Mamta Mittal, Ajith Abraham, and Arpad G. Kelemen, eds. Deep learning techniques for biomedical and health informatics. Cham: Springer, 2020.

4. Joshi, Ameet V. Machine learning and artificial intelligence. Springer, 2020.


106

Reference Books: 1. StephenMarsland,“MachineLearning:AnAlgorithmicPerspective”,CRCPress,2015. 2. TonJ.Cleophas,AeilkoH.Zwinderman,“MachineLearninginMedicine”,Springer,Revis

edEdition2, 2015. 3. Santosh, K. C., Sameer Antani, Devanur S. Guru, and Nilanjan Dey, eds. Medical

Imaging: Artificial Intelligence, Image Recognition, and Machine Learning Techniques. CRC Press, 2019.

4. Xing, Lei, Maryellen L. Giger, and James K. Min, eds. Artificial intelligence in medicine: technical basis and clinical applications. Academic Press, 2020.

5. Rothman, Denis. Artificial Intelligence By Example: Acquire advanced AI, machine learning, and deep learning design skills. Packt Publishing Limited, 2020.

6. Nagy, Zsolt. Artificial Intelligence and Machine Learning Fundamentals: Develop real-world applications powered by the latest AI advances. Packt Publishing Ltd, 2018.



1 Module 1 1.1 Structure of biological neurons relevant to ANNs– Comparison Basic

building blocks of ANN. 2

1.2 Activation functions, linear, nonlinear, ReLU 1 1.3 McCulloch-Pitts Neuron Model, AND, OR, NAND, XOR

implementation 2

1.4 Learning Rules-Hebbian Learning Rule, Perceptron, Delta, Competitive

2

2 Module 2 2.1 Perceptron networks- single layer, multilayer 1 2.2 Gradient descent algorithm, Back Propagation, algorithm Learning

Rule 3

2.3 Architecture, training algorithm, problems 3 2.4 Counter Propagation Network: Full CPN, Forward only CPN 2 2.5 Architecture, training phases 1 3 Module 3

3.1 Adaptive resonance Theory, stability plasticity concept 1 3.2 Architecture ART 1 and ART 2 Learning, Problems 3 3.3 Self-Organising feature maps, Kohonen network, SOM learning 2 3.4 Applications of ART and SOM in Biomedical Engineering 2 4 Module 4

4.1 Associative memory networks Algorithms for pattern association 2 4.2 Hetero associative networks, Auto associative memory networks

Bidirectional associative memory networks 2

4.3 Energy Function. Problems 1 4.4 Support vector machines: hard-margin and soft-margin SVMs , 3




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concepts of kernels and feature spaces, basics of optimization and quadratic programming

4.5 Applications of SVM in Biomedical Engineering 1 5 Module 5

5.1 Convolutional Neural Networks Architectures, convolution / pooling layers

2

5.2 Recurrent Neural Networks LSTM, GRU, Encoder Decoder architectures

2

5.3 Introduction to Deep Unsupervised Learning: Autoencoders, Variational Autoencoders, Adversarial Generative Networks,

3

5.4 Applications in Biomedical Engineering (just an overview of different applications)

2


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CODE COURSE NAME CATEGORY L T P CREDIT EBT308 COMPREHENSIVE COURSE WORK PCC 1 0 0 1

Preamble:

The course Comprehensive Course work is designed to assess the knowledge gained by the students in the core courses in the B Tech programme in Electronics and Biomedical Engineering. The core subjects identified in the area of study is listed in the Prerequisite section of the syllabus. The course shall have an objective type written test of 50 marks similar to comprehensive examination like GATE. The pass minimum for this course is 25. The course will help the students in preparing for comprehensive examinations and improve the confidence in answering questions in objective mode. The course will be mapped to a faculty. The hour allotted for the course may be used by the students for practicing questions in core courses, library reading and for oral assessment if needed.

Prerequisite:

The students must have gone through the following courses before attending the comprehensive examination.

1. EBT201 ANATOMY & PHYSIOLOGY FOR BIOMEDICAL ENGINEERS 2. EBT202 BIOMEDICAL SIGNALS & TRANSDUCERS 3. EBT301 ANALYTICAL AND DIAGNOSTIC EQUIPMENTS 4. EBT305 MEDICAL IMAGAING TECHNIQUES 5. EBT307 INTRODUCTION TO BIOMEDICAL SIGNAL PROCESSING


CO No. Course Outcome (CO)

CO 1 Explain the core concepts in the courses listed in the prerequisite section (EBT201, EBT202, EBT301, EBT305, EBT307)

CO 2 Interpret questions asked and answer them with confidence

CO 3 Practice the comprehensive knowledge gained in basic courses in the field of Electronics and Biomedical Engineering to build confidence for appearing for a competitive examination


109


POs COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

CO 1 3 - - 2 - - 1 - - 1 - 3 CO 2 3 - - 2 - - 1 - - 1 - 3 CO 3 3 1 1 - - 2 - - - - - -

Assessment Pattern

Mark distribution

Total Marks CIE ESE ESE

Duration

50 - 50 1 Hour

End Semester Examination Pattern:

Written examination will be conducted by the University at the end of the sixth semester. The written examination will be of objective type similar to the competitive examination like GATE.Syllabus for the comprehensive examination consists of 5 modules based on following five core courses in the curriculum.

1. EBT201 ANATOMY & PHYSIOLOGY FOR BIOMEDICAL ENGINEERS 2. EBT202 BIOMEDICAL SIGNALS & TRANSDUCERS 3. EBT301 ANALYTICAL AND DIAGNOSTIC EQUIPMENTS 4. EBT305 MEDICAL IMAGAING TECHNIQUES 5. EBT307 INTRODUCTION TO BIOMEDICAL SIGNAL PROCESSING 6.

The written test will be of 50 marks with 50 multiple choice questions (10 questions from each module) with 4 choices of 1 mark each covering all the five core courses. There will be no negative marking. The pass minimum for this course is 25. The course should be mapped with a faculty and classes shall be arranged for practicing questions based on the core courses listed above.

Written examination : 50marks Total : 50 marks


110

Course Level Assessment and Sample Questions:

1. Sensitivity of a differential capacitive transducer is proportional to

A) 1/distance between plates

B) Area2

C) 1/distance between plates2

D) 1/Area2

2. A thermistor has ----------------------temperature coefficient of resistance

A) positive

B) negative

C) zero

D) None of the above

3. Distance can be measured by -----------------

A) capacitive transducer

B) LVDT

C) Strain gauge

D) All of the above

4. Contrast can be obtained from ------------- in a MRI image

A) T1

B) T2

C) diffusion

D) All of the above

5. For an ophthalmic application -------------ultra sound transducer is preferred

A) 1MHz

B) 3MHz

C) 12 MHz

D) None of these

6. Nuclear medicine images have----------------------spatial resolution compared to CT images

A) more

B) less

C). equal

D) same

7. A pacemaker pulse should occur ----------------------

A) Outside refractory


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B) Inside refractory period

C) Anywhere in the cardiac cycle

D) Outside cardiac cycle 8. The greatest volume of gas that can be inspired by voluntary effort after maximum

expiration, irrespective of time

A) vital capacity

B) functional residual capacity

C) tidal volume

D) residual volume

9. Blood flow velocity can be measured by utilizing----------------

A) Doppler effect

B) Nuclear magnetic resonance

C) Electromagnetic induction

D) All of the above

10. For prominent diffraction pattern the slit width has to be------------------

A) less than the wavelength of the light

B) Greater than the wavelength of light

C) Independent of the wavelength of light

D) Slit width is always fixed

11. A ramp signal is -------------------

A) Energy signal

B) Power signal

C) Neither energy signal nor power signal

D) Both energy and power signal 12. If Fourier Transform (FT) of x(t) is X(ω) then, FT of x(t-t0) ----------------

13. sin(t)/t is a -----------------function

A) Sampling function B) Sinc function C) Sine or cosine function D) All of the above

14. Second heart sound is caused by the closing of the . A) Tricuspidvalve B) Aorticvalve C) Bicuspidvalve


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D) Mitralvalve 15. The energy stored in a defibrillator using 16µF capacitor that is charged to a potential of 5000Vdcis .

A) 20J B) 200J C) 400J D) 800J

Syllabus

Module 1: BASIC ANATOMY&PHYSIOLOGY FOR BIOMEDICAL ENGINEERS

Structural & functional organization of human body – cells, tissues, organs & systems -their functions. Organization and functioning of nervous system, Special senses, Muscular System, endocrine system, Cardiovascular system, heart, Circulatory systems, Respiratory system and Urinary System Module 2: BIOMEDICAL SIGNALS & TRANSDUCERS

Cell Potentials: Resting membrane potential, Action potential (muscle and nerve) Bio signals: ECG, EEG, EMG- Generation of signals, applications Biosensors: Enzyme electrodes. Nanomaterial based biosensors-Applications Biomedical Transducers and Electrodes: Different types and applications, X-ray tubes--Functional blocks of X-ray machine – tubes for various applications. Module 3: ANALYTICAL AND DIAGNOSTIC EQUIPMENTS Principle and operation of analytical and diagnostic equipment used in the clinical environment, Spectrophotometers: Electrolyte Analysers Automated clinical analysers Electrophoresis- Principles, Chromatography Coulter Counters, Blood Gas Analysers Instrumentation of ECG, EEG, EMG, NIBP, PPG-Temperature measurements, Arrhythmia monitors, Ambulatory recorders- Holter monitors, Sleep apnoea monitors. Bipolar and tetrapolar circuits Audiometers Respiratory Measurements Blood flowmeters Module 4: MEDICAL IMAGAING TECHNIQUES

Fundamentals of different imaging modalities: Ultrasound imaging: Properties of acoustic waves, ultrasonic transducer deign, different types of probes, Modes of scanning, Principles of 3D/4D ultrasound Computed Tomography: Scanner configurations Different Geometries, pencil beam and cone beam projections- CT Detector Technology, Image reconstruction algorithms. Magnetic Resonance Imaging Principles of Nuclear Magnetic Resonance. Spin Echoes and T2*, Inversion Recovery, Image Reconstruction, Gradients fields - Rapid MR Imaging - MR Instrumentation, Functional MRI Radionuclide Imaging Radio-isotopes Nuclear Radiation Detectors, SPECT, PET. Hybrid Imaging, Intraoperative imaging.


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Module 5: INTRODUCTION TO BIOMEDICAL SIGNAL PROCESSING

Signal representation, Aliasing-Sampling theorem. Classification of discrete signals Properties of. LTI system- convolution- correlation - difference equation representation of discrete systems Fourier Analysis: Fourier Analysis of discrete time signals - DFT-properties FFT algorithms. Spectrum analysis & Z Transform: parametric & non parametric methods. Z transform –Properties, Inverse Z transform, Digital filters: FIR, IIR filter design Applications of biomedical signal processing

Reference Books

1. Mahin Basha - Analytical Techniques in Biochemistry-Springer US_Humana (2020)

2. RüdigerKramme, Heike Kramme, Springer Handbook of Medical Technology, Springer-Verlag Berlin Heidelberg, Year: 2011

3. Khandpur R S, Handbook of Bio-Medical Instrumentation, Tata McGraw Hill, 2nd Ed., 2003

4. Guyton and Hall: Text book of Medical Physiology,Saunders, an imprint of Elsevier Inc.12thedn, 2011

5. Richard Aston: Principles of Biomedical Instrumentation and measurements 6. Tagawa, Tatsuo, Toshiyo Tamura, and P. Ake Oberg. Biomedical sensors and

instruments. CRC press, 2019. 7. John G Proakis& Dimitris G Manolakis, Digital Signal Processing-Principles,

Algorithms and Applications, PHI, 4 th Edition, 2016 8. Rangaraj M Rangayyan: Biomedical Signal Analysis, John Wiley, 2 nd Edition,

2015. 9. Suresh R Devasahayam , Signals & Systems in Biomedical Engineering ,

Springer 2 nd Edition, 2013 10. P. Ramesh Babu: Digital Signal Processing, Scitech Publications, India, 6th

Edition, 2014. 11. Hoskins, Peter R., Kevin Martin, and Abigail Thrush, eds. Diagnostic ultrasound:

physics and equipment. CRC Press, 2019. 12. Szabo, Thomas L. Diagnostic ultrasound imaging: inside out. Academic Press,

2004. 13. M Flower ,Webb’s Physics of Medical Imaging, Taylor & Francis, 2016. 14. Shah, N. Jon, ed. Hybrid MR-PET Imaging: Systems, Methods and Applications.


Applications, and Quality Control. Elsevier Health Sciences, 2015. 16. Ferenc A. Jolesz Editor, Intraoperative Imaging and Image-Guided therapy,

Springer,2008 17. Weishaupt, Dominik, Köchli, Victor D, Marincek, Borut, How does MRI work?

An Introduction to the Physics and Function of Magnetic Resonance Imaging, Springer, 2006.


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EBL332 BIO-ENGINEERING LAB CATEGORY L T P CREDIT

PCC 0 0 3 2

Preamble: This course focuses on familiarization with the design of electronic circuits used in biomedical equipment and biosignal acquisition systems.

Prerequisite: Basic Electronics Lab and Medical Electronics Lab


CO 1 Design electronic circuits for biomedical applications

CO 2 Develop systems used in biomedical equipment which involve the interconnection

between engineering and the life sciences, including issues of patient safety

CO 3 Acquire biological signals from human body and process it

CO 4 Implement circuits using transducers for body parameter monitoring



CO 1 2 2 2 1 - - 1 2 1 1 - CO 2 2 2 2 1 - - 1 2 1 1 - CO 3 2 2 3 1 - - 1 2 1 1 1 CO 4 3 2 3 1 - - 1 2 1 1 1

Mark distribution


150 75 75 2.5 hours

Continuous Internal Evaluation Pattern: Attendance : 15 marks Continuous Assessment : 30 marks Internal Test (Immediately before the second series test) : 30 Marks End Semester Examination Pattern: The following guidelines should be followed regarding award of marks

(a)Preliminary work : 15 Marks (b)Implementing the work/Conducting the experiment : 10 Marks (c)Performance, result and inference


115

(usage of equipment and troubleshooting) : 25 Marks (d)Viva voce : 20 marks (e)Record : 5 Marks

General instructions: Practical examination to be conducted immediately after the second series test covering the entire syllabus given below. Evaluation is a serious process that is to be conducted under the equal responsibility of both the internal and external examiners. The number of candidates evaluated per day should not exceed 20. Students shall be allowed for the University examination only on submitting the duly certified record. The external examiner shall endorse the record. Course Level Assessment Questions Course Outcome 1 (CO1)

1.Design a Patient isolation circuit and observe the performance

2.Set up front end of an ECG machine and study its performance

3.Implement ESU waveform generator

Course Outcome 2 (CO2)

1. Setup a circuit for Analog to Digital converter

2. Design an Automatic gain compensator


1. Design QRS detector circuit.

2. Set up a PCG acquisition circuit and study its performance

3. Design ECG acquisition circuits


1. Design a circuit to study the temperature transducer ICs

2. Setup a circuit for Systolic and diastolic pressure measurement. List of Exercises/ Experiments

(Minimum 12 are mandatory-4 from each group)

GROUP 1

1.Patient isolation circuit

2.PCG acquisition circuit

3.ECG lead selection using 4051 IC

4.Study of IC 7107

5.Flash ADC


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GROUP 2

1. Automatic gain compensator

2. QRS detector circuit

3. Chart drive circuit for biosignal recorders

4. Systolic and diastolic pressure measurement.

5. ECG acquisition using Arduino board and ECG module (8232)

6. ECG Simulator Circuit

GROUP 3

1. Power amplifier for stylus movement

2. X-ray timer circuit

3. ESU waveform generator

4. Front end circuit of ECG machine

5. Front end circuit of photo plethysmograph

(Include one open ended experiment from each group to the students to make them

understand the concepts learned)

Reference Books

1. R E Boylstead and L Nashelsky: Electronic Devices and Circuit Theory, 9/e, Pearson Education.

2. Allan Mottershead, Electronic Devices &Circuits, Prentice Hall of India, NewDelhi, 2003.

3. Millman and Taub, Pulse, digital and Switching Waveforms, Tata McGrawHill, 2007.

4. Handbook of Biomedical Instrumentation by R S Khandpur, Second Edition 5. Encyclopedia of Medical Devices and Instrumentation Dr. John G. Webster, 2nd

Edition


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CODE COURSE NAME CATEGORY L T P CREDIT

EBD334 MINIPROJECT PWS 0 0 3 2

Preamble: This course is designed for enabling the students to apply the engineering knowledge they have imbibed to address the real-world situations/problems and find solutions. The course is also intended to estimate the ability of the students in transforming theoretical knowledge studied as part of the curriculum so far in to a working model. The students are expected to design and develop a software/hardware or hybrid project to innovatively solve a real-world problem preferably related to healthcare.

Prerequisites: Understanding on the basic concepts of electronic circuits, programming, biomedical instruments and the requirements of healthcare sector.


CO No. Course Outcome (CO)

CO 1 Make use of acquired knowledge within the selected area of technology for project development.

CO 2 Identify, discuss and justify the technical aspects and design aspects of the project with a systematic approach.

CO 3 Interpret, improve and refine technical aspects for engineering projects.

CO 4 Associate with a team as an effective team player for the development of technical projects.

CO 5 Report effectively the project related activities and findings.


POs COs

PO 1

PO 2

PO 3

PO 4

PO 5

PO 6

PO 7

PO 8

PO 9

PO 10

PO 11

PO 12

CO 1 3 3 3 3 3 3 3 3 - - - 3 CO 2 3 3 3 3 3 - 2 3 - 3 2 3 CO 3 3 3 3 3 3 2 3 3 - 2 3 3 CO 4 3 3 2 2 - - - 3 3 3 3 3 CO 5 3 - - - 2 - - 3 2 3 2 3

Assessment Pattern

The End Semester Evaluation (ESE) will be conducted as an internal evaluation based on the prototype developed, the report prepared and a viva- voce examination, conducted by a 3-member committee appointed by Head of the Department comprising of a senior faculty member of the department, project coordinator and project guide. The Committee will be evaluating the level of completion and demonstration of functionality/specifications,


118

presentation, oral examination, working knowledge and involvement of the student as an individual and a team member.

The Continuous Internal Evaluation (CIE) is conducted by evaluating the progress of the mini project through minimum of TWO reviews. At the time of the 1st review, students are supposed to propose a new system/design/idea, after completing a thorough literature study of the existing systems under their chosen area. In the 2nd review students are expected to highlight the implementation details of the proposed solution. The review committee should assess the extent to which the implementation reflects the proposed design. A well coded, assembled and completely functional product is the expected output at this stage. The final CIE mark is the average of 1st and 2nd review marks.

A zeroth review may be conducted before the beginning of the project to give a chance for the students to present their area of interest or problem domain or conduct open brain storming sessions for innovative ideas. Zeroth review will not be a part of the CIE evaluation process.

Marks Distribution

Total Marks CIE ESE

150 75 75

Continuous Internal Evaluation Pattern: Attendance : 10 marks Marks awarded by Guide : 15 marks Project Report : 10 marks Evaluation by the Committee : 40 Marks End Semester Examination Pattern: The following guidelines should be followed regarding award of marks. (a) Demonstration : 50 Marks (b) Project report : 10 Marks (d) Viva voce : 15marks

Course Plan

In this course, each group consisting of three/four members is expected to design and develop a moderately complex software/hardware system with practical application preferably related to healthcare sector. The basic concept of product design may be taken into consideration while developing the working model.

Students should identify a topic of interest in consultation with Faculty-in-charge of miniproject/Advisor. After the zeroth review project guide should be allotted for each project


119

batch and project guide should be present for the 1st and 2nd review. The major steps in the course pan are

1. Review the literature and gather information pertaining to the chosen topic. ‘

2. State the objectives and develop a methodology to achieve the objectives.

3. Carryout the design/fabrication or develop codes/programs to achieve the objectives.

4. Demonstrate the novelty of the project through the results and outputs.

The progress of the mini project is evaluated based on a minimum of two reviews. The review committee may be constituted by the Head of the Department. A project report is required at the end of the semester. The product has to be demonstrated for its full design specifications. Innovative design concepts, reliability considerations, aesthetics/ergonomic aspects taken care in the project shall be given due weightage.


SEMESTER VI PROGRAM ELECTIVE I


120

EBT312 ELECTRICAL NETWORKS & ANALYSIS

CATEGORY L T P CREDITS

PEC 2 1 0 3

Preamble: This course aims to make students able to understand the basics of electrical networks and their analysis.

Prerequisite: Basics of Electrical Engineering


CO 1 Apply circuit theorems to solve electric networks.

CO 2 Apply Laplace Transform to find steady state and transient response of electric networks.

CO 3 Analyze coupled networks.

CO 4 Analyze three-phase networks.

CO 5 Analyze two-port networks and passive filters.



CO 1 3 3 2 2 CO 2 3 3 2 2 CO 3 3 3 2 2 1 CO 4 3 3 2 2 1 CO 5 3 3 2 2 1

Assessment Pattern



Remember 20% 20% 20% Understand 40% 40% 40% Apply 40% 40% 40%

Mark distribution


150 50 100 3 hours


121


Attendance : 10 marks Continuous Assessment Test (2 numbers) : 25 marks Assignment/Quiz/Course project : 15 marks End Semester Examination Pattern: There will be two parts; Part A and Part B. Part A contain 10 questions with 2 questions from each module, having 3 marks for each question. Students should answer all questions. Part B contains 2 questions from each module, of which student should answer any one. Each question can have maximum 2 sub-divisions and carry 14 marks.


Course Outcome 1 (CO1):

1. State and explain network theorems.

2. Problems on solving circuits using network theorems.


1. Distinguish between the natural response and forced response. 2. Problems on steady state and transient analysis of RL, RC and RLC series circuitswith

DC excitation and initial conditions. 3. Problems on steady state and transient analysis of RL, RC and RLC series circuitswith

sinusoidal excitation.

Course Outcome 3(CO3):

1. Problems on mesh analysis and node analysis of transformed circuits in s-domain. 2. Problems on solution of transformed circuits including mutually coupled circuits in s

domain. Course Outcome 4 (CO4): 1. Problems on analysis of three phase networks 2. Problems on steady state analysis of three-phase three-wire and four-wire balanced

circuits. 3. Define the parameters such as Bandwidth, quality factor and draw the frequency

dependence of impedance of an RLC network. 4. Develop the impedance/admittance Vs frequency plot for the given RLC network.


1. Problems on finding Z, Y, h and T parameters of simple two port networks. 2. Problems on analysis of passive filters.


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Total Pages: 2

Reg No.:_______________ Name:__________________________

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY SIXTH SEMESTER B.TECH DEGREE EXAMINATION, _____________ 20__

Course Code: EBT312 Course Name: Electrical Networks & Analysis


Answer all questions; each question carries 3 marks. Marks

1 Apply Superposition theorem to determine the current I in the circuit shown in figure.

(3)

2 In the circuit shown in figure (1), steady state exists when switch is in position 1. At t= 0, it is moved to position 2. Determine the expression for current i(t) through the inductance for t ≥ 0.

(3)

3 Define time constant of a circuit. What is the time constant of an RL circuit? (3)

4 How are RLC networks classified according to damping ratios? Sketch the various responses when an RLC series circuit is excited by a DC source.

(3)

5 Explain the dot convention used in coupled circuits. (3)

6 Derive the s-domain equivalent circuit of an inductor carrying an initial current of Io.

(3)

7 Define quality factor. Derive quality factor for inductive and capacitive circuits. (3)

8 Draw the variation of impedance with respect to frequency of an R-L-C series circuit.

(3)

9 Derive the condition for symmetry & reciprocity in terms of T parameters. (3)

10 For a constant K filter composed of a series impedance Z, and a shunt admittance Y, discuss the derivation of image impedance.

(3)

PART B Answer one question from each module; each question carries 14 marks.

Module 1

11 a) Find the Norton’s equivalent circuit across a-b for the network shown in

figure.

(8)


123

b) Find current, ‘i’ in the network shown in Fig. using super position theorem.

(6)

OR

12 a) For the circuit shown in Fig. find the value of RL that absorbs maximum power from the circuit and the corresponding power under this condition.

(10)

b) State and explain superposition theorem using an example. (4)

Module 2

13 a) For the circuit shown in Fig. , the DPDT switch at position 2 for a long time. At t=0 sec. contact is moved from position 2 to 1 and at t= 10 sec. the contact is moved from 1 to 2. Derive a expression for the iC(t) and vC(t) in both cases. Plot variation of iC(t) and vC(t).

(8)

b) In the circuit shown in figure, steady state exists when switch is in position 1. At t= 0, it is moved to position 2. Determine the expression for current i(t) through the inductance for t ≥ 0.

(6)

OR

14 a) For the following circuit, switch ‘S’ is in position ‘a’ for a very long time. At time t = 0, the switch is thrown to position ‘b’. Find the expression for current through 5kΩ.

(10)

b) State and prove initial and final value theorem. (4)

Module 3

15 a) In the circuit shown in figure (11), draw the transformed circuit and (8)


124

determine the current i2(t) using mesh analysis. Assume the initial conditions as zeros.

b) In the circuit shown in figure (12), the switch is closed at t = 0. Determine

the voltage vo(t) for t ≥ 0.

(6)

OR

16 a) Find the expression for the current through the inductor iL(t) in a parallel RLC(three branch) circuit when a step input of I amperes is applied across it at time t = 0. Assume all initial conditions are zero. Apply Laplace transform technique.

(10)

b) Describe the variation of impedance and phase angle as a function of frequency in a series RLC circuit.

(4)

Module 4

17 a) The following load is delta connected to a 100V three phase system. Find the phase currents, line currents and total power consumed by the load.

(14)

OR

18 a) An RLC series circuit consists of a resistance of 100 Ω, an inductance of 10 mH and capacitance of 10 μF. If a voltage of 200 V is applied across the combination find (i) resonant frequency (ii) Q factor of the circuit and half power frequencies.

(8)

b) For an R-L-C series circuit with R=10 Ω, L=0.1 H and C=10 µF is excited with an alternating voltage source. Determine the impedance (i) at resonant frequency, (ii) 10 Hz above resonant frequency, and (iii) 10 Hz below resonant frequency.

(6)

Module 5

19 a) Derive the inter-relationship between Z and Y parameters (10)

b) A network is given as I1 = 2.5V1 – V2;I2 = -V1 + 5V2 .Draw its equivalent π network.

(4)

OR

20 a) Obtain h parameters of the following network:

(10)

b) Derive the design equations for a constant k low pass filter (4)

****


125

Syllabus

Module 1

Circuit theorems: DC and Sinusoidal steady state analysis of circuits with dependent and independent sources applying Superposition principle, Source transformation, Thevenin’s, Norton’s and Maximum Power Transfer theorems - Reciprocity theorem.

Module 2

Network Analysis: Transients - DC and sinusoidal response of RL, RC and RLC circuits, Initial and final conditions, Rise and decay of current, Time constant; Application of Laplace Transforms in circuit analysis – circuit elements in S domain.

Module 3

Transformed circuits in s-domain: Transform impedance/admittance of R, L and C - Transfer Function representation – Poles and zeros. Analysis of Coupled Circuits: – Dot polarity convention – Sinusoidal steady state analysis of coupled circuits - Linear Transformer as a coupled circuit - Analysis of coupled circuits in s-domain. Module 4

Three phase networks: Complex Power in sinusoidal steady state. Steady-state analysis of three-phase three-wire and four-wire balanced circuits. Resonance in Series and Parallel RLC circuits – Quality factor – Bandwidth – Impedance Vs Frequency, Admittance Vs Frequency, Phase angle Vs frequency for series resonant circuit. Module 5

Two port networks: Characterization of two port networks using Z, Y, Hybrid and Transmission parameters, Tand π representations. Passive filters – Filter fundamentals, Classification of Filters, Characteristic impedance, Design of Constant K - Low Pass, High Pass & Band Pass filters. Text Books

1. Joseph A. Edminister and MahmoodNahvi, "Theory and Problems in Electric circuits", McGraw Hill, 5th Edition, 2010.

2. Ravish R. Singh, "Network Analysis and Synthesis", McGraw-Hill Education, 2013

Reference Books

1. Hayt and Kemmerly, “Engineering Circuit Analysis”, McGraw Hill Education, New Delhi, 8thEdition, 2013.

2. Van Valkenberg, "Network Analysis", Prentice Hall India Learning Pvt. Ltd., 3rd edition, 1980.


126

3. K. S. Suresh Kumar, “Electric Circuit Analysis”, Pearson Publications, 2013. 4. Chakrabarti, "Circuit Theory Analysis and Synthesis", DhanpatRai& Co., Seventh -Revised

edition, 2018 5. R. Gupta, "Network Analysis and Synthesis", S. Chand & Company Ltd, 2010.

Course Contents And Lecture Schedule

No. Topic No. of Lectures

1 Module 1

1.1 Linearity and Superposition principle - Application to the analysis of DC and AC (sinusoidal excitation) circuits. Application of source transformation in electric circuit analysis.

2

1.2 Thevenin’s and Norton’s theorem - Application to the analysis of DC and AC circuits with dependent and independent sources. 2

1.3 Maximum power transfer theorem - DC and AC steady state analysis with dependent and independent sources. 2

1.4 Reciprocity Theorem - Application to the analysis of DC and AC Circuits 2

2 Module 2

2.1 Review of Laplace Transforms – Formulae of Laplace Transforms of common functions/signals, Initial value theorem and final value theorem, Inverse Laplace Transforms

1

2.2

Formulation of dynamic equations of RL, RC and RLC series networks and solution using Laplace Transforms – with DC excitation and initial conditions. Natural response and forced response. Time constant.

2

2.3 Formulation of dynamic equations of RL, RC and RLC series networks and solution with sinusoidal excitation. Complete solution (Solution using Laplace transforms).

2

2.4 Formulation of dynamic equations of RL, RC and RLC parallel networks and solution using Laplace Transforms – with DC and Sinusoidal excitations. Damping ratio.

2

3 Module 3

3.1 Transformed circuits in s-domain: Transformation of elements (R, L, and C) with and without initial conditions. 2

3.2 Mesh analysis and Mesh analysis of transformed circuits in s-domain. 1 3.3 Transfer Function representation – Poles and zeros. 1

3.4 Analysis of coupled circuits: mutual inductance – Coupling Coefficient- Dot polarity convention –– Conductively coupled equivalent circuits. Linear Transformer as a coupled circuit.

2

3.5 Analysis of coupled circuits in s-domain. 2

4 Module 4

4.1 Review of power, power factor, reactive and active power in sinusoidally excited circuits. Concept of complex power. 1

4.2 Steady state analysis of three-phase three-wire and four-wire balanced circuits. 2


127

4.3 Resonance in Series and Parallel RLC circuits – Quality factor – Bandwidth – Impedance Vs Frequency, Admittance Vs Frequency and Phase angleVs frequency for series resonant circuit.

3

5 Module 5

5.1 Two port networks: Terminals and Ports, Driving point and transfer functions. Voltage transfer ratio, Current transfer ratio, transfer impedance, transfer admittance, poles and zeros.

1

5.2 Z ,Y,h and T–parameters. Equivalent circuit representation. 2

5.3

Conditions for symmetry & reciprocity, relationship between network parameter sets. Interconnections of two port networks (series, parallel and cascade). 1 T-π Transformation.

2

5.4 Analysis of passive networks. Filter fundamentals, Classification of Filters, Characteristic impedance, Design of Constant K - Low Pass, High Pass & Band Pass filters

2


128

EBT322 MEDICAL INFORMATICS CATEGORY L T P CREDIT

PEC 3 0 0 3

Preamble: This course is intended for understanding the basics of health information system and advantages of using electronic health records in hospitals. Help students familiarize themselves with the concepts of healthcare analytics, asses the privacy and security risks in healthcare data & m-healthcare informatics.

Prerequisite: NIL


CO 1 Analyze the concepts of health information systems CO 2 Identify the benefits and role of electronic health records. CO 3 Assess the challenges of health information exchanges and healthcare analytics. CO 4 Appraise the security and privacy risks of healthcare data. CO 5 Familiarize the fundamentals of bioinformatics and m- Health care informatics


PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8 PO 9 PO 10 PO 11 PO 12

CO 1 2 2 1 1 1 1 - 1 - - - -

CO 2 2 1 1 2 1 1 - 1 - - - -

CO 3 2 2 2 1 3 2 - 1 - - - 1

CO 4 2 2 2 1 1 2 1 2 - - - 1

CO 5 2 1 2 1 2 2 1 1 1 1 1 1

Assessment Pattern



Remember 10 10 20 Understand 20 20 50 Apply 20 20 30

Mark distribution


150 50 100 3hours


129



Course Outcome 1 (CO1)Analyze the fundamentals of health information systems.

1. Elaborate on health informatics.

2. Examine on basic theories & models involved in healthcare informatics.

Course Outcome 2 (CO2)Identify the benefits and role of electronic health records.

1. Enlist the features of Electronic Health Records.

2. Assess the key components of Electronic Health Records

Course Outcome 3 (CO3)Assess the challenges of health information exchanges and healthcare analytics.

1. Determine the basic data standards used in health care informatics

2. Examine on the 2 main components of HIPAA Act.

Course Outcome 4 (CO4)Appraise the security and privacy risks of healthcare data.

1. How Privacy, Security & confidentiality of patient medical information is maintained.

2. Compare the external & internal Vulnerabilities associated with security of healthcare

data.

Course Outcome 5 (CO5)Familiarize the fundamentals of bioinformatics and m- Health care informatics

1. Discuss on the basics of bioinformatics.

2. Identify the opportunities & obstacles in adoption of m-health.


130


Total Pages: 3

Reg No.:_______________ Name:__________________________

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY SIXTH SEMESTER B. TECH DEGREE EXAMINATION, _____________ 20__

Course Code: EBT 322 Course Name: MEDICAL INFORMATICS


Answer all questions. Each question carries 3 marks

1 Why informatics is needed in healthcare. (3)

2 Write a short note on learning theory. (3)

3 Compare and contrast the electronic health record & electronic medical record.

(3)

4 What is the use of technology to provide healthcare at a distance? (3)

5 Explain the role of analytics in healthcare. (3)

6 What is health information exchange & why is it important? (3)

7 Why privacy & confidentiality is important in healthcare? (3)

8 What is healthcare information security? (3)

9 Discuss on the benefits of m-health. (3)

10 Write a short note on ChIP-Chip and ChIP-Seq. (3)

PART B 11 a) Discuss on Staggers & Nelson System life cycle model. (10)

b) Illustrate the ACE star model of knowledge transformation. (4)

OR

12 a) Why change theory is used as effective tool in planning & implementing change in social systems & organizations.

(9)

b) Explain the 5 internal organizational characteristics that can be used to understand how an organization will respond to an innovation

(5)

13 a) List the key components of electronic health record. (10)

b) Identify the benefits of electronic health record. (4)


131

OR

14 a) Describe the benefits &challenges of computerized order entry &clinical decision support systems.

(10)

b) Describe the obstacles implementing in electronic health record. (4)

15 a) Enlist the salient features of python. (7)

b) Describe the various components of health care analytics. (7)

OR

16 a) Define SOA &its benefits? (7)

b) Explain the linear regression model with an example. (7)

17 a) Explain the External & Internal Vulnerabilities that occurs in healthcare system.

(10)

b) Write notes on use of ICT in healthcare. (4)

OR

18 a) Describe the various physical, administrative & technical security controls for information security in healthcare

(14)

19 a) Explain the opportunities & obstacles in the adoption of m-health (9)

b) With the help of a diagram explain the basic building block of m health. (5)

OR

20 a) Explain the following principles of genetics i) Mendel and Morgan’s Legacy, ii) Disease Gene Mapping in the Genomic Era

(14)

Syllabus

Module 1

Overview of health informatics: Definition of health informatics, Theories & models underlying health informatics-Systems Theory, Chaos’s Theory, Complexity Theory, Information Theory, Diffusion of innovation theory, Learning Theory, Change Theory, System Life cycle models, Staggers & Nelson system Life cycle model, Evidence based practice & Informatics-Evidence based practice models, ACE star model of knowledge transformation, Knowledge, Data mining & Practice based medicine

Module 2

Information system in healthcare delivery: Electronic health Records– Definition, Electronic medical Record versus Electronic Health Record, EHR: components, Functions & Attributes, EHR applications used in clinical settings, benefits, Barriers to EHR adoption. Telehealth & Applications for delivering care at a distance–Technologies, Clinical Practice


132

considerations for healthcare professionals, Operational & Organizational success factors & barriers, Telehealth challenges, Clinical Decision support system in Health care

Module 3

Health information exchange & health care analytics Health information exchange-Basic definitions, The Nationwide Health Information Network (NHIN) and, NHIN Exchange &NHIN Direct, Health Information Organizations (HIOs), Federal Gateway Overview, Web Services and Service Oriented Architecture, Healthcare Analytics-Introduction, Components of healthcare analytics, Tools: SQL (basics)-SQLite, Python Features-Lists and tuples, Dictionaries, Sets, Python libraries- pandas and scikit-learn- Linear regression model, Logistic Regression

Module: 4

Healthcare security & data integrity Patient medical Information-Privacy, Confidentiality, Security-Definition, Legal & historical context, Principles, laws & Regulations, The importance of information security, Current security Vulnerabilities-External, Internal Vulnerabilities, Use of ICT in healthcare, Managing security risk with security controls-Administrative, Technical & Physical.

Module 5:

Bioinformatics & mobile computing in health care Basics for Bioinformatics- Cells, DNA and Chromosome, the Central Dogma, Genes and the Genome, DNA Sequencing, Transcriptomics and DNA Microarrays, Proteomics and Mass Spectrometer, ChIP-Chip and ChIP-Seq,Basic Principles of Genetics-Mendel and Morgan’s Legacy, Disease Gene Mapping in the Genomic Era. m-health-Introduction, Basic building block of m-Health, Old Episodic model of health care delivery, Benefits of m-health, Opportunities & obstacles in adoption of m-health

*Course-project in hospital standardization of data using m- health app*

Text Books

1. Ramona Nelson, Nancy Staggers “Health Informatics: An Interprofessional Approach “ Elsevier , 2nd Edition,2013

2. Edward H. Shortliffe, James J. Cimino “Biomedical Informatics-Computer Applications in Health Care and Biomedicine” Springer, Fourth edition, 2013

3. David J. Lubliner “An Introduction to Information Systems and Software in Medicine and Health “CRC Press, New Jersey Institute of Technology, Newark, USA,2015

4. C Willam Hanson III MD “Health care informatics “, Medical Publishing Division McGraw-Hill Education / Medical; 1st edition, 2006

5. Rick Krohn, MA, MAS, David Metcalf, PhD” mHealth: From Smartphones to Smart Systems “Himss 2012


https://www.google.co.in/search?hl=en&q=inauthor:%22Rick+Krohn,+MA,+MAS%22&tbm=bks

https://www.google.co.in/search?hl=en&q=inauthor:%22David+Metcalf,+PhD%22&tbm=bks

133

6. Vikas (Vik) Kumar “Healthcare Analytics Made Simple”Packt Publishing, Second edition ,2018

References

1. K. Schaper “Health Informatics: Digital Health Service Delivery - The Future is Now “ IOS Press ,2013

2. Penny Duquenoy, Carlisle George, Kai Kimppa “Ethical, Legal, and Social Issues in Medical Informatics”Medical Information Science Reference, New York,2008

3.Eta S. Berner “Clinical Decision Support Systems Theory and Practice” Springer, 2007

4. Rui Jiang • Xuegong Zhang • Michael Q. Zhan,” Basics of Bioinformatics”Springer, 2013



1 Module 1 1.1 Definition of health informatics, Theories & models underlying health

informatics-Systems Theory, Chaos’s Theory, Complexity Theory, Information Theory, Diffusion of innovation theory, Learning Theory, Change Theory

3

1.2 System Life cycle models, Staggers & Nelson system Life cycle model, Evidence based practice & Informatics-Evidence based practice models,

2

1.3 ACE star model of knowledge transformation, Knowledge, Data mining & Practice based medicine 2

2 Module 2 2.1 Electronic health Records– Definition, Electronic medical Record

versus Electronic Health Record, 3

2.2 EHR: components, Functions & Attributes, EHR applications used in clinical settings, benefits, Barriers to EHR adoption. Telehealth & Applications for delivering care at a distance–Technologies

2

2.3 Clinical Practice considerations for healthcare professionals, Operational & Organizational success factors & barriers, Telehealth challenges, Clinical Decision support system in Health care

2

3 Module 3 3.1 Health information exchange-Basic definitions, The Nationwide Health

Information Network (NHIN) and, NHIN Exchange &NHIN Direct, Health Information Organizations (HIOs), Federal Gateway Overview, Web Services and Service Oriented Architecture

3

3.2 Healthcare Analytics-Introduction, Components of healthcare analytics 2 3.3 Tools: SQL (basics)-SQLite, Python features-Lists and tuples,

Dictionaries, Sets, Python libraries- pandas and scikit-learn- Linear regression model, Logistic Regression

3

4 Module 4 4.1 Patient medical Information-Privacy, Confidentiality, Security-

Definition, Legal & historical context, 2


134

4.2 Principles, laws & Regulations, The importance of information security, Current security Vulnerabilities-External, Internal Vulnerabilities,

3

4.3 Use of ICT in healthcare, Managing security risk with security controls-Administrative, Technical & Physical 2

5 Module 5 5.1 Basics for Bioinformatics- Cells, DNA and Chromosome, the Central

Dogma, Genes and the Genome, DNA Sequencing, Transcriptomics and DNA Microarrays, Proteomics and Mass Spectrometer, ChIP-Chip and ChIP-Seq,

3

5.2 Basic Principles of Genetics- Mendel and Morgan’s Legacy, Disease Gene Mapping in the Genomic Era 2

5.3 m-health-Introduction, Basic building block of m-Health, Old Episodic model of health care delivery, Benefits of m-health, Opportunities & obstacles in adoption of m-health

2


135

EBT332 ADVANCED

MICROPROCESSORS AND MICROCONTROLLERS


PEC 3 0 0 3

Preamble: This course gives an insight into the architecture of advanced microprocessors and microcontrollers.

Prerequisite: EBT 206 MICROCONTROLLERS AND APPLICATIONS


CO 1 Understand the fundamentals of 8086 microprocessor architecture

CO 2 Demonstrate the features of advanced microprocessors.

CO 3 Describe the functions of the high-performance RISC architecture.

CO 4 Familiarize the basic features of GPUs .

CO 5 Describe the basic concepts of PIC microcontroller.


PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8 PO 9 PO 10 PO 11 PO 12

CO 1 3 1 - - - - - - - - - 3 CO 2 3 2 1 - - - - - - - - 3 CO 3 3 2 1 - - - - - - - - 3 CO 4 3 - 2 - - - - - - - - 3 CO 5 3 3 1 - - - - - - - - 3

Assessment Pattern




Mark distribution


150 50 100 3 hours


136


Attendance : 10 marks Continuous Assessment Test (2 numbers) : 25 marks Assignment/Quiz/Course project : 15 marks (Micro projects, based on Single On chip Computers (SoC) may be given as assignments) End Semester Examination Pattern: There will be two parts; Part A and Part B. Part A contain 10 questions with 2 questions from each module, having 3 marks for each question. Students should answer all questions. Part B contains 2 questions from each module of which student should answer any one. Each question can have maximum 2 sub-divisions and carry 14 marks. Course Level Assessment Questions


1. Discuss the architecture of 8086 microprocessor.

2. Examine the physical memory organization in 8086.

3. Describe the concept of segmented memory. What are its advantages?


1. Enlist the salient features of 80386.

2. Write notes on the paging registers.

3. Discuss the different descriptor types supported by 80386.


1. Explain the instruction pipeline in ARM7TDMI processor.

2. Classify the registers of ARM7TDMI processor.

3. Discuss the functional diagram of ARM7TDMI processor.


1.What is a GPU?

2.Which are the basic building blocks in a GPU?

3.Compare Raspberry Pi and Jetson nano.


1. Explain the working of registers used in CCP module of PIC16F877.

2. Examine the function of status register in PIC16F877.

3. Which are the registers associated with the interrupts in PIC microcontroller.


137


Total Pages: 3

Reg No.:_______________ Name:________________________

__

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY SIXTH SEMESTER B. TECH DEGREE EXAMINATION, _____________ 20__

Course Code: EBT 332 Course Name: ADVANCED MICROPROCESSORS AND

MICROCONTROLLERS Max. Marks: 100 Duration: 3 Hours

PART A Answer all questions. Each question carries 3 marks

1 How stacks are accessed in 8086? (3)

2 Write notes on segmentation in 8086. (3)

3 What are segment descriptors registers in 80386? (3)

4 Describe the paging mechanism in 80386. (3)

5 Write notes on memory formats in ARM7TDMI processor. (3)

6 List the different memory cycles in ARM7TDMI processor. (3)

7 Draw the block diagram of a GPU. (3)

8 List the peripherals in a Raspberry Pi board. (3)

9 What is the function of Brown out Reset in PIC microcontroller. (3)

10 Enlist the features of Timer 0 module in PIC16F877. (3)

PART B 11 a) Explain the different addressing modes of 8086. (9)

b) What are assembler directives? Explain with examples. (5)

OR

12 a) How does the 8086 CPU identify the 8 bit and 16 bit operations? (8)

b) Illustrate the interrupt response sequence of 8086. (6)

13 a) Describe the register organization in 80386. (10)

b) What are descriptor tables? List the descriptor tables in 80386. (4)

OR

14 a) Explain the protected mode of operation in 808386. (6)


138

b) Explain the paging operation in 80386. (8)

15 a) Explain the instruction pipeline in ARM7TDMI processor. (6)

b) Write notes on Thumb instruction set in ARM7TDMI processor. (8)

OR

16 a) Describe the functional diagram of ARM7TDMI processor. (7)

b) Discuss the functionality of the registers of ARM7TDMI processor. (7)

17 a) Explain the architecture of GPUs. (8)

b) Compare the functionalities of Raspberry Pi and Jetson Nano. (6)

OR

18 a) Write notes on the basic GPU hardware. (7)

b) Discuss the single instruction multiple thread concept. (7)

19 a) Explain the memory organization in PIC16F877 (9)

b) Which are the registers associated with the interrupts in PIC microcontroller. (5)

OR

20 a) Explain the function of status register in PIC16F877. (6)

b) Illustrate the working of registers used in CCP module of PIC16F877. (8)

Syllabus

Module 1

8086 Microprocessor: Register organization, Signal descriptions of 8086 chip, Physical Memory organization,Addressing Modes, Introduction to Stack, Interrupts & Interrupt service routines, Min mode and Max mode operation, Memory Interface, Address decoding.

Module 2

80386 Microprocessor:Salient features, Architecture and Signal Description, Register Organization. Real Address mode, Protected mode, Segmentation, Paging & Virtual modes. Pentium - General features, pipelining and super scalar architecture. Introduction to multicore processors: Limitations of single core processor - Concept of multi core processing - advantages, comparison, homogeneous and heterogeneous multicore processors -- major issues in multicore processing - Internal architecture of Intel Core2 Duo (Simple block diagram level only) - important technological features of IA processors - Comparison of Core i3, i5 and i7 processors


139

Module 3 High performance RISC architecture – ARM : ARM Processor Fundamentals: ARM category overview- Classic ARM, ARM Cortex, ARM for Embedded Applications. The ARM7TDMI programmer’s model: ARM7TDMI-S functional diagram, operating modes, Memory format-big endian and little endian, ARM registers-General purpose, CPSR, SPSR, load and store architecture. ARM instruction set.ARM based SOC:Basic system-on-chip (SoC) architecture, Raspberry Pi family- overview and general features, architecture, accessories.

Module 4

Introduction to high performance computing: Overview of GPU architecture- GPU hardware structure, GPU programming mode, GPU programming languages (basic idea), Advantages of GPU, Comparison with other parallel processing platforms, Application areas-GPU in Radiation imaging (basic idea), Raspberry Pi vs NVIDIA Jetson NANO.

Module 5

PIC 16F877 Microcontroller:Introduction to PIC architecture, 16F877 pin details and specifications, Memory organization, Special function registers, I/O ports, timer module, CCP module. Text Books

1. Advanced Microprocessors and Peripherals by K.M Bhurchandi and A. K Ray , 3rd Edition 2013

2. The Pentium Microprocessor by James L Antonakos, Pearson Education 4th Edition 2009.

3. ARM7TDMI (Rev 3) Technical Reference Manual 4. Microchip PIC16F87XA Datasheet 2003 5. Tor M . Aamodt, ‎Wilson Wai Lun Fung , ‎Timothy G. Rogers, ”General Purpose

Graphic Processor Architectures”, Morgan & Claypool Publishers,2018. 6. Derek Molloy, ”Exploring Raspberry Pi-Interfacing to the Real world with

Embedded Linux”, Wiley , 2016 7. Xun Jia, Steve B. Jiang,”GPU based high performance computing in Radiation

Therapy”, CRC Press, 2018.

References 1. Intel Microprocessors- Architecture, Programming and Interfacing by Barry B Brey,

Pearson Prentice Hall, 8th Edition, 2008

2. ARM7TDMI-S Data sheet Programmer’s Model


140



1 Module 1

1.1 Register organization, Signal descriptions of 8086 chip, Physical Memory organization 2

1.2 Addressing Modes, Introduction to Stack, Interrupts & Interrupt service routines 2

1.3 Min mode and Max mode operation, 1 1.4 Memory Interface, 1 1.5 Address decoding. 1 2 Module 2

2.1 Salient features, Architecture and Signal Description, Register Organization. 1

2.2 Real Address mode, Protected mode, Segmentation, Paging & Virtual modes. 2

2.3 Pentium - General features, pipelining and super scalar architecture. 1

2.4 Introduction to multicore processors: Limitations of single core processor - Concept of multi core processing - advantages, comparison 2

2.5 homogeneous and heterogeneous multicore processors -- major issues in multicore processing - 1

2.6 Internal architecture of Intel Core2 Duo (Simple block diagram level only) - important technological features of IA processors - Comparison of Core i3, i5 and i7 processors.

2

3 Module 3

3.1 ARM Processor Fundamentals: ARM category overview- Classic ARM, ARM Cortex, ARM for Embedded Applications. 1

3.2 The ARM7TDMI programmer’s model:ARM7TDMI-S functional diagram, operating modes 2

3.3 Memory format-big endian and little endian, ARM registers-General purpose, CPSR, SPSR, load and store architecture. ARM instruction set.

2

3.4 ARM based SOC:Basic system-on-chip (SoC) architecture, Raspberry Pi family- overview and general features, architecture, accessories. 2

4 Module 4

4.1 Overview of GPU architecture- GPU hardware structure, GPU programming mode, GPU programming languages(basic idea), Advantages of GPU

2

4.2 Comparison with other parallel processing platforms, Application areas-GPU in Radiation therapy 2

4.3 Raspberry Pi vs NVIDIA Jetson NANO. 2


141

5 Module 5

5.1 Introduction to PIC architecture 1 5.2 16F877 pin details and specifications 1 5.3 Memory organization, Special function registers 1 5.4 I/O ports, Timer module, CCP module. 3


142

EBT342 DESIGN OF BIOMEDICAL DEVICES


PEC 3 0 0 3 Preamble: This course gives an overview of design concepts for a medical device starting from generating ideas, classifying medical devices and understanding the design procedures. It aims to develop product specification, enhance quality in design are very much essential for a product design. The course looks into the manufacturing supply chain components and post market surveillance.

Prerequisite: Basic concepts of design engineering.


CO 1 Prepare documentation based on needs identification and specification preparation.

CO 2 Evaluate the design aspects of biomedical equipment and its safety.

CO 3 Identify steps in the verification and validation of the product design

CO 4 Assess the quality control and performance in manufacturing supply chain

CO 5 Familiarise with the standards and regulations for medical devices



CO 1 3 3 3 2 3 3 2 CO 2 3 3 3 2 3 2 1 2 CO 3 3 3 3 2 3 2 2 CO 4 3 3 2 1 1 3 2 2 CO 5 3 3 3 2 3 1 2

Assessment Pattern



Mark distribution


150 50 100 3 hours


143


Attendance : 10 marks Continuous Assessment Test (2 numbers) : 25 marks Assignment/Quiz/Course project : 15 marks



Course Outcome 1 (CO1):Prepare documentation based on needs identification and specification preparation.

1. Document with an example a medical device life cycle. 2. What are the different types of brain storming and idea generation techniques? 3. With the help of an example describe process of developing specification for a

medical device.

Course Outcome 2 (CO2): Evaluate the design aspects of biomedical equipment and its safety.

1. Why are human factors important in medical device design? 2. What are the common errors while designing a medical device? 3. What are the types of FMEA?

Course Outcome 3 (CO3):Identify steps in the verification and validation of the product design

1. What are the anticipated risks and roadblocks in the process of a medical device

design and how will you mitigate them? 2. Why is verification important in medical device design 3. Identify the steps in design transfer process.

Course Outcome 4 (CO4): Assess the quality control and performance in

manufacturing supply chain.

1. What are the 5 basic steps of supply chain management? 2. Explain the advances and challenges linked to bio design tools and biomanufacturing

technologies 3. With the help of a block diagram explain the risk management process.

Course Outcome 5 (CO5): Familiarise with the standards and regulations for medical devices

1. What are the regulatory guidelines for medical devices in India? 2. Explain the preparation of FDA submission (510k process), 3. What are the legal tests to validate an invention as a patent? Explain the patent

process steps.


144


Reg No.: _______________ Name: __________________________


Course Code: EBT 342

Course Name: DESIGN OF BIOMEDICAL DEVICES



1 List the generalised steps a product life cycle may follow. (3)

2 What is proof of concept? (3)

3 State the different stages of quality function deployment process. (3)

4 What are the components of product specification (3)

5 What are human factors in medical device design (3)

6 Define software design description (3)

7 What do you verify in system testing? (3)

8 What are the 5 basic steps of supply chain management? (3)

9 What are quality system regulations? (3)

10 What are design controls FDA? (3)

PART B


MODULE 1

11

a) Explain the steps in Idea feasibility/Generating concept : prototype development to prove the idea. (7)

b) Determine the classification (EU and USA) for I) A single-use scalpel ii) An x-ray imaging machine

(7)

12

a) Consider a simple medical equipment such as automatic BP monitor. Develop a list of customer needs and system-level requirements.

a. Develop the system and subsystem architecture.

b. Cascade system-level requirements to each subsystem.

(10)


145

Review the system specification

b) Differentiate between proof of concept and prototype (4)

MODULE 2

13

a) How does a FMEA process work? Explain the steps to perform a FMEA

(6)

b) Product specification is the first step in the process of transforming product ideas into approved product development efforts. What are the different factors that affect product specification?

(8)

14

a) Define software requirement specification. Explain the components of typical software requirement specification

(8)

b) What is bill of materials. How bill of materials for software is prepared. (6)

MODULE 3

15

a) Explain the three verification elements required to carry out verification of design process

(7)

b) Describe a validation life cycle model explaining the procedures followed in different phases of product development.

(7)

16

a) What is System Testing? Explain the various types and give definition with example.

(6)

b) What is the difference between design verification and design validation? What are the different methods of design verification?

(8)

MODULE 4

17

a) Explain the advances and challenges linked to bio design tools and biomanufacturing technologies

(7)

b) Differentiate between micro-manufacturing and nano-manufacturing Technologies

(7)

18 a) Explain the importance of In-Silico testing (7)

b) With the help of a block diagram explain the risk management process. (7)

MODULE 5

19 a) What are the ISO standards for medical devices? (7)

b) What are the regulatory guidelines for medical devices in India (7)

20

a) What are the legal tests to validate an invention as a patent? Explain the patent process steps.

(8)

b) What are the benefits of ISO 13485 Medical Devices? (6)


146

Syllabus

Module 1

Determining and Documenting device requirements: Idea feasibility and Generating concept: Need identification, prototype development to prove the idea, proof of concept. Device requirements: Product specification, specification review, design specification Software and / or Hardware requirement specification, Software/Hardware design description, Device Records (Case study- Automatic BP monitor, ECG machine etc.) Medical device classification

Module 2

Design Phase – Risk analysis- hazards review, risk trace matrix, Failure Mode and Effects Analysis (FMEA): Design and system FMEA, Hardware design, Software design, design reviews, Design of experiments, safety margin, environmental protection, product misuse, Biocompatibility, sterilization requirements, human factors engineering, Bill of materials preparation (mechanical/electrical/software/system). (Case study: Example drug infusion system)

Module 3

Design Verification, Product Validation and Design Transfer: Basic concepts, Design verification plan, protocols, design transfer process, software-hardware test plan for medical devices, system testing- subsystem and full device, Risk assessment of medical devices. Computer-Aided Design (CAD), and Computer-Aided Manufacturing (CAM) in biomedical device design.

Module 4

Manufacturing supply chain: Product manufacturing, Installation Qualification, Operational Qualification and Performance Qualification (IQ/OQ/PQ) protocols, Labelling-Instructions for Use (IFU), design and manufacture process, Quality assurance, audits, post market surveillance, Manufacturing supply chain- process optimization in manufacturing, Rapid prototyping-3D printing (Case study for manufacturing supply chain).

Module 5 Medical Device Standards and Regulations:Food and Drug Administration (FDA) regulations, Preparing FDA submission (510k process), European standards, International Organisation for Standardisation (ISO)- ISO-13485/14971, International Electrotechnical Commission (IEC)- IEC-60601(1-2), Indian Certification for Medical Devices (ICMED)-ICMED 13485, Safety and essential performance of medical electrical equipment, Intellectual Property (IP)- protection for medical devices. Steps for patent process. Text Books

1. Fries, Richard C. Reliable design of medical devices. CRC Press, 2012. 2. PeterOgrodnik,“MedicalDeviceDesignInnovationfromConcepttoMarket”,Elsevier,

2013.


147

3. Lam, Raymond HW, and Weiqiang Chen. Biomedical devices: materials, design, and manufacturing. Springer, 2019

4. Paul H. King,Richard C. Fries,Arthur T. Johnson,“Design of Biomedical Device andSystems”,Third Edition 2015

5. Jamnia, Ali. Introduction to product design and development for engineers. CRC Press, 2018.

Reference Books 1. Teixeira, Marie B. Design controls for the medical device industry. CRC press,

2019. 2. Ramakrishna, Seeram, Lingling Tian, Charlene Wang, Susan Liao, and Wee Eong

Teo. Medical devices: regulations, standards and practices. Woodhead Publishing, 2015.

3. Fries, Richard C., ed. Handbook of medical device design. CRC Press, 2019. 4. JackWong,,RaymondTong,

“HandbookofMedicalDeviceRegulatoryAffairsinAsia”Second Edition, 2018 5. Yock, Paul G., Stefanos Zenios, Josh Makower, Todd J. Brinton, Uday N. Kumar,

FT Jay Watkins, Lyn Denend, Thomas M. Krummel, and Christine Q. Kurihara. Biodesign: the process of innovating medical technologies. Cambridge University Press, 2015.

6. Vogel, David A. Medical device software verification, validation and compliance. Artech House, 2011.


No Topic No. of

Lectures 1 Module 1 1.1 Idea feasibility/Generating concept : prototype development to prove the

idea, proof of concept 2

1.2 Device Requirements: Product specification, Specification review, design specification,

1

1.3 Software/Hardware requirement specification, Software/Hardware design description,

1

1.4 Device History Record, Device Master Record, Design history files, Medical device classification

2

1.5 Case study for a biomedical device 1

2 Module 2

2.1 Risk analysis- hazards review, risk trace matrix, FMEA: Design and system FMEA,

2


148

2.2 Hardware design, Software design, design reviews, Design of experiments, safety margin, environmental protection, product misuse,

2

2.3 Biocompatibility – sterilization requirements 1

2.4 Human factors engineering in design 2

2.5 Bill of materials preparation (mechanical/electrical/software/system). 1

3 Module 3

3.1 Basic concepts, Design verification plan, protocols, design transfer process

2

3.2 Software-hardware test plan for medical devices, system testing- subsystem and full device

2

3.3 Risk assessment of medical devices 1

3.4 Computer-Aided Design (CAD), and Computer-Aided Manufacturing (CAM) in biomedical device design.

2

4 Module 4

4.1 Product manufacturing, Installation Qualification, Operational Qualification and Performance Qualification (IQ/OQ/PQ) protocols

2

4.2 Labelling-Instructions For Use (IFU), design and manufacture process, 2

4.3 Quality assurance, audits, post market surveillance, 1

4.4 Manufacturing supply chain, optimization in manufacturing 1

4.5 Rapid prototyping-3D printing 1

5 Module 5

5.1 Food and Drug Administration (FDA) regulations, Preparing FDA submission (510k process),

2

5.2 European standards, International Organisation for Standardisation (ISO)- ISO-13485/14971, International Electrotechnical Commission (IEC)- IEC-60601(1-2) Indian Certification for Medical Devices (ICMED)-ICMED 13485

2

5.3 Safety and essential performance of medical electrical equipment 1 5.4 Intellectual Property (IP)- protection for medical devices. Steps for

patent process. 2


149

EBT352

BIOSTATISTICS

CATEGORY L T P CREDITS

PEC 2 1 0 3

Preamble: This course aims to make students able to understand and apply the fundamental principles of biostatistics in data analysis.

Prerequisite: NIL


CO 1 Understand the basic concepts in statistics, types of data and probability distributions.

CO 2 Apply the different methods of statistical inference

CO 3 Perform analysis of variance on data obtained from a designed experiment

CO 4 Apply the principles of regression and correlation

CO 5 Understand the scope of statistics in biomedical data analysis



CO 1 3 - 2 CO 2 3 2 2 CO 3 3 2 2 CO 4 3 2 2 CO 5 3 2 2

Assessment Pattern




Mark distribution


150 50 100 3 hours


150




Course Outcome 1 (CO1): Understand the basic concepts in statistics, types of data and probability distributions.

1. Demonstrate the ways in which data can be organized and condensed.

2. Show how probability distributions can be used in calculating probabilities in medical problems.

Course Outcome 2 (CO2):Apply the different methods of statistical inference

1. Explain the need for and methods of estimation with examples.

2. Develop a method to conduct a structured hypothesis test to make statistical inferences.

Course Outcome 3 (CO3):Perform analysis of variance on data obtained from a designed experiment

1. What is ANOVA?

2. Making use of ANOVA, device a methodology to for partition the total variance computed from a data set into components

3. Show how ANOVA can be used to estimate and test hypothesis on means & variances.

Course Outcome 4 (CO4): Apply the principles of regression and correlation

1. Using examples, show how regression and correlation can be applied in medical statistical analysis?

2. How can we test the significance of a simple regression line?


1. What are the principles behind design of experiments? 2. What are the different types of designs?


151

MODEL QUESTION PAPER

Total Pages: 2

Reg No.:_______________ Name:__________________________


Course Code: EBT352 Course Name: Biostatistics



1 List out the different measures of central tendency used in statistics. (3)

2 What is probability density function? (3)

3 Define confidence interval. (3)

4 What is a null hypothesis? (3)

5 What is single factor ANOVA? (3)

6 What are the applications of ANOVA? (3)

7 Differentiate between correlation and regression analysis in statistics. (3)

8 What is a scatter diagram? (3)

9 What is categorical data? (3)

10 What is confounding? (3)


Module 1

11 The following is the systolic blood pressures recorded by a digital BP

meter of 20 individuals.

87 103 130 160 180 195 132 145 125

105 145 153 152 138 101 99 93 119

129 143

i. Calculate the sample mean, median and mode.

ii. Calculate the sample variance and standard deviation.

(10)

b) If the 1st observation had been 400 rather than 87, how would the mean and median change? (4)

OR


152

12 a) What is a random variable? What are the different types? (4)

b) In a certain population an average of 13 new cases of oesophageal

cancer are diagnosed each year. If the annual incidence of oesophageal

cancer follows a Poisson distribution, find the probability that in a given

year the number of newly diagnosed cases of oesophageal cancer will

be:

(a) Exactly 10 (b) At least eight (c) No more than

12 (d) Fewer than seven (e) Between nine and 15, inclusive

(10)

Module 2

13 a) It is desired to estimate the average number of heart beats per minute for a certain population. The average number of heart beats per minute for a sample of 49 subjects was found to be 90. Assume that these 49 patients constitute a random sample, and that the population is normally distributed with a standard deviation of 10. Construct 90, 95, and 99 percent confidence intervals for the population mean.

(9)

b) What is goodness of fit? How do we test it? (5)

OR

14 a) What do you mean by non-parametric tests? When do we use them? (4)

b) Cardiac output (liters/minute) was measured by thermo-dilution in a simple random sample of 15 post-cardiac surgical patients in the left lateral position. The results were as follows:

4.91 4.10 6.74 7.27 7.42 7.50 6.56 4.64 5.98 3.14 3.23 5.80 6.17 5.39 5.77

Using Wilcoxin signed-rank test, determine whether we can conclude on the basis of these data that the population mean is different from 5.05.

(10)

Module 3

15 a) What are the fundamental assumptions in the use of ANOVA (9)

b) Differentiate between completely randomized design and randomized complete block design (5)

OR

16 a) What are the steps adopted in the analysis of variance? (10)

b) Define the terms i) Within sum of squares ii) Between sum of squares (4)


153

iii) Total sum of squares

Module 4

17 a) How can we test the significance of a simple regression line? (7)

b) What is Spearman’s rank correlation coefficient? How do we calculate it? (7)

OR

18 a) What is multiple regression? How is it useful in statistical analysis of medical data? (10)

b) Describe the least squares method of fitting a regression line. (4)

Module 5

19 a) What are cross over designs? What are their applications in statistical data analysis? (10)

b) What do you mean by clustered binary data? (4)

OR

20 a) What is meta-analysis? What are the different methods? (10)

b) Differentiate between random effects and fixed effects models. (4)

Syllabus

Module 1

Basic concepts: Measures of central tendency – measure of dispersion – properties. Random variables – discrete and continuous – probability density function – binomial, Poisson and normal distributions – Joint probability density function – marginal and conditional distributions.

Module 2

Statistical inference: Interval estimation – mean and variance – testing of hypothesis – single population mean – difference between two population means. Hypothesis testing for categorical data – Fisher exact test – chi square distribution – Goodness of fit. Non parametric tests – sign test – Wilcoxon sign rank test – Wilcoxon rank sum test.

Module 3

Multisample inference –Introduction to analysis of variance – one way analysis of variance (fixed effects model) – hypothesis testing in one-wayanova (fixed effects model) – comparison of specific groups in one-wayanova.


154

Module 4

Regression and correlation: Fitting of regression line (least squares method) – linear regression – statistical inference on parameters from regression line – correlation coefficient – statistical inference on correlation coefficient – multiple regression – partial and multiple correlation – rank correlation coefficient. Module 5

Scope of statistics in biomedical data analysis - Statistical design of experiments for clinical and laboratory data – Study design - Measure of effect for categorical data – confounding and standardization – methods of inference for stratified categorical data – power and sample size estimation for categorical data – multiple logistic regression – meta analysis – equivalence studies - Crossover designs – clustered binary data – measurement-error method – missing data. (Basic concepts of these only) Text Books

1. W. Daniel, Biostatistics- A Foundation for Analysis in the Health Sciences, Wiley, 2013.

2. B. Rosner, Fundamentals of Biostatistics, Cengage Learning, 2011.

Reference Books

1. Martin Bland, An Introduction to Medical Statistics, Oxford University Press, 2015 2. Antonisamy B, Premkumar P S & Christopher S, Principles and Practice of

Biostatistics, Elsevier (Relex India Pvt. Ltd.), New Delhi, 2017.

COURSE CONTENTS AND LECTURE SCHEDULE


1 Module 1

1.1 Introduction to Biostatistics 1

1.2 Measures of central tendency & dispersion 2

1.3 Random variables & Probability density function – discrete and continuous 3

1.4 Joint probability density function 2

2 Module 2

2.1 Interval estimation – mean and variance 1

2.2 Testing of hypothesis 2


155

2.3 Categorical data & hypothesis testing 2

2.4 Non parametric tests 2

3 Module 3

3.1 Introduction to ANOVA 1

3.2 One way ANOVA (fixed effects model) 2

3.3 Hypothesis testing in one-wayanova (fixed effects model) 2

3.4 Comparison of specific groups in one-wayanova. 2

4 Module 4

4.1 Fitting of regression line ( least squares method) – linear regression 2

4.2 Statistical inference on parameters from regression line 1

4.3 Multiple regression 1

4.4 Correlation coefficient & statistical inference, partial and multiple correlation 2

4.5 Rank correlation coefficient 1

5 Module 5

5.1 Statistical design of experiments for clinical and laboratory data – Study design 2

5.2 Categorical data analysis 2

5.3 Multiple logistic regression 1

5.4 Meta analysis& Crossover designs 2


156

EBT362 BIOMEDICAL SIGNAL PROCESSING & APPLICATIONS


PEC 3 0 0 3

Preamble: This course makes students familiarized with concepts of advanced digital signal processing techniques which includes adaptive filtering, wavelet analysis, power spectrum estimation and multivariate analysis Prerequisite: Thorough understanding of the basic concepts in Biomedical signal Processing Course Outcomes: After the completion of the course the student will be able to CO 1 Analyse parametric and nonparametric methods of power spectrum estimation CO 2 Investigate the techniques in adaptive filters CO 3 Apply the methods of wavelet analysis in biomedical signal processing CO 4 Analyse the basics of multivariate analysis CO 5 Implement various signal processing techniques in biomedical applications Mapping of course outcomes with program outcomes

Assessment Pattern




Mark distribution


150 50 100 3 hours

Continuous Internal Evaluation Pattern: Attendance : 10 marks Continuous Assessment Test (2 numbers) : 25 marks

PO 1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8 PO 9 PO 10 PO 11 PO 12 CO 1 3 3 3 1 2 1 CO 2 3 3 3 2 2 2 CO 3 3 3 2 2 2 1 CO 4 3 3 3 2 2 2 CO 5 3 3 2 1 2 1 1 1 1 1 1


157

Assignment/Quiz/Course project : 15 marks It is mandatory that at least one assignment should be Course Project. The course project can be simulation of biomedical signal processing technique End Semester Examination Pattern: There will be two parts; Part A and Part B. Part A contain 10 questions with 2 questions from each module, having 3 marks for each question. Students should answer all questions. Part B contains 2 questions from each module of which student should answer any one. Each question can have maximum 2 sub-divisions and carry 14 marks.

Course Outcome 1 (CO1): Analyse parametric and nonparametric methods of power spectrum estimation

1. Identify the drawbacks of Periodogram method of PSD estimation 2. Compare parametric & non parametric spectrum estimation 3. What are linear prediction models?

Course Outcome 2 (CO2): Investigate the techniques in adaptive filters

1. What is the significance and the features of adaptive filters?

2. How the maternal ECG cancellation from foetal ECG is possible using adaptive noise

canceller

3. What are optimum filters? Course Outcome 3 (CO3): Apply the methods of wavelet analysis in biomedical signal processing.

1. Establish the relationship between DWT &filter banks

2. Explain the significance of wavelet analysis in biomedical signal processing

3. What is the principle of orthogonal wavelet decomposition?

Course Outcome 4 (CO4): Analyse the basics of multivariate analysis.

1. How the dimensionality reduction is possible using PCA techniques

2. Explain QRS wave detection using PCA

3. Explain how blind source separation is possible by ICA

Course Outcome 5 (CO5): Implement various signal processing techniques in biomedical applications.

1. What are the significant bands observed in spectrum of HRV data?

2. How QRS wave detection is possible by wavelet analysis

3. Explain the techniques of filtering of ECG signals using PCA


158


Total Pages:

Reg No.: _______________ Name: __________________________

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY SEMESTER B. TECH DEGREE EXAMINATION

Course Code: EBT362 Course Name:

BIOMEDICAL SIGNAL PROCESSING & APPLICATIONS


Answer full questions, each carries 3 marks.

1 How power density spectrum is estimated? (3)

2 What are the general characteristics of the ARMA model-based power spectrum estimation method?

(3)

3 Suggest a method for the spectrum estimation of ECG (3)

4 Model based approaches are preferred in EEG analysis, why? (3)

5 Draw the structure of a typical filter bank. (3)

6 Compare the scaling and wavelet coefficients (3)

7 Enlist the advantages of adaptive filters (3)

8 What is the principle of adaptive noise canceller (3)

9 What are the limitations of PCA? (3)

10 What are the applications of heart rate variability analysis (3)

PART B Answer any one question, each carries 14 marks.

11 a) Describe the steps involved in obtaining the Welch power spectrum

estimate. Also, determine the mean and variance of the Welch power

spectrum estimate.

8

b) Explain the process of estimation of parameters for ARMA model 6

OR

12 a) Differentiate AR, MA and ARMA models 9

b) Explain the periodogram method of power spectrum estimation 5

13 a) Describe Levinson Durbin algorithm for solving normal equations 8

b) Derive the minimum MSE for forward and backward linear

predictor 6


159

OR

14 a) Explain Yule –Walker method for determination of AR model

parameters 8

b) Illustrate the method used for determining the EEG power spectrum 6

15 a) How the high frequency random artefacts are removed from ECG

using DWT 8

b) Explain how heart sounds are extracted using DWT 6

OR

16 a) Explain the method of orthogonal wavelet decomposition 8

b) What are the properties of orthonormal wavelets 6

17 a) Explain the optimisation method in steepest descent algorithm 8

b) What are the characteristics of Weiner filters 6

OR

18 a) Explain the steps used in LMS algorithm 9

b) Explain the techniques of adaptive noise cancellation of power line

interference in ECG 5

19 a) Explain the method of computing PCA using co variance method 8

b) How noise removal of ECG signal is possible by PCA 6

OR

20 a) What is independent component analysis? 7

b) Describe denoising of EEG using ICA 7

Syllabus Module 1 Power spectrum analysis: Estimation of power density spectrum, non-parametric methods- Periodogram - Bartlett, Welch, Blackman and Tukey Methods-comparison. Parametric models, estimation Auto regressive (AR), Moving average (MA) Autoregressive moving average (ARMA) models.

Module 2

Linear Prediction Theory& Applications of PSD: Parametric model based linear prediction theory-Forward and backward linear prediction Relationship between autocorrelation and model parameters - The Yule -Walker method. Solution of normal equations - Levinson Durbin Algorithm. Estimation of parameters - spectrum estimation of ECG, Power spectrum estimation of Heart rate variability data. Application, Spectrum estimation of EEG


160

Module 3

Wavelet Analysis Introduction to wavelet transforms – CWT & DWT Orthogonal wavelet decomposition, Orthonormal wavelets - filter banks. Applications of DWT: wavelet de-noising, ECG feature detection & Heart sound Analysis.

Module 4

Adaptive filters: Optimal and adaptive filters, Weiner filters, Adaptive signal processing -Steepest descent algorithm LMS adaptive algorithm, Adaptive noise canceller – cancellation of 50 Hz signal in ECG- cancellation of maternal ECG in foetal electrocardiography

Module 5

Multivariate Analysis: Principal Component Analysis – denoising of ECG & EEG signals using PCA, IndependentComponent Analysis-EEG denoising.Computation of diagnostic signal parameters of ECG: Heart rate and QRS detection using Multivariate analysis (PCA and ICA).

Text Books: 1. John G Proakis& Dimitris G Manolakis, Digital Signal Processing-Principles,

Algorithms and Applications, PHI, 4 th Edition, 2016 2. Rangaraj M Rangayyan: Biomedical Signal Analysis, John Wiley, 2 ndEdition, 2015. 3. Suresh R Devasahayam , Signals & Systems in Biomedical Engineering , Springer 2

ndEdition, 2013 4. K P Soman, K I Ramachandran, N G Resmi, Insight into wavelets: from theory to

practice, PHI, 3rd Edition, 2015 5. HannuOlkkonen, Discrete Wavelet Transforms-Biomedical Applications, In Tech,1st

Edition,2011 6. Bernard Widrow and Samuel D. Stearns, "Adaptive Signal Processing", Person

Education, 2005

References:

1. D C Reddy: Biomedical signal Processing, Tata McGraw-Hill, New Delhi, 1st Edition,2005

2. John L.Semmlow: Biosignal and Biomedical Image Processing – Matlab Based Applications, Marcel Dekker Inc. New York, 2004.

3. Raghuveer M Rao et al: Wavelet Transforms- Introduction to Theory and Applications, Pearson Education Asia, 1999

4. Monalokis, Ingle and Kogon , Statistical and Adaptive Signal Processing-– Artech House INC, 2005

5. Simon Haykin, Adaptive Filter theory, Pearson Education India ,5thEdition, 2013 6. I.T Jolliffe,Principal Component Analysis, Springer, 2ndEdition, 2002 7. Ganesh R. Naik, Independent Component Analysis for Audio and Bio signal

Applications, In Tech, 2012


161

Course Contents and Lecture Schedule No Topic No. of

Lectures 1 Module 1

1.1 Power spectrum analysis, Estimation of power density spectrum, non-parametric methods

1

1.2 Periodogram - Bartlett, Welch, Blackman and Tukey Methods-comparison.

3

1.3 Parametric models, estimation Auto regressive (AR) 2

1.4 Moving average (MA) Autoregressive moving average (ARMA) models

1

2 Module 2 2.1 Parametric model based linear prediction theory-Forward and

backward linear prediction 1

2.2 Relationship between autocorrelation and model parameters - The Yule -Walker method

2

2.3 Solution of normal equations - Levinson Durbin Algorithm 1 2.4 Estimation of parameters - spectrum estimation of ECG 1 2.5 Power spectrum estimation of Heart rate variability data. 1 2.6 Spectrum estimation of EEG 1 3 Module 3

3.1 Introduction to wavelet transforms – CWT & DWT 1

3.2 Orthogonal wavelet decomposition 2 3.3 Orthonormal wavelets 1 3.4 Filter banks 1 3.5 Applications of DWT: wavelet de-noising, ECG feature detection &

Heart sound Analysis 2

4 Module 4 4.1 Optimal and adaptive filters: Weiner filters 1 4.2 Adaptive signal processing -Steepest descent algorithm 2 4.3 LMS adaptive algorithm 2 4.4 Adaptive noise canceller – cancellation of 50 Hz signal in ECG-

cancellation of maternal ECG in foetal electrocardiography 2

5 Module 5 5.1 Multivariate Analysis: Principal Component Analysis 2 5.2 Denoising of ECG & EEG signals using PCA 1 5.3 Independent Component Analysis-EEG denoising 2 5.4 Computation of diagnostic signal parameters of ECG: Heart rate and

QRS detection using Multivariate analysis (PCA and ICA) 2


162

EBT372 COMMUNICATION TECHNIQUES


PEC 3 0 0 3

Preamble: This course aims to make students able to understand different types of communication systems, the effect of noise in communication, the importance of different methods of modulation, digital communication and an introduction to advanced communication systems.

Prerequisite: NIL


CO 1 Explain the fundamental concepts of electronic communication systems and importance of modulation.

CO 2 Compare Amplitude modulation and Angle modulation techniques.

CO 3 Discuss Pulse modulation, Digital modulation schemes and the importance of Modems in communication.

CO 4 Understand the fundamental concepts of Advanced Communication systems.

CO 5 Describe the Wireless Communication and Data Services.



CO 1 3 3 1 CO 2 3 3 1 CO 3 3 2 1 2 CO 4 3 2 1 1 1 1 1 CO 5 2 2 1 1 1 1

Assessment Pattern




Mark distribution


150 50 100 3 hours


163




Course Outcome 1 (CO1): Explain the fundamental concepts of electronic communication systems and importance of modulation.

1. Introduce the basics of communication system with its essential components. 2. Explain the need for modulation. 3. Compare the features with advantages and disadvantages of analog and digital

communication systems.

Course Outcome 2 (CO2): Compare Amplitude modulation and Angle modulation techniques.

1. Introduce and explain Amplitude Modulation with its representation, frequency spectrum and modulation index.

2. Understand and explain Frequency Modulation with its mathematical representation, frequency spectrum, waveforms, frequency deviation and bandwidth requirement.

3. Problems on Amplitude Modulation and Frequency Modulation. 4. Understand the process of FM generation, FM transmission and reception with

appropriate block diagram.

Course Outcome 3(CO3):Discuss Pulse modulation, Digital modulation schemes and the importance of Modems in communication.

1. Introduce and understand Pulse Modulation, need for Pulse Modulation and its different types with their principle of operation.

2. Explain in detail different digital modulation schemes. 3. Explain the classification and different modes of operation of Modems with modem

interfacing.

Course Outcome 4 (CO4): Understand the fundamental concepts of Advanced Communication systems.

1. Introduce and understand in detail the Microwave communication system with its advantages.

2. Understand Satellite communication system with its governing principles. 3. Explain in detail the Optical communication system. 4. Explain in detail the cellular communication systems.


164

Course Outcome 5 (CO5): Describe the Wireless Communication and Data Services.

1. Explain the features of Bluetooth technology. 2. Compare the features of CDMA, FDMA and TDMA. 3. Introduce different multiple access technologies. 4. Introduce and understand new Data Services.


Total Pages: 2 Reg No.:_______________ Name:__________________________


Course Code: EBT372 Course Name: Communication Techniques



1 What are the essential components of the communication system. (3)

2 What are the different communication channels? (3)

3 Draw the frequency spectrum of an AM wave. (3)

4 Compare Frequency Modulation and Phase Modulation. (3)

5 What is the need for Pulse Modulation. (3)

6 What is DPSK? (3)

7 What is frequency reuse in a cellular system. (3)

8 What is the need for cell splitting in cellular system. (3)

9 Mention the features of Bluetooth. (3)

10 Give the concepts of Push To Talk (PTT) technology. (3)


Module 1

11 a) With the help of a block diagram, explain the communication system. (8)

b) Compare analog and digital communication systems. (6)

OR

12 a) Explain the different noise types. (8)

b) Explain the need for modulation and its significance. (6)

Module 2


165

13 a) Explain the principle of Amplitude Modulation with its mathematical analysis. Draw the frequency spectrum of AM. (8)

b) Explain Balanced Modulator. (6)

OR

14 a) Explain the different methods of FM generation. (6)

b) With the help of a block diagram, explain different methods of AM Generation.

(8)

Module 3

15 a) With the help of appropriate diagrams, explain Pulse Code Modulation.

(10)

b) Explain modem interfacing. (4)

OR

16 a) Explain the principle of Pulse Width Modulation. (8)

b) Compare BPSK and QPSK. (6)

Module 4

17 a) With necessary diagrams explain the technique ‘Hand off ‘. Describe the different Hand off strategies.

(10)

b) With the help of a block diagram briefly explain Satellite Transponder Subsystem.

(4)

OR

18 a) Explain the optical fiber communication system in detail with necessary block diagrams.

(9)

b) Explain the principle of cellular communications. (5)

Module 5

19 a) Explain in detail about the characteristics and network architecture of GPRS.

(10)

b) What are the different versions of WLAN. (4)

OR

20 a) Explain the OFDM implementation of multicarrier modulation with necessary diagrams.

(8)

b) Explain Digital Enhanced Cordless Telecommunications (DECT) data service.

(6)


166

Syllabus

Module 1

Introduction to communication systems: Definition, Block level representation, Information – transmitter – receiver. Analog and digital communication systems: Comparison, Need for modulation. Channel: Different types, characteristics. Noise: white noise –narrow band noise–noise figure.

Module 2

Amplitude Modulation: Representation of AM, Modulation index, Frequency spectrum, Power relations in AM wave, AM Generation, Envelope AM Detection, Superheterodyne AM receiver, Balanced modulator.Angle modulation: Frequency modulation- Mathematical representation, waveforms, frequency deviation, bandwidth requirement, FM Generation– Varactor Diode Modulator & Armstrong method, Pre-emphasis and De-emphasis, Balanced slope detector, FM transmitters and FM receivers (block diagram). Phase modulation: Mathematical representation, waveforms, deviation, bandwidth requirement. Module 3

Pulse Modulation: Need for pulse modulation, Different types, Pulse Amplitude Modulation, Pulse Width Modulation, Pulse Position Modulation and Pulse Code Modulation – principles of operation. Digital Modulation Schemes: BPSK, QPSK, BFSK, Differential Phase Shift Keying (DPSK), QAM. Modems: Classification, Modes of operation, Modem interfacing. Module 4

Microwave communication system: Introduction- transmitter- repeater- receiver, frequency bands. Satellite communication system: Introduction- transponder, Kepler’s laws, Satellite sub systems. Optical communication system: Features: fiber optic technology- total internal reflection- Snell’s law- light transmission through an optical fiber- numerical aperture, Optical fiber communication system. Cellular communications: principles of cellular networks, frequency reuse, operation of cellular system, hand off strategies, roaming, improving capacity in cellular system. Module 5

Wireless communication systems: Introduction to modern wireless communication systems, Wireless local area networks, Bluetooth and Personal Area networks, Overview of WIMAX Technologies. Introduction to Multiple Access: FDMA, TDMA, Spread Spectrum Multiple Access, Space division Multiple Access, CDMA, OFDM. GSM services, architecture of GSM network. Data Services: GPRS, HSCSD, DECT, EDGE, UWB, Push To Talk(PTT).


167

Text Books

1. Dr. Sanjay Sharma,”Analog Communication Systems”, Katson Books, 2009. 2. Dr. Sanjay Sharma,”Communication Systems(Analog and Digital)”, Katson Books,

2009. 3. Tomasi, Advanced Electronic Communication Systems, 6/e, Pearson, 2015. 4. Mishra, Wireless communications and Networks, McGraw Hill, 2/e, 2013.

Reference Books

1. Dennis Roody and John Coolen,”Electronic Communication”, Prentice Hall of India, New Delhi.

2. George Kennedy &Davis,”Electronic communication Systems”, Tata Mc Graw Hill, 6thedition.

3. Sam Shanmugham,”Digital and Analog Communication Systems”, John Wiley & Sons.

4. Simon Haykin, Michael Mohar, Modern wireless communication, Pearson Education. 5. Dennis Roody, Satellite communication, 4/e, McGraw Hill.

Course Contents And Lecture Schedule


1 Module 1

1.1 Introduction to Communication Systems: Definition, Block level representation, Information – transmitter – receiver. 1

1.2 Analog and digital communication systems: Comparison, Need for modulation. 1

1.3 Channel: Different types, characteristics. 1

1.4 Noise: white noise –narrow band noise–noise figure. 1

2 Module 2

2.1

Amplitude Modulation: Representation of AM, Modulation index, Frequency spectrum, Power relations in AM wave. AM Generation, Envelope AM Detection, Superheterodyne AM receiver, Balanced modulator.

3

2.2

Frequency modulation: Mathematical representation, waveforms, frequency deviation, bandwidth requirement, FM Generation– Varactor Diode Modulator & Armstrong method, Pre-emphasis and De-emphasis, Balanced slope detector, FM transmitters and FM receivers (block diagram).

4

2.3 Phase modulation: Mathematical representation, waveforms, deviation, bandwidth requirement.

1


168

3 Module 3

3.1 Pulse Modulation: Need for pulse modulation, Different types, Pulse Amplitude Modulation, Pulse Width Modulation, Pulse Position Modulation and Pulse Code Modulation – principles of operation.

3

3.2 Digital Modulation Schemes: BPSK, QPSK, BFSK, Differential Phase Shift Keying (DPSK), QAM.

2

3.3 Modems: Classification, Modes of operation, Modem interfacing. 1

4 Module 4

4.1 Microwave communication system: Introduction- transmitter- repeater- receiver, frequency bands.

1

4.2 Satellite communication system: Introduction- transponder, Kepler’s laws, Satellite sub systems.

1

4.3 Optical communication system: Features: fiber optic technology- total internal reflection- snell’s law- light transmission through an optical fiber- numerical aperture, Optical fiber communication system.

3

4.4 Cellular communications: principles of cellular networks, frequency reuse, operation of cellular system, hand off strategies, roaming, improving capacity in cellular system.

3

5 Module 5

5.1 Wireless communication systems: Introduction to modern wireless communication systems, Wireless local area networks, Bluetooth and Personal Area networks, Overview of WIMAX Technologies.

3

5.2 Introduction to Multiple Access: FDMA, TDMA, Spread Spectrum Multiple Access, Space division Multiple Access, CDMA, OFDM. GSM services, architecture of GSM network.

3

5.3 Data Services: GPRS, HSCSD, DECT, EDGE, UWB, Push To Talk (PTT). 3


SEMESTER VI MINOR


169

EBT382 BIOMEDICAL IMAGE PROCESSING


VAC 4 0 0 4

Preamble: This course aims to introduce the students to the image processing techniques for

biomedical images to extract clinically relevant information.

Prerequisite: Through knowledge about the mathematical concepts of transform methods

and medical imaging techniques.


CO 1 Analyse the use of transforms in medical image processing. CO 2 Apply the methods of enhancement for medical images. CO 3 Implement segmentation of medical images. CO 4 Differentiate normal and abnormal objects from medical images by feature

extraction and classification. CO 5 Analyse machine and deep learning algorithms for medical image analysis.



CO 1 3 2 2 1 CO 2 3 3 2 1 2 1 CO 3 3 2 3 2 2 1 CO 4 3 2 2 2 2 1 CO 5 3 1 1 1 2 2

Assessment Pattern




Mark distribution


150 50 100 3 hours


170




Course Outcome 1 (CO1): Analyse the use of transforms in medical image processing

1. Write the mathematical expressions for the forward and inverse 2D- DFT . 2. Elaborate three important properties and the main application of DCT in medical

image processing. 3. Design a filter to remove high frequency noise from medical images.

Course Outcome 2 (CO2): Apply the methods of enhancement for medical images.

1. Analyse the use of interpolation in medical image enhancement. 2. Design a filter to remove high frequency noise from medical images. 3. Select an enhancement operation to remove artifacts on medical images.

Course Outcome 3(CO3): Implement segmentation of medical images.

1. Select an edge detection method for boundary extraction in medical images. 2. Compare region growing and region merging techniques for medical image

segmentation. 3. Analyse the thresholding-based medical image segmentation.

Course Outcome 4 (CO4): Differentiate normal and abnormal objects from medical images by feature extraction and classification.

1. Compare supervised and unsupervised classification algorithm. 2. Describe features related to the contents and the shape of objects. 3. Analyse an unsupervised classification algorithm.

Course Outcome 5 (CO5): Analyse machine and deep learning algorithms for medical image analysis.

1. Identify the role of deep learning methods in medical image analysis. 2. Elaborate the Convolutional Neural Network architecture.


171

3. Apply Convolutional Neural Network for Pancreas Segmentation in CT and MRI images.


Total Pages: 2

Reg No.:_______________ Name:__________________________

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY SIXTH SEMESTER B. TECH DEGREE EXAMINATION

Course Code: EBT382 Course Name: BIOMEDICAL IMAGE PROCESSING


PART A Answer all questions, each carries 3 marks. 10x3 = 30marks

1 Illustrate the property of different components of the Human Visual

System.

(3)

2 Draw the sampled spectrum of an image. (3)

3 Compare the clipping and thresholding operations for medical image

enhancement.

(3)

4 Design a mask to do the smoothing operation on an image. (3)

5 Identify any two operators used for edge detection in medical images. (3)

6 Compare the morphological operations. - erosion and dilation. (3)

7 Identify five important features used for classification. (3)

8 Differentiate supervised and unsupervised classification algorithms. (3)

9 Analyse the different layers in Convolutional Neural Network. (3)

10 Identify the role of convolutional layer in Convolutional Neural Network. (3)

PART B Answer five full questions, each carries 14 marks.

11 a) Elaborate three important properties and the main application of 2D-DFT in medical image processing.

(8)

b) Identify the importance and principle ofimage sampling and quantization in medical image processing.

(6)

OR 12. a) Demonstrate the importance of Nyquist criterion based on the sampled

spectrum of the image. (8)

b) Write the mathematical expressions for the forward and inverse 2D- (6)


172

DCTand explain any three of its properties.

13 a) Summarize the process of histogram equalization for medical image enhancement.

(9)

b) Design a sharpening filter to pre-process a medical image. (5) OR

14 a) Design a filter to filter out the high frequency artifacts from a medical image.

(8)

b) Analyse the use of interpolation in medical image enhancement. (6)

15 a) Analyse the thresholding-based medical image segmentation. (8) b) Compare the two region-based segmentation methods for medical

images. (6)

OR 16 a) Analyse the process of boundary-based image segmentation methods. (8)

b) Describe edge detection and linking used for segmentation of images. (6)

17 a) Analyse the working of an unsupervised classifier for medical image classification.

(8)

b) Elaborate the role of supervised learning in medical image classification. (6) OR

18 a) When is the Linear Discriminant Analysis used for classification? (8)

b) Describe the principle of k-nearest-Neighbor (k-NN) classifier. (6)

19 a) Draw a basic architecture of a Convolutional Neural Network and identify the role of each layer.

(6)

b) Analyse the technique of deep learning in medical image analysis. (8) OR

20 a) Identify the role and advantages of Convolutional Neural Network in medical image analysis.

(7)

b) Describe the role of Convolution and Pooling Layers in Convolutional Neural Network.

(7)


173

Syllabus

Module 1

Image perception: Monochrome and colour vision models, Image sampling and quantization. Image transforms- 2D DFT, DCT, Hadamard, Haar. Pixels and voxels, gray scale and colour representation. Medical image file formats- DICOM. Read and load DICOM images.

Module 2

Image enhancement: contrast enhancement, clipping and thresholding - digital negative, intensity level slicing- bit extraction. Histogram processing, Magnification and interpolation. Image Enhancement in Spatial domain: Smoothing and sharpening operations in time domain, Smoothing and sharpening frequency domain filters. Apply contrast enhancement techniques to images for artifact removal, apply filtering to the images.

Module 3

Image segmentation- ROI definition and centroids, Thresholding- Basic and optimal. Region-based methods- region growing and region merging, Boundary-based methods- edge detection and linking, boundary tracking, Morphological operations. - erosion and dilation. Detection of calcifications in mammograms by region growing.

Module 4

Feature recognition and classification: Features - describing the contents and the shape of objects, Object recognition and classification- discriminant analysis, k-nearest-neighbor (k-NN) classifier. Unsupervised- k-means clustering. Supervised learning for classification.Shape and texture analysis of tumours.

Module 5

Deep Learning for Medical Image Analysis: Convolutional Neural Networks, Convolution and Pooling Layer, Computing Gradients, Deep Models, Vanishing Gradient Problem. Convolutional Neural Network for Pancreas Segmentation in CT and MRI images.

(The topics given in italics are for assignments. The assignments may be the implementation of the above topics or other processing steps on medical images using a suitable

programming language.)

Text Books

1. Digital Image Processing, Gonzalez Rafel C, Fourth Edition, 2018. 2. Applied Medical Image Processing, Second Edition, Wolfgang Birkfellner, CRC Press,

2014. 3. Hybrid Image Processing Methods for Medical Image Examination, Venkatesan

Rajinikanth, E. Priya, Hong Lin, and Fuhua Lin, First Edition, CRC Press, 2021.


174

Reference Books

1. Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics, Le Lu Xiaosong Wang Gustavo Carneiro Lin Yang Editors.

2. Deep Learning for Medical Image Analysis, Edited by S. Kevin Zhou Hayit Greenspan Dinggang Shen, Academic Press, Elsevier, Ist Edition, 2017.

3. Jain Anil K: Fundamentals of Digital Image Processing-, Prentice Hall of India. 1989.

4. Digital Image Processing for Medical Applications, Geoff Dougherty, Cambridge University Press, 2007.


No Topic No. of

Lectures 1 Module 1 1.1 Monochrome and colour vision models, Image sampling and

quantization. 2

1.2 Image transforms -2D DFT, DCT, Hadamard and Haar. 3 1.3 Pixels and voxels, gray scale and colour representation. 2 1.4 Medical image file formats- DICOM. 2 2 Module 2 2.1 Contrast enhancement, clipping and thresholding - digital negative,

intensity level slicing- bit extraction. 3

2.2 Histogram processing, Magnification and interpolation. 2

2.3 Image Enhancement in Spatial domain: Smoothing and sharpening operations in time domain.

2

2.4 Smoothing and sharpening frequency domain filters. 2 3 Module 3 3.1 ROI definition and centroids, Thresholding- Basic and optimal. 2 3.2 Region-based methods- region growing and region merging. 2 3.3 Boundary-based methods- edge detection and linking, boundary

tracking, 3

3.4 Morphological operations. - erosion and dilation. 2 4 Module 4 4.1 Features - describing the contents and the shape of objects. 2 4.2 Object recognition and classification- discriminant analysis, k-

nearest-neighbour (k-NN) classifier. 3

4.3 Unsupervised- k-means clustering. 2


175

4.4 Supervised learning for classification. 2 5 Module 5 5.1 Convolutional Neural Networks, Convolution and Pooling Layer. 3 5.2 Computing Gradients, Deep Models. 3 5.3 Vanishing Gradient Problem. 2


176

EBT384 THERAPEUTIC DEVICES CATEGORY L T P CREDIT

VAC 4 0 0 4 Preamble: This course describes the basic principles of different therapeutic equipment used in clinical environments. Prerequisite: NIL Course Outcomes: After the completion of the course the student will be able to

CO 1 Compare different types of cardiac pacemakers and the power sources used.

CO 2 Distinguish different types of defibrillators.

CO 3 Analyse the modes of operation of ventilators.

CO 4 Examine the therapeutic applications of electric current.

CO 5 Understand the principles of endoscopy, anaesthetic and angioplasty techniques in medicine.


CO 1 3 2 1 2 2 1 CO 2 3 3 1 1 CO 3 3 1 1 2 CO 4 3 2 1 1 1 CO 5 3 2 1 1 2

Assessment Pattern


Examination 1 2



Apply 20% 20% 20%

Analyse 20% 20% 20%


177

Mark distribution


150 50 100 3 hours




Course Outcome 1 (CO1):Compare different types of cardiac pacemakers and the power sources used.

1. List the conditions that necessitate the use of a pacemaker 2. What are programmable pacemakers? Explain the different methods of transmitting

information to the pacemaker unit.

Course Outcome 2 (CO2):Distinguish different types of defibrillators.

1. How is Lown waveform produced in defibrillator? 2. Compare emergency and synchronized modes of defibrillator?

Course Outcome 3(CO3):Analyse the modes of operation of ventilators.

1. What is the importance of pressure volume graphs in ventilators 2. Define i) Lung Compliance ii) Airway Resistance iii) Mean Airway Pressure 3. Explain PEEP mode in ventilators.

Course Outcome 4 (CO4):Examine the therapeutic applications of electric current

1. What are the applications of short-wave diathermy in medicine. 2. What is principle of surgical diathermy. 3. With the help of a block diagram explain the concept of functional electrical

stimulation

Course Outcome 5 (CO5):Understand the principles of endoscopy, anaesthetic and angioplasty techniques in medicine.


178

1. What are dialysers.

2. With the help of a block diagram explain the principle of operation of endoscope.

3. What are the basic types of lithotripsy techniques?


SET Total Pages:

Reg No.:_______________ Name:__________________________

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY SIXTH SEMESTER B. TECH DEGREE EXAMINATION, DECEMBER 2022

Course Code: EBT384

Course Name: THERAPEUTIC DEVICES


PART A

Answer all questions(3 marks). Marks

1 Classify the pacemaker based on the output waveforms. (3)

2 List the requirements for an implantable pacemaker. (3)

3 Write notes on electrodes of implantable defibrillators. (3)

4 What are the different defibrillator electrodes (3)

5 Explain ultrasonic stimulator? (3)

6 How Microwaves are produced in microwave diathermy. How does the circuit work?

(3)

7 Which ventilator parameters need to be adjusted to maintain optimum minute ventilation? How is it calculated?

(3)

8 What is monopolar and bipolar technique used in diathermy (3)

9 Explain the following term variable bypass vaporizer (3)

10 What are the limitations in traditional intravenous infusion system? Suggest how to overcome the mentioned limitations.

(3)


179

PART B


11 a) What are the different power sources for cardiac pacemaker (7)

b) What are current limited and voltage limited pacemakers (7)

OR

12 a) Explain the different types of gas exchange systems found in Heart lung machines

(9)

b) Illustrate and explain programmable pacemakers (5)

13 a) Illustrate and explain the anaesthesia machine and breathing circuit (10)

b) How RF ablation can be used for arrythmia treatment (4)

OR

14 a) Write short notes on Defibrillator Analysers (8)

b) List down the basic requirements for implantable pacemakers (6)

15 a) In acute respiratory distress syndrome condition, it requires a higher PEEP. Explain the concept of PEEP graphically.

(9)

b) How CPAP differ from BiPAP (5)

OR

16 a) Which ventilator parameters need to be adjusted to maintain optimum minute ventilation? How is it calculated?

(10)

b) Define the terms i) Inspiratory Expiratory Phase Time Ratio ii) Synchronized Intermittent Mandatory Ventilation (SIMV):

(4)

17 a) Electrocution of patient from the faulty mains operated equipment is a serious hazard. Appraise the technical approach required for output configuration to minimize it.

(7)

b) Explain the commonly used Acoustic shock wave sources and the focusing methods in a lithotripter

(7)

OR

18 a) Explain the physiology of pain relief through electrical stimulators. (7)


180

b) How does the waste removal happen across the dialysis membrane (7)

19 a) What is the working principle of an implantable infusion pump system

(7)

b) Explain the technical characteristics and the components of flexible fibre optic endoscopic equipment incorporated with imaging techniques, using necessary diagrams.

(7)

OR

20 a) Write notes on Programme Controlled Insulin Dosing Device (9)

b) Explain the principle of Peristaltic pump (5)

Syllabus

Module 1

Natural Pacemaker Cells and nerve conduction: Effects of electric field on cardiac muscles and laws of stimulation. Need for cardiac pacemaker.External pacemakers – types - voltage pacemakers - current pacemakers - current limited voltage pacemakers. Internal pacemakers - basic requirement – types: fixed rate, demand pacemakers, R wave triggered. Atrial triggered pacemakers. Programmable pacemakers - Functional block diagram and description. Power sources - Mercury battery, biological power sources, Nuclear battery & lithium cells.Heart lung machines - Principle of operation -Functional block diagram.

Module 2

Defibrillators - Need for a defibrillator- basic principle. Defibrillator electrodes. DC defibrillator with synchronizer: Functional block diagram. Implantable defibrillators – components - block diagram- Power sources. RF ablation treatment for arrhythmia

Module 3

Ventilator Instrumentation - Basic Concept-Different Modules-Power Supply, Gas Mixer, Pressure Generator, Breathing System, Gas Humidifier, Expiratory Valve, Operating and Display Unit, Alarm System, Patient Monitoring. Airflow systems: Continuous flow systems, Demand and Combined Flow Systems Ventilation Procedures- Controlled Ventilation-Supported Spontaneous Ventilation, Spontaneous Breathing- Mixed Ventilation

Module 4

Electrical stimulators, nerve and muscle stimulators - Stimulators for pain and relief- functional electrical stimulation- Ultrasonic stimulators Surgical diathermy -Principles and applications, Functional block diagram - monopolar & bipolar techniques Lithotripsy –


181

Basic principles, Extra corporeal Short-Wave Lithotripsy (ESWL) & Ultrasonic lithotripters – applications Drug delivery devices - Infusion pumps - Functional block diagram

Module 5

Endoscopy – Principles, types & applications. Block diagram of a fiber optic endoscope with integral TV cameras Anaesthetic machines: Need of anesthesia, gas used and their sources, gas blending and vaporizers, anesthesia delivery system, breathing circuits Angioplasty- Basic Principle, Different types Text Books

1. RüdigerKramme, Heike Kramme, Springer Handbook of Medical Technology, Springer-Verlag Berlin Heidelberg, Year: 2011

2. Bronzino, Joseph D., and Donald R. Peterson. Biomedical engineering fundamentals. CRC press, 2014.

3. Lei, Yuan. Medical Ventilator System Basics: A Clinical Guide. Oxford University Press, 2017.

4. Khandpur, Raghbir Singh. Handbook of biomedical instrumentation. McGraw-Hill Education, 2004

5. Webster, John G. Encyclopedia of medical devices and instrumentation. Vol. 4. Wiley-Interscience, 1988

Reference Books

1. Webster, John G., ed. Medical instrumentation: application and design. John Wiley

& Sons, 2009. 2. Mushin, William Woolf. "Automatic ventilation of the lungs." (1980). 3. Joseph J. Carr, John M. Brown, Introduction to Biomedical Equipment Technology,

Pearson Education (Singapore) Pvt. Ltd., 2001. 4. Geddes & Baker, Principles of Applied Biomedical Instrumentation Wiley, 1989

Biomedical Engineering Handbook, CRC Press, 1995



1 Module 1

1.1 Therapeutic devices and diagnostic devices- Comparison and correlation. Effects of electric field on cardiac muscles and laws of stimulation. Need for cardiac pacemaker.

2


182

1.2 External pacemakers – types - voltage pacemakers - current pacemakers - current limited voltage pacemakers. Internal pacemakers - basic requirement – types: fixed rate, demand pacemakers, R wave triggered. Atrial triggered pacemakers. Programmable pacemakers - Functional block diagram and description.

4

1.3 Power sources - Mercury battery, biological power sources, Nuclear battery & lithium cells.

2

1.4 Heart lung machines - Principle of operation -Functional block diagram 2

2 Module 2

2.1 Defibrillators - Need for a defibrillator- basic principle and comparison of output wave forms of different DC defibrillators.

2

2.2 Defibrillator electrodes. Functional block diagram. Automatic external defibrillators-Block diagram

2

2.3 Implantable defibrillators – components - block diagram -defibrillator analysers.

2

2.4 RF ablation treatment for arrhythmia. 2

3 Module 3

3.1 Ventilators: Basic Concept-Different Modules -Power Supply, Gas Mixer, Pressure Generator,

2

3.2 Breathing System, Gas Humidifier, Expiratory Valve, Operating and Display Unit, Alarm System, Patient Monitoring.

2

3.3 Airflow systems: Continuous flow systems, Demand and Combined Flow Systems,

2

3.4 Ventilation Procedures- Controlled Ventilation-Supported Spontaneous Ventilation, Spontaneous Breathing- Mixed Ventilation

3

4 Module 4

4.1 Electrical stimulators, nerve and muscle stimulators - Stimulators for pain and relief- functional electrical stimulation- Ultrasonic stimulators.

2

4.2 Surgical diathermy -Principles and applications, Functional block diagram - monopolar & bipolar techniques, Electrodes.

2

4.3 Principles of short wave and microwave diathermy 2

4.4 Lithotripsy – Basic principles, Extra corporeal Short Wave Lithotripsy (ESWL )& ultrasonic lithotripters - applications.

2

4.5 Drug delivery devices - Infusion pumps - Functional block diagram. 2


183

5 Module 5

5.1 Endoscopy – Principles, types & applications. Block diagram of a fiber optic endoscope

3

5.2 Anaesthetic machines: Need of anaesthesia, gas used and their sources, gas blending and vaporizers, anaesthesia delivery system, breathing circuits

3

5.3 Angioplasty- Basic Principle 1


184

EBT386 PHYSIOLOGICAL SYSTEM MODELLING

CATEGORY L T P CREDIT VAC 4 0 0 4

Preamble: This course introduces quantitative approaches to understanding various physiological systems, Topics include mathematical analysis of transport mechanisms across cell membrane, propagation of impulse, processes in respiratory systems, cardiac electrophysiology, and computational aspects of neuronal models.

Prerequisite: Basic knowledge in solving ODE, PDE using analytical and numerical methods.


CO 1 Examine the mathematical approaches of modelling physiological systems

CO 2 Analyse the mathematical principles of respiratory function

CO 3 Interpret models of cardiac electrophysiology

CO 4 Examine models of computational neuroscience

CO 5 Analyse the dynamical system properties of neuronal models



CO 1 3 3 1 2 2 2 CO 2 3 1 3 2 2 2 CO 3 3 3 2 2 3 2 1 3 CO 4 3 3 2 1 3 1 1 3 CO 5 3 3 3 3 3 2 1 3

Assessment Pattern




Mark distribution


185


150 50 100 3 hours




Course Outcome 1 (CO1): Examine the mathematical approaches of modelling physiological systems

1. What are the different factors that make physiological systems complex? 2. Explain the different types of feedback in human physiology with examples, 3. Compare parametric and non-parametric modelling approaches.

Course Outcome 2 (CO2): Analyse the mathematical principles of respiratory function

1. What are the different factors affecting alveolar gas exchange 2. Explain the mathematical basis of oxygen uptake in haemoglobin. 3. With the help of a model explain the ventilation perfusion.

Course Outcome 3 (CO3): Interpret models of cardiac electrophysiology

1. Explain biophysical models of cardiac cells 2. Compare the monodomain and bidomain models in cardiac electrophysiology 3. Explain the physiological basis of the generation of ECG

Course Outcome 4 (CO4): Examine models of computational neuroscience

1. Explain the electrophysiology of neurons 2. Formulate Hodgkin Huxley model. 3. Compare spike response and rate-based neuron models

Course Outcome 5 (CO5): Evaluate the neuronal models

1. How the stability of a dynamical system can be evaluated.


186

2. What are phase plane diagram. How the behaviour of a neuron model can be analysed using phase plane plots

3. Explain the dynamics of Izhikevich neuron models


Reg No.:_______________ Name:__________________________


Course Code: EBT 386 Course Name: PHYSIOLOGICAL SYSTEM MODELLING



1 List the steps in the formulation of a mathematical model (3)

2 What is need for physiological system model? (3)

3 What are the different factors that affect CO2 transport in blood (3)

4 List factors that affect the respiration rate. (3)

5 Sketch the action potential of cardiac muscle cells. (3)

6 Compare bidomain and monodomain models (3)

7 Differentiate active and passive transport mechanism across cell membrane

(3)

8 What is voltage gating? (3)

9 Give an example of limit cycle oscillation in biological system. (3)

10 Compare saddle node bifurcation and Hopf bifurcation (3)

PART B


MODULE 1

11

a) Explain the compartmental modelling approaches in system

physiology (6)

b) Based on the control system approach explain how temperature is

regulated in the human body (9)

12 a) Compare parametric and non-parametric modelling approaches in

system physiology with examples. (7)


187

b) Give an example of positive feedback in human physiological

system. (7)

MODULE 2

13

a) What are the different factors affecting alveolar gas exchange? (9)

b) With the help of a model explain Oxygen- Carbon dioxide dissociation curve

(6)

14

a) Explain the mathematical basis of oxygen uptake in haemoglobin.

(9)

b) With the help of a model explain the regulation of ventilation. (6)

MODULE 3

15

a) With the help of a neat diagram explain the physiological basis of the generation of ECG

(7)

b) How the noble model proposed for Purkinje cell is different from Hodgkin Huxley model,

(7)

16 a) Derive cable equation. (8)

b) What are the applications of cardiac cell models (6)

MODULE 4

17 a) Explain the mathematical basis different types of transport

mechanisms across cell membrane. (6)

b) Formulate Hodgkin Huxley model for cell excitability (8)

18 a) What are the different types of gating mechanism across cell

membrane (6)

b) Explain integrate fire neuron model (8)

MODULE 5

19

a) Determine nullclines and draw the phase portrait of the van der Pol oscillator of the form

where b>0 is a parameter

(7)

b) Describe the dynamics of Integrate and fire neuron model (7)

20

a) Illustrate the phase plane analysis of Fitzhugh Nagumo model showing excitability, biostability and oscillation

(10)

b) What are nullclines

(4)


188

Syllabus Module 1

Modelling approaches in physiological systems: Physiological complexity and need for models, Feedback and control in physiological systems. Modelling process-steps, Different approaches in system modelling- parametric and nonparametric modelling, linear and nonlinear, compartmental modelling. (Examples of each type in physiological system).

Module 2

Mathematical modelling of pulmonary gas exchange:Mathematical analysis of gas transport in the lungs-the alveolar air equation- the venous admixture equation- the Fick principle of blood flow, - the estimation of dead space. models of diffusion, models of ventilation perfusion, Application of mathematical models of ventilation-perfusion and diffusion (Refer Text Book Chapter 13 Modelling Methodology for Physiology and Medicine) Module 3 Mathematical analysis of cardiac physiology: Basic Cardiac Anatomy and Electro cardiology Conduction System: The Electrocardiogram (ECG) Cardiac Action Potential Models, Biophysical models Noble-Noble models, reduced cell models. Mathematical models of Cardiac Cells Arrangements: The Bidomain and monodomain models. (Refer Text Book Mathematical cardiac electrophysiology )

Module 4

Mathematical models of computational neuroscience: Electrophysiology of neurons, Ionic currents and conductance, Equivalent circuit representation of a patch of cell membrane, resting membrane potential, voltage-gated channels, Hodgkin–Huxley model formulation for action potential, Compartmental models, Simplified models of neurons Integrate-and-fire neurons Spike-response model neurons Rate-based models (Refer Text Book Principles of computational modelling in neuroscience)

Module 5 Dynamical systems in physiology: Dynamical system analysis- Types of fixed points, Phase plane analysis - nullclines - Hopf bifurcation and limit cycles. van der Pol oscillator, Fitzhugh Nagumo model Phase-plane analysis, showing excitability, bistability and oscillations. Simulation studies of simplified models (Eg.Izhikevich neuron models) (Refer Text Book Principles of Computational Modelling in Neuroscience)

Text Books

1. Cobelli, Claudio, and Ewart Carson. Introduction to Modelling in physiology and medicine. Academic Press, 2019.


189

2. Carson, Ewart, and Claudio Cobelli. Modelling methodology for physiology and medicine. Newnes, 2013.

3. Franzone, Piero Colli, Luca Franco Pavarino, and Simone Scacchi. Mathematical cardiac electrophysiology. Vol. 13. Springer, 2014.

4. Sterratt, David, Bruce Graham, Andrew Gillies, and David Willshaw. Principles of Computational Modelling in neuroscience. Cambridge University Press, 2011

5. Izhikevich, Eugene M. Dynamical systems in neuroscience. MIT press, 2007.

Reference Books

1. Dayan, Peter, and Laurence F. Abbott. Theoretical neuroscience: computational and mathematical modelling of neural systems. Computational Neuroscience Series, 2001.

2. Ottesen, Johnny T., Mette S. Olufsen, and Jesper K. Larsen. Applied mathematical models in human physiology. Society for Industrial and Applied Mathematics, 2004.

3. Mazumdar, Jagannath. An introduction to mathematical physiology and biology. Cambridge University Press, 1999.

4. Schiesser, William E. Partial differential equation analysis in biomedical engineering: case studies with MATLAB. Cambridge University Press, 2012.

5. Murray, James D. Mathematical biology: I. An introduction. Vol. 17. Springer Science & Business Media, 2007.

6. Strogatz, Steven H. Nonlinear dynamics and chaos with student solutions manual: With applications to physics, biology, chemistry, and engineering. CRC press, 2018.

7. Plonsey, Robert, and Roger C. Barr. "Mathematical modelling of electrical activity of the heart." Journal of electrocardiology 20, no. 3 (1987): 219-226.

8. Golemati, Spyretta, and Konstantina S. Nikita, eds. Cardiovascular Computing--Methodologies and Clinical Applications. Springer, 2019.

9. Koch, Christof. Biophysics of computation: information processing in single neurons. Oxford university press, 2004.



1 Module 1 1.1 Physiological complexity and need for models 2 1.2 Feedback and control in physiological systems Temperature regulation

example 2

1.3 Modelling process-steps, Different approaches in system modelling 2 1.4 Parametric and nonparametric modelling, linear and nonlinear-,

compartmental modelling 2

2 Module 2 2.1 Alveolar gas exchange, Mathematical analysis of gas transport in the

lungs-the alveolar air equation 1

2.2 The venous admixture equation- the estimation of dead space. models of 3


190

diffusion 2.3 Models of ventilation perfusion, Regulation of Ventilation 3 2.4 Application of mathematical models of ventilation-perfusion and

diffusion 2

3 Module 3 3.1 Basic Cardiac Anatomy and Electro cardiology Conduction System: SA

and AV Node, Purkinje Network 2

3.2 Cardiac Tissue Organization Cardiac Action Potentials, ECG 3 3.3 Cardiac action potential models, Biophysical models -Noble-Noble

model, Reduced cell models-AlievPanfilov model 3

3.4 Mathematical Models of Cardiac Cells Arrangements: The Bidomain and monodomain models,

2

3.5 Simulation Studies of Cardiac Bioelectrical Activity (Assignment) 4 Module 4

4.1 Electrophysiology of neurons, Ionic Currents and Conductance Equivalent circuit representation of a patch of cell membrane

2

4.2 Resting membrane potential, Voltage-Gated Channels, Hodgkin–Huxley model formulation for action potential

3

4.3 Compartmental models, Simplified models of neurons Integrate-and-fire neurons

1

4.4 Spike-response model neurons Rate-based models 3 5 Module 5

5.1 Dynamical system analysis- Types of fixed points, Phase plane analysis - nullclines.

2

5.2 Hopf bifurcation and limit cycles. 2 5.3 van der Pol oscillator, Fitzhugh Nagumo model -analysis Phase-plane

analysis, showing excitability, bistability and oscillations 2

5.4 Simulation studies of simplified models (Eg.Izhikevich neuron models) 2


SEMESTER VI HONOURS


191

EBT394 ADAPTIVE SIGNAL PROCESSING


VAC 4 0 0 4

Preamble: This course aims to introduce the students to the domain of adaptive signal processing including the convergence and stability issues associated with adaptive filter design and the design of optimum adaptive filtering solutions for real life applications. Prerequisite: Thorough understanding of signal processing techniques


CO 1 Identify the need for adaptation in filter design. CO 2 Analyse convergence and stability issues associated with adaptive filter design. CO 3 Evaluate the performance of various methods for designing adaptive filters. CO 4 Analyse the LMS adaptive algorithm which uses an iterative procedure. CO 5 Design filtering solutions for applications such as channel equalisation,

interference cancelling and inverse control.



CO 1 3 2 1 CO 2 3 2 2 1 CO 3 2 2 3 2 1 CO 4 2 3 2 1 1 CO 5 2 2 2 3 3 1

Assessment Pattern



Apply 40% 40% 40%

Analyse 40% 40% 40%

Evaluate 20% 20% 20%

Mark distribution


150 50 100 3 hours


192



Course Outcome 1 (CO1): Identify the need for adaptation in filter design.

1. Identify the major properties of Input Correlation matrix in adaptive systems. 2. Summarize the relative merits and demerits of open loop and closed loop adaptation. 3. Compare single input and multiple input adaptive linear combiner.

Course Outcome 2 (CO2): Analyse convergence and stability issues associated with adaptive filter design.

1. How does the learning rate affect the search characteristics? 2. Write the normal form of Input Correlation matrix. 3. What is the difference between Newton’s method and Steepest descent method?

Course Outcome 3(CO3):Evaluate the performance of various methods for designing adaptive filters.

1. How does the variance of the gradient estimate affect weight vector solution? 2. Illustrate the excess mean square error. 3. Examine the importance of perturbation and mis adjustment.

Course Outcome 4 (CO4): Analyse the LMS adaptive algorithm which uses an iterative procedure.

1. Express the LMS algorithm for an individual weight in a single input adaptive linear combiner.

2. Why Tmse and are identical in the case of LMS algorithm? 3. Examine theconvergence to the optimum weight vector solutions in LMS algorithm. Course Outcome 5 (CO5): Design filtering solutions for applications such as interference cancelling, inverse control and segmentation.

1. Design an adaptive filter to cancel 50Hz interference in Electrocardiography. 2. Suggest an adaptive filter to be employed in biosignal processing.


193

3. Why is an adaptive system superior in EEG segmentation?


Total Pages: 2

Reg No.:_______________ Name:__________________________

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY SIXTH SEMESTER B.TECH DEGREE EXAMINATION,

Course Code: EBT394 Course Name: ADAPTIVE SIGNAL PROCESSING


Answer all questions, each carries 3 marks. 10x3=30marks 1 Define adaptive system and summarize its characteristics. (3) 2 Differentiate closed loop and open loop adaptation. (3) 3 Identify the geometrical significance of Eigen Vectors and Eigen Values in

an adaptive system. (3)

4 What do you mean by Rate of convergence and Stability? (3) 5 Define “performance penalty” and “perturbation”. (3) 6 Is a negative performance penalty possible with quadratic functions? Justify

the answer. (3)

7 Write the expression for misadjustment in LMS algorithm. (3) 8 Compare the LMS adaptive algorithm with other algorithms. (3) 9 Draw the block diagram of a multiple-reference noise canceller in foetal

ECG. (3)

10 Identify the role of adaptive algorithm in system modelling, (3) PART B 5x14=70marks

Answer five full questions, each carries 14 marks. 11 a) In the adaptive linear combiner shown in Fig.1, let N=10, Find the optimum

weight vector.

(8)

b) Derive the expression for gradient and Minimum Mean Square Error with 2-Dimensional Performance surface plots.

(6)


194

OR 12. a)

For the Adaptive linear combiner given P = [−1 1]T, E[dk2] = 4,

derive the expression for performance surface ξ, and find ξmin.

(9)

b) Illustrate an example of a Biomedical Adaptive system. (5)

13 a) Write an expression and plot the learning curve for the performance surface ξ = 0.4w2 + 4w +11. Given an initial value w0 = 0 and a convergence parameter µ = 1.5.

(8)

b) Compare the similarities and differences between the Newton’s method and the method of steepest descent. (6)

OR

14 a) Deduce the mathematical expression of gradient search by Newton’s method. (8) b) Find the eigen values of

(6)

15 a) Derive the expression for excess mean square error for Newton’s method. (8) b) Examine the effect of a “noisy” gradient estimate on the weight vector during

the adaptation process. (6)

OR 16 a) Write the difference equations that describe the learning curves for Newton’s

method in terms of natural coordinates. (8)

b) Derive a general expression for perturbation with multiple weights. (6) 17 a) Examine the convergence and stability of the LMS algorithm. (8)


195

b) Illustrate the convergence of mean weight vector employing LMS algorithm using a two-weight combiner. (6)

OR 18 a) Derive LMS algorithm. Explain the convergence of weight vector. (8) b) Identify the advantages and the application areas of LMS algorithm. (6)

19 a) Demonstrate the usefulness of adaptive noise cancelling in fetal

Electrocardiography. (7)

b) How can an adaptive system be useful in inverse modelling? (7) OR

20 a) What is adaptive interference cancelling. Illustrate with suitable example. (7) b) Suggest two possible areas where adaptive filters can be employed in

biosignal processing. (7)

Syllabus

Module 1

Adaptive systems - definitions and characteristics - applications - properties- example of a biomedical adaptive system. Adaptive linear combiner -input signal and weight vectors, desired response and error, the performance function, Gradient and minimum mean square error,

Module 2

Properties of the quadratic performance surface, Normal form, eigen values and eigen vectors of the input correlation matrix. Searching the performance surface – basic ideas of gradient search methods, Stability and rate of convergence - learning curve -gradient search by Newton's method and the method of steepest descent - Comparison of learning curves.

Module 3

Gradient estimation and its effect on adaptation: gradient estimation by derivative method, the performance penalty ‐ variance ‐ derivative measurement with multiple weights, excess MSE and time constants ‐ misadjustments.

Module 4

Least-Mean-Square (LMS) adaptive filters: Derivation of the LMS algorithm, convergence of the weight vector, an example of convergence, learning curve, noise in the weight vector solution, misadjustment, performance.

Module 5


196

Applications: Adaptive modelling and system identification, Adaptive inverse control, adaptive interference cancellation- cancelling powerline interference in ECG, cancelling maternal ECG in foetal Electrocardiography. Adaptive filters for segmentation of EEG signals. (Implementation of any of the above applications on a simulation platform is mandatory).

Text Books

1. Adaptive Signal Processing, Bernard Widrow, Samuel D. Stearns, Pearson Education, 2002.

2. Adaptive filter theory, Simon Haykin, Fifth Edition, Pearson, 2014. 3. Biomedical Signal Analysis, Second Edition. By Rangaraj M. Rangayyan, The

Institute of Electrical and Electronics Engineers, Inc., 2015. Reference Books

1. Fundamentals of Adaptive Filtering, Ali H. Sayed, Wiley's student edition, 2016. 2. Intelligent and Adaptive Systems in Medicine (Series in Medical Physics and

Biomedical Engineering, Olivier C. L. Haas (Editor), Keith J. Burnham (Editor) September, 2019.

3. Fundamentals of Adaptive Signal Processing, Aurelio Uncini, Springer, 2015. 4. Adaptive Signal Processing, Next Generation Solutions, TulayAdalı Simon Haykin,

John Wiley, 2010. 5. Alexander D. Poularikas, Zayed M. Ramadan, Adaptive filtering primer with

MATLAB, CRC Press, 2006 Course Contents and Lecture Schedule


1 Module 1 1.1 Definitions and characteristics of Adaptive systems.

2

1.2 Applications, properties and example of a biomedical adaptive system.

3

1.3 Adaptive linear combiner -input signal and weight vectors, desired response and error.

2

1.4 The performance function, Gradient and minimum mean square error,

2

2 Module 2 2.1 Properties of the quadratic performance surface, Normal form,

eigen values and eigen vectors of the input correlation matrix. 2

2.2 Searching the performance surface – basic ideas of gradient search methods.

2


197

2.3 Stability, rate of convergence and learning curve. 2 2.4 Gradient search by Newton's method and the method of steepest

descent - Comparison of learning curves. 3

3 Module 3 3.1 Gradient estimation by derivative method. 3 3.2 The performance penalty ‐ variance. 2 3.3 Derivative measurement with multiple weights. 2 3.4 Excess MSE and time constants ‐ misadjustments. 2

4 Module 4 4.1 Derivation of the LMS algorithm, convergence of the weight

vector. 3

4.2 An example of convergence, learning curve. 2 4.3 Noise in the weight vector solution. 2

4.4 Misadjustments and performance. 2

5 Module 5 5.1 Adaptive modelling and system identification, Adaptive inverse

control. 3

5.2 Adaptive interference cancellation- cancelling powerline interference in ECG, cancelling maternal ECG in foetal Electrocardiography.

4

5.3 Adaptive filters for segmentation of EEG signals.

2


198

EBT396 DIGITAL INTEGRATED CIRCUITS


VAC 4 0 0 4

Preamble: This course gives an insight into the CMOS logic circuits and their applications.

Pre requisite: Basic knowledge of analog integrated circuit design.


CO 1 Recognise the CMOS logic circuits and analyse the impacts of interconnects present in them.

CO 2 Demonstrate an understanding of the design of combinational logic gates in CMOS

CO 3 Illustrate the implementation techniques of dynamic CMOS design.

CO 4 Design sequential logic gates in CMOS.

CO 5 Analyze the various configurations of common data path operators.


CO 1 3 1 1 1 1 1 CO 2 3 1 1 1 1 1 CO 3 3 2 2 2 1 1 CO 4 3 3 2 2 1 1 CO 5 3 3 3 2 1 1

Assessment Pattern



Mark distribution


150 50 100 3 hours


199


Attendance : 10 marks Continuous Assessment Test (2 numbers) : 25 marks Assignment/Quiz/Course project : 15 marks (50% of the assignment shall be of circuit simulation using any of the open source tools.) End Semester Examination Pattern: There will be two parts; Part A and Part B. Part A contain 10 questions with 2 questions from each module, having 3 marks for each question. Students should answer all questions. Part B contains 2 questions from each module of which student should answer any one. Each question can have maximum 2 sub-divisions and carry 14 marks.

Course Level Assessment Questions Course Outcome 1 (CO1): Recognise the CMOS logic circuits and analyse the impacts of interconnects present in them.

1. What are skewed inverters? 2. Explain the important properties of static CMOS circuits. 3. Sketch a transistor-level schematic for a CMOS 4-input NOR gate.

Course Outcome 2 (CO2) :Demonstrate an understanding of the design of combinational logic gates in CMOS

1. Write notes on pull down networks. 2. Discuss the concept of ratioed logic. 3. What are pass transistors?

Course Outcome 3(CO3):Illustrate the implementation techniques of dynamic CMOS design.

1. What is min delay constraint? 2. Write notes on logic propagation delay. 3. Discuss the power dissipation in dynamic logic circuits.

Course Outcome 4 (CO4): Design sequential logic gates in CMOS.

1. What are true single phase clocked register? 2. What is the propagation delay in dynamic edge triggered registers? 3. State the bi stability principle.

Course Outcome 5 (CO5): Analyse the various configurations of common data path operators.

1. What are barrel shifters? 2. Discuss carry propagate addition. 3. Explain the unsigned array multiplication.


200


SET1 Total Pages:

Reg No.:______________ Name:__________________________

APJ ABDUL KALAM TECHNOLOGICAL UNIVERSITY

SIXTH SEMESTER B.TECH DEGREE EXAMINATION

Course Code: EBT396

Course Name: DIGITAL INTEGRATED CIRCUITS


PART A

Answer all questions. Each carries 3 marks

1 Define static noise margin. (3)

2 What are skewed inverters? (3)

3 Write notes on pull up networks. (3)

4 Comment on the propagation delay in complementary CMOS gates. (3)

5 Illustrate the clocking issues in dynamic CMOS circuits? (3)

6 What is known as race condition? (3)

7 What is the propagation delay in dynamic edge triggered registers? (3)

8 State the bi-stability principle in static latches. (3)

9 Write notes on one/zero detectors. (3)

10 What are funnel shifters? (3)

PART B

11 a) Sketch a 3 input CMOS NOR gate. 6

b) Explain the important properties of static CMOS circuits. 8

OR

12 a) ______________ Sketch a static CMOS gate computing Y = (A + B + C) · D.

7

b) Write notes on the impact of interconnect in logic circuits. 7

13 a) Explain the power dissipation in CMOS logic circuits. 8


201

b) Discuss the Pass transistor threshold drops with necessary diagrams. 6

OR

14 a) Draw and explain the operation of a two-input NAND gate in complementary static CMOS style.

6

b) Discuss the static properties of complementary CMOS gates. 8

15 a) Explain the following sequencing element timing delays corresponding to a latch: i)logic propagation delay ii) Latch D to Q Contamination delay iii) Latch set up time iv) Latch hold time

8

b) Discuss the phases, pre-charge and evaluation in dynamic logic gates. 6

OR

16 a) Explain the speed and power dissipation in dynamic logic. 8

b) Discuss the issues associated with dynamic design. 6

17 a) Discuss the advantages of using true single phase clocked registers. 6

b) Analyse the min-delay constraint in the design of Flip-flop latch. 8

OR

18 a) Illustrate the operation of clocked CMOS registers. 8

b) Explain the max-delay timing constraints on a path between two flip-flops.

6

19 a) What are barrel shifters? Explain the operation of masking logic used in barrel shifters.

8

b) Discuss the operation of a 4 bit ripple carry adder and comment on its delay.

6

OR

20 a) Explain the operation of a 4 × 4 array multiplier for unsigned numbers using an array of Carry Save adders.

9

b) Write notes on the operation of subtractors. 5


202

Syllabus

Module 1

CMOS Logic: Static CMOS Inverter – DC characteristics, beta ratio effects, noise margin, NAND gate, NOR gate, compound gates. Interconnects-wire geometry, skin effect, impact of interconnect - delay, energy, cross talk.

Module 2

Combinational Logic Circuits: Static CMOS design- basic concept of complementary CMOS, Ratioed logic and pass transistor logic, transmission gates, designing with transmission gates, power dissipation in CMOS logic circuits- dynamic power, static power.

Module 3

Dynamic CMOS design: Basic principles of dynamic logic, speed and power dissipation in in dynamic logic, domino CMOS logic - non inverting property, optimization of domino logic gates, clocking issues, two phase clocking.

Module 4

Sequential Logic Circuits: Timing metrics for sequential circuits, classification of memory elements, static latches and registers - the bi stability principle, SR flip-flops, multiplexer-based latches, dynamic latches and registers - dynamic transmission gate edge triggered registers, C2MOS register, true single phase clocked register (TSPCR), Max delay constraints and Min delay constraints – effect of constraints in flip flop.

Module 5

Datapath Subsystems- Addition-single bit addition, carry propagate addition-ripple carry adder, carry look ahead adder, subtraction, One/Zero detectors, Shifters - funnel shifter, barrel shifter, multiplication - unsigned array multiplication.

Note: Circuit simulation using open source tools should be carried out as a part of instruction for all modules.

Text Books:

1. David Money Harris, Neil Weste, “CMOS VLSI design-A circuit and Systems

perspectives”,Pearson, 4th edition 2010 2. Jan M. Rabaey, AnanthaChandrakasan, Borivoje Nikolic, “Digital Integrated Circuits:

A design perspective ’’, Pearson Education India; Second edition, 2016.

References:

1. John E. Ayers, “Digital Integrated Circuits”, CRC Press, second edition, 2010. 2. John P. Uyemura,“CMOS Logic Circuit Design”, Springer US, third edition, 2013.


203

3. Sung-Mo Kang, Yusuf Leblebici, “CMOS Digital Integrated Circuits”, Tata McGraw-Hill, third edition, 2008



1 Module 1

1.1 Static CMOS Inverter – DC characteristics, beta ratio effects, noise margin 3

1.2 NAND gate, NOR gate, Compound gates. 3

1.3 Interconnects-wire geometry, skin effect, impact of interconnect-delay, energy, cross talk. 3

2 Module 2

2.1 Static CMOS design- basic concept of Complementary CMOS, 2

2.2 Ratioed logic and Pass Transistor logic ,Transmission Gates, 3

2.3 Designing with transmission gates, 1

2.4 Power dissipation in CMOS logic circuits- dynamic power, static power 3

3 Module 3 3.1 Basic principles of dynamic logic, Speed and power dissipation in in

dynamic logic 3

3.2 domino CMOS Logic-non inverting property, 3

3.3 Optimization of domino logic gates 1

3.4 Clocking Issues, Two phase clocking. 2

4 Module 4

4.1 Sequential Logic Circuits: Timing Metrics for Sequential Circuits, Classification of Memory Elements 2

4.2 Static Latches and Registers-The Bi-stability Principle, SR Flip-Flops, Multiplexer-Based Latches 3

4.3 Dynamic Latches and Registers-Dynamic Transmission-Gate Edge-triggered Registers, C2MOS Register, True Single-Phase Clocked Register (TSPCR)

3

4.4 Max delay constraints and Min delay constraints - flip flop. 1

5 Module 5

5.1 Addition-single bit addition 3

5.2 Carry propagate addition-ripple carry adder, carry look ahead adder 3

5.3 Subtraction, Multiplication-unsigned array multiplication 3


204

EBT398 STATISTICAL METHODS IN BIOMEDICAL ENGINEERING


VAC 3 1 0 4

Preamble: This course aims to make students able to apply the fundamental principles of statistical methods used in biological and medical research.

Prerequisite: NIL


CO 1 Understand the basic concepts in statistics and be able to calculate and interpret descriptive measures of data.

CO 2 Apply probability distributions to real world problems.

CO 3 Apply principles of estimation and hypothesis testing for statistical inferences.

CO 4 Apply principles of analysis of variance for design of experiments.

CO 5 Apply principles of regression and correlation for statistical data analysis.


PO1 PO 2 PO 3 PO 4 PO 5 PO 6 PO 7 PO 8 PO 9 PO10 PO11 PO12 CO 1 3 3 2 CO 2 3 3 2 1 CO 3 3 3 2 1 CO 4 3 3 2 1 CO 5 3 3 2 1

Assessment Pattern




Mark distribution


150 50 100 3 hours


205




Course Outcome 1 (CO1): Understand the basic concepts in statistics and be able to calculate and interpret descriptive measures of data/

1. What are the basic statistical terms and concepts?

2. Illustrate the different techniques to condense and organize information into a set of descriptive measures.

3. Demonstrate the different means of representing data to enhance the understanding of complex data.

Course Outcome 2 (CO2):Apply probability distributions to real world problems. 1. Explain the different types of discrete and continuous probability distributions.

2. Develop methods to make statistical inferences using probability distributions.

Course Outcome 3(CO3):Apply principles of estimation and hypothesis testing for statistical inferences.

1. What is Central Limit Theorem?

2. Identify the statistical distributions to be used to make statistical inferences

3. Demonstrate how structured hypothesis test to make statistical inference.

Course Outcome 4 (CO4): Apply principles of analysis of variance for design of experiments

1. What are the commonly used experimental designs?

2. Identify the methods of partitioning the total variance computed in a data set into different components.

3. Utilize the partitioning to estimate and test hypotheses about population variances and means.

Course Outcome 5 (CO5): Apply principles of regression and correlation for statistical data analysis.

1. How methods of linear regression can be made use to objectively predict or estimate the value of one variable given a value of another variable?


206

2. How methods of correlation can be made use of to find an objective measure of the strength of the relationship between two variables?


Total Pages: 2

Reg No.:_______________ Name:__________________________


Course Code: EBT398 Course Name: Statistical Methods in Biomedical Engineering



1 Compare the properties of mean and median. (3)

2 What is a box plot? (3)

3 What is the difference between a frequency distribution and a probability distribution?

(3)

4 Define binomial distribution. What are its parameters? (3)

5 Differentiate between null and alternate hypothesis. (3)

6 What is p-value? (3)

7 What do you mean by student’s t-test? (3)

8 What do you mean by a completely randomized design? (3)

9 What are scatter diagrams? (3)

10 What do you mean by a regression line? (3)


Module 1

11 a) Compute the mean, median and mode of the data given below that

shows the birth weight (in grams) of babies born in a period of one

week. 1 3265 5 4146 9 3031 13 3609 17 3248

2 3260 6 3323 10 2069 14 2838 18 3314

3 3245 7 3649 11 2581 15 3541 19 3101

4 3484 8 3200 12 2841 16 2759 20 2834

(9)

b) What are the different classifications of data? Give examples. (5)


207

OR

12 a) Define range, variance and standard deviation of data. (6)

b) The following data shows the number of hours 45 hospital patients slept

following the administration of a certain anaesthetic. 7 10 12 4 8 7 3 8 5 12 11 3 8 1 1 13 10 4 4 5 5 8 7 7 3 2 3 8 13 1 7 17 3 4 5 5 3 1 17 10 4 7 7 11 8 From these data construct:

a) A frequency distribution b) A relative frequency distribution c) A histogram d) A frequency polygon

(8)

Module 2

13 a) What is a discrete random variable? Define the probability distribution of a discrete random variable. Give one example of each.

(6)

b) Given a normally distributed random variable X with σ = 10 and P(X≤ 40) = 0.0080, find μ. Given a normally distributed random variable X with μ = 25 and P(X≤ 10) = 0.0778, find σ.

(8)

OR

14 a) What is a continuous random variable? Define the probability distribution of a continuous random variable. Give one example of each.

(6)

b) Define a Poisson distribution. Find its mean and variance. Under what conditions can a binomial distribution be approximated to a Poisson distribution?

(8)

Module 3

15 a) State the central limit theorem and illustrate it with an example. (6)

b) Define confidence interval. How is it useful in statistical estimation? Derive (100-α)% confidence limits for the parameter λ of the Poisson distribution. Write the 95% and 99% confidence intervals for the parameter λ

(8)

OR

16 a) Define chi-square, t, F tests and bring out the relations connecting them. What are the important assumptions in each?

(9)

b) Differentiate between Type I and Type II errors. (5)

Module 4

17 a) Students were given two different drug treatments before revising for their exams. The drugs given and the exam scores in percentage are given below for three different groups. Carry out one-way ANOVA and construct the ANOVA table to test the hypothesis that the treatments will have different effects.

(14)


208

Memory drug Placebo No treatment

70 37 3

77 43 10

83 50 17

90 57 23

97 63 30

Mean 83.40 50.00 16.60

Variance 112.30 109.00 112.30

Grand mean 50.00

Grand Variance 892.14

OR

18 a) What do you mean by two-way ANOVA? How is it different from one-way ANOVA?

(5)

b) What are the different steps in conducting two-way ANOVA? (9)

Module 5

19 a) What do you mean by a scatter diagram? (2)

b) The following scores represent a nurse’s assessment (X) and a physician’s assessment (Y) of the condition of 10 patients at time of admission to a trauma center. X: 18 13 18 15 10 12 8 4 7 3 Y: 23 20 18 16 14 11 10 7 6 4 (a) Construct a scatter diagram for these data. (b) Plot the following regression equations on the scatter diagram and indicate which one you think best fits the data. State the reason for your choice. (1) ŷ = 8 + 0.5x (2) ŷ = -10 + 2x (3) ŷ = 1 + 1x

(12)

OR

20 a) What are the assumptions underlying simple linear regression? (7)

b) How do you obtain a regression equation to fit a scatter diagram? (7)


209

Syllabus

Module 1

Introduction to statistics: Basic concepts and terminology – Data: Types - Binary (dichotomous), Categorical, Nominal categorical, Ordinal categorical, Continuous, Time to Event Data. Population & sampling - data organization – frequency distributions. Data display – Histograms, Frequency polygon & Box plots. Sample distributions – shapes - symmetric & skewed Descriptive statistics: Measures of central tendency – Mean, median & mode, Measures of dispersion – Range, variance, standard deviation, Kurtosis. Applications in Biomedical engineering.

Module 2

Probability distributions: Random variables – discrete & continuous, Probability distributions of discrete variables – Binomial and Poisson distributions – Continuous probability distributions - Normal distribution - features - Mean, variability, Calculating normal (z) scores - applications.Joint probability density function – marginal and conditional distributions. Applications in Biomedical engineering.

Module 3

Statistical Inference: Estimation - Central Limit theorem – Estimation of confidence interval – mean & variance - t, chi-square & F distributions – Chi-square test for goodness of fit. Hypothesis testing – null & alternate hypothesis, steps in testing, p values calculations and interpretations - Type I error and Significance level, Type II errors. Single population mean & difference between two population means – Single population variance & ratio of population variances. Applications in Biomedical engineering.

Module 4

Paired t-Test, Two sample (Unpaired) t-test, Confidence intervals for mean difference between two independent populations. Non-parametric test - Mann Whitney Rank Sum Test. Analysis of variance: Introduction – Completely randomized design and randomized block design - One way and two-way ANOVA. Applications in Biomedical engineering.

Module 5

Regression & Correlation: Regression model,Linear regression – scatter diagrams, least squares method, regression equation – evaluation & use. Correlation model and correlation coefficient. Applications in Biomedical engineering.

Assignments shall be given on statistical programming using suitable software to generate charts, graphs, computation of descriptive statistics, plotting of standard distributions.


210

Text Books 1. W.W.Daniel, Biostatistics- A Foundation for Analysis in the Health Sciences,

Wiley, 2013. 2. B. Rosner, Fundamentals of Biostatistics, Cengage Learning, 2011.

Reference Books

1. Martin Bland, An Introduction to Medical Statistics, Oxford University Press, 2015 2. Jay Devore, Probability and Statistics for Engineering and the Sciences, Cengage

Learning, 2012. 3. Conrad Carlberg, Statistical analysis MicroSoft® EXCEl 2010, Pearson Education,

Inc., 2011. Course Contents and Lecture Schedule


1 Module 1

1.1 Basic concepts and terminology in Statistics 3 1.2 Data organization & display 2 1.3 Measures of central tendency 2 1.4 Measures of dispersion 2 2 Module 2 2.1 Random variables 1 2.2 Probability distributions of discrete variables 3 2.3 Probability distributions of continuous variables 3 2.4 Joint probability density function 2 3 Module 3 3.1 Central Limit theorem 1 3.2 Estimation of confidence interval 2 3.3 t, chi-square & F distributions 3 3.4 Hypothesis testing 3 3.5 Single population mean & variance 2 4 Module 4 4.1 Paired & unpaired t-tests 3 4.2 Non-parametric test 1 4.3 Analysis of variance 4 5 Module 5 5.1 Regression model, evaluation & use 4 5.2 Correlation model, evaluation & use 4

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electronics & biomedical engineering

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