1. 1. Knee Rehabilitation Monitor Nicholas Pesce ECE 445 Senior Design Hall of Fame Spring 2015
2. 2. Introduction There are over 100,000 reconstructive ACL knee surgeries and 700,000 total knee replacement surgeries annually in the U.S. Patients are prescribed supervised, physical therapy as a crucial component for rehabilitation What can be done to reduce a persons physical therapy time and promote safety?
3. 3. Problems with Knee Rehabilitation Disrupted everyday life after surgery; dedicated to physical therapy for at least 10 weeks up to 4 sessions per week Therapists cannot monitor patients at home activity to ensure safe practice Patients may not be motivated or confident to perform self exercises without the physical therapists guidance Therapy is expensive and can cost on average around $100- $500 per session without insurance There is an Increased risk of further injury and prolonged rehabilitation when the patient is unsupervised costing the patient time and money
4. 4. What is Important to Target? How much can a patient flex their injured knee? How strong are the muscular contractions of the muscles surrounding the knee? Are patients actually performing at home exercises? How can therapists see what a patient does at home to provide better care? How can a patient be assured that the movements they perform with their knee are safe and cannot reinjure their knee? How can we give patients the confidence to carry out their prescribed home exercise routine? How can the cost of physical therapy after knee surgery be reduced by a significant factor?
5. 5. The Solution: A Knee Rehabilitation Monitor Features: A 4 flex sensor tracks the amount a patient can flex their knee A custom Electromyography sensor detects the strength of voltage contractions in the quadriceps of the injured knee A Texas Instruments MSP430 Launchpad Microcontroller uses the flex sensor, an accelerometer and a gyroscope to drive vibration motors which alert the patient to unhealthy knee movements Data collection algorithms programmed into the microcontroller collect exercise data for review by a physical therapist Vibration motors also help guide patients through prescribed at home physical therapy exercises in a safe and healthy manner with positive feedback A battery management system allows the user to detect low power from the battery source to ensure proper component operation
6. 6. Design Considerations The overall design must be built into a flexible and wearable sleeve Fabricated microchips must be small enough to allow easy integration into such a sleeve Fabricated microchips must be thin and low profile The selected microcontroller must have sufficient storage capability for logical operations and programmed algorithms Selected sensors must be capable of withstanding regular daily use EMG and the motherboard chip must be separated into two different PCB boards to ensure low noise acquisition of data Overall design must cost less than the average cost of a week of physical therapy Power to the chips must come from a singular 9V battery to ensure small size package
7. 7. System Block Diagram
8. 8. Knee Rehabilitation Monitor Flex Sensor EMG + Flex Sensor PCB Main PCB + Accelerometer Gyroscope Vibration Motor #2 Vibration Motor #1 EMG Electrode Push Buttons Front View of Right Leg Side View of Right Leg
9. 9. Modes of Operation Push buttons on the PCB allow the user to select between different modes programmed into the microcontroller Mode 1 = Calibration Mode Used to set benchmarks Mode 2 = Everyday Mode Used to detect unhealthy movements Mode 3 = Exercise Mode Used to track and promote at home exercises Mode 4 = Inactivity Mode Used to prevent knee stiffness
10. 10. Selected Sensors Flex Sensor EMG Gyroscopes + Accelerometer
11. 11. Flex Sensor Oriented in front of the knee cap to measure the knee joint angle Acts as a variable resistor between 10k Ohms and 35k Ohms, changing its resistance based on how the sensor is bent Implemented into a voltage divider circuit so that an output voltage can drive the microcontroller Flex sensor voltage divider equation Flex sensor
12. 12. Calibration Mode: Flex Sensor Ensures that any patient can use this device based on their own personal ability A patients range of motion changes throughout rehabilitation and calibration accounts for this Captures max/min flexion angles Captures maximum base quad contraction strength Maximum Knee Extension Maximum Knee Flexion
13. 13. 0 2 4 6 8 10 12 14 16 18 20 1.5 1.55 1.6 1.65 1.7 1.75 1.8 1.85 1.9 1.95 2 Time (s) Voltage(v) Flex Sensor Data for Heel Slide Exercise Exercise Mode: Heel Slide Exercise Poor Knee Flexion Poor Knee Extension Notifies patient if they are coming close to their maximum flexion and extension during this exercise Give positive vibrational feedback when the patient surpasses a given threshold
14. 14. Everyday Mode: Knee Joint Jerk Detection 0 1 2 3 4 5 6 7 8 9 10 1.5 1.6 1.7 1.8 1.9 2 2.1 2.2 Time (s) Voltage(V) Flex Sensor Data for Jerk Detection 0 1 2 3 4 5 6 7 8 9 10 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 Time (s) |V|(V) Absolute Derivative of Data (100ms samples) Jerks Detected
15. 15. Selected Sensors Flex Sensor EMG Gyroscopes + Accelerometer
16. 16. EMG Used for feedback during quad contraction exercise Important for providing a measure of how much the muscles around the knee have atrophied after repair The signal detected originates from action potentials fired by cells which are collected at the surface of the skin with electrodes Based on the relative strength of a persons quad contraction, more or less voltage will be detected indicating muscular health/recovery
17. 17. EMG Calculations EMG signals are nested between 20-500 Hz and are in the magnitude of microvolts-millivolts. Larger muscles are in the lower half of the band. The resistor and capacitor values for the EMG band-pass filter were determined to satisfy the following gain and cut-off frequency requirements: 2 1 10 R Gain R 1 1 1 1 20 2 fc Hz R C 2 2 2 1 300 2 fc Hz R C Band-Pass Gain Calculation Lower Frequency Cut-Off Calculation Upper Frequency Cut-Off Calculation R1 = 1k Ohm C1 = 8.5 F R2 = 10k Ohm C2 = 53 nF Overall Gain = = / Bio-Amp Gain Calculation = (50.5/(120))+1 = 422 V/V
18. 18. Electrode Collection AD622 Instrumentation Amplifier used to derive a voltage drop (Gain of 422 V/V) LM358 Bandpass Filter (19.89Hz - 300.29Hz Range) (Gain of 10 V/V) LM 358 Full wave Rectifiation Detection Filter Full Wave Rectify
19. 19. 0 2 4 6 8 10 12 0 0.5 1 1.5 2 2.5 Time (s) Voltage(v) EMG Data for Quadricep Activity Exercise Exercise Mode: Quadricep Activity Strong Contraction Weak Contraction Constant Contraction
20. 20. Selected Sensors Flex Sensor EMG Gyroscopes + Accelerometer
21. 21. Gyroscope and Accelerometer Used to detect motion of the upper and lower leg Gyroscope: rotational acceleration Accelerometer: linear acceleration SPI interface Selectable low-pass filters and full-scale range MPU-6500: Accelerometer and Gyroscope ITG-3400: Gyroscope
22. 22. Everyday Mode: Twist Detection Compare the output values between the upper and lower gyroscope abs(upper lower) > threshold
23. 23. Challenges Single supply op-amp implementation Solved with voltage charge pumps Data storage Solved with external card Variations in sensor placement Somewhat solved with calibration mode Bulky PCB board Could be solved with flexible PCB Technology Successes Used robust calibration methods to address knee variations Implemented four feedback algorithms for everyday use and exercising Created a system that acquires a variety of sensor data facilitating future feedback algorithms Challenges and Successes
24. 24. Our goal was to create a product designed for a patients safety, recovery and to be cost effective If our device reduces PT time by just 1 week it would be a difference of around $300-$500 in savings for the patient This product is extremely marketable and was the winner of the Lextech Most Marketable Product Award which was one of 3 cash awards given to over 60 competing senior, Electrical Engineering teams Target Bullseye
25. 25. Add a Bluetooth module and smart phone application to facilitate data acquisition, to increase processing capabilities and appeal to users Improve signal analysis for sensor data to implement more accurate feedback algorithms Allow physical therapists to easily adjust settings on the device Develop a smaller PCB board and clean up mechanical design-flexible PCB board Tech Alternative applications using our technology: Athletic brace to prevent potential knee injury Weightlifting form correction Retail or factory inactivity monitor Future Work
26. 26. Acknowledgements My Teammates: Gurmehar Lugani Mark Hernandez TA Cara Yang Professor Oelze Professor Carney Jonathan Hernandez, DPT Kristin Buesing, DPT Heather Schaefer, DPT Rebecca Nef-Heffernan, PT ECE Store and ECE Shop
27. 27. Questions?