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Centre for Integrated Electronic Systems and Biomedical Engineering (CEBE) Tallinn University of Technology
www.cebe.ttu.ee
Research Results in Biomedical Engineering:
from lab to hospitals
Ivo Fridolin Department of Biomedical Engineering, Technomedicum
Ivo Fridolin
Biofluid Optics
P5
8
Platform based design of embedded systems
Processor architectures
P1
Verification and diagnosis
P2 1
Semicond. technology
P7
5
Testing and reliability
P6
2
4
Applications
Healthcare needs
Other industry
needs
CEBE Competences and Projects Flow
P8
Signal processing methods
Society
Engineering resources,
training
P6 P1 P3 P4 P5
3
P4
6
Brain Studies
P3 7
Cardiovascu-lar diseases
P1
Ivo Fridolin
5
Biomedical Engineering Research at TM
R&D Topics:
Brain diagnostics
Diagnostics of cardiovascular diseases
Optical kidney dialysis monitoring
Ivo Fridolin
6
Brain Diagnostics: principle and problem
+ The brain bioelectrical activity
(EEG signal) is a good source
of knowledge about the
functioning of the brain
providing objective information
related directly to its ability to
process information.
- Useful diagnostical
information is hidden in
highly complex natural
variability of the EEG signal
Ivo Fridolin
7
Evaluation of the state of the brain
Detection of characteristic features of electroencphalographyc (EEG) signals related to
i) Mental disorders (depression, stress etc.)
According to the analysis by WHO, depressive disorder is a leading cause of burden
of disease in high- and middle-income countries nowadays and it is projected to take the first place in the world in 2030. Methods for objective and early detection of
depression is an highly actual topic (f.e. the case of Germanwings co-pilot).
ii) Excitation of the brain by external stressor (effect of radiofrequency electromagnetic fields - EMF)
Importance of the problem of the EMF (mobile phones, wifi, relay antenna etc) health effects is underlined in the resolution by European Parliament from 2009 and Council of Europe 2011 on health concerns of population associated with EMF fields and potential danger of EMF. The health protection regulations are still based on the thermal effects only.
Ivo Fridolin
8
Evaluation of sensitivity of a new method – Spectral Assymmetry Index (SASI)
SASI bases on the balance of powers of two EEG
frequency bands selected higher and lower than
the EEG spectral maximun (alpha band). US8244341B2 granted 14.08.2012: Method and device
for diagnosing a mental disorder by measuring
bioelectromagnetic signals of the brain,”
The classification accuracy of SASI in detection of depression compared to nonlinear EEG
analyses methods, Higuchi’s Fractal Dimension (HFD), Detrended Fluctuation Analysis
(DFA), and Lempel Ziv Complexity (LZC), based on single channel P3 signal
HFD 85 % SASI 85 %
DFA 70,6 % SASI 76,5 %
LZC 77 % SASI 80,5 %
The developed original SASI method provides at least similar sensitivity but much
less computing power compared to traditional nonlinear methods is required.
Bachmann et al., Computational and Mathematical Methods in Medicine, 2013,
Bachmann et al., IFMBE Proceedings 2014
Bachmann et al., IFMBE Proceedings 2015
Ivo Fridolin
9
FPGA based EEG Analyzer Prototype for implementation of SASI – CEBE project 4
Cooperation between with the Departments of Computer Engineering and Biomedical
Engineering
The project is targeted
to development of
method and device for
early detection of
mental disorders.
The EEG Analyzer is a portable device offering real-time in-field analysis, convenience of
obtaining experimental data for further research and acceleration of the calculation
procedure. It is applicable for evaluation of high-risk personnel such as pilots, police,
military, rescue workers.
The EEG analyser prototype is being under testing in Qvalitas Medical Center, the
largest occupational health care provider in Estonia and has got first positive responses.
Ivo Fridolin
The mechanism of low-level microwave effect on brain
10
Effect on
hydrogen
bonding
Rotation of
dipolar water
molecules
Enhanced
diffusion
Membrane resting
potential of
neurons
Transfer rate of
neurotransmitters
in synapses
Physiological
consequen ces
Parametric excitation of
brain bioelectric
oscillations
Effect on EEG rhythms
First, the nonthermal
mechanism of the
microwave radiation
effect on brain
oscillations was proposed
and proved by
experiments.
Hinrikus et al., Electromagnetic Biology and
Medicine, 2014.
Suhhova et al., Bioelectromagnetics, 2013.
Hinrikus, et al., Int J Radiat Biology, 2011.
Ivo Fridolin
11
Evaluation of the state of the brain
Cooperation:
North Estonia Medical Center, Estonia
Qvalitas, Estonia
West-Tallinn Central Hospital, Estonia
University of Skopje,
Nalecz Institute of Biocybernetics and Biomedical
Engineering of the Polish Academy of Sciences, Poland
University of Eastern Finland, Finland
Ivo Fridolin
12
Biomedical Engineering Research at TM
R&D Topics:
Brain diagnostics
Diagnostics of cardiovascular diseases
Optical kidney dialysis monitoring
Ivo Fridolin
Diagnostics of Cardiovascular Diseases
(K.Meigas)
Atherosclerosis is an endovascular inflammatory disease, resulting in a build up of a plaque, which may partially or totally block blood flow in artery.
13
Technomedicum
Ivo Fridolin
Diagnostics of Cardiovascular Diseases
(K.Meigas)
Optical methods for early diagnosis of atherosclerosis
Pulse waveform analysis method for estimation of arterial ageing
Novelty – rapid, inexpensive, and noninvasive method
• results are obtained after ~1 minute long registration of optical signal
• Current Standard method: needs trained operator, depends on the subject the registration procedure may take ~15 minutes, expensive equipment
Experimental measurement complex:
Experimental complex for investigation of arterial system using optical, piezoelectrical, phonocardiographical and electrocardiographical methods and signals.
15
Technomedicum
Ivo Fridolin
Diagnostics of cardiovascular diseases
The algoritm for estimation of arterial ageing.
The setup in Centre of Cardiology The setup in DialysisForum
PPGb
PPGd
A
AA
A
PPGAI b
d
Ivo Fridolin
Pulse wave analysis in Technomedicum
Registration of pulse wave from patient for estimation of arterial ageing.
17
Ivo Fridolin
TM
Cardiology
team
Interpretation
of biosignals
and signal
processing
algorithms
Project
P3
Optical sensor
Project P1
P3: Development of optical sensor for pulse wave registration from artery
ATI
Design
Team
Design
solutions
Estimation of arterial stiffness based
on pulse wave velocity and pulse
waveform analysis. Pulse waveform
analyzer PA-21 –
device for pulse
waveform analysis
and estimation of
arterial ageing.
New concept:
Novel optical sensor for pulse
wave from arteries and
peripheral blood vessels.
Pulse wave
registration
Ivo Fridolin
Diagnostics of cardiovascular diseases
There is collaboration with North Estonia Medical Center (Tallinn Estonia) in order to carry out studies on diabetes, coronary artery, and chronic kidney disease patients:
Center of General Internal Medicine:
Dr. Anu Ambos
Centre of Nephrology:
Dr. Merike Luman
Center of Cardiology:
Dr. Marika Heinpalu-Kuum
Laboratory:
Dr. Galina Zemtsovskaja
Dr. Marika Pikta
Ivo Fridolin
20
Biomedical Engineering Research at TM
R&D Topics:
Brain diagnostics
Diagnostics of cardiovascular diseases
Optical kidney dialysis monitoring
Ivo Fridolin
21
Optical kidney dialysis monitoring
Kidney dialysis -
treatment of the end
stage renal disease
(ESRD) patients by the
artificial kidney (dialysis
machine) in order to
replace all main kidney
functions.
Ivo Fridolin
24
Clinical kidney dialysis dose
Dialysis dose should be expressed in terms of equilibrated Kt/V
(eKt/V) with the rate equation based on the regional blood flow two-pool
urea kinetic model (evidence level: B).
European Best Practice Guidelines Expert Group on Haemodialysis. Nephrol
Dial Transplant 2002: 17(Suppl 7): S16–S31
4. Minimum adequate dialysis: Guideline 4.1
In anuric patients, treated by three times per week
dialysis, the prescribed target eKt/V should be at least 1.2.
Tattersall, J., A. Martin-Malo, et al. (2007). "EBPG guideline on dialysis
strategies." Nephrology Dialysis Transplantation 22: 5-21.
Current dialysis dose quality parameters are based only on a singel
markermolecule – urea!
Ivo Fridolin
25
Optical kidney dialysis monitoring
Commercially available options:
• Option Adimea, B. Braun Avitum AG
• Dialysis Dose Monitor, Nikkiso Co, Ltd.
Ivo Fridolin
26
Dialysis adequacy estimation: what is wrong with Kt/V?
Urea per se is not toxic
There are > 100 uremic retention solutes
removed normally by the kidneys
How removal of a single (non-toxic)
molecule can be valid for all 100 molecules
with different kinetics, i.e. removed differently
during dialysis ?
Ivo Fridolin
28
Optical kidney dialysis multi component monitoring
MCM:
· Uremic toxins
· Cardiovascular markers
Small
Molecules
< 500 Da
Protein Bound
Molecules
< 500 Da
Middle
Molecules
500 .. 12 000 Da
Enhanced Vision
for
Dialysis Quality
Monitoring
via
Multi component
monitoring
Ivo Fridolin
29
Multicomponent (MCM©) Sensor concept
Optofluid Technologies OÜ (OFT ) is a spin off company based on the research from CEBE.
MCM© sensor is an official trade mark of OFT.
MCM© sensor
Built-in module
Dialysis
machine
Benefits
• Enhanced dialysis dose quality monitoring
• Cardioprotective therapy assurance
• Improved dialysis care
• Improved life quality
• Longer life expectancy
• Lower healthcare costs
Ivo Fridolin
ATI
Verification
Team
Fault diagnosis
methods
Toolkit
for
dialysis
monitoring
New
algorithms of
signal analysis
Project P2
Optical methods for monitoring of
dialysis
Clinical experiments
Project P5
TM
Biofluids Optics
Team
Cooperation Project P5
Ivo Fridolin
32
CEBE Cooperation Project P5
The advantages of the SMART algorithm compared to the L-M algorithm are that:
• data processing is done without any time delay providing instantly exact information about the treatment process; • it allows for extrapolating at any time moment the current knowledge about the treatment process to predict the end for the treatment.
Fridolin, I.; Karai, D. ;Kostin, S. ;Ubar, R. (2013). Accurate Dialysis Dose
Evaluation and Extrapolation Algorithms during On-line Optical Dialysis
Monitoring . IEEE Transactions on Biomedical Engineering, 60(5), 1371 - 1377.
Ivo Fridolin
33
Conclusions: from labs to hospitals
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