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ECG processing pipelines
on steroids
how we replaced math models with machine learning?
Vitalii Sahan, Artem Bachinskyi
MAWI Solutions
Domain meetup: E-Healthcare #2
Domain meetup: E-Healthcare #2
About MAWI
● Wellness analysis
● Cardio health
● Stress management
● Sleep quality
● Biometrics
Domain meetup: E-Healthcare #2
Domain meetup: E-Healthcare #2
Evolution of our device
Source: imgur.com/gallery/BpNZAj7
Domain meetup: E-Healthcare #2
Domain meetup: E-Healthcare #2
How your heart works?
Source: imgur.com/gallery/BpNZAj7
What is ECG
Electrocardiogram (ECG)
PPG vs ECG
How ECG is used in Medicine?
Medical Big Data in Ukraine?
● P (Pase/Pulse) - depolarization of the
atria
● P-Q Interval - reflects the time the
electrical impulse takes to travel from
the sinus node through the AV node
● QRS Complex - represents the rapid
depolarization of the right and left
ventricles
● T wave represents the repolarization
of the ventricles - Restoration of
original state of the heart
What is QRS complex
Source: gfycat.com/ru/naiverealistichorseshoebat
Machine Learning
Domain meetup: E-Healthcare #2
Domain meetup: E-Healthcare #2
What is machine learning?
Data Knowledge
Cats vs Dogs
Cats vs Dogs
How to train ML model?
Image data
Image representation
Image data
Convolutional filters
Feature map
FiltrationRaw ECG Annotation
Feature
Extraction
Feature
Analysis
Conventional ECG processing pipeline
Source:https://biosppy.readthedocs.io/en/stable/
FiltrationRaw ECG Annotation
Feature
Extraction
Feature
Analysis
Conventional ECG processing pipeline
Filtration
Raw
ECG Annotation
Feature
Extraction
Feature
Analysis
Conventional ECG processing pipeline
Validation
Muscle noize
filtration
Inversion
detection
Disease
detection
Filtration
ECG signal filtration
Muscle noize
Power line interference
FIR and IIR FIltering
Denoising autoencoder
1D Convolution
1D MaxPooling
Raw ECG signal with
EMG noize
Denoized ECG
Source:https://github.com/softserveinc-rnd/ecg-denoise
ML ECG signal filtration
ML ECG signal filtration
Annotation
Pan-Tompkins algorithm:
1. Smooth ECG signal.
2. Clarify peaks using several rules:
a. ignore all peaks in the range of 400
ms from the highest peak
b. if a peaks occurs, check if the raw
signal has both positive and negative
slopes
c. …
ECG annotation
0
0
0
0
0
1
0
.
.
.
0
1
0
0
0
0
ML ECG annotation
1D Convolution 1D MaxPooling
Validation
ECG validation
High quality signal Poor quality signal
Conventional ECG validation approach
1D Convolution
1D Max Pooling
ML ECG validation
Batch Normalization
Activation (ReLU)
Dropout
Result-oriented Validation
Mawi band validation example
Disease detection
AFib
Atrial fibrillation
Atrial fibrillation features
in the heart biomechanics
Normal Sinus Rhythm Atrial Fibrillation Rhythm
Atrial fibrillation
Sinus Rhythm AFib rhythm
Traditional AFib detection
Source:https://stanfordmlgroup.github.io/projects/ecg/
Stanford Deep CNN approach
Our deep CNN approach
Train size: 40k, Test size: 10k, F1-score: 0.98
Disease detection
Mawi research platform
● Facebook: vsahan95, artem.bachinskyi
● Medium: @artem.bachinsky
● Linkedin: vitaliisahan, bachinskyi
● https://physionet.org/
● https://stanfordmlgroup.github.io/proj
ects/ecg/
● https://biosppy.readthedocs.io/en/sta
ble/
Useful links and contacts
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Domain meetup: E-Healthcare #2

Editor's Notes

  • #8: imgur.com/gallery/BpNZAj7
  • #11: imgur.com/gallery/BpNZAj7
  • #12: Нобелевская премия
  • #26: вивчати в?зерунки
  • #55: 64,121 ECG recordsfrom 29,163 patients 30 seconds