Enhancing Diagnostic Quality of ECG in Mobile Environment 11/30/2018 ESS Open Day Enhancing Diagnostic Quality of ECG in Mobile Environment PhD: Taihai CHEN Supervisor: Dr. Koushik Maharatna what is the problem? what are the previous attempts to solve this problem?  what is your solution?, your contribution ?  

Outlines Background & Motivation ECG Feature Detection 11/30/2018 ESS Open Day Outlines Background & Motivation ECG Feature Detection Robust Feature Exploration Enhance with More Features Digital System Design Conclusion

Outlines Background & Motivation ECG Feature Detection 11/30/2018 ESS Open Day Outlines Background & Motivation ECG Feature Detection Robust Feature Exploration Enhance with More Features Digital System Design Conclusion

Background & Motivation 11/30/2018 ESS Open Day Background & Motivation Electrocardiogram (ECG) System Standard 12-Lead ECG System Mobile ECG System

Background & Motivation 11/30/2018 ESS Open Day Background & Motivation The problem of continuous monitoring… Battery just dies…

Outlines Background & Motivation ECG Feature Detection 11/30/2018 ESS Open Day Outlines Background & Motivation ECG Feature Detection Robust Feature Exploration Enhance with More Features Digital System Design Conclusion

ECG Feature Detection Proposed Two Algorithms: 11/30/2018 ESS Open Day ECG Feature Detection Proposed Two Algorithms: Time-Domain Morphology and Gradient Algorithm (TDMG) Gradient Analysis Adaptive Thresholds Hybrid Feature Detection Algorithm (HFDA) Time-Frequency Analysis Discrete Wavelet Transform

Outlines Background & Motivation ECG Feature Detection 11/30/2018 ESS Open Day Outlines Background & Motivation ECG Feature Detection Robust Feature Exploration Enhance with More Features Digital System Design Conclusion

Robust Feature Exploration 11/30/2018 ESS Open Day Robust Feature Exploration Spectral Energy Discrete Wavelet Transform Spectral Energy Extraction P Energy T Energy QRS Energy

Robust Feature Exploration 11/30/2018 ESS Open Day Robust Feature Exploration Four Ways to Derive Spectral Energy Chose one that give us the best accuracy Robustness of Spectral Energy against Misdetection Statistical Analysis of the Variation of Spectral Energy Under Misdetection Classification Performance using Spectral Energy as a Feature Under Misdetection Misdetection Error

Robust Feature Exploration 11/30/2018 ESS Open Day Robust Feature Exploration Choice of Classifiers Linear & Quadratic Discriminant Analysis Support Vector Machine (SVM) with Linear & Quadratic Kernels k-Nearest Neighbor (k-NN)

11/30/2018 ESS Open Day

Outlines Background & Motivation ECG Feature Detection 11/30/2018 ESS Open Day Outlines Background & Motivation ECG Feature Detection Robust Feature Exploration Enhance with More Features Digital System Design Conclusion

Enhance with More Features 11/30/2018 ESS Open Day Enhance with More Features Spectral energy-based Classification with More Features Various features from FFT, DWT, etc. Four selected most representative and useful feature selection algorithms ReliefF InfoGain Correlation-based Feature Selection (CFS) Fast Correlation-based Filter (FCBF) Single Heart-beat and Multiple Heart-beat Analysis

Enhance with More Features 11/30/2018 ESS Open Day Enhance with More Features

Outlines Background & Motivation ECG Feature Detection 11/30/2018 ESS Open Day Outlines Background & Motivation ECG Feature Detection Robust Feature Exploration Enhance with More Features Digital System Design Conclusion

11/30/2018 ESS Open Day Digital System Design

11/30/2018 ESS Open Day Digital System Design

Outlines Background & Motivation ECG Feature Detection 11/30/2018 ESS Open Day Outlines Background & Motivation ECG Feature Detection Robust Feature Exploration Enhance with More Features Digital System Design Conclusion

Conclusion Proposed two ECG feature detection algorithms 11/30/2018 ESS Open Day Conclusion Proposed two ECG feature detection algorithms Robustness Feature Exploration More Feature to Enhance Application-Specific Integrated Circuits (ASIC) chip design

11/30/2018 ESS Open Day Thanks for listening!

11/30/2018 ESS Open Day Q & A

11/30/2018 ESS Open Day ECG Feature Detection TDMG 1 3 2

11/30/2018 ESS Open Day ECG Feature Detection HFDA 1 3 2

Robust Feature Exploration 11/30/2018 ESS Open Day Robust Feature Exploration Stage 1 Stage 2 Stage 3 Wave Boundary Localisation QRS ECG Snap Shot Spectral Energy Extraction T P DWT Analysis (Haar Wavelet)

Experiments & Analysis 11/30/2018 ESS Open Day Experiments & Analysis Database 52 Normal and 52 Abnormal 12-Lead ECG signals Feature Generation Feature Ranking Fisher’s criterion Feature Space Selection Exhaustive simulation 10-fold cross validation Testing Accuracy F 84 F 36

Robust Feature Exploration 11/30/2018 ESS Open Day Robust Feature Exploration F P F T F PR F QRS F’ QRS F QT F’ QT Lead 1 F P F T F PR F QRS F’ QRS F QT F’ QT Lead 2 … F P F T F PR F QRS F’ QRS F QT F’ QT Lead 12 Low Freq High Freq Combined Freq

Best subset of leads with associated best features for classification 11/30/2018 ESS Open Day Best subset of leads with associated best features for classification QDA SVML SVMQ k-NN # of Lead 1 Lead 2 Leads 3 Leads 4 Leads 5 Leads LDA # of Lead 1 Lead 2 Leads 3 Leads 4 Leads 5 Leads F F F F F F F F F F F F F F F

Robust Feature Exploration 11/30/2018 ESS Open Day Robust Feature Exploration Jitter Effect Introduce Misdetection Errors

Robust Feature Exploration 11/30/2018 ESS Open Day Robust Feature Exploration Modified 10-fold Cross Validation

Enhance with More Features 11/30/2018 ESS Open Day Enhance with More Features Spectral energy-based Classification A more in-depth analysis for five selected classifiers Single Heart-beat and Multiple Heart-beat Analysis

11/30/2018 ESS Open Day