1. Classifying Normal and Abnormal Heartbeats From a Noisy ECG Eric Peterson ECE 539

2. Outline Filtering – Some Basics Filtering – Some Basics Beat Detection – Failed Beat Detection – Failed MLP Beat Classification – Works…Sometimes MLP Beat Classification – Works…Sometimes SVM Beat Classification – Similar Results SVM Beat Classification – Similar Results Conclusion – More Pre-Processing Needed Conclusion – More Pre-Processing Needed

3. Filtering – High-Pass

4. Filtering – Band-Pass

5. Beat Detection Supplied the Filtered Signal Supplied the Filtered Signal Overwhelmed the ANN Overwhelmed the ANN SNR does not matter SNR does not matter FAILURE!!! FAILURE!!! Pan-Tompkins Pan-Tompkins Overwhelmed again Overwhelmed again May not actually be linearly seperable May not actually be linearly seperable Modifications requred Modifications requred

6. MLP Beat Classification Used annotations to focus on beats only Used annotations to focus on beats only Annotations of either normal or abnormal beats Annotations of either normal or abnormal beats Attempted many parameter variations Attempted many parameter variations Best classification rate: 95.8824% Best classification rate: 95.8824% Confusion Matrix: 1592 Confusion Matrix: 1592 84 84 Results were dominated by the normal beats Results were dominated by the normal beats Failed with a SNR<24dB Failed with a SNR<24dB

7. MLP Beat Classification

8. SVM Beat Classification RBF kernel did not work RBF kernel did not work Similar results to MLP Similar results to MLP Still seems dominated by the normal beats Still seems dominated by the normal beats Failed at <24dB SNR Failed at <24dB SNR

9. SVM Beat Classification

10. Conclusion More Pre-Processing is needed!!! More Pre-Processing is needed!!! Possibility of better filtering? Possibility of better filtering? Further analysis of the signal Further analysis of the signal Feed the neural nets with important values Feed the neural nets with important values Templates were used in many previous papers Templates were used in many previous papers Not ideal for many types of abnormal beats Not ideal for many types of abnormal beats

11. Questions? http://www.metamemes.com