Study on Optimal Selection of Wavelet Vanishing Moments for ECG Denoising

Figure 1. Amplitude-frequency characteristics of the orthogonal wavelet high pass filter with vanishing moments N.

Figure 2. Real-time ECG image (a), and its frequency characteristics (b).

Figure 3. High frequency components of ECG signals after 4- (above) and 6-order vanishing moments (below).

Figure 4. High frequency components of ECG signals after 8- (above) and 10-order vanishing moments (below).

Figure 5. Low frequency component and frequency characteristics of ECG signal after DB6 filter.

Figure 6. High frequency component of the ECG signal through the N-order vanishing moment filter.

Figure 7. ECG signal with high frequency noise and its frequency characteristics.

Figure 8. Original ECG signals filtered once (a,b) and twice (c,d) through the band-pass filter.

Figure 9. Original ECG signals twice filtered through the band-pass filter.

Figure 10. Comparison of denoising results with different denoising algorithms. A is the original ECG, B is the ECG containing noise, C is the ECG after processed by Threshold DWT, D is the ECG processed by Genetic EEMD, and E is the ECG processed by the algorithm in the paper.