Comparative Analysis of Wavelet Thresholding Techniques with Wavelet-wiener Filter on ECG Signal

The electrocardiogram (ECG) records the electrical activity of the heart muscle and displays this data as a trace on a screen or on paper. This data is then interpreted for identification of a particular malfunctioning of the heart. Before the identification of a particular disease the ECG signal is first de-noised, as the raw ECG signal is contaminated with various other signals called artefacts. This is the crucial step as the signal has to be extracted from the noisy signal, without losing much of the valid information. In this paper, wavelet transform technique is considered for de-noising the ECG signal. The ECG signal is de-noised using different threshold techniques like hard, soft, SURE shrink, hybrid shrink and compared with the wavelet based wiener filter. The performance of these techniques is analysed. It is observed that there is a trade- off between the bias and variance in case of hard, soft, sure shrink, hybrid shrink whereas, in case of wavelet- wiener filter, bias and variance reduces simultaneously and gives a minimum MSE.