Denoising of weak ECG signals by using wavelet analysis and fuzzy thresholding

Abstract

The electrocardiogram (ECG) is a biological signal that contains important information about the cardiac activities of heart. ECG signal plays a very important role in the diagnosis and analysis of heart diseases. ECG signal is corrupted by various types of noise such as electrode movement, strong electromagnetic effect and muscle noise. Noisy ECG signal has been extracted using signal processing. This paper presents a weak ECG signal denoising method based on fuzzy thresholding and wavelet packet analysis. Firstly, the weak ECG signal is decomposed into various levels by wavelet packet transform. Then, the threshold value is determined using the fuzzy s-function. The reconstruction of the ECG signal from the retained coefficients is achieved by using inverse wavelet packet transform. We carried out several experiments to show the effectiveness of the proposed method and compared the results with the traditional wavelet packet soft and hard thresholding methods for weak signal denoising. The results are satisfactory according to calculated the correlation coefficient.