Title :
Fuzzy rule based multiwavelet ECG signal denoising
Author :
Ling, Bingo Wing-Kuen ; Ho, Charlotte Yuk-Fan ; Lam, Hak-Keung ; Wong, Thomas Pak-Lin ; Chan, Albert Yick-Po ; Tam, Peter Kwong Shun
Abstract :
Since different multiwavelets, pre- and post-filters have different impulse responses and frequency responses, different multiwavelets, pre- and post-filters should be selected and applied at different noise levels for signal denoising if signals are corrupted by additive white Gaussian noises. In this paper, some fuzzy rules are formulated for integrating different multiwavelets, pre- and post-filters together so that expert knowledge on employing different multiwavelets, pre- and post-filters at different noise levels on denoising performances is exploited. When an ECG signal is received, the noise level is first estimated. Then, based on the estimated noise level and our proposed fuzzy rules, different multiwavelets, pre- and post-filters are integrated together. A hard thresholding is applied on the multiwavelet coefficients. According to extensive numerical computer simulations, our proposed fuzzy rule based multiwavelet denoising algorithm outperforms traditional multiwavelet denoising algorithms by 30%.
Keywords :
AWGN; electrocardiography; filtering theory; frequency response; fuzzy reasoning; medical signal processing; signal denoising; transient response; wavelet transforms; additive white Gaussian noise; expert knowledge; frequency response; fuzzy rule; impulse response; multiwavelet ECG signal denoising; post-filter; pre-filter; AWGN; Computer simulation; Degradation; Electrocardiography; Noise level; Noise reduction; Signal denoising; Signal processing; Signal processing algorithms; Wavelet domain;
Conference_Titel :
Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1818-3
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZY.2008.4630501