Genetic algorithm and wavelet hybrid scheme for ECG signal denoising |
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Authors: | El-Sayed A El-Dahshan |
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Affiliation: | (1) Department of Electrical Engineering, National Institute of Technology, Calicut, Kerala, India, 673601;(2) Department of ECE, Ngee Ann Polytechnic, Singapore, 599489, Singapore; |
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Abstract: | This paper introduces an effective hybrid scheme for the denoising of electrocardiogram (ECG) signals corrupted by non-stationary
noises using genetic algorithm (GA) and wavelet transform (WT). We first applied a wavelet denoising in noise reduction of
multi-channel high resolution ECG signals. In particular, the influence of the selection of wavelet function and the choice
of decomposition level on efficiency of denoising process was considered. Selection of a suitable wavelet denoising parameters
is critical for the success of ECG signal filtration in wavelet domain. Therefore, in our noise elimination method the genetic
algorithm has been used to select the optimal wavelet denoising parameters which lead to maximize the filtration performance.
The efficiency performance of our scheme is evaluated using percentage root mean square difference (PRD) and signal to noise
ratio (SNR). The experimental results show that the introduced hybrid scheme using GA has obtain better performance than the
other reported wavelet thresholding algorithms as well as the quality of the denoising ECG signal is more suitable for the
clinical diagnosis. |
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Keywords: | |
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