Abstract

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Title:: An improved wavelet threshold algorithm for cancelling EMG signal from ECG signal

Author(s):: GU Xuan; ZHANG Wei; L?Shanshan; LIANG Fue; LIU Donghua; College of Information Engineering, Gansu University of Chinese Medicine, Lanzhou 730100, China

Keywords:: Keywords: electrocardiogram signal electromyogram signal wavelet threshold algorithm denoising threshold functionPearson correlation coefficient

Abstract:: After removing the electromyogram (EMG) signal from electrocardiogram (ECG) signal with the traditional soft and hard threshold algorithms,the amplitude of ECG signal decreases and there are local abnormal peaks, leading to unsatisfactory denoising results. By studying the denoising principle and optimization rules of the wavelet threshold algorithm, based on the hyperbolic tangent function, an adjustable threshold function with continuity, simple structure and high flexibility, and an improved hierarchical threshold are constructed. The optimal wavelet basis function and wavelet decomposition level for noisy ECG signals are obtained through analysis. Finally, an improved wavelet threshold algorithm is proposed.The soft and hard threshold algorithms, the threshold algorithm in the relevant literatures, and the proposed algorithm are used to cancel the real EMG signal from ECG signal. The experimental results show that the improved threshold algorithm can better remove EMG signal from ECG signal and preserve the waveform characteristics of ECG signal, and has a greater Pearson correlation coefficient value than other threshold algorithms. Both qualitative and quantitative results confirm that the proposed threshold algorithm is effective in cancelling EMG signal from ECG signal.