Abstract

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Title:: Denoising of diaphragmatic electromyogram signals using dual-threshold filtering algorithm

Author(s):: LI Shuangmiao1; LI Zhiwei1; ZHANG Han1; ZHANG Jianheng2; 1. School of Electrical and Information Engineering, South China Normal University, Guangzhou 510631, China 2. Respiratory Department, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou 520120, China

Keywords:: Keywords: diaphragmatic electromyogram electrocardiogram contamination wavelet coefficient dual-threshold filtering

Abstract:: Abstract: Given that the traditional algorithms for elimination of electrocardiogram (ECG) contamination have a poor performance on abnormal ECG signals, a denoising algorithm for diaphragmatic electromyogram (EMGdi) signals based on wavelet dual-threshold filtering is presented. The method constructs the detection threshold of R peak in QRS group wave based on wavelet coefficient for accurately locating the position of the R peak, and takes the average energy on both sides of one interference range as the threshold of this interference range for eliminating ECG contamination. Experimental results of eliminating ECG contamination from clinical EMGdi signals show that the proposed algorithm surpasses the traditional algorithms in interference removal, especially for weak EMGdi signals.