Abstract

Info

Author(s):: YU Wei1; LI Zhengquan1; 2; XING Song3; 1. School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China 2. Changzhou Key Laboratory of 5G+ Industrial Internet Fusion Application, Jiangsu University of Technology, Changzhou 213001, China 3. Information Systems Department, California State University, Los Angeles CA 90032, USA

Keywords:: Keywords: electrocardiogram signal denoising whale optimization algorithm variational modal decomposition wavelet threshold correlation coefficient

Abstract:: Abstract: The traditional method for decomposing electrocardiogram (ECG) signals is based on empirically identifying intrinsic mode functions (IMF) using QRS feature waves. However, there is a frequency band aliasing between ECG and noise signals, which significantly affects the denoising performance. To solve this problem, an improved whale optimization algorithm (WOA) is proposed to optimize the parameters of the variational mode decomposition (VMD) algorithm, and combined it with an improved wavelet threshold method. For VMD is based on the completely non-recursive decomposition, a perception disturbance mechanism is introduced into WOA, and an equal pitch Archimedean spiral instead of the classic logarithmic spiral is used to optimize the number of modalities K and the penalty parameter α in VMD. Then, the ECG signal is decomposed using VMD to obtain a series of IMF components. The noise components are determined by correlation coefficient and removed using the improved wavelet threshold method. Finally, the various components are reconstructed to obtain the denoised signal. The comparison with wavelet threshold algorithm and VMD algorithm shows that the proposed method (WOA-VMD algorithm) can effectively remove various interferences in the ECG signal and better retain the waveform characteristics of the ECG signal, which is of potential significance in clinic.