Optimal decomposition level selection approach in wavelet
threshold denoising algorithm for ECG signal

doi:10.19682/j.cnki.1005-8885.2023.2019

中国邮电高校学报(英文) ›› 2023, Vol. 30 ›› Issue (4): 86-104.doi: 10.19682/j.cnki.1005-8885.2023.2019

Optimal decomposition level selection approach in wavelet threshold denoising algorithm for ECG signal

Yao Yindi, Yi Jun, Zeng Zhibin, Li Xiong, Wang Chen, Li Yuhang

1. School of Communications and Information Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China 2. School of Microelectronics, Xidian University, Xi'an 710071, China 3. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China

收稿日期:2022-09-01 修回日期:2023-03-21 接受日期:2023-08-31 出版日期:2023-08-31 发布日期:2023-08-31
通讯作者: Yi Jun, E-mail: Johnie_Yi730@163.com E-mail:Johnie_Yi730@163.com
基金资助:
This work was supported by the National Nature Science Foundation of China (U1965102), the Science and Technology Innovation Team for Talent Promotion Plan of Shaanxi Province (2019TD-028), the Science and Technology Department of Shaanxi Province Project (2021NY-180).

Optimal decomposition level selection approach in wavelet threshold denoising algorithm for ECG signal

Yao Yindi, Yi Jun, Zeng Zhibin, Li Xiong, Wang Chen, Li Yuhang

1. School of Communications and Information Engineering, Xi'an University of Posts and Telecommunications, Xi'an 710121, China 2. School of Microelectronics, Xidian University, Xi'an 710071, China 3. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China

Received:2022-09-01 Revised:2023-03-21 Accepted:2023-08-31 Online:2023-08-31 Published:2023-08-31
Contact: Yi Jun, E-mail: Johnie_Yi730@163.com E-mail:Johnie_Yi730@163.com
Supported by:
This work was supported by the National Nature Science Foundation of China (U1965102), the Science and Technology Innovation Team for Talent Promotion Plan of Shaanxi Province (2019TD-028), the Science and Technology Department of Shaanxi Province Project (2021NY-180).

摘要/Abstract

摘要： The effect of electrocardiogram (ECG) signal wavelet denoising depends on the optimal configuration of its control parameters and the selection of the optimal decomposition level. Nevertheless, the existing optimal decomposition level selection scheme has some problems, such as lack of reliable theoretical guidance and insufficient accuracy, which need to be solved urgently. To solve this problem, this paper proposes an optimal decomposition level selection method based on multi-index fusion, which is used to select the optimal decomposition level for wavelet threshold denoising of ECG signal. In the stage of index selection, in order to overcome the limitation of a single evaluation index, the optimal multi-evaluation index is selected through the joint analysis of the geometric and physical significance of traditional evaluation indexes. In the stage of index fusion, based on the method of weighting the selected multiple indexes by the information entropy weight method and the coefficient of variation method, an optimal decomposition level selection method based on the evaluation index Z is proposed to improve the accuracy of the optimal decomposition level selection. Finally, extensive experiments are carried out on the real ECG signal from the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database and simulated signal to test the performance of the proposed method. The experimental results show that the accuracy of this method is superior to other related methods, and it can achieve better denoising effect of ECG signal.

关键词: ECG signal, wavelet threshold denoising, optimal decomposition level, muti-index fusion

Abstract: The effect of electrocardiogram (ECG) signal wavelet denoising depends on the optimal configuration of its control parameters and the selection of the optimal decomposition level. Nevertheless, the existing optimal decomposition level selection scheme has some problems, such as lack of reliable theoretical guidance and insufficient accuracy, which need to be solved urgently. To solve this problem, this paper proposes an optimal decomposition level selection method based on multi-index fusion, which is used to select the optimal decomposition level for wavelet threshold denoising of ECG signal. In the stage of index selection, in order to overcome the limitation of a single evaluation index, the optimal multi-evaluation index is selected through the joint analysis of the geometric and physical significance of traditional evaluation indexes. In the stage of index fusion, based on the method of weighting the selected multiple indexes by the information entropy weight method and the coefficient of variation method, an optimal decomposition level selection method based on the evaluation index Z is proposed to improve the accuracy of the optimal decomposition level selection. Finally, extensive experiments are carried out on the real ECG signal from the Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database and simulated signal to test the performance of the proposed method. The experimental results show that the accuracy of this method is superior to other related methods, and it can achieve better denoising effect of ECG signal.

Key words: ECG signal, wavelet threshold denoising, optimal decomposition level, muti-index fusion

Yao Yindi, Yi Jun, Zeng Zhibin, Li Xiong, Wang Chen, Li Yuhang. Optimal decomposition level selection approach in wavelet threshold denoising algorithm for ECG signal[J]. The Journal of China Universities of Posts and Telecommunications, 2023, 30(4): 86-104.

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Optimal decomposition level selection approach in wavelet threshold denoising algorithm for ECG signal

Optimal decomposition level selection approach in wavelet threshold denoising algorithm for ECG signal

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