Research on electrocardiogram de-noising algorithm based on wavelet neural networks.
- Author:
Xiangkui WAN
1
;
Jun ZHANG
Author Information
1. Information Engineering College, Guangdong University of Technology, Guangzhou 510006, China. xkwan@gdut.edu.cn
- Publication Type:Journal Article
- MeSH:
Algorithms;
Electrocardiography;
methods;
Humans;
Neural Networks (Computer);
Signal Processing, Computer-Assisted;
Wavelet Analysis
- From:
Journal of Biomedical Engineering
2010;27(6):1197-1201
- CountryChina
- Language:Chinese
-
Abstract:
In this paper, the ECG de-noising technology based on wavelet neural networks (WNN) is used to deal with the noises in Electrocardiogram (ECG) signal. The structure of WNN, which has the outstanding nonlinear mapping capability, is designed as a nonlinear filter used for ECG to cancel the baseline wander, electromyo-graphical interference and powerline interference. The network training algorithm and de-noising experiments results are presented, and some key points of the WNN filter using ECG de-noising are discussed.
