Exercise ECG signal de-noising using unbiased risk estimate and wavelet transform.
- Author:
Xuelong TIAN
1
;
Tianxing WANG
;
Binglian ZHU
;
Guochuan LIU
;
Shouzhong XIAO
Author Information
1. College of Bioengineering and Key Lab for Biomechanics & Tissue Engineering under the State Ministry of Education, Chongqing University, Chongqing 400044, China.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Echocardiography, Stress;
Electrocardiography;
methods;
Exercise Test;
methods;
Humans;
Signal Processing, Computer-Assisted
- From:
Journal of Biomedical Engineering
2005;22(1):137-142
- CountryChina
- Language:Chinese
-
Abstract:
In this paper a filtering method for EECG (Exercise ECG) signal is proposed which is based on wavelet transform (WT) and Stein's unbiased risk estimate (SURE). This algorithm was used to decompose original EECG signals into detail signals on different frequency bands by using WT and get different thresholds with SURE. According to EECG signal features and by using the above thresholds, the method amended several detail signals so that the main interferences in EECG signal can be removed efficiently. The authors also put forward two indexes to estimate the validity of such algorithms. Our experimental results demonstrate that this is an efficient de-noising method for EECG.
