Exercise ECG signal de-noising using unbiased risk estimate and wavelet transform

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 differe...

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Bibliographic Details
Published inSheng wu yi xue gong cheng xue za zhi Vol. 22; no. 1; p. 137
Main Authors Tian, Xuelong, Wang, Tianxing, Zhu, Binglian, Liu, Guochuan, Xiao, Shouzhong
Format Journal Article
LanguageChinese
Published China 01.02.2005
Subjects
Algorithms
Echocardiography, Stress
Electrocardiography - methods
Exercise Test - methods
Humans
Signal Processing, Computer-Assisted
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Summary: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.
ISSN:1001-5515