Please wait a minute...
FITEE
Front. Inform. Technol. Electron. Eng.  2011, Vol. 12 Issue (5): 397-403    DOI: 10.1631/jzus.C1010311
    
Removal of baseline wander from ECG signal based on a statistical weighted moving average filter
Xiao Hu*,1, Zhong Xiao1, Ni Zhang2
1 School of Mechanical and Electric Engineering, Guangzhou University, Guangzhou 510006, China 2 Guangdong General Hospital, Guangzhou 510080, China
Removal of baseline wander from ECG signal based on a statistical weighted moving average filter
Xiao Hu*,1, Zhong Xiao1, Ni Zhang2
1 School of Mechanical and Electric Engineering, Guangzhou University, Guangzhou 510006, China 2 Guangdong General Hospital, Guangzhou 510080, China
 全文: PDF(276 KB)  
摘要： Baseline wander is a common noise in electrocardiogram (ECG) results. To effectively correct the baseline and to preserve more underlying components of an ECG signal, we propose a simple and novel filtering method based on a statistical weighted moving average filter. Supposed a and b are the minimum and maximum of all sample values within a moving window, respectively. First, the whole region [a, b] is divided into M equal sub-regions without overlap. Second, three sub-regions with the largest sample distribution probabilities are chosen (except M<3) and incorporated into one region, denoted as [a0, b0] for simplicity. Third, for every sample point in the moving window, its weight is set to 1 if its value falls in [a0, b0]; otherwise, its weight is 0. Last, all sample points with weight 1 are averaged to estimate the baseline. The algorithm was tested by simulated ECG signal and real ECG signal from www.physionet.org. The results showed that the proposed filter could more effectively extract baseline wander from ECG signal and affect the morphological feature of ECG signal considerably less than both the traditional moving average filter and wavelet package translation did.
关键词： ECG signal;  Baseline wander;  Morphological feature;  Moving average filter;  Wavelet package translation    
Abstract: Baseline wander is a common noise in electrocardiogram (ECG) results. To effectively correct the baseline and to preserve more underlying components of an ECG signal, we propose a simple and novel filtering method based on a statistical weighted moving average filter. Supposed a and b are the minimum and maximum of all sample values within a moving window, respectively. First, the whole region [a, b] is divided into M equal sub-regions without overlap. Second, three sub-regions with the largest sample distribution probabilities are chosen (except M<3) and incorporated into one region, denoted as [a0, b0] for simplicity. Third, for every sample point in the moving window, its weight is set to 1 if its value falls in [a0, b0]; otherwise, its weight is 0. Last, all sample points with weight 1 are averaged to estimate the baseline. The algorithm was tested by simulated ECG signal and real ECG signal from www.physionet.org. The results showed that the proposed filter could more effectively extract baseline wander from ECG signal and affect the morphological feature of ECG signal considerably less than both the traditional moving average filter and wavelet package translation did.
Key words: ECG signal    Baseline wander    Morphological feature    Moving average filter    Wavelet package translation
收稿日期: 2010-08-27 出版日期: 2011-05-09
CLC:  TN911.72  
服务　　
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章　　
Xiao Hu
Zhong Xiao
Ni Zhang

引用本文:

Xiao Hu, Zhong Xiao, Ni Zhang. Removal of baseline wander from ECG signal based on a statistical weighted moving average filter. Front. Inform. Technol. Electron. Eng., 2011, 12(5): 397-403.

链接本文:

http://www.zjujournals.com/xueshu/fitee/CN/10.1631/jzus.C1010311    或    http://www.zjujournals.com/xueshu/fitee/CN/Y2011/V12/I5/397

No related articles found!