DocumentCode
2256914
Title
Ensemble empirical mode decomposition based ECG noise filtering method
Author
Chang, Kang-Ming
Author_Institution
Dept. of Photonics & Commun. Eng., Asia Univ., Wufeng, Taiwan
Volume
1
fYear
2010
fDate
11-14 July 2010
Firstpage
210
Lastpage
213
Abstract
Electrocardiogram is often corrupted by various noises, such as high-frequency muscle contraction. In this study, ensemble empirical mode decomposition (EEMD) was used for ECG noise reduction. Gaussian noise was applied and the average (ensemble) intrinsic mode function (IMF) was used for ECG reconstruction. Three high frequency ECG noises; muscle contraction, 50 Hz power line interferences and Gaussian noise were examined. Mean square error (MSE) between filtered ECG and clean ECG was used as a reconstruction performance index. Results showed that the first two IMF levels were deleted owing to their noise components, while the other ensemble IMF constituted clean ECG components for ECG reconstruction. The MSE of EEMD is lower than EMD and IIR filter on these three noise types due to the reduction of mode-mixing effect between separate IMFs.
Keywords
Gaussian noise; IIR filters; electrocardiography; filtering theory; mean square error methods; signal denoising; ECG noise filtering method; ECG noise reduction; ECG reconstruction; Gaussian noise; IIR filter; electrocardiogram; ensemble empirical mode decomposition; high-frequency muscle contraction; infinite impulse response filters; intrinsic mode function; mean square error; Electrocardiography; Filter bank; Finite impulse response filter; IIR filters; Noise; Noise reduction; Electrocardiogram (ECG); Ensemble Empirical mode decomposition (EEMD); Noise reduction;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location
Qingdao
Print_ISBN
978-1-4244-6526-2
Type
conf
DOI
10.1109/ICMLC.2010.5581064
Filename
5581064
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