Artifacts and noise removal in electrocardiograms using independent component analysis

Independent component analysis (ICA) is a novel technique capable of separating independent components from electrocardiogram (ECG) complex signals. The purpose of this analysis is to evaluate the effectiveness of ICA in removing artifacts and noise from ECG recordings. ICA is applied to remove arti...

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Bibliographic Details
Published in:International journal of cardiology 2008-09, Vol.129 (2), p.278-281
Main Authors: CHAWLA, M. P. S, VERMA, H. K, KUMAR, Vinod
Format: Article
Language:English
Subjects:
Algorithms
Biological and medical sciences
Cardiology. Vascular system
Cardiovascular Diseases - diagnosis
Cardiovascular Diseases - physiopathology
Electrocardiography - methods
Humans
Medical sciences
Models, Statistical
Signal Processing, Computer-Assisted
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Summary:Independent component analysis (ICA) is a novel technique capable of separating independent components from electrocardiogram (ECG) complex signals. The purpose of this analysis is to evaluate the effectiveness of ICA in removing artifacts and noise from ECG recordings. ICA is applied to remove artifacts and noise in ECG segments of either an individual ECG CSE data base file or all files. The reconstructed ECGs are compared with the original ECG signal. For the four special cases discussed, the R-Peak magnitudes of the CSE data base ECG waveforms before and after applying ICA are also found. In the results, it is shown that in most of the cases, the percentage error in reconstruction is very small. The results show that there is a significant improvement in signal quality, i.e. SNR. All the ECG recording cases dealt showed an improved ECG appearance after the use of ICA. This establishes the efficacy of ICA in elimination of noise and artifacts in electrocardiograms.
ISSN:0167-5273
1874-1754
DOI:10.1016/j.ijcard.2007.06.037