A comparative study of ICA algorithms for ECG signal processing

Sarfraz, M; Li, FF; Javed, M

Abstract

Electro Cardiogram (ECG) signals are affected by various kinds of noise and artifacts that may hide important information of interest. Independent component analysis is a new technique suitable for separating independent component from ECG complexes. This paper compares the various Independent Component Analysis (ICA) algorithms with respect to their capability to remove noise from ECG. The data bases of ECG samples attributing to different beat types were sampled from MIT-BIH arrhythmia database for experiment. We compare the signal to noise ratio (SNR) improvement in the real ECG data with different ICA algorithms also we compare the SNR for simulated ECG signal on matlab; giving the selection choice of various ICA algorithms for different database.

Citation

Sarfraz, M., Li, F., & Javed, M. (2011). A comparative study of ICA algorithms for ECG signal processing. In ACAI '11 Proceedings of the International Conference on Advances in Computing and Artificial Intelligence (135-138). ACM Digital Library. https://doi.org/10.1145/2007052.2007079

• Publication Date: Jan 1, 2011
• Deposit Date: May 12, 2016
• Pages: 135-138
• Book Title: ACAI '11 Proceedings of the International Conference on Advances in Computing and Artificial Intelligence
• ISBN: 9781450306355
• DOI: https://doi.org/10.1145/2007052.2007079
• Publisher URL: http://dx.doi.org/10.1145/2007052.2007079
• Additional Information: Event Type : Conference