A comparative study of ICA algorithms for ECG signal processing
Sarfraz, M, Li, FF and 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 , ACM New York, pp. 135-138.
- Published Version
Restricted to Repository staff only
Download (440kB) | Request a copy
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.
|Item Type:||Book Section|
|Schools:||Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre (SIRC)|
|Publisher:||ACM New York|
|Funders:||University of Salford|
|Depositing User:||FF Li|
|Date Deposited:||12 May 2016 08:03|
|Last Modified:||12 May 2016 08:03|
Actions (login required)
|Edit record (repository staff only)|