Independent component analysis for motion artifacts removal from electrocardiogram

Sarfraz, M; Li, FF

Abstract

A method of using Independent Component Analysis to remove motion induced artifacts in the signals picked up by ECG electrodes is developed in this paper. In a first aid setting, ECG electrodes on patients cannot always keep stationary, resulting in a large amount of contact noise in acquired signals. Similar problems occur in ECGs in motion, e.g. sports and ambulatory ECGs. The motion induced artifacts are known to undermine the arrhythmia recognition. An artificial neural system for automated ECG classification with an extra independent component analysis de-noising pre-processor is proposed and validated by pre-recorded real ECG and noise datasets. The proposed system shows improved recognition accuracy, providing a useful means to more accurately detect arrhythmia from ECGs in the presence of no trivial motion related noises.

Citation

Sarfraz, M., & Li, F. (2013). Independent component analysis for motion artifacts removal from electrocardiogram. Global perspectives on artificial intelligence (Online), 1(4), 49-55

• Journal Article Type: Article
• Publication Date: Oct 1, 2013
• Deposit Date: May 9, 2016
• Journal: Global Perspectives on Artificial Intelligence (GPAI)
• Print ISSN: 2327-7289
• Electronic ISSN: 2327-7580
• Volume: 1
• Issue: 4
• Pages: 49-55