Hybrid ICA algorithm for ECG analysis

Abstract

Electrocardiogram (ECG) signals are among the most important sources of diagnostic information in healthcare, so improvements in their analysis are also of growing importance. The rapidly developing signal technology and a flourishing variety of algorithms have proved successful targets for recent advances in research. Several techniques have been proposed to extract the ECG components contaminated with the background noise and allow the measurement of subtle features in the ECG signal. This paper illustrates the ability of Independent Component Analysis (ICA) for removal of noises and artifacts and source separation. With the discussions on some ICA schemes such as JADE algorithm, Fast ICA and constrained ICA (cICA), a hybrid algorithm using Fast ICA for noise removal and cICA for source separation has been proposed along with their simulation results.