Quality Assessment of ICA for ECG Signal Analysis

The immense scope in the field of biomedical signal processing independent component analysis (ICA ) is gaining momentum due to huge data base requirement for quality testing. The diagnosis of patient is based on visual observation of recorded ECG signals may not be accurate. Many attempts have been carried out to remove noise or artifacts such as interference (few Hz), electromagnetic emission, muscle activities and others from ECG signal. To achieve better understanding, ICA algorithms helps in analyzing ECG signals.This paper describes some algorithms of ICA in brief, such as Fast-ICA, Kernel-ICA, MS -ICA, JADE, EGLD-ICA, Robust ICA etc. The quality & performance of some of the ICA algorithms are tested and analysis of each can be done with respect to noise/artifacts, SIR(signal interference ratio), PI(performance index). In the conclusion tries giving selection type of ICA algorithm for different ECG database.