ARTIFACTS REMOVAL AND ANALYSIS OF ECG SIGNAL USING INDEPENDENT COMPONENT ANALYSIS (ICA

Abstract

During Multi channel ECG recording, along with ECG signal noise and artifacts are also recorded. ECG, noise and artifacts are statistically independent of each oiler. Disease classification and diagnostic feature extraction from ECG is difficult until and unless noise and artifacts are removed from ECG. Here we have used ICA for identification and removal of artifacts and noise from ECG. ICA is a statistical technique used for analyzing multivariant data and it decomposes the multivariant data into different independent components with an assumption that different components are statistically independent of each other. In this approach. ~'' algorithm has been used which separates the ECG signal from noise and artifacts. 'screte Wavelet Transform has been used for detecting R-peak and other diagnostic pars._ --(R-R interval, R-Peak, Heart rate etc) extraction from ECG signal