ECG signal decomposition using PCA and ICA

This paper covers the fundamental concepts involved in Independent Component analysis (ICA) and Principle Component Analysis (PCA) techniques and review its applications. ICA is used Separation of source signal from mixture signals. These mixture of signals may consists of source signals, sensor signals, surface signals etc. ICA consists a higher order statistics which performs its function by making the signal components independent to each other but for the lower order statistics there is also a technique called as PCA (Principle Component Analysis) that performs uncorrelation in signal components. In this Paper, we describe the working of PCA with flowcharts and tried find out principle components of an ECG signal with its Kurtosis value.