Applying The Blind Separation Of Correlated Sources For FECG Extraction Based On The Second Order Statistics

The extraction of the fetal electrocardiogram (FECG) from the skin electrode signals recorded of the mother's body is a problem of concern to signal processing. Blind signal separation (BSS) technique that separates some signals from their combinations without acknowledgments about transmission channel, is a fundamental method for solving this problem. The most proposed BSS algorithm for separation of fetal electrocardiogram (FECG) and mother electrocardiogram (MECG) relies on the independence of these signals (ICA). This paper introduces a novel technique for the cases that signals are correlated with each other, i.e. considering a real assumption. The method uses Wold decomposition principle for extracting the desired and proper information from the predictable part of the measured data, and exploits approaches based on the second-order statistics to estimate source signals. Simulation results are showed the effectiveness of the method for separation of electrocardiogram signals.