A comparative survey on removal of MECG artifacts from FECG using ICA algorithms

The extraction of the fetal electrocardiogram (FECG) from maternal cutaneous electrode recordings accepts a blind source separation (BSS) formulation. From this perspective, the problem reduces to the estimation of the independent sources of fetal cardiac bioelectric activity. In this contribution, a BSS method based on higher-order statistics is contrasted with a significant classical technique for FECG extraction. In this paper, the Pearson-ICA algorithm and BELL's (Bell and Sejnowski) algorithm for BSS are used for FECG extraction. They were applied to multichannel ECG recording obtained from a pregnant woman. For robustness, two scenarios, i.e, (a) different amplitude ratios of simulated maternal and fetal ECG and (b) different values of additive white Gaussian noise, were investigated. It was observed that if the ratio of the amplitude of maternal to fetal ECG is 10:1 with an input SNR of 2 dB, both algorithms were able to extract the fetal ECG. The signal-to-error (SER) ratios of the extracted maternal and fetal ECG were around 3 dB and 1 dB, respectively. The experiment outcomes demonstrate the more robust performance of Pearson-ICA and Bell's algorithm in this important biomedical application.