Evaluation of BSS Methods for Fetal ECG Extraction and Analysis

Assessing the health state of the fetal cardiovascular system during pregnancy represents a major challenge in the current medical system. To be able to prevent cardiac malformations, a non-invasive fetal diagnosis method is needed, which highlights the cardiac status of the fetus. The fetal electrocardiogram (fECG), extracted from abdominal signals, recorded non-invasively, can overcome the limitations of the classic methods of intrauterine monitoring, without endangering the fetus and highlighting more diagnostic features compared to ones obtains with the methods in clinical practice. However, fECG is a very noisy signal, being sensitive to fetal or maternal movements, to other physiological signals that can be recorded from the abdomen like the maternal electrocardiogram (mECG) and the powerline interference (PLI). This paper evaluates the performance of two methods for fECG extraction from abdominal signals. One is based on the cancellation of the interferences through time-frequency signal processing methods and the band-pass filtering to isolate fetal QRS complexes. The other method is based on Blind Source Separation (BSS) method, namely the Independent Component Analysis (ICA). Isolation of the PLI, the motion artifacts (MA) and the baseline wander (BW) is performed, in both cases using Empirical Mode Decomposition (EMD) and Empirical Wavelet Transform (EWT). The mECG is approximated and eliminated using Fractional Fourier Transform (FrFT) and Maximum Likelihood Estimation (MLE). The two methods are evaluated on a synthetic database in order to evaluate the effectiveness of the BSS methods, compared to a more general approach.