  The abdominal electrocardiogram (AECG) gives a safe and non-invasive way to
monitor fetal well-being during pregnancy. However, due to the overlap with
maternal ECG (MECG) as well as significant external noise, it is challenging to
extract weak fetal ECG (FECG) using surface electrodes. In this study, we
introduce a novel periodic progressive FastICA peel-off (PPFP) method for
noninvasive extraction of weak surface FECG signals, leveraging the two-step
FastICA method and a peel-off strategy from the progressive FastICA peel-off
(PFP) approach. Specifically, for ECG signals, the periodic constrained FastICA
that integrates ECG signal characteristics enables precise extraction of MECG
and FECG spike trains. Additionally, a peel-off strategy incorporating SVD
waveform reconstruction ensures comprehensive identification of subtle source
signals. The performance of the proposed method was examined on public datasets
with reference, synthetic data and clinical data, with an F1-scores for FECG
extraction on public dataset of 99.59%, on synthetic data with the highest
noise level of 99.50%, which are all superior to other comparative methods.
Furthermore, clearly periodic and physiologically consistent FECG signals were
extracted from clinically collected data. The results indicates that our
proposed method has potential and effectiveness to separate MECG and weak FECG
from multichannel AECG with high precision in high noise condition, which is of
vital importance for ensuring the safety of both the fetus and the mother, as
well as the advancement of artificial intelligent clinical monitoring.
