Related Experiment Video
Updated: May 7, 2026

Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
Published on: April 26, 2024
De-noising the abdominal phonogram for foetal heart rate extraction: blind source separation versus empirical
Abstract:
This work explored the suitability of using the foetal phonocardiogram (FPCG) blindly separated from the abdominal phonogram as a source for foetal heart rate (FHR) measuring in antenatal surveillance. To this end, and working on a dataset of 15 abdominal phonograms, the FPCG was estimated by using two de-noising approaches (1) single-channel independent component analysis (SCICA) to produce FPCG(e) and (2) empirical filtering to produce FPCG(g). Next, the FPCGs were further processed to collect the beat-to-beat FHR and the resulting time-series (FCTG(e) and FCTG(g) were compared to the reference signal given by the abdominal ECG (FCTG(r)). Results are promising, the FPCG(e) gives rise to a FCTG(e) that resembles FCTG(r) and, most importantly, whose mean FHR value is statistically equivalent to that given by FCTG(r) (p > 0.05). Thus, the mean FHR value obtained from the FPCG(e), is likely to be equivalent to the value given by the abdominal ECG, which is especially significant since the FPCG(e) is retrieved from the noisy abdominal phonogram. Hence, as far as this study has gone, it can be said that, when using SCICA to de-noise the abdominal phonogram, the resulting FPCG is likely to become a useful source for FHR collection in antenatal surveillance.

