Fetal Electrocardiogram Extraction Using Dual-Path Source Separation of Single-Channel Non-Invasive Abdominal Recordings

Objective: The development of a method for non-invasive monitoring of fetal electrocardiogram (FECG) signals from single-channel abdominal recordings. Methods: The dual-path source separation (DPSS) architecture is introduced for the simultaneous separation of fetal and maternal ECG signals from abdominal ECG recordings. DPSS initially denoises abdominal ECG (AECG) recordings using a generative dual-path long short-term memory (DP-LSTM) network. An inception module along with a series of DP-LSTM blocks is then employed to extract the masking maps associated with fetal and maternal components. Finally, these masking maps are weighted by the AECG recording to separate maternal and fetal ECG signals. The performance of this network is evaluated on 10 pregnancies from the fetal ECG synthetic database (FECGSYNDB), 22 cases of labor and pregnancy from the abdominal and direct fetal ECG database (ADFECGDB), and 69 pregnancies from set A of non-invasive FECG challenge (NIFECGC) datasets. Results: F1-scores of 99.03%, 97.7%, and 95.3% are reported for the detection of fetal QRS complexes in FECGSYNDB, ADFECGDB, and NIFECGC respectively. DPSS technique is also evaluated in terms of separability of fetal and maternal clusters. According to the clustering-based analyses, the average purity index of 0.9750, Jaccard index of 0.9705, and Davies-Bouldin index of 0.7429 demonstrate the high source separation capability of DPSS. Conclusion: The achieved performance suggests that DPSS enables accurate single-channel FECG extraction, and can replace state-of-the-art source separation techniques for this purpose. Significance: This study signifies a fundamental step towards non-invasive fetal ECG monitoring systems, which favors at-home prenatal care.