The MCA-FM method achieved average Pearson correlation coefficients of 0.94 ± 0.050 on the ADDB dataset and 0.91 ± 0.122 on the BDDB dataset for non-invasive fetal ECG extraction.
Does the MCA-FM method accurately extract non-invasive fetal ECG from maternal abdominal ECG?
The MCA-FM method provides a robust and accurate approach for extracting fetal ECG from maternal abdominal recordings, potentially improving non-invasive fetal heart health monitoring.
Non-invasive fetal electrocardiogram (FECG) extraction from maternal abdominal ECG (AECG) is crucial for prenatal monitoring but remains challenging due to strong interference from maternal ECG (MECG), baseline drift, and noise. We propose an FECG extraction method based on minimal channel attention (MCA) and flow matching (FM), learning a deterministic mapping from AECG to FECG via a probabilistic path. To balance the preservation of physiological signals and separation of interference, we employ bridge variance scheduling for the diffusion process. Target matching loss is introduced to regress the FECG directly, enhancing training stability and waveform fidelity. For feature selection, a minimal channel attention module with global average pooling and a single linear layer is embedded after feature extraction, capturing cross-channel dependencies with minimal parameters. Enhanced residual connections are incorporated to retain underlying features and optimize gradient flow in deep networks. Experiments on two public datasets (ADDB and BDDB) with a leave-one-out cross-validation strategy show that our method achieves average Pearson correlation coefficients (PCCs) of 0.94 ± 0.050 on ADDB and 0.91 ± 0.122 on BDDB, demonstrating robust performance across diverse real-world recording conditions. The method balances high accuracy with efficient feature extraction, offering a reliable solution for non-invasive fetal heart health monitoring.
Duan et al. (Fri,) conducted a other in Prenatal monitoring (fetal ECG extraction). MCA-FM (minimal channel attention and flow matching) was evaluated on Pearson correlation coefficient (PCC). The MCA-FM method achieved average Pearson correlation coefficients of 0.94 ± 0.050 on the ADDB dataset and 0.91 ± 0.122 on the BDDB dataset for non-invasive fetal ECG extraction.