AAFA-Net: Adaptive Amplitude-Frequency Attention Network for Fetal Monitoring From Noninvasive Abdominal Recordings

The noninvasive fetal electrocardiogram (FECG) is helpful for fetal well-being monitoring. However, it is difficult to obtain high-quality FECG signals because of the maternal electrocardiogram (MECG) and noise in the abdominal ECG (AECG). To address this problem, an adaptive amplitude-frequency attention network (AAFA-Net) is proposed for extracting FECG signals from AECG signals, where the frequency encoder-decoder (FED) module is developed to distinguish the FECG frequency components from AECG signals, and the amplitude encoder-decoder (AED) module is devised to extract FECG amplitude components from AECG signals, while the window encoder-decoder (WED) module is designed to determine the temporal window around the FECG signal. Experiments conducted on the benchmarks show that the proposed AAFA-Net performs better than the state-of-the-art approaches.

Automated summary

The noninvasive fetal electrocardiogram (FECG) is difficult to obtain due to the interference of the maternal electrocardiogram (MECG) and noise in the abdominal electrocardiogram (AECG). In this study, an adaptive amplitude-frequency attention network (AAFA-Net) was proposed to extract FECG signals from AECG signals. Experimental results demonstrate the superiority of the proposed method over existing approaches.