The proposed AAFA-Net improves the extraction of high-quality fetal ECG signals from noninvasive abdominal recordings compared to existing methods.
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.
Liao et al. (Sun,) studied this question.
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