Non-Invasive Fetal Well-Being Monitoring Approaches: A Mini Review on Fetal Signal Separation Techniques

Abstract

Fetal signal separation is vital in producing an accurate interpretation of the health condition of a fetal. In the context of a non-invasive fetal monitoring approach, the signals are acquired from the abdomen of pregnant women. As a result, a mix of maternal and fetal signals is obtained. These maternal and fetal signals are vague, as both signals are interchanged during the signal acquisition stage. Since the signals are overlapped, a signal separation technique must be employed to process the fetal signal for further analysis. This paper presents published studies on applying signal processing techniques involving fetal signal separation. These papers are obtained through a strategy known as the PRISMA technique. The online databases include ACM, Emerald Publishing, IEEE Explore Digital Library, Science Direct, Scopus, and Springer, with published years spanning from 2018 until 2022. Numerous separation techniques were found, such as adaptive filtering, blind source separation (BSS), and alternative approaches. Issues on the existing methods for fetal signal separation are discussed. In addition, the limitations and drawbacks of the research work involving existing fetal signal separation are reviewed in the paper. The potential direction of future research in this field is addressed as well. Based on this mini-review, it can be concluded that noise and ambiguity can still occur in the extracted fetal signals, even when signal processing techniques are applied. In the future, deep learning would be accommodating in improving the efficiency of extracting fetal signals obtained from the non-invasive fetal well-being monitoring technique. Meanwhile, apart from fetal heart rate (fHR) detection, fetal hypoxia can also be another important focus of study for improving fetal well-being monitoring.