Fetal monitoring is important to diagnose complications that can occur during pregnancy. If detected timely, these complications might be resolved before they lead to irreversible damage. Current fetal monitoring mainly relies on cardiotocography, the simultaneous registration of fetal heart rate and uterine activity. Unfortunately, the technology to obtain the cardiotocogram has limitations. In current clinical practice the fetal heart rate is obtained via either an invasive scalp electrode, that poses risks and can only be applied during labor and after rupture of the fetal membranes, or via non-invasive Doppler ultrasound technology that is inaccurate and suffers from loss of signal, in particular in women with high body mass, during motion, or in preterm pregnancies. In this study, transabdominal electrophysiological measurements are exploited to provide fetal heart rate non-invasively and in a more reliable manner than Doppler ultrasound. The performance of the fetal heart rate detection is determined by comparing the fetal heart rate to that obtained with an invasive scalp electrode during intrapartum monitoring. The performance is gauged by comparing it to performances mentioned in literature on Doppler ultrasound and on two commercially-available devices that are also based on transabdominal fetal electrocardiography.
Keywords: artificial intelligence; cardiotocography; electrophysiology; fetal electrocardiogram; fetal heart rate; signal processing.
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