Abstract Background and Objective The patterns present in biosignals, such as fetal heart
rate (FHR), are valuable indicators of fetal well-being. In designing biosignal analysis …

Monitoring fetal heart rate (FHR) through cardiotocography is crucial for the early diagnosis
of fetal distress situations, necessitating prompt obstetrical intervention. However, FHR …

Objective Traditional methods face challenges in accurately analyzing fetal heart rate (FHR)
signals due to the complexity of accelerations and decelerations (Acc/Dec) and their cyclic …

Objective According to guidelines on electronic fetal heart rate (FHR) monitoring, visual FHR
interpretation by obstetricians depends on the recognition of patterns (mainly including …

We have developed deep learning models for automatic identification of the maternal heart
rate (MHR) and, more generally, false signals (FSs) on fetal heart rate (FHR) recordings. The …

Background Automated fetal heart rate (FHR) analysis removes inter-and intra-expert
variability, and is a promising solution for reducing the occurrence of fetal acidosis and the …

Automatic baseline determination is crucial for reducing the occurrence of fetal acidosis in
clinical practice. However, there is a nonnegligible gap between the results of automatic …

Accurate analysis of Fetal Heart Rate (FHR) signal is often impeded by challenges such as
data scarcity and label imbalance, which affect the reliability and robustness of deep …

Objective To develop a research database for mother-and-child clinical and laboratory data
and digital foetal heart rate (FHR) recordings. Methods The Base Bien Naître (BBN) …

Fetal heart rate (FHR) monitoring is the most widely used tool in clinics to assess fetal
health. However, FHR with low-quality signals may somehow exaggerate the risk of the fetus …