The rapid advancement of deep neural networks (DNNs) has significantly transformed
various sectors, demonstrating unparalleled proficiency in managing intricate tasks in …

Intelligent classification of antepartum cardiotocography (CTG) can assist obstetricians to
make clinical decisions, which is helpful to improve the accuracy of fetal abnormality …

Computerized Cardiotocography (cCTG), which involves the continuous recording of the
fetal heart rate (FHR) and uterine contraction (UC) signals, plays a critical role in the …

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 …

Introduction Cardiotocography, which consists in monitoring the fetal heart rate as well as
uterine activity, is widely used in clinical practice to assess fetal wellbeing during labor and …

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

CTG (cardiotocography) has consistently been used to diagnose fetal hypoxia. It is
susceptible to identifying the average fetal acid-base balance but lacks specificity in …

Monitoring the heart rate of a fetus is the only method for continuously monitoring fetal well-
being during labour. Decelerations in the fetal heart rate, usually corresponding with …

Abstract Clinically, Fetal Heart Rate (FHR)-based intelligent cardiotocography classification
to diagnose fetal well-being is of utmost importance for obstetricians and gynecologists …

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 …