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

Bio-magnetic field imaging systems are of great significance to biomedical research. This
study proposes a compact and high-resolution four-channel optically pumped …

Arrhythmia is one of the causes of sudden infant death, and it is very important to detect fetal
arrhythmia for fetal well-being. Fetal electrocardiogram (FECG) is one of the methods to …

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 …

Cardiotocography (CTG) measurements are critical for assessing fetal wellbeing during
monitoring, and accurate assessment requires well-traceable CTG signals. The current FHR …

Cardiotocography (CTG) is the main tool available to detect neonatal acidemia during
delivery. Presently, obstetricians and midwives primarily rely on visual interpretation, leading …

This work aims to compare the performance of Machine Learning (ML) and Deep Learning
(DL) algorithms in detecting users' heartbeats on a smart bed. Targeting non-intrusive …

Cardiotocography (CTG) is widely used to assess fetal well-being. CTG is typically obtained
using ultrasound and autocorrelation methods, which extract periodicity from the signal to …

This article presents an innovative approach to analyzing and extracting electrocardiogram
(ECG) signals from the abdomen and thorax of pregnant women, with the primary goal of …

Introduction: Increased fetal heart rate variability (IFHRV), defined as fetal heart rate (FHR)
baseline amplitude changes of> 25 beats per minute with a duration of≥ 1 min, is an early …