Neonatal intensive care units (NICUs) greatly expand the use of technology. There is a need
to accurately diagnose discomfort, pain, and complications, such as sepsis, mainly before …

Abstract The second Signal Processing and Monitoring in Labor workshop gathered
researchers who utilize promising new research strategies and initiatives to tackle the …

The wavelet scattering transform is an invariant and stable signal representation suitable for
many signal processing and machine learning applications. We present the Kymatio …

Background Despite intensive efforts directed at initial training in fetal heart rate
interpretation, continuing medical education, board certification/recertification, team training …

Fetal heart rate (FHR) is very significant to evaluate the status of fetus. However, based on
traditional classification criteria is not accurate. With the rapid development of computer …

Deep convolutional neural networks (DCNNs) have recently emerged as a powerful tool to
deliver breakthrough performances in various image analysis and processing applications …

Fetal heart rate (FHR) monitoring is routinely used in clinical practice to help obstetricians
assess fetal health status during delivery. However, early detection of fetal acidosis that …

In time series classification and regression, signals are typically mapped into some
intermediate representation used for constructing models. Since the underlying task is often …

Rationale, aims and objectives To evaluate obstetricians' inter‐and intra‐observer
agreement on intrapartum cardiotocogram (CTG) recordings and to examine obstetricians' …

Motivated by analyzing complicated time series, nonlinear-type time–frequency analysis has
become an active research topic in the past decades. Those developed tools have been …