An automated pre-term prediction system using EHG signal with the aid of deep learning technique

A Veena, S Gowrishankar - Multimedia Tools and Applications, 2024 - Springer
Prematurity is the leading cause of infant morbidity and mortality around the world. Surface
uterine electromyogram (sEMG) is a non-invasive uterine electromyogram. One of most …

N-beats as an EHG signal forecasting method for labour prediction in full term pregnancy

TR Jossou, Z Tahori, G Houdji, D Medenou, A Lasfar… - Electronics, 2022 - mdpi.com
The early prediction of onset labour is critical for avoiding the risk of death due to pregnancy
delay. Low-income countries often struggle to deliver timely service to pregnant women due …

[HTML][HTML] Uterine myoelectrical activity as biomarker of successful induction with Dinoprostone: Influence of parity

A Diaz-Martinez, R Monfort-Ortiz, Y Ye-Lin… - biocybernetics and …, 2023 - Elsevier
The prolonged latent phase of Induction of Labour (IOL) is associated with increased risks of
maternal mortality and morbidity. Electrohysterography (EHG) has outperformed traditional …

ML-Based Interpretation of Cardiotocography Data: Current State and Future Research

TM Kadarina, D Gunawan - 2023 International Conference of …, 2023 - ieeexplore.ieee.org
To evaluate the health and well-being of an unborn child throughout pregnancy, fetal risk
prediction is a crucial component of prenatal care. The evaluation of potential risks and …

A real-time ecg ctg based ensemble feature extraction and unsupervised learning based classification framework for multi-class abnormality prediction

Y Aditya, SS Devi… - International Journal of …, 2023 - search.proquest.com
Cardiovascular diseases (CVDs) are a leading cause of death worldwide. Early detection
and diagnosis of these diseases can greatly reduce complications and improve outcomes …

An automatic classification approach for preterm delivery detection based on deep learning

KSN Rao, V Asha - Biomedical Signal Processing and Control, 2023 - Elsevier
Recently, tocography (TOCO) and electrohysterogram (EHG) signals are real-time and non-
invasive technology that has been applied to detect preterm delivery. This paper proposes a …

Predicting risk factors associated with preterm delivery using a machine learning model

SN Kavitha, V Asha - Multimedia Tools and Applications, 2024 - Springer
The evaluation of uterine contraction offers significant information regarding the progression
of labour. The occurrence of deliveries before the expected dates leads to undesirable …

Design and assessment of a computer-assisted artificial intelligence system for predicting preterm labor in women attending regular check-ups. Emphasis in …

F Nieto del Amor - 2023 - riunet.upv.es
[EN] Preterm delivery, defined as birth before 37 weeks of gestation, is a significant global
concern with implications for the health of newborns and economic costs. It affects …

ANALYSIS OF ELECTROHYSTEROGRAM SIGNALS AND PREDICTION OF PRETERM BIRTHS USING MACHINE LEARNING

D Raghavan, HH Adithya, S Raghuram… - Biomedical …, 2023 - World Scientific
The World Health Organization (WHO) estimates that over 15 million infants are born before
the entire period of pregnancy. Over a million neonatal deaths occurred in 2015 as a result …

MATRA: An Automated System for MATernal Risk Assessment

A Chakraborty, S Dutta, A Biswas, P Das… - Human-Centric Smart …, 2022 - Springer
The progress of science and technology in recent times has gifted numerous solutions that
have revolutionized our lifestyle. The advent of Internet of Things (IoT) and associated …