Review on EHG signal analysis and its application in preterm diagnosis

J Xu, Z Chen, H Lou, G Shen, A Pumir - Biomedical Signal Processing and …, 2022 - Elsevier
Preterm birth is the leading cause of neonatal morbidity and mortality. Early identification of
high-risk deliveries, combined with appropriate medication appears as the way to treat the …

[HTML][HTML] A cybernetic framework for predicting preterm and enhancing care strategies: A review

E Nsugbe - Biomedical Engineering Advances, 2021 - Elsevier
Preterm is viewed as the birth of a human foetus prior to 37 complete weeks of gestation. It
has effects on the health of both the foetus and the mother, has financial consequences to …

Combination of feature selection and resampling methods to predict preterm birth based on electrohysterographic signals from imbalance data

F Nieto-del-Amor, G Prats-Boluda, J Garcia-Casado… - Sensors, 2022 - mdpi.com
Due to its high sensitivity, electrohysterography (EHG) has emerged as an alternative
technique for predicting preterm labor. The main obstacle in designing preterm labor …

Novel multichannel entropy features and machine learning for early assessment of pregnancy progression using electrohysterography

A Cheng, Y Yao, Y Jin, C Chen… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Objective: Preterm birth is the leading cause of morbidity and mortality involving over 10% of
infants. Tools for timely diagnosis of preterm birth are lacking and the underlying …

Network theory based EHG signal analysis and its application in preterm prediction

J Xu, M Wang, J Zhang, Z Chen… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Objective: Preterm birth is the leading cause of neonatal morbidity and mortality. Early
identification of high-risk patients followed by medical interventions is essential to the …

Accurate diagnosis of term–preterm births by spectral analysis of electrohysterography signals

DK Degbedzui, ME Yüksel - Computers in Biology and Medicine, 2020 - Elsevier
Preterm delivery contributes to an increased risk of fetal and maternal death as well as
several health deficiencies, thereby requiring special care and treatment that result in high …

Assessment of dispersion and bubble entropy measures for enhancing preterm birth prediction based on electrohysterographic signals

F Nieto-del-Amor, R Beskhani, Y Ye-Lin… - Sensors, 2021 - mdpi.com
One of the remaining challenges for the scientific-technical community is predicting preterm
births, for which electrohysterography (EHG) has emerged as a highly sensitive prediction …

Optimized feature subset selection using genetic algorithm for preterm labor prediction based on electrohysterography

F Nieto-del-Amor, G Prats-Boluda… - Sensors, 2021 - mdpi.com
Electrohysterography (EHG) has emerged as an alternative technique to predict preterm
labor, which still remains a challenge for the scientific-technical community. Based on EHG …

Robust characterization of the uterine myoelectrical activity in different obstetric scenarios

J Mas-Cabo, Y Ye-Lin, J Garcia-Casado… - Entropy, 2020 - mdpi.com
Electrohysterography (EHG) has been shown to provide relevant information on uterine
activity and could be used for predicting preterm labor and identifying other maternal fetal …

Predicting preterm births from electrohysterogram recordings via deep learning

U Goldsztejn, A Nehorai - Plos one, 2023 - journals.plos.org
About one in ten babies is born preterm, ie, before completing 37 weeks of gestation, which
can result in permanent neurologic deficit and is a leading cause of child mortality. Although …