Performance comparison of coupling-evaluation methods in discriminating between pregnancy and labor EHG signals-Reference-Cited by-同舟云学术

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Performance comparison of coupling-evaluation methods in discriminating between pregnancy and labor EHG signals

Published:2021-05 Issue: Volume:132 Page:104308
ISSN:0010-4825
Container-title:Computers in Biology and Medicine
language:en
Short-container-title:Computers in Biology and Medicine

Author:

Diab Ahmad,Boudaoud Sofiane,Karlsson Brynjar,Marque Catherine

Funder

French Government Ministry of Higher Education and Research

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

Reference44 articles.

1. Effect of decimation on the classification rate of nonlinear analysis methods applied to uterine EMG signals;Diab;IRBM,2013

2. Windowed multivariate autoregressive model improving classification of labor vs. pregnancy contractions;Karlsson,2013

3. Estimation of coupling and directionality between signals applied to physiological uterine EMG model and real EHG signals;Diab,2014

4. Visualization of synchronization of the uterine contraction signals: running cross-correlation and wavelet running cross-correlation methods;Oczeretko;Med. Eng. Phys.,2006

5. Constraining minimum-norm inverse by phase synchronization and signal power of the scalp EEG channels;Majumdar;IEEE Trans. Biomed. Eng.,2009

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A deep learning framework for noninvasive fetal ECG signal extraction;Frontiers in Physiology;2024-04-22

2. Recurrence quantification analysis of uterine vectormyometriogram to identify pregnant women with threatened preterm labor;Biomedical Signal Processing and Control;2024-03

3. Automated Method for Uterine Contraction Extraction and Classification of Term Versus Pre-Term EHG Signals;IEEE Access;2024

4. An open dataset with electrohysterogram records of pregnancies ending in induced and cesarean section delivery;Scientific Data;2023-10-02

5. Estimating uterine activity from electrohysterogram measurements via statistical tensor decomposition;Biomedical Signal Processing and Control;2023-08

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