ArticleBMC pregnancy and childbirth2018
Automated electrohysterographic detection of uterine contractions for monitoring of pregnancy: feasibility and prospects.
Article in BMC pregnancy and childbirth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 40 citations in OpenAlex.
- Analysis of electrohysterogram signals for predicting obstetric outcome using machine learning methods: a scoping review.BMC pregnancy and childbirth · 2026Article
- Comparison of advanced electronic intrapartum monitoring system (Keyar device and Daksh application) with standard cardiotocography for assessment of fetal heart rate and uterine contractions.Journal of family medicine and primary care · 2026Article
- Enhancing uterine contraction detection through novel EHG signal processing: a pilot study leveraging the relationship between slow and fast wave components to improve signal quality and noise resilience.Frontiers in physiology · 2025Article
- IDENTIFICATION OF UTERINE CONTRACTIONS BY AN ENSEMBLE OF GAUSSIAN PROCESSES.Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP (Conference) · 2021Article
- Optimization of Imminent Labor Prediction Systems in Women with Threatened Preterm Labor Based on Electrohysterography.Sensors (Basel, Switzerland) · 2021Article
- Automatic recognition of uterine contractions with electrohysterogram signals based on the zero-crossing rate.Scientific reports · 2021Article
- Microelectrode array analysis of mouse uterine smooth muscle electrical activity†.Biology of reproduction · 2020Article
- Acquisition and Analysis of Electrohysterogram Signal.Journal of medical systems · 2020Article
- Evaluation of convolutional neural network for recognizing uterine contractions with electrohysterogram.Computers in biology and medicine · 2019Article
- Preliminary Study on the Efficient Electrohysterogram Segments for Recognizing Uterine Contractions with Convolutional Neural Networks.BioMed research international · 2019Article
- Using smart devices for prenatal care: Assessing the willingness among women with pregnancy-related anxiety.Digital healthArticle
- A flexible wearable system for uterine contraction monitoring and admission decision support.Digital healthArticle
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
backgroundPreterm birth is a major public health problem in developed countries. In this context, we have conducted research into outpatient monitoring of uterine electrical activity in women at risk of preterm delivery. The objective of this preliminary study was to perform automated detection of uterine contractions (without human intervention or tocographic signal, TOCO) by processing the EHG recorded on the abdomen of pregnant women. The feasibility and accuracy of uterine contraction detection based on EHG processing were tested and compared to expert decision using external tocodynamometry (TOCO) .
methodsThe study protocol was approved by local Ethics Committees under numbers ID-RCB 2016-A00663-48 for France and VSN 02-0006-V2 for Iceland. Two populations of women were included (threatened preterm birth and labour) in order to test our system of recognition of the various types of uterine contractions. EHG signal acquisition was performed according to a standardized protocol to ensure optimal reproducibility of EHG recordings. A system of 18 Ag/AgCl surface electrodes was used by placing 16 recording electrodes between the woman's pubis and umbilicus according to a 4 × 4 matrix. TOCO was recorded simultaneously with EHG recording. EHG signals were analysed in real-time by calculation of the nonlinear correlation coefficient H
resultsThe EHG database contained 51 recordings from pregnant women, with a total of 501 contractions previously labelled by analysis of the corresponding tocographic recording. The percentage recognitions obtained by application of the method based on coefficient H
conclusionThese preliminary results appear to be encouraging for monitoring of uterine contractions by algorithm-based automated detection to process the electrohysterographic signal (EHG). This compact recording system, based on the use of surface electrodes attached to the skin, appears to be particularly suitable for outpatient monitoring of uterine contractions, possibly at home, allowing telemonitoring of pregnancies. One of the advantages of EHG processing is that useful information concerning contraction efficiency can be extracted from this signal, which is not possible with the TOCO signal.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.