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Methods to distinguish labour and pregnancy contractions: a systematic literature review
- Source :
- Health and Technology. 11:745-757
- Publication Year :
- 2021
- Publisher :
- Springer Science and Business Media LLC, 2021.
-
Abstract
- Uterine contractions monitoring is essential during pregnancy progression for due date prediction and the screening of preterm deliveries, i.e., those related to labour contractions occurring before 37 weeks of gestation. As there are different kinds of uterine contraction, distinguishing between true labour ones and normal physiological ones during pregnancy is not trivial. Thus, early identification is necessary for the effective and efficient care of pregnant women to avoid unnecessary and costly hospitalization. In this regard, while classical clinical methods proved their limitations, real-time monitoring of uterine contractions is now possible thanks to a new technique called ElectroHysteroGraphy which measures the uterine electrical activity that is a proxy for the mechanical activity of the muscles of the uterus. An exhaustive and comprehensive literature review was conducted to retrieve and report the state-of-the-art of the methods to distinguish labour contractions from pregnancy contractions. A systematic search was run on different search engines using a search string. A snowball sampling approach was applied to the references of the retrieved articles to identify further appropriate papers. According to this, the relevant references included in the bibliography of each analysed article led to other appropriate articles. Thus, papers dealing with the methods to distinguish labour from pregnancy (normal physiological) contractions and published between 2001 and 2020 were selected. Linear and nonlinear methods have been developed for uterine contractions signals (EHG/EMG) analysis to distinguish labour from pregnancy contractions. Nonlinear methods yielded better results compared to the linear methods, but not all nonlinear methods are promising in terms of clinical application.
- Subjects :
- medicine.medical_specialty
Pregnancy
020205 medical informatics
Obstetrics
business.industry
Nonlinear methods
Biomedical Engineering
Bioengineering
02 engineering and technology
medicine.disease
Applied Microbiology and Biotechnology
Linear methods
Clinical method
Uterine contraction
03 medical and health sciences
0302 clinical medicine
Snowball sampling
Systematic review
Due date
0202 electrical engineering, electronic engineering, information engineering
medicine
030212 general & internal medicine
medicine.symptom
business
Biotechnology
Subjects
Details
- ISSN :
- 21907196 and 21907188
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- Health and Technology
- Accession number :
- edsair.doi...........966f33991fac440eec65d06d7b55c119
- Full Text :
- https://doi.org/10.1007/s12553-021-00563-5