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Automatic contraction detection using uterine electromyography

2020-10-09Artigo científico Acesso aberto
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dc.contributor.authorCardoso, Filipa Esgalhado de Oliveira Gouveia
dc.contributor.authorBatista, Arnaldo
dc.contributor.authorMouriño, Helena
dc.contributor.authorRusso, Sara Filipa Marques
dc.contributor.authorPalma dos Reis, Catarina R
dc.contributor.authorSerrano, Fátima
dc.contributor.authorVassilenko, Valentina
dc.contributor.authorOrtigueira, Manuel D.
dc.contributor.institutionFaculdade de Ciências e Tecnologia (FCT)
dc.contributor.institutionCTS - Centro de Tecnologia e Sistemas
dc.contributor.institutionUNINOVA-Instituto de Desenvolvimento de Novas Tecnologias
dc.contributor.institutionNOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)
dc.contributor.institutionComprehensive Health Research Centre (CHRC) - pólo NMS
dc.contributor.pblMDPI - Multidisciplinary Digital Publishing Institute
dc.date.accessioned2021-03-23T23:25:56Z
dc.date.available2021-03-23T23:25:56Z
dc.date.issued2020-10-09
dc.descriptionUIDB/00066/2020 UID/MAT/04561/2019 PD/BDE/150312/2019
dc.description.abstractElectrohysterography (EHG) is a promising technique for pregnancy monitoring and preterm risk evaluation. It allows for uterine contraction monitoring as early as the 20th gestational week, and it is a non-invasive technique based on recording the electric signal of the uterine muscle activity from electrodes located in the abdominal surface. In this work, EHG-based contraction detection methodologies are applied using signal envelope features. Automatic contraction detection is an important step for the development of unsupervised pregnancy monitoring systems based on EHG. The exploratory methodologies include wavelet energy, Teager energy, root mean square (RMS), squared RMS, and Hilbert envelope. In this work, two main features were evaluated: contraction detection and its related delineation accuracy. The squared RMS produced the best contraction (97.15 ± 4.66%) and delineation (89.43 ± 8.10%) accuracy and the lowest false positive rate (0.63%). Despite the wavelet energy method having a contraction accuracy (92.28%) below the first-rated method, its standard deviation was the second best (6.66%). The average false positive rate ranged between 0.63% and 4.74%—a remarkably low value.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent14
dc.format.extent3130789
dc.identifier.doi10.3390/app10207014
dc.identifier.issn2076-3417
dc.identifier.otherPURE: 26768627
dc.identifier.otherPURE UUID: 173ac151-3e5c-40dc-8071-85313a30c09d
dc.identifier.otherScopus: 85092795627
dc.identifier.otherWOS: 000582921400001
dc.identifier.otherORCID: /0000-0002-2287-4265/work/91113159
dc.identifier.otherORCID: /0000-0003-4270-3284/work/91113566
dc.identifier.urihttp://hdl.handle.net/10362/114329
dc.language.isoeng
dc.peerreviewedyes
dc.titleAutomatic contraction detection using uterine electromyographyen
dc.typejournal article
degois.publication.issue20
degois.publication.titleApplied Sciences
degois.publication.volume10
dspace.entity.typePublication
rcaap.rightsopenAccess

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