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Automatic identification of motion artifacts in EHG recording for robust analysis of uterine contractions

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Automatic identification of motion artifacts in EHG recording for robust analysis of uterine contractions

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dc.contributor.author Ye-Lin, Yiyao es_ES
dc.contributor.author Garcia Casado, Francisco Javier es_ES
dc.contributor.author Prats Boluda, Gema es_ES
dc.contributor.author Alberola Rubio, José es_ES
dc.contributor.author Perales Marin, Alfredo Jose es_ES
dc.date.accessioned 2015-06-15T08:39:33Z
dc.date.available 2015-06-15T08:39:33Z
dc.date.issued 2014-01-09
dc.identifier.issn 1748-670X
dc.identifier.uri http://hdl.handle.net/10251/51682
dc.description.abstract Electrohysterography (EHG) is a non-invasive technique for monitoring uterine electrical activity. However, the presence of artifacts in the EHG signal may give rise to erroneous interpretations and make it difficult to extract useful information from these recordings. The aim of this work was to develop an automatic system of segmenting EHG recordings that distinguishes between uterine contractions and artifacts. Firstly, the segmentation is performed using an algorithm that generates the toco-like signal derived from the EHG and detects windows with significant changes in amplitude. After that, these segments are classified in two groups: artifacted and non-artifacted signals. To develop a classifier, a total of eleven spectral, temporal and non-linear features were calculated from EHG signal windows from 12 women in the first stage of labor that had previously been classified by experts. The combination of characteristics that led to the highest degree of accuracy in detecting artifacts was then determined. The results showed that it is possible to obtain automatic detection of motion artifacts in segmented EHG recordings with a precision of 92.2% using only seven features. The proposed algorithm and classifier together compose a useful tool for analyzing EHG signals and would help to promote clinical applications of this technique. es_ES
dc.description.sponsorship The authors are grateful to the R + D + I Linguistic Assistance Office at the UPV for their help in proofreading this paper. The work was supported by the Ministerio de Ciencia e Innovacion de Espana (TEC2010-16945). en_EN
dc.language Inglés es_ES
dc.publisher Hindawi Publishing Corporation es_ES
dc.relation.ispartof Computational and Mathematical Methods in Medicine es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Electrohysterogram es_ES
dc.subject Uterine electrical activity es_ES
dc.subject Uterine electromyogram es_ES
dc.subject Motion artifacts es_ES
dc.subject Feature analysis es_ES
dc.subject Artifact detection es_ES
dc.subject.classification TECNOLOGIA ELECTRONICA es_ES
dc.title Automatic identification of motion artifacts in EHG recording for robust analysis of uterine contractions es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1155/2014/470786
dc.relation.projectID info:eu-repo/grantAgreement/MICINN//TEC2010-16945/ES/APLICACION DE TECNICAS LAPLACIANAS PARA LA MONITORIZACION DE LA ACTIVIDAD ELECTRICA DEL MUSCULO LISO HUMANO: ENFASIS EN ELECTROHISTEROGRAMA/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Electrónica - Departament d'Enginyeria Electrònica es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Interuniversitario de Investigación en Bioingeniería y Tecnología Orientada al Ser Humano - Institut Interuniversitari d'Investigació en Bioenginyeria i Tecnologia Orientada a l'Ésser Humà es_ES
dc.contributor.affiliation Universitat Politècnica de València. Servicio de Alumnado - Servei d'Alumnat es_ES
dc.description.bibliographicCitation Ye-Lin, Y.; Garcia Casado, FJ.; Prats Boluda, G.; Alberola Rubio, J.; Perales Marin, AJ. (2014). Automatic identification of motion artifacts in EHG recording for robust analysis of uterine contractions. Computational and Mathematical Methods in Medicine. 2014:1-11. https://doi.org/10.1155/2014/470786 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1155/2014/470786 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 11 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 2014 es_ES
dc.relation.senia 254224
dc.identifier.eissn 1748-6718
dc.identifier.pmid 24523828 en_EN
dc.identifier.pmcid PMC3912778 en_EN
dc.contributor.funder Ministerio de Ciencia e Innovación es_ES
dc.contributor.funder Universitat Politècnica de València es_ES
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