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Analysis of sEMG signals using discrete wavelet transform for muscle fatigue detection

dc.contributor.editorLepore N.
dc.contributor.editorBrieva J.
dc.contributor.editorGarcia J.D.
dc.contributor.editorRomero E.
dc.creatorFlórez-Prias L.A.
dc.creatorContreras Ortiz, Sonia Helena
dc.date.accessioned2020-03-26T16:32:38Z
dc.date.available2020-03-26T16:32:38Z
dc.date.issued2017
dc.identifier.citationProceedings of SPIE - The International Society for Optical Engineering; Vol. 10572
dc.identifier.isbn9781510616332
dc.identifier.issn0277786X
dc.identifier.urihttps://hdl.handle.net/20.500.12585/8944
dc.description.abstractThe purpose of the present article is to characterize sEMG signals to determine muscular fatigue levels. To do this, the signal is decomposed using the discrete wavelet transform, which offers noise filtering features, simplicity and efficiency. sEMG signals on the forearm were acquired and analyzed during the execution of cyclic muscular contractions in the presence and absence of fatigue. When the muscle fatigues, the sEMG signal shows a more erratic behavior of the signal as more energy is required to maintain the effort levels. © 2017 SPIE.eng
dc.description.sponsorshipMedical Image Computing and Computer Assisted Intervention (MICCAI);SIPAIM Foundation;Universidad Nacional de Colombia;Universidad Nacional de Colombia, Direccion de Relaciones Exteriores
dc.format.mediumRecurso electrónico
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherSPIE
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.sourcehttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85038430967&doi=10.1117%2f12.2285950&partnerID=40&md5=ce5142fe15a705014ee3f0d3a8bdcbb3
dc.sourceScopus2-s2.0-85038430967
dc.titleAnalysis of sEMG signals using discrete wavelet transform for muscle fatigue detection
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dcterms.bibliographicCitationMontoya, M., Surface EMG based muscle fatigue detection using a low-cost wearable sensor and amplitude frequency analysis (2015) Conf. Int. de Ingeniería, 1 (1), pp. 29-33
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datacite.rightshttp://purl.org/coar/access_right/c_16ec
oaire.resourceTypehttp://purl.org/coar/resource_type/c_c94f
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
dc.source.event13th International Conference on Medical Information Processing and Analysis, SIPAIM 2017
dc.type.driverinfo:eu-repo/semantics/conferenceObject
dc.type.hasversioninfo:eu-repo/semantics/publishedVersion
dc.identifier.doi10.1117/12.2285950
dc.subject.keywordsMuscle fatigue
dc.subject.keywordsSemg
dc.subject.keywordsWavelet transform
dc.subject.keywordsBioinformatics
dc.subject.keywordsDiscrete wavelet transforms
dc.subject.keywordsMuscle
dc.subject.keywordsSignal analysis
dc.subject.keywordsSignal processing
dc.subject.keywordsSignal reconstruction
dc.subject.keywordsMuscle fatigues
dc.subject.keywordsMuscular contraction
dc.subject.keywordsMuscular fatigues
dc.subject.keywordsNoise filtering
dc.subject.keywordsSemg
dc.subject.keywordsSemg signals
dc.subject.keywordsWavelet transforms
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.rights.ccAtribución-NoComercial 4.0 Internacional
dc.identifier.instnameUniversidad Tecnológica de Bolívar
dc.identifier.reponameRepositorio UTB
dc.relation.conferencedate5 October 2017 through 7 October 2017
dc.type.spaConferencia
dc.identifier.orcid57199857784
dc.identifier.orcid57210822856


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Universidad Tecnológica de Bolívar - 2017 Institución de Educación Superior sujeta a inspección y vigilancia por el Ministerio de Educación Nacional. Resolución No 961 del 26 de octubre de 1970 a través de la cual la Gobernación de Bolívar otorga la Personería Jurídica a la Universidad Tecnológica de Bolívar.