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Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/48800
DC FieldValueLanguage
dc.contributor.authorSteinmetzer, Tobiasen_US
dc.contributor.authorBonninger, Ingriden_US
dc.contributor.authorPriwitzer, Barbaraen_US
dc.contributor.authorReinhardt, Fritjofen_US
dc.contributor.authorReckhardt, Markus Christophen_US
dc.contributor.authorErk, Dorelaen_US
dc.contributor.authorTravieso, Carlos M.en_US
dc.date.accessioned2018-11-24T01:02:40Z-
dc.date.available2018-11-24T01:02:40Z-
dc.date.issued2018en_US
dc.identifier.isbn9781538675069en_US
dc.identifier.urihttp://hdl.handle.net/10553/48800-
dc.description.abstractWe present a new method for detecting gait disorders according to their stadium using cluster methods for sensor data. 21 healthy and 18 Parkinson subjects performed the Time Up and Go test. The time series were segmented into separate steps. For the analysis the horizontal acceleration measured by a mobile sensor system was considered. We used Dynamic Time Warping and Hierarchical Custering to distinguish the stadiums. A specificity of 92% was achieved.en_US
dc.languageengen_US
dc.relation.ispartof2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedingsen_US
dc.source2018 IEEE International Work Conference on Bioinspired Intelligence, IWOBI 2018 - Proceedings (8464203)en_US
dc.subject3314 Tecnología médicaen_US
dc.subject.otherDTWen_US
dc.subject.otherParkinson diseaseen_US
dc.subject.otherclusteringen_US
dc.subject.othertime seriesen_US
dc.titleClustering of Human Gait with Parkinson's Disease by Using Dynamic Time Warpingen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.identifier.doi10.1109/IWOBI.2018.8464203en_US
dc.identifier.scopus85054550393-
dc.contributor.authorscopusid57204115368-
dc.contributor.authorscopusid56395430400-
dc.contributor.authorscopusid57204107644-
dc.contributor.authorscopusid57198038929-
dc.contributor.authorscopusid7801554279-
dc.contributor.authorscopusid57204106522-
dc.contributor.authorscopusid6602376272-
dc.identifier.issue8464203-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.utils.revisionSíen_US
dc.identifier.ulpgcSíes
item.grantfulltextnone-
item.fulltextSin texto completo-
crisitem.author.deptGIR IDeTIC: División de Procesado Digital de Señales-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.orcid0000-0002-4621-2768-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.fullNameTravieso González, Carlos Manuel-
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