Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/105788
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dc.contributor.authorCarmona Duarte, María Cristinaen_US
dc.contributor.authorFerrer Ballester, Miguel Ángelen_US
dc.contributor.authorGómez-Vilda, Pedroen_US
dc.contributor.authorVan Gemmer, Arend W.A.en_US
dc.contributor.authorPlamondon, Réjeanen_US
dc.date.accessioned2021-03-16T09:03:56Z-
dc.date.available2021-03-16T09:03:56Z-
dc.date.issued2018en_US
dc.identifier.isbn1-895193-06-0en_US
dc.identifier.urihttp://hdl.handle.net/10553/105788-
dc.description.abstractParkinson’s disease is manifested as well in handwriting as in voice. Previous researches have carried out different procedures to estimate the dysfunctions of the illness in voice and handwriting separately. This paper proposes one parameter to evaluate the influence of the illness on both voice and handwriting as the symptoms affecting both has a common origin. Specifically, the parameter proposed is based on the Kinematic Theory of rapid human movements. It allows to quantify the deficits caused by Parkinson’s disease in both handwriting and voice. The velocity profile obtained to characterize voice between the first and second formant is computed by a spatio-temporal approximation. In handwriting, the velocity profile is obtained from the sampled positions of the pen on a digital tablet. Once the velocity profile is derived, it is transformed to fit into the lognormal model in which similarities between voice and handwriting has been found for performance of these tasks by Parkinson’s patients. The experiments with different databases of voice and handwriting recorded from different patients in different labs display encouraging results.-
dc.languageengen_US
dc.sourceProceedings of 1st International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI 2018)en_US
dc.subject3325 Tecnología de las telecomunicaciones-
dc.subject1203 Ciencia de los ordenadores-
dc.subject.otherSigma-lognormal model-
dc.subject.otherkinematic theory of rapid movements-
dc.subject.otherarticulation;-
dc.subject.otherParkinson-
dc.subject.otherVoice-
dc.subject.otherHandwriting-
dc.titleA common framework to evaluate Parkinson’s disease in voice and handwritingen_US
dc.typeinfo:eu-repo/semantics/conferenceobjecten_US
dc.typeConferenceObjecten_US
dc.relation.conferenceICPRAI 2018 - International Conference on Pattern Recognition and Artificial Intelligenceen_US
dc.description.lastpage799en_US
dc.description.firstpage795en_US
dc.investigacionIngeniería y Arquitectura-
dc.type2Actas de congresosen_US
dc.utils.revision-
dc.date.coverdatemayo 2018en_US
dc.identifier.ulpgc-
dc.contributor.buulpgcBU-TELen_US
item.grantfulltextopen-
item.fulltextCon texto completo-
crisitem.event.eventsstartdate14-05-2018-
crisitem.event.eventsenddate17-05-2018-
crisitem.author.deptGIR IDeTIC: División de Procesado Digital de Señales-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Informática y Sistemas-
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.orcid0000-0002-4441-6652-
crisitem.author.orcid0000-0002-2924-1225-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.fullNameCarmona Duarte, María Cristina-
crisitem.author.fullNameFerrer Ballester, Miguel Ángel-
Appears in Collections:Actas de congresos
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