Please use this identifier to cite or link to this item:
http://hdl.handle.net/10553/105788
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Carmona Duarte, María Cristina | en_US |
dc.contributor.author | Ferrer Ballester, Miguel Ángel | en_US |
dc.contributor.author | Gómez-Vilda, Pedro | en_US |
dc.contributor.author | Van Gemmer, Arend W.A. | en_US |
dc.contributor.author | Plamondon, Réjean | en_US |
dc.date.accessioned | 2021-03-16T09:03:56Z | - |
dc.date.available | 2021-03-16T09:03:56Z | - |
dc.date.issued | 2018 | en_US |
dc.identifier.isbn | 1-895193-06-0 | en_US |
dc.identifier.uri | http://hdl.handle.net/10553/105788 | - |
dc.description.abstract | Parkinson’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.language | eng | en_US |
dc.source | Proceedings of 1st International Conference on Pattern Recognition and Artificial Intelligence (ICPRAI 2018) | en_US |
dc.subject | 3325 Tecnología de las telecomunicaciones | - |
dc.subject | 1203 Ciencia de los ordenadores | - |
dc.subject.other | Sigma-lognormal model | - |
dc.subject.other | kinematic theory of rapid movements | - |
dc.subject.other | articulation; | - |
dc.subject.other | Parkinson | - |
dc.subject.other | Voice | - |
dc.subject.other | Handwriting | - |
dc.title | A common framework to evaluate Parkinson’s disease in voice and handwriting | en_US |
dc.type | info:eu-repo/semantics/conferenceobject | en_US |
dc.type | ConferenceObject | en_US |
dc.relation.conference | ICPRAI 2018 - International Conference on Pattern Recognition and Artificial Intelligence | en_US |
dc.description.lastpage | 799 | en_US |
dc.description.firstpage | 795 | en_US |
dc.investigacion | Ingeniería y Arquitectura | - |
dc.type2 | Actas de congresos | en_US |
dc.utils.revision | Sí | - |
dc.date.coverdate | mayo 2018 | en_US |
dc.identifier.ulpgc | Sí | - |
dc.contributor.buulpgc | BU-TEL | en_US |
item.grantfulltext | open | - |
item.fulltext | Con texto completo | - |
crisitem.event.eventsstartdate | 14-05-2018 | - |
crisitem.event.eventsenddate | 17-05-2018 | - |
crisitem.author.dept | GIR IDeTIC: División de Procesado Digital de Señales | - |
crisitem.author.dept | IU para el Desarrollo Tecnológico y la Innovación | - |
crisitem.author.dept | Departamento de Informática y Sistemas | - |
crisitem.author.dept | GIR IDeTIC: División de Procesado Digital de Señales | - |
crisitem.author.dept | IU para el Desarrollo Tecnológico y la Innovación | - |
crisitem.author.dept | Departamento de Señales y Comunicaciones | - |
crisitem.author.orcid | 0000-0002-4441-6652 | - |
crisitem.author.orcid | 0000-0002-2924-1225 | - |
crisitem.author.parentorg | IU para el Desarrollo Tecnológico y la Innovación | - |
crisitem.author.parentorg | IU para el Desarrollo Tecnológico y la Innovación | - |
crisitem.author.fullName | Carmona Duarte, María Cristina | - |
crisitem.author.fullName | Ferrer Ballester, Miguel Ángel | - |
Appears in Collections: | Actas de congresos |
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