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Publicação:
A step towards the automated diagnosis of parkinson's disease: Analyzing handwriting movements

dc.contributor.authorPereira, Clayton R.
dc.contributor.authorPereira, Danillo R.
dc.contributor.authorSilva, Francisco A. Da
dc.contributor.authorHook, Christian
dc.contributor.authorWeber, Silke A.T. [UNESP]
dc.contributor.authorPereira, Luis A.M. [UNESP]
dc.contributor.authorPapa, Joao P. [UNESP]
dc.contributor.institutionUniversidade Federal de São Carlos (UFSCar)
dc.contributor.institutionWestern University, UNOEST
dc.contributor.institutionOstbayerische Technische Hochschule
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2018-12-11T17:25:55Z
dc.date.available2018-12-11T17:25:55Z
dc.date.issued2015-01-01
dc.description.abstractParkinson's disease (PD) has affected millions of people world-wide, being its major problem the loss of movements and, consequently, the ability of working and locomotion. Although we can find several works that attempt at dealing with this problem out there, most of them make use of datasets composed by a few subjects only. In this work, we present some results toward the automated diagnosis of PD by means of computer vision-based techniques in a dataset composed by dozens of patients, which is one of the main contributions of this work. The dataset is part of a joint research project that aims at extracting both visual and signal-based information from healthy and PD patients in order to go forward the early diagnosis of PD patients. The dataset is composed by handwriting clinical exams that are analyzed by means of image processing and machine learning techniques, being the preliminary results encouraging and promising. Additionally, a new quantitative feature to measure the amount of tremor of an individual's handwritten trace called Mean Relative Tremor is also presented.en
dc.description.affiliationFederal University, UFSCAR
dc.description.affiliationWestern University, UNOEST
dc.description.affiliationOstbayerische Technische Hochschule
dc.description.affiliationSão Paulo State University, UNESP
dc.description.affiliationUnespSão Paulo State University, UNESP
dc.format.extent171-176
dc.identifierhttp://dx.doi.org/10.1109/CBMS.2015.34
dc.identifier.citationProceedings - IEEE Symposium on Computer-Based Medical Systems, v. 2015-July, p. 171-176.
dc.identifier.doi10.1109/CBMS.2015.34
dc.identifier.issn1063-7125
dc.identifier.scopus2-s2.0-84944190477
dc.identifier.urihttp://hdl.handle.net/11449/177541
dc.language.isoeng
dc.relation.ispartofProceedings - IEEE Symposium on Computer-Based Medical Systems
dc.relation.ispartofsjr0,183
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectmachine learning
dc.subjectmovement disorders
dc.subjectParkinson's disease
dc.titleA step towards the automated diagnosis of parkinson's disease: Analyzing handwriting movementsen
dc.typeTrabalho apresentado em evento
dspace.entity.typePublication
unesp.campusUniversidade Estadual Paulista (UNESP), Faculdade de Ciências, Baurupt
unesp.departmentComputação - FCpt

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