Publicação: A step towards the automated diagnosis of parkinson's disease: Analyzing handwriting movements
dc.contributor.author | Pereira, Clayton R. | |
dc.contributor.author | Pereira, Danillo R. | |
dc.contributor.author | Silva, Francisco A. Da | |
dc.contributor.author | Hook, Christian | |
dc.contributor.author | Weber, Silke A.T. [UNESP] | |
dc.contributor.author | Pereira, Luis A.M. [UNESP] | |
dc.contributor.author | Papa, Joao P. [UNESP] | |
dc.contributor.institution | Universidade Federal de São Carlos (UFSCar) | |
dc.contributor.institution | Western University, UNOEST | |
dc.contributor.institution | Ostbayerische Technische Hochschule | |
dc.contributor.institution | Universidade Estadual Paulista (Unesp) | |
dc.date.accessioned | 2018-12-11T17:25:55Z | |
dc.date.available | 2018-12-11T17:25:55Z | |
dc.date.issued | 2015-01-01 | |
dc.description.abstract | Parkinson'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.affiliation | Federal University, UFSCAR | |
dc.description.affiliation | Western University, UNOEST | |
dc.description.affiliation | Ostbayerische Technische Hochschule | |
dc.description.affiliation | São Paulo State University, UNESP | |
dc.description.affiliationUnesp | São Paulo State University, UNESP | |
dc.format.extent | 171-176 | |
dc.identifier | http://dx.doi.org/10.1109/CBMS.2015.34 | |
dc.identifier.citation | Proceedings - IEEE Symposium on Computer-Based Medical Systems, v. 2015-July, p. 171-176. | |
dc.identifier.doi | 10.1109/CBMS.2015.34 | |
dc.identifier.issn | 1063-7125 | |
dc.identifier.scopus | 2-s2.0-84944190477 | |
dc.identifier.uri | http://hdl.handle.net/11449/177541 | |
dc.language.iso | eng | |
dc.relation.ispartof | Proceedings - IEEE Symposium on Computer-Based Medical Systems | |
dc.relation.ispartofsjr | 0,183 | |
dc.rights.accessRights | Acesso aberto | |
dc.source | Scopus | |
dc.subject | machine learning | |
dc.subject | movement disorders | |
dc.subject | Parkinson's disease | |
dc.title | A step towards the automated diagnosis of parkinson's disease: Analyzing handwriting movements | en |
dc.type | Trabalho apresentado em evento | |
dspace.entity.type | Publication | |
unesp.campus | Universidade Estadual Paulista (UNESP), Faculdade de Ciências, Bauru | pt |
unesp.department | Computação - FC | pt |