A step towards the automated diagnosis of parkinson's disease: Analyzing handwriting movements
Main Author: | |
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Publication Date: | 2015 |
Other Authors: | , , , , , |
Format: | Conference object |
Language: | eng |
Source: | Repositório Institucional da UNESP |
Download full: | http://dx.doi.org/10.1109/CBMS.2015.34 http://hdl.handle.net/11449/177541 |
Summary: | 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. |
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A step towards the automated diagnosis of parkinson's disease: Analyzing handwriting movementsmachine learningmovement disordersParkinson's diseaseParkinson'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.Federal University, UFSCARWestern University, UNOESTOstbayerische Technische HochschuleSão Paulo State University, UNESPSão Paulo State University, UNESPUniversidade Federal de São Carlos (UFSCar)Western University, UNOESTOstbayerische Technische HochschuleUniversidade Estadual Paulista (Unesp)Pereira, Clayton R.Pereira, Danillo R.Silva, Francisco A. DaHook, ChristianWeber, Silke A.T. [UNESP]Pereira, Luis A.M. [UNESP]Papa, Joao P. [UNESP]2018-12-11T17:25:55Z2018-12-11T17:25:55Z2015-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject171-176http://dx.doi.org/10.1109/CBMS.2015.34Proceedings - IEEE Symposium on Computer-Based Medical Systems, v. 2015-July, p. 171-176.1063-7125http://hdl.handle.net/11449/17754110.1109/CBMS.2015.342-s2.0-84944190477Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengProceedings - IEEE Symposium on Computer-Based Medical Systems0,183info:eu-repo/semantics/openAccess2024-04-23T16:11:34Zoai:repositorio.unesp.br:11449/177541Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-04-23T16:11:34Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
A step towards the automated diagnosis of parkinson's disease: Analyzing handwriting movements |
title |
A step towards the automated diagnosis of parkinson's disease: Analyzing handwriting movements |
spellingShingle |
A step towards the automated diagnosis of parkinson's disease: Analyzing handwriting movements Pereira, Clayton R. machine learning movement disorders Parkinson's disease |
title_short |
A step towards the automated diagnosis of parkinson's disease: Analyzing handwriting movements |
title_full |
A step towards the automated diagnosis of parkinson's disease: Analyzing handwriting movements |
title_fullStr |
A step towards the automated diagnosis of parkinson's disease: Analyzing handwriting movements |
title_full_unstemmed |
A step towards the automated diagnosis of parkinson's disease: Analyzing handwriting movements |
title_sort |
A step towards the automated diagnosis of parkinson's disease: Analyzing handwriting movements |
author |
Pereira, Clayton R. |
author_facet |
Pereira, Clayton R. Pereira, Danillo R. Silva, Francisco A. Da Hook, Christian Weber, Silke A.T. [UNESP] Pereira, Luis A.M. [UNESP] Papa, Joao P. [UNESP] |
author_role |
author |
author2 |
Pereira, Danillo R. Silva, Francisco A. Da Hook, Christian Weber, Silke A.T. [UNESP] Pereira, Luis A.M. [UNESP] Papa, Joao P. [UNESP] |
author2_role |
author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Federal de São Carlos (UFSCar) Western University, UNOEST Ostbayerische Technische Hochschule Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Pereira, Clayton R. Pereira, Danillo R. Silva, Francisco A. Da Hook, Christian Weber, Silke A.T. [UNESP] Pereira, Luis A.M. [UNESP] Papa, Joao P. [UNESP] |
dc.subject.por.fl_str_mv |
machine learning movement disorders Parkinson's disease |
topic |
machine learning movement disorders Parkinson's disease |
description |
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. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-01-01 2018-12-11T17:25:55Z 2018-12-11T17:25:55Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1109/CBMS.2015.34 Proceedings - IEEE Symposium on Computer-Based Medical Systems, v. 2015-July, p. 171-176. 1063-7125 http://hdl.handle.net/11449/177541 10.1109/CBMS.2015.34 2-s2.0-84944190477 |
url |
http://dx.doi.org/10.1109/CBMS.2015.34 http://hdl.handle.net/11449/177541 |
identifier_str_mv |
Proceedings - IEEE Symposium on Computer-Based Medical Systems, v. 2015-July, p. 171-176. 1063-7125 10.1109/CBMS.2015.34 2-s2.0-84944190477 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Proceedings - IEEE Symposium on Computer-Based Medical Systems 0,183 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
171-176 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
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1799965735001260032 |