Computer vision devices for tracking gross upper limb movements in post-stroke rehabilitation
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Research, Society and Development |
Texto Completo: | https://rsdjournal.org/index.php/rsd/article/view/16143 |
Resumo: | Games and virtual reality are new concepts applied to upper limb rehabilitation after stroke. To perform upper limb physiotherapy rehabilitation and restore motor skills through virtual reality resources it is necessary to use an arm tracker, which would be the input of the video game. However, one of the main issues when starting a post-stroke rehabilitation game project is choosing the most suitable gross upper limb motion tracking device. Thus, this article aims to explore the gross upper limb motion tracking devices most commonly used in the scientific literature. To carry out this research, literature searches in English were conducted up to December 2020 in the ACM, PubMed and IEEE Xplore databases. We have selected a total of ninety-five (95) articles. In these studies, we identified the most used gross upper limb motion devices and we classified them into 5 different categories: RGB-D skeletal tracking, RGB object tracking, IR marker tracking, LeapMotion and RGB markerless body tracking. We found that most studies (52%) used RGB-D skeletal tracking. In addition, we found fifteen (15) different commercial systems or tracking devices and the most used was Kinect® (47% of all studies). However, it was not possible to generalize whether one device is better than the other. Although the amount of research in this area has increased significantly in recent years, additional studies are still needed to quantify the potential of the use of gross upper limb motion tracking devices in rehabilitation with games in post-stroke treatment. |
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Computer vision devices for tracking gross upper limb movements in post-stroke rehabilitationDispositivos de visión por computador para el rastreo de los movimientos gruesos de las extremidades superiores en la rehabilitación posterior al accidente cerebrovascularDispositivos de visão computacional para rastrear movimentos grossos de membros superiores na reabilitação pós-acidente vascular cerebralAcidente Vascular CerebralReabilitaçãoMembro superiorVisão computacionalFunção Motora Grossa.StrokeRehabilitationUpper limbComputer visionGross Motor function.Accidentes cerebrovascularesRehabilitaciónMiembro superiorVisión por computadorFunción Motora Gruesa.Games and virtual reality are new concepts applied to upper limb rehabilitation after stroke. To perform upper limb physiotherapy rehabilitation and restore motor skills through virtual reality resources it is necessary to use an arm tracker, which would be the input of the video game. However, one of the main issues when starting a post-stroke rehabilitation game project is choosing the most suitable gross upper limb motion tracking device. Thus, this article aims to explore the gross upper limb motion tracking devices most commonly used in the scientific literature. To carry out this research, literature searches in English were conducted up to December 2020 in the ACM, PubMed and IEEE Xplore databases. We have selected a total of ninety-five (95) articles. In these studies, we identified the most used gross upper limb motion devices and we classified them into 5 different categories: RGB-D skeletal tracking, RGB object tracking, IR marker tracking, LeapMotion and RGB markerless body tracking. We found that most studies (52%) used RGB-D skeletal tracking. In addition, we found fifteen (15) different commercial systems or tracking devices and the most used was Kinect® (47% of all studies). However, it was not possible to generalize whether one device is better than the other. Although the amount of research in this area has increased significantly in recent years, additional studies are still needed to quantify the potential of the use of gross upper limb motion tracking devices in rehabilitation with games in post-stroke treatment.Los juegos y la realidad virtual son nuevos conceptos aplicados a la rehabilitación de las extremidades superiores tras un ictus. Para llevar a cabo la rehabilitación fisioterapéutica del miembro superior y restaurar las habilidades motoras mediante recursos de realidad virtual es necesario utilizar un rastreador de brazos, que sería la entrada del videojuego. Sin embargo, uno de los principales problemas a la hora de iniciar un proyecto de juego de rehabilitación tras un ictus es la elección del dispositivo de rastreo del movimiento del miembro superior más adecuado. Así, este artículo pretende explorar los dispositivos de rastreo del movimiento grueso del miembro superior más utilizados en la literatura científica. Para llevar a cabo esta investigación, se realizaron búsquedas bibliográficas en inglés hasta diciembre de 2020 en las bases de datos ACM, PubMed e IEEE Xplore. Hemos seleccionado un total de noventa y cinco (95) artículos. En estos estudios, identificamos los dispositivos de movimiento de la extremidad superior más utilizados y los clasificamos en 5 categorías diferentes: RGB-D skeletal tracking, RGB object tracking, IR marker tracking, LeapMotion y RGB markerless body tracking. Encontramos que la mayoría de los estudios (52%) utilizaron el RGB-D skeletal tracking. Además, encontramos quince (15) sistemas o dispositivos de rastreo comerciales diferentes y el más utilizado fue Kinect® (47% de todos los estudios). No obstante, no fue posible generalizar si un dispositivo es mejor que el otro. Aunque la cantidad de investigaciones en esta área ha aumentado significativamente en los últimos años, todavía se necesitan estudios adicionales para cuantificar el potencial del uso de dispositivos de seguimiento del movimiento del miembro superior grueso en la rehabilitación con juegos en el tratamiento posterior al accidente cerebrovascular.Jogos e realidade virtual são novos conceitos aplicados à reabilitação dos membros superiores após o acidente vascular cerebral (AVC). Para realizar a reabilitação fisioterapêutica dos membros superiores e restaurar as capacidades motoras através dos recursos da realidade virtual é necessário utilizar um rastreador do membro superior, o qual seria a entrada de um jogo. Contudo, uma das principais questões ao iniciar um projeto de jogo de reabilitação pós-acidente é escolher o dispositivo de rastreamento do movimento grosso do membro superior mais adequado. Assim, este artigo visa explorar os dispositivos de rastreio do movimento grosso dos membros superiores mais comumente utilizados na literatura científica. Para realizar esta pesquisa, foram realizadas buscas bibliográficas em inglês até Dezembro de 2020 nas bases de dados ACM, PubMed e IEEE Xplore. Selecionamos um total de noventa e cinco (95) artigos. Nestes estudos, identificamos os dispositivos de rastreio do movimento grosso de membros superiores mais utilizados e classificamos em 5 categorias diferentes: RGB-D skeletal tracking, RGB object tracking, IR marker tracking, LeapMotion e RGB markerless body tracking. Verificamos que a maioria dos estudos (52%) utilizou o skeletal tracking RGB-D. Além disso, encontramos quinze (15) sistemas comerciais ou dispositivos de rastreio diferentes e o mais utilizado foi Kinect® (47% de todos os estudos). No entanto, não foi possível generalizar se um dispositivo é melhor do que o outro. Embora a quantidade de investigação nesta área tenha aumentado significativamente nos últimos anos, ainda são necessários estudos adicionais para quantificar o potencial da utilização de dispositivos de rastreio do movimento grosso dos membros superiores na reabilitação com jogos no tratamento pós-AVC.Research, Society and Development2021-06-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/1614310.33448/rsd-v10i6.16143Research, Society and Development; Vol. 10 No. 6; e57910616143Research, Society and Development; Vol. 10 Núm. 6; e57910616143Research, Society and Development; v. 10 n. 6; e579106161432525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIenghttps://rsdjournal.org/index.php/rsd/article/view/16143/14430Copyright (c) 2021 Júlia Tannús de Souza; Eduardo Lázaro Martins Naves; Angela Abreu Rosa de Sáhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSouza, Júlia Tannús deNaves, Eduardo Lázaro Martins Sá, Angela Abreu Rosa de2021-06-10T22:51:46Zoai:ojs.pkp.sfu.ca:article/16143Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:36:46.739192Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false |
dc.title.none.fl_str_mv |
Computer vision devices for tracking gross upper limb movements in post-stroke rehabilitation Dispositivos de visión por computador para el rastreo de los movimientos gruesos de las extremidades superiores en la rehabilitación posterior al accidente cerebrovascular Dispositivos de visão computacional para rastrear movimentos grossos de membros superiores na reabilitação pós-acidente vascular cerebral |
title |
Computer vision devices for tracking gross upper limb movements in post-stroke rehabilitation |
spellingShingle |
Computer vision devices for tracking gross upper limb movements in post-stroke rehabilitation Souza, Júlia Tannús de Acidente Vascular Cerebral Reabilitação Membro superior Visão computacional Função Motora Grossa. Stroke Rehabilitation Upper limb Computer vision Gross Motor function. Accidentes cerebrovasculares Rehabilitación Miembro superior Visión por computador Función Motora Gruesa. |
title_short |
Computer vision devices for tracking gross upper limb movements in post-stroke rehabilitation |
title_full |
Computer vision devices for tracking gross upper limb movements in post-stroke rehabilitation |
title_fullStr |
Computer vision devices for tracking gross upper limb movements in post-stroke rehabilitation |
title_full_unstemmed |
Computer vision devices for tracking gross upper limb movements in post-stroke rehabilitation |
title_sort |
Computer vision devices for tracking gross upper limb movements in post-stroke rehabilitation |
author |
Souza, Júlia Tannús de |
author_facet |
Souza, Júlia Tannús de Naves, Eduardo Lázaro Martins Sá, Angela Abreu Rosa de |
author_role |
author |
author2 |
Naves, Eduardo Lázaro Martins Sá, Angela Abreu Rosa de |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Souza, Júlia Tannús de Naves, Eduardo Lázaro Martins Sá, Angela Abreu Rosa de |
dc.subject.por.fl_str_mv |
Acidente Vascular Cerebral Reabilitação Membro superior Visão computacional Função Motora Grossa. Stroke Rehabilitation Upper limb Computer vision Gross Motor function. Accidentes cerebrovasculares Rehabilitación Miembro superior Visión por computador Función Motora Gruesa. |
topic |
Acidente Vascular Cerebral Reabilitação Membro superior Visão computacional Função Motora Grossa. Stroke Rehabilitation Upper limb Computer vision Gross Motor function. Accidentes cerebrovasculares Rehabilitación Miembro superior Visión por computador Función Motora Gruesa. |
description |
Games and virtual reality are new concepts applied to upper limb rehabilitation after stroke. To perform upper limb physiotherapy rehabilitation and restore motor skills through virtual reality resources it is necessary to use an arm tracker, which would be the input of the video game. However, one of the main issues when starting a post-stroke rehabilitation game project is choosing the most suitable gross upper limb motion tracking device. Thus, this article aims to explore the gross upper limb motion tracking devices most commonly used in the scientific literature. To carry out this research, literature searches in English were conducted up to December 2020 in the ACM, PubMed and IEEE Xplore databases. We have selected a total of ninety-five (95) articles. In these studies, we identified the most used gross upper limb motion devices and we classified them into 5 different categories: RGB-D skeletal tracking, RGB object tracking, IR marker tracking, LeapMotion and RGB markerless body tracking. We found that most studies (52%) used RGB-D skeletal tracking. In addition, we found fifteen (15) different commercial systems or tracking devices and the most used was Kinect® (47% of all studies). However, it was not possible to generalize whether one device is better than the other. Although the amount of research in this area has increased significantly in recent years, additional studies are still needed to quantify the potential of the use of gross upper limb motion tracking devices in rehabilitation with games in post-stroke treatment. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-06-10 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/16143 10.33448/rsd-v10i6.16143 |
url |
https://rsdjournal.org/index.php/rsd/article/view/16143 |
identifier_str_mv |
10.33448/rsd-v10i6.16143 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/16143/14430 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2021 Júlia Tannús de Souza; Eduardo Lázaro Martins Naves; Angela Abreu Rosa de Sá https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2021 Júlia Tannús de Souza; Eduardo Lázaro Martins Naves; Angela Abreu Rosa de Sá https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Research, Society and Development |
publisher.none.fl_str_mv |
Research, Society and Development |
dc.source.none.fl_str_mv |
Research, Society and Development; Vol. 10 No. 6; e57910616143 Research, Society and Development; Vol. 10 Núm. 6; e57910616143 Research, Society and Development; v. 10 n. 6; e57910616143 2525-3409 reponame:Research, Society and Development instname:Universidade Federal de Itajubá (UNIFEI) instacron:UNIFEI |
instname_str |
Universidade Federal de Itajubá (UNIFEI) |
instacron_str |
UNIFEI |
institution |
UNIFEI |
reponame_str |
Research, Society and Development |
collection |
Research, Society and Development |
repository.name.fl_str_mv |
Research, Society and Development - Universidade Federal de Itajubá (UNIFEI) |
repository.mail.fl_str_mv |
rsd.articles@gmail.com |
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1797052806968901632 |