A cybersickness review: causes, strategies, and classification methods
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Journal on Interactive Systems |
Texto Completo: | https://sol.sbc.org.br/journals/index.php/jis/article/view/2058 |
Resumo: | Virtual reality (VR) and head-mounted displays are continually gaining popularity in various fields such as education, military, entertainment, and health. Although such technologies provide a high sense of immersion, they can also trigger symptoms of discomfort. This condition is called cybersickness (CS) and is quite popular in recent virtual reality research. In this work we first present a review of the literature on theories of discomfort manifestations usually attributed to virtual reality environments. Following, we reviewed existing strategies aimed at minimizing CS problems and discussed how the CS measurement has been conducted based on subjective, biosignal (or objective), and users profile data. We also describe and discuss related works that are aiming to mitigate cybersickness problems using deep and symbolic machine learning approaches. Although some works used methods to make deep learning explainable, they are not strongly affirmed by literature. For this reason in this work we argue that symbolic classifiers can be a good way to identify CS causes, once they possibilities human-readability which is crucial for analyze the machine learning decision paths. In summary, from a total of 157 observed studies, 24 were excluded. Moreover, we believe that this work facilitates researchers to identify the leading causes for most discomfort situations in virtual reality environments, associate the most recommended strategies to minimize such discomfort, and explore different ways to conduct experiments involving machine learning to overcome cybersickness. |
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Journal on Interactive Systems |
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A cybersickness review: causes, strategies, and classification methodsvirtual realityhead-mounted displayscybersicknesscausesstrategiesmachine learningVirtual reality (VR) and head-mounted displays are continually gaining popularity in various fields such as education, military, entertainment, and health. Although such technologies provide a high sense of immersion, they can also trigger symptoms of discomfort. This condition is called cybersickness (CS) and is quite popular in recent virtual reality research. In this work we first present a review of the literature on theories of discomfort manifestations usually attributed to virtual reality environments. Following, we reviewed existing strategies aimed at minimizing CS problems and discussed how the CS measurement has been conducted based on subjective, biosignal (or objective), and users profile data. We also describe and discuss related works that are aiming to mitigate cybersickness problems using deep and symbolic machine learning approaches. Although some works used methods to make deep learning explainable, they are not strongly affirmed by literature. For this reason in this work we argue that symbolic classifiers can be a good way to identify CS causes, once they possibilities human-readability which is crucial for analyze the machine learning decision paths. In summary, from a total of 157 observed studies, 24 were excluded. Moreover, we believe that this work facilitates researchers to identify the leading causes for most discomfort situations in virtual reality environments, associate the most recommended strategies to minimize such discomfort, and explore different ways to conduct experiments involving machine learning to overcome cybersickness.Brazilian Computer Society2021-11-26info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://sol.sbc.org.br/journals/index.php/jis/article/view/205810.5753/jis.2021.2058Journal of Interactive Systems; v. 12 n. 1 (2021); 269-282Journal on Interactive Systems; Vol. 12 No. 1 (2021); 269-2822763-771910.5753/jis.2021reponame:Journal on Interactive Systemsinstname:Sociedade Brasileira de Computação (SBC)instacron:SBCenghttps://sol.sbc.org.br/journals/index.php/jis/article/view/2058/1875Copyright (c) 2021 Thiago Porcino, Daniela Trevisan, Esteban Cluahttp://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessPorcino, ThiagoTrevisan, DanielaClua, Esteban2023-10-12T20:48:07Zoai:ojs2.sol.sbc.org.br:article/2058Revistahttps://sol.sbc.org.br/journals/index.php/jis/ONGhttps://sol.sbc.org.br/journals/index.php/jis/oaijis@sbc.org.br2763-77192763-7719opendoar:2023-10-12T20:48:07Journal on Interactive Systems - Sociedade Brasileira de Computação (SBC)false |
dc.title.none.fl_str_mv |
A cybersickness review: causes, strategies, and classification methods |
title |
A cybersickness review: causes, strategies, and classification methods |
spellingShingle |
A cybersickness review: causes, strategies, and classification methods Porcino, Thiago virtual reality head-mounted displays cybersickness causes strategies machine learning |
title_short |
A cybersickness review: causes, strategies, and classification methods |
title_full |
A cybersickness review: causes, strategies, and classification methods |
title_fullStr |
A cybersickness review: causes, strategies, and classification methods |
title_full_unstemmed |
A cybersickness review: causes, strategies, and classification methods |
title_sort |
A cybersickness review: causes, strategies, and classification methods |
author |
Porcino, Thiago |
author_facet |
Porcino, Thiago Trevisan, Daniela Clua, Esteban |
author_role |
author |
author2 |
Trevisan, Daniela Clua, Esteban |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Porcino, Thiago Trevisan, Daniela Clua, Esteban |
dc.subject.por.fl_str_mv |
virtual reality head-mounted displays cybersickness causes strategies machine learning |
topic |
virtual reality head-mounted displays cybersickness causes strategies machine learning |
description |
Virtual reality (VR) and head-mounted displays are continually gaining popularity in various fields such as education, military, entertainment, and health. Although such technologies provide a high sense of immersion, they can also trigger symptoms of discomfort. This condition is called cybersickness (CS) and is quite popular in recent virtual reality research. In this work we first present a review of the literature on theories of discomfort manifestations usually attributed to virtual reality environments. Following, we reviewed existing strategies aimed at minimizing CS problems and discussed how the CS measurement has been conducted based on subjective, biosignal (or objective), and users profile data. We also describe and discuss related works that are aiming to mitigate cybersickness problems using deep and symbolic machine learning approaches. Although some works used methods to make deep learning explainable, they are not strongly affirmed by literature. For this reason in this work we argue that symbolic classifiers can be a good way to identify CS causes, once they possibilities human-readability which is crucial for analyze the machine learning decision paths. In summary, from a total of 157 observed studies, 24 were excluded. Moreover, we believe that this work facilitates researchers to identify the leading causes for most discomfort situations in virtual reality environments, associate the most recommended strategies to minimize such discomfort, and explore different ways to conduct experiments involving machine learning to overcome cybersickness. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-11-26 |
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://sol.sbc.org.br/journals/index.php/jis/article/view/2058 10.5753/jis.2021.2058 |
url |
https://sol.sbc.org.br/journals/index.php/jis/article/view/2058 |
identifier_str_mv |
10.5753/jis.2021.2058 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://sol.sbc.org.br/journals/index.php/jis/article/view/2058/1875 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2021 Thiago Porcino, Daniela Trevisan, Esteban Clua http://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2021 Thiago Porcino, Daniela Trevisan, Esteban Clua http://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 |
Brazilian Computer Society |
publisher.none.fl_str_mv |
Brazilian Computer Society |
dc.source.none.fl_str_mv |
Journal of Interactive Systems; v. 12 n. 1 (2021); 269-282 Journal on Interactive Systems; Vol. 12 No. 1 (2021); 269-282 2763-7719 10.5753/jis.2021 reponame:Journal on Interactive Systems instname:Sociedade Brasileira de Computação (SBC) instacron:SBC |
instname_str |
Sociedade Brasileira de Computação (SBC) |
instacron_str |
SBC |
institution |
SBC |
reponame_str |
Journal on Interactive Systems |
collection |
Journal on Interactive Systems |
repository.name.fl_str_mv |
Journal on Interactive Systems - Sociedade Brasileira de Computação (SBC) |
repository.mail.fl_str_mv |
jis@sbc.org.br |
_version_ |
1796797411122741248 |