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Physiological-Based Difficulty Assessment for Virtual Reality Rehabilitation Games

2023-04Documento de conferência Acesso aberto
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dc.contributor.authorRodrigues, Pedro
dc.contributor.authorFonseca, Micaela
dc.contributor.authorLopes, Phil
dc.contributor.institutionDF – Departamento de Física
dc.contributor.institutionLIBPhys-UNL
dc.coverage.spatialNew York
dc.date.accessioned2023-07-14T22:08:13Z
dc.date.available2023-07-14T22:08:13Z
dc.date.issued2023-04
dc.descriptionFunding Information: This work is supported by Fundação para a Ciência e Tecnologia (FCT), under HEI-Lab R&D Unit (UIDB/05380/2020) and Project PlayersAll: media agency and empowerment (EXPL/COM-OUT/088 2/2021). Publisher Copyright: © 2023 Owner/Author.
dc.description.abstractThis paper proposes an empirical framework that aims to classify difficulty according to the player's physiological response. As part of the experimental protocol, a simple puzzle-based Virtual Reality (VR) videogame with three levels of difficulty was developed, each targeting a distinct region of the valence-arousal space. A study involving 32 participants was conducted, during which physiological responses (EDA, ECG, Respiration), were measured alongside emotional ratings, which were self-assessed using the Self-Assessment Manikin (SAM) during gameplay. Statistical analysis of the self-reports verified the effectiveness of the three levels in eliciting different emotions. Furthermore, classification using a Support Vector Machine (SVM) was performed to predict difficulty considering the physiological responses associated with each level. Results report an overall F1-score of 74.05% in detecting the three levels of difficulty, which validates the adopted methodology and encourages further research with a larger dataset.en
dc.description.versionpublished
dc.format.extent4
dc.format.extent562212
dc.identifier.doi10.1145/3582437.3587187
dc.identifier.isbn978-145039856-5
dc.identifier.otherPURE: 66001122
dc.identifier.otherPURE UUID: a2219ab0-d689-4535-9579-3b1d95e89d9f
dc.identifier.otherScopus: 85153562758
dc.identifier.otherORCID: /0000-0001-7946-4825/work/151427190
dc.identifier.urihttp://hdl.handle.net/10362/155271
dc.identifier.urlhttps://www.scopus.com/pages/publications/85153562758
dc.language.isoeng
dc.peerreviewedyes
dc.publisherACM - Association for Computing Machinery
dc.subjectAffective computing
dc.subjectemotion assessment
dc.subjectgames
dc.subjectmultimodal dataset
dc.subjectvirtual reality
dc.subjectHuman-Computer Interaction
dc.subjectComputer Networks and Communications
dc.subjectComputer Vision and Pattern Recognition
dc.subjectSoftware
dc.titlePhysiological-Based Difficulty Assessment for Virtual Reality Rehabilitation Gamesen
dc.typeconference object
degois.publication.titleFoundations of Digital Games 2023 (FDG 2023), April 12–14, 2023, Lisbon, Portugal
degois.publication.title18th International Conference on the Foundations of Digital Games, FDG 2023
dspace.entity.typePublication
rcaap.rightsopenAccess

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