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Toward emotionally adaptive virtual reality for mental health applications

2019Journal article Restricted access
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dc.contributor.authorBermúdez i Badia, Sergi
dc.contributor.authorVelez Quintero, Luis
dc.contributor.authorCameirão, Mónica S.
dc.contributor.authorChirico, Alice
dc.contributor.authorTriberti, Stefano
dc.contributor.authorCipresso, Pietro
dc.contributor.authorGaggioli, Andrea
dc.date.accessioned2019-12-11T09:52:20Z
dc.date.available2019-12-11T09:52:20Z
dc.date.issued2019
dc.description.abstractHere, we introduce the design and preliminary validation of a general-purpose architecture for affective-driven procedural content generation in virtual reality (VR) applications in mental health and wellbeing. The architecture supports seven commercial physiological sensing technologies and can be deployed in immersive and non-immersive VR systems. To demonstrate the concept, we developed the "The Emotional Labyrinth," a non-linear scenario in which navigation in a procedurally generated three-dimensional maze is entirely decided by the user, and whose features are dynamically adapted according to a set of emotional states. During navigation, affective states are dynamically represented through pictures, music, and animated visual metaphors chosen to represent and induce affective states. The underlying hypothesis is that exposing users to multimodal representations of their affective states can create a feedback loop that supports emotional self-awareness and fosters more effective emotional regulation strategies. We carried out a first study to, first, assess the effectiveness of the selected metaphors in inducing target emotions, and second, identify relevant psycho-physiological markers of the emotional experience generated by the labyrinth. Results show that the Emotional Labyrinth is overall a pleasant experience in which the proposed procedural content generation can induce distinctive psycho-physiological patterns, generally coherent with the meaning of the metaphors used in the labyrinth design. Furthermore, collected psycho-physiological responses such as electrocardiography, respiration, electrodermal activity, and electromyography are used to generate computational models of users' reported experience. These models enable the future implementation of the closed loop mechanism to adapt the Labyrinth procedurally to the users' affective state.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationBermúdez i Badia, S., Velez Quintero, L., Cameirão, M. S., Chirico, A., Triberti, S., Cipresso, P., & Gaggioli, A. (2019). Towards emotionally-adaptive virtual reality for mental health applications. IEEE journal of biomedical and health informatics, 23(5), 1877-1887.pt_PT
dc.identifier.doi10.1109/JBHI.2018.2878846pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.13/2643
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherInstitute of Electrical and Electronics Engineerspt_PT
dc.subjectEmotion regulationpt_PT
dc.subjectPhysiological computingpt_PT
dc.subjectPhysiology-driven VRpt_PT
dc.subjectProcedural content generationpt_PT
dc.subject.pt_PT
dc.subjectFaculdade de Ciências Exatas e da Engenhariapt_PT
dc.titleToward emotionally adaptive virtual reality for mental health applicationspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage1887pt_PT
oaire.citation.startPage1877pt_PT
oaire.citation.titleIEEE Journal of Biomedical and Health Informaticspt_PT
oaire.citation.volume23(5)pt_PT
person.familyNameBermúdez i Badia
person.familyNameCameirão
person.givenNameSergi
person.givenNameMónica
person.identifier239789
person.identifier.ciencia-idCA17-5E88-2B37
person.identifier.ciencia-id0A12-4F21-0CC2
person.identifier.orcid0000-0003-4452-0414
person.identifier.orcid0000-0002-5352-0128
person.identifier.ridC-8681-2018
person.identifier.ridC-8675-2018
person.identifier.scopus-author-id6506360007
person.identifier.scopus-author-id21740694600
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationef8f1e3b-3c09-4817-80d0-d96aa88051a2
relation.isAuthorOfPublication644f9f6a-81be-4b72-9ded-6eb1b8e251f4
relation.isAuthorOfPublication.latestForDiscoveryef8f1e3b-3c09-4817-80d0-d96aa88051a2

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