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Multi-Componential Analysis of Emotions Using Virtual Reality

Published: 08 December 2021 Publication History

Abstract

In this study, we propose our data-driven approach to investigate the emotional experience triggered using Virtual Reality (VR) games. We considered a full Component Process Model (CPM) which theorise emotional experience as a multi-process phenomenon. We validated the possibility of the proposed approach through a pilot experiment and confirmed that VR games can be used to trigger a diverse range of emotions. Using hierarchical clustering, we showed a clear distinction between positive and negative emotion in the CPM space.

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References

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L. Hinkle, K. Khoshhal, and V. Metsis. 2019. Physiological Measurement for Emotion Recognition in Virtual Reality. In 2019 2nd International Conference on Data Intelligence and Security (ICDIS). 136–143.
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Jih-Hsuan Tammy Lin. 2017. Fear in virtual reality (VR): Fear elements, coping reactions, immediate and next-day fright responses toward a survival horror zombie virtual reality game. Computers in Human Behavior 72 (2017), 350–361.
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[3] Maëlan Menétrey.2019. Assessing the Component Process Model of Emotion using multivariate pattern classification analyses. Thesis.
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Ben Meuleman and David Rudrauf. 2018. Induction and profiling of strong multi-componential emotions in virtual reality. IEEE Transactions on Affective Computing PP (2018), 1–1.
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G. Mohammadi, K. Lin, and P. Vuilleumier. 2019. Towards Understanding Emotional Experience in a Componential Framework. In 2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII). 123–129.
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Klaus R. Scherer, Johnny R. F. Fontaine, and Cristina Soriano. 2013. CoreGRID and MiniGRID: Development and validation of two short versions of the GRID instrument1. Oxford University Press, Oxford.
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I. Shumailov and H. Gunes. 2017. Computational analysis of valence and arousal in virtual reality gaming using lower arm electromyograms. In 2017 Seventh International Conference on Affective Computing and Intelligent Interaction (ACII). 164–169.
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Vera Shuman, Katja Schlegel, and Klaus Scherer. 2015. Geneva Emotion Wheel Rating Study.
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R. Subramanian, J. Wache, M. K. Abadi, R. L. Vieriu, S. Winkler, and N. Sebe. 2018. ASCERTAIN: Emotion and Personality Recognition Using Commercial Sensors. IEEE Transactions on Affective Computing 9, 2 (2018), 147–160.

Cited By

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  • (2024)EmoStim: A Database of Emotional Film Clips With Discrete and Componential AssessmentIEEE Transactions on Affective Computing10.1109/TAFFC.2023.332890015:3(1202-1212)Online publication date: Jul-2024
  • (2023)Brain-Metaverse Interaction for Anxiety Regulation2023 9th International Conference on Virtual Reality (ICVR)10.1109/ICVR57957.2023.10169785(385-392)Online publication date: 12-May-2023
  • (2022)An Exploratory Analysis of Interactive VR-Based Framework for Multi-Componential Analysis of Emotion2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops53856.2022.9767281(353-358)Online publication date: 21-Mar-2022

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Published In

cover image ACM Conferences
VRST '21: Proceedings of the 27th ACM Symposium on Virtual Reality Software and Technology
December 2021
563 pages
ISBN:9781450390927
DOI:10.1145/3489849
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 December 2021

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Author Tags

  1. Component Process Model
  2. Data-driven methods
  3. Emotion-recognition
  4. Virtual Reality

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  • Refereed limited

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VRST '21

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Overall Acceptance Rate 66 of 254 submissions, 26%

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Cited By

View all
  • (2024)EmoStim: A Database of Emotional Film Clips With Discrete and Componential AssessmentIEEE Transactions on Affective Computing10.1109/TAFFC.2023.332890015:3(1202-1212)Online publication date: Jul-2024
  • (2023)Brain-Metaverse Interaction for Anxiety Regulation2023 9th International Conference on Virtual Reality (ICVR)10.1109/ICVR57957.2023.10169785(385-392)Online publication date: 12-May-2023
  • (2022)An Exploratory Analysis of Interactive VR-Based Framework for Multi-Componential Analysis of Emotion2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops53856.2022.9767281(353-358)Online publication date: 21-Mar-2022

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