Affect Recognition using Psychophysiological Correlates in High Intensity VR Exergaming

Soumya C. Barathi; Michael Proulx; Eamonn O'Neill; Christof Lutteroth

doi:10.1145/3313831.3376596

Affect Recognition using Psychophysiological Correlates in High Intensity VR Exergaming

Soumya C. Barathi, Michael Proulx, Eamonn O'Neill, Christof Lutteroth

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

15 Citations (SciVal)

550 Downloads (Pure)

Abstract

User experience estimation of VR exergame players by recognising their affective state could enable us to personalise and optimise their experience. Affect recognition based on psychophysiological measurements has been successful for moderate intensity activities. High intensity VR exergames pose challenges as the effects of exercise and VR headsets interfere with those measurements. We present two experiments that investigate the use of different sensors for affect recognition in a VR exergame. The first experiment compares the impact of physical exertion and gamification on psychophysiological measurements during rest, conventional exercise, VR exergaming, and sedentary VR gaming. The second experiment compares underwhelming, overwhelming and optimal VR exergaming scenarios. We identify gaze fixations, eye blinks, pupil diameter and skin conductivity as psychophysiological measures suitable for affect recognition in VR exergaming and analyse their utility in determining affective valence and arousal. Our findings provide guidelines for researchers of affective VR exergames.

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 665992

Original language	English
Title of host publication	CHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
Place of Publication	New York, U.S.A.
Publisher	Association for Computing Machinery
Pages	1-15
Number of pages	15
Volume	2020-April
ISBN (Electronic)	9781450367080
DOIs	https://doi.org/10.1145/3313831.3376596
Publication status	Published - 21 Apr 2020

Publication series

Name	Conference on Human Factors in Computing Systems - Proceedings

Keywords

VR exergaming
affect recognition
high intensity exercise
psychophysiological correlates

ASJC Scopus subject areas

Computer Graphics and Computer-Aided Design
Human-Computer Interaction
Software

Access to Document

10.1145/3313831.3376596

AffectRecognitionInVRExergaming-CHI2020 Updated.pdf
© ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in http://doi.acm.org/10.1145/3313831.3376596
Accepted author manuscript, 285 KB

Cite this

Barathi, S. C., Proulx, M., O'Neill, E., & Lutteroth, C. (2020). Affect Recognition using Psychophysiological Correlates in High Intensity VR Exergaming. In CHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (Vol. 2020-April, pp. 1-15). (Conference on Human Factors in Computing Systems - Proceedings). Association for Computing Machinery. https://doi.org/10.1145/3313831.3376596

Affect Recognition using Psychophysiological Correlates in High Intensity VR Exergaming. / Barathi, Soumya C.; Proulx, Michael ; O'Neill, Eamonn et al.
CHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. Vol. 2020-April New York, U.S.A.: Association for Computing Machinery, 2020. p. 1-15 (Conference on Human Factors in Computing Systems - Proceedings).

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

Barathi, SC, Proulx, M , O'Neill, E & Lutteroth, C 2020, Affect Recognition using Psychophysiological Correlates in High Intensity VR Exergaming. in CHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. vol. 2020-April, Conference on Human Factors in Computing Systems - Proceedings, Association for Computing Machinery, New York, U.S.A., pp. 1-15. https://doi.org/10.1145/3313831.3376596

Barathi SC, Proulx M , O'Neill E , Lutteroth C. Affect Recognition using Psychophysiological Correlates in High Intensity VR Exergaming. In CHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. Vol. 2020-April. New York, U.S.A.: Association for Computing Machinery. 2020. p. 1-15. (Conference on Human Factors in Computing Systems - Proceedings). doi: 10.1145/3313831.3376596

Barathi, Soumya C. ; Proulx, Michael ; O'Neill, Eamonn et al. / Affect Recognition using Psychophysiological Correlates in High Intensity VR Exergaming. CHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. Vol. 2020-April New York, U.S.A. : Association for Computing Machinery, 2020. pp. 1-15 (Conference on Human Factors in Computing Systems - Proceedings).

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Affect Recognition using Psychophysiological Correlates in High Intensity VR Exergaming

Abstract

Publication series

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA) - 2.0

Fellow for Industrial Research Enhancement (FIRE)

Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA)

Christof Lutteroth

Eamonn O'Neill

Datasets and Analyses for "Affect Recognition using Psychophysiological Correlates in High Intensity VR Exergaming"

Cite this

Affect Recognition using Psychophysiological Correlates in High Intensity VR Exergaming

Abstract

Publication series

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Projects

Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA) - 2.0

Fellow for Industrial Research Enhancement (FIRE)

Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA)

Profiles

Christof Lutteroth

Eamonn O'Neill

Datasets

Datasets and Analyses for "Affect Recognition using Psychophysiological Correlates in High Intensity VR Exergaming"

Cite this