Affect Recognition using Psychophysiological Correlates in High Intensity VR Exergaming
- Submitting institution
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The University of Bath
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 204276075
- Type
- E - Conference contribution
- DOI
-
10.1145/3313831.3376596
- Title of conference / published proceedings
- CHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
- First page
- 1
- Volume
- -
- Issue
- -
- ISSN
- -
- Open access status
- -
- Month of publication
- April
- Year of publication
- 2020
- URL
-
-
- Supplementary information
-
https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3313831.3376596&file=paper469vf.mp4&download=true
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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3
- Research group(s)
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-
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- CHI is the top Human-Computer Interaction conference. The paper received top reviewer scores and a CHI best paper award. It shows, for the first time, that fit-looking avatars can have a negative effect on the performance of VR users. The paper was featured by by at least 26 news outlets, including ScienceDaily, Business Standard, Sciences et Avenir, EurekAlert!, ScienceNode and ACM TechNews, with total reach of more than 6.4M readers.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -