Race Yourselves: A Longitudinal Exploration of Self-Competition Between Past, Present, and Future Performances in a VR Exergame
- Submitting institution
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The University of Bath
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 210639182
- Type
- E - Conference contribution
- DOI
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10.1145/3313831.3376256
- Title of conference / published proceedings
- Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
- First page
- 1
- Volume
- -
- Issue
- -
- ISSN
- 1062-9432
- Open access status
- Compliant
- Month of publication
- April
- Year of publication
- 2020
- URL
-
-
- Supplementary information
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https://dl.acm.org/action/downloadSupplement?doi=10.1145%2F3313831.3376256&file=paper129pv.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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1
- Research group(s)
-
-
- 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 describes a novel VR training technique enabling users to achieve much higher physical performance improvements than in traditional high-intensity training. The publication was picked up by the press and featured in at least 12 news outlets, including ACM TechNews, Science X, Medical News Bulletin, News Break, Newslocker.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -