Projects per year
Abstract
Exergames commonly use low to moderate intensity exercise protocols. Their effectiveness in implementing high intensity protocols remains uncertain. We propose a method for improving performance while maintaining intrinsic motivation in high intensity VR exergaming. Our method is based on an interactive adaptation of the feedforward method: a psychophysical training technique achieving rapid improvement in performance by exposing participants to self models showing previously unachieved performance levels. We evaluated our method in a cycling-based exergame. Participants competed against (i) a self model which represented their previous speed; (ii) a self model representing their previous speed but increased resistance therefore requiring higher performance to keep up; or (iii) a virtual competitor at the same two levels of performance. We varied participants’ awareness of these differences. Interactivefeedforwardledtoimprovedperformance while maintaining intrinsic motivation even when participants wereawareoftheinterventions,andwassuperiortocompeting against a virtual competitor.
Original language | English |
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Title of host publication | Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems |
Place of Publication | New York, U. S. A. |
Publisher | Association for Computing Machinery |
Pages | 1-14 |
Number of pages | 14 |
Volume | 2018-April |
ISBN (Electronic) | 9781450356206, 9781450356213 |
ISBN (Print) | 9781450356206 |
DOIs | |
Publication status | Published - 21 Apr 2018 |
Publication series
Name | CHI: Conference on Human Factors and Computing Systems |
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Publisher | ACM Press |
ISSN (Electronic) | 1062-9432 |
Keywords
- Exergame
- Feedforward
- Intrinsic motivation
- Performance
- Virtual reality (VR)
ASJC Scopus subject areas
- Human-Computer Interaction
- Computer Graphics and Computer-Aided Design
- Software
Projects
- 1 Active
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Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA)
Cosker, D., Campbell, N., Fincham Haines, T., Hall, P., Kim, K. I., Lutteroth, C., O'Neill, E., Richardt, C. & Yang, Y.
Engineering and Physical Sciences Research Council
1/09/15 → 28/02/21
Project: Research council
Profiles
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Eamonn O'Neill
- Department of Computer Science - Professor
- UKRI CDT in Accountable, Responsible and Transparent AI
- Centre for the Analysis of Motion, Entertainment Research & Applications
- Centre for Networks and Collective Behaviour
- Centre for Autonomous Robotics (CENTAUR)
- EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa)
- Centre for Doctoral Training in Decarbonisation of the Built Environment (dCarb)
- REal and Virtual Environments Augmentation Labs (REVEAL)
Person: Research & Teaching