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How Should Robots Exercise with People? Robot-Mediated Exergames Win with Music, Social Analogues, and Gameplay Clarity

2024

Article

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The modern worldwide trend toward sedentary behavior comes with significant health risks. An accompanying wave of health technologies has tried to encourage physical activity, but these approaches often yield limited use and retention. Due to their unique ability to serve as both a health-promoting technology and a social peer, we propose robots as a game-changing solution for encouraging physical activity. This article analyzes the eight exergames we previously created for the Rethink Baxter Research Robot in terms of four key components that are grounded in the video-game literature: repetition, pattern matching, music, and social design. We use these four game facets to assess gameplay data from 40 adult users who each experienced the games in balanced random order. In agreement with prior research, our results show that relevant musical cultural references, recognizable social analogues, and gameplay clarity are good strategies for taking an otherwise highly repetitive physical activity and making it engaging and popular among users. Others who study socially assistive robots and rehabilitation robotics can benefit from this work by considering the presented design attributes to generate future hypotheses and by using our eight open-source games to pursue follow-up work on social-physical exercise with robots.

Author(s): Naomi T. Fitter and Mayumi Mohan and Rhian C. Preston and Michelle J. Johnson and Katherine J. Kuchenbecker
Journal: Frontiers in Robotics and AI
Volume: 10
Number (issue): 1155837
Pages: 1--18
Year: 2024
Month: January

Department(s): Haptic Intelligence
Research Project(s): Exercise Games with Baxter
Bibtex Type: Article (article)
Paper Type: Journal

DOI: 10.3389/frobt.2023.1155837
State: Published

BibTex

@article{Fitter24-FRAI-Exercise,
  title = {How Should Robots Exercise with People? {R}obot-Mediated Exergames Win with Music, Social Analogues, and Gameplay Clarity},
  author = {Fitter, Naomi T. and Mohan, Mayumi and Preston, Rhian C. and Johnson, Michelle J. and Kuchenbecker, Katherine J.},
  journal = {Frontiers in Robotics and AI},
  volume = {10},
  number = {1155837},
  pages = {1--18},
  month = jan,
  year = {2024},
  doi = {10.3389/frobt.2023.1155837},
  month_numeric = {1}
}