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Weight-Mate: Adaptive training support for weight lifting

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

Abstract

Weightlifting is easy to learn, but difficult to master. People who do weightlifting do it to improve their health, strengthen their muscles and build their physique. However, due to the complex and precise body positioning required, even experienced weightlifters require assistance in perfecting their technique. At the same time, the training requirements of the individual change over time, as they perfect and hone their craft. To help weightlifters achieve optimum personal performance, we designed Weight-Mate, a prototype wearable system for giving weightlifters of different skill levels personalized, precise and non-distracting immediate feedback on how to correct their current body positioning during deadlift training. By iterating Weight-Mate using cooperative usability testing (CUT) with weightlifters of different competencies with their coaches we designed a system that could adapt to individual physiology and training needs. The Weight-Mate sensor suit maps the lifter's body configuration against the ideal deadlift position throughout all stages of the life, as defined by their coach, and provides nonintrusive feedback to the lifter to correct their body position. Our formative evaluation with ten weightlifters shows that an adaptive approach to digital weight training offers great promise in assisting weight lifters of all levels to improve their technique, and hence improve the safety of the sport.

Original languageEnglish
Title of host publicationProceedings of the 31st Australian Conference on Human-Computer-Interaction (OzCHI'19)
EditorsJared Donovan, Simon Perrault
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages95-105
Number of pages11
ISBN (Electronic)9781450376969
DOIs
Publication statusPublished - 2019
Externally publishedYes
EventAustralian Computer Human Interaction Conference 2019 - Esplanade Hotel Fremantle, Fremantle, Australia
Duration: 2 Dec 20195 Dec 2019
Conference number: 31st
http://ozchi2019.visemex.org/wp/
https://dl.acm.org/doi/proceedings/10.1145/3369457 (Proceedings)

Conference

ConferenceAustralian Computer Human Interaction Conference 2019
Abbreviated titleOZCHI 2019
Country/TerritoryAustralia
CityFremantle
Period2/12/195/12/19
Internet address

Keywords

  • Adaptive systems
  • Assistive training technologies
  • IMU sensors
  • Interaction design
  • User feedback.
  • Wearables
  • Weightlifting

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