Weight-Mate: Adaptive Training Support for Weight Lifting

Jeniece Michelle Paay*, Jesper Kjeldskov, Frederik Sørensen, Thomas Guldborg Jensen, Oren Tirosh

*Corresponding author for this work

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

2 Citations (Scopus)
226 Downloads (Pure)

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 2019
Number of pages11
PublisherAssociation for Computing Machinery
Publication date2 Dec 2019
Pages95-105
ISBN (Electronic)9781450376969
DOIs
Publication statusPublished - 2 Dec 2019
Event31th Australian Conference on Computer-Human Interaction - Perth/Fremantle, Western Australia, Australia, Perth/Fremantle, Australia
Duration: 3 Dec 20195 Dec 2019
Conference number: 31
http://ozchi2019.visemex.org/wp/

Conference

Conference31th Australian Conference on Computer-Human Interaction
Number31
LocationPerth/Fremantle, Western Australia, Australia
Country/TerritoryAustralia
CityPerth/Fremantle
Period03/12/201905/12/2019
Internet address

Keywords

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

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