BodyLights: Open-Ended Augmented Feedback to Support Training Towards a Correct Exercise Execution

要旨

Technologies targeting a correct execution of physical training exercises typically use pre-determined models for what they consider correct, automatizing instruction and feedback. This falls short on catering to diverse trainees and exercises. We explore an alternative design approach, in which technology provides open-ended feedback for trainers and trainees to use during training. With a personal trainer we designed the augmentation of 18 strength training exercises with BodyLights: 3D printed wearable projecting lights that augment body movement and orientation. To study them, 15 trainees at different skill levels trained three times with our personal trainer and BodyLights. Our findings show that BodyLights catered to a wide range of trainees and exercises, and supported understanding, executing and correcting diverse technique parameters. We discuss design features and methodological aspects that allowed this; and what open-ended feedback offered in comparison to current technology approaches to support training towards a correct exercise execution.

キーワード
Wearables
Physical Training
Strength Training
Correct Performance
Augmented Feedback
Activity Design
RtD
著者
Laia Turmo Vidal
Uppsala University, Uppsala, Sweden
Hui Zhu
Uppsala University, Uppsala, Sweden
Abraham Riego-Delgado
Uppsala University, Uppsala, Sweden
DOI

10.1145/3313831.3376268

論文URL

https://doi.org/10.1145/3313831.3376268

会議: CHI 2020

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2020.acm.org/)

セッション: Designing for health

Paper session
313C O'AHU
5 件の発表
2020-04-29 23:00:00
2020-04-30 00:15:00
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