Abstract

We present a novel framework and system for at-home rehabilitative exercise in the absence of a physical therapist. The framework includes metrics for assessing motor performance on a wide variety of exercises. We present our system, the Autonomous Training Assistant, which utilizes this framework and a low-cost accessible exercise device called the Intelligent Stick to deliver feedback as a user trains at home. We evaluated the system's multimodal feedback mechanism in a case study whose results indicate that individual preference may have a significant effect on modality assignment for optimal learning. We conclude with ideas for future work.

Original languageEnglish (US)
Title of host publicationASSETS 2016 - Proceedings of the 18th International ACM SIGACCESS Conference on Computers and Accessibility
PublisherAssociation for Computing Machinery, Inc
Pages293-294
Number of pages2
ISBN (Electronic)9781450341240
DOIs
StatePublished - Oct 23 2016
Event18th International ACM SIGACCESS Conference on Computers and Accessibility, ASSETS 2016 - Reno, United States
Duration: Oct 24 2016Oct 26 2016

Publication series

NameASSETS 2016 - Proceedings of the 18th International ACM SIGACCESS Conference on Computers and Accessibility

Other

Other18th International ACM SIGACCESS Conference on Computers and Accessibility, ASSETS 2016
CountryUnited States
CityReno
Period10/24/1610/26/16

Keywords

  • At-home training
  • Human-computer interaction
  • Motor learning
  • Rehabilitation

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Human-Computer Interaction
  • Hardware and Architecture
  • Software

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