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Performance Monitoring for Exercise Movements using Mobile Cameras

  • Old Dominion University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Scopus citations

Abstract

Despite numerous devices targeted to fitness tracking, the strength training domain has often been overlooked and understudied. In this paper, we propose a smartphone camera based approach to track users' strength training workouts, as well as metrics pertaining to their form and performance. Our goal is to detect the repetitions in a workout without requiring user intervention or any training data from the user. Unlike many existing systems, our proposed system is scalable, low-cost, and widely accessible. We gather data from two sources for 5 exercises across 25 subjects. We compute performance metrics such as range of motion, velocity, and duration from each repetition with median errors less than 10%. These results demonstrate that commercial off the shelf smartphone cameras can be used to accurately detect and count repetitions in user movements, as well as to compute rep-by-rep user performance.

Original languageEnglish
Title of host publicationBodySys 2021 - Proceedings of the 2021 ACM Workshop on Body Centric Computing Systems
PublisherAssociation for Computing Machinery, Inc
Pages1-6
Number of pages6
ISBN (Electronic)9781450386005
DOIs
StatePublished - Jun 29 2021
Event2021 ACM Workshop on Body Centric Computing Systems, BodySys 2021 - Virtual, Online, United States
Duration: Jun 24 2021 → …

Publication series

NameBodySys 2021 - Proceedings of the 2021 ACM Workshop on Body Centric Computing Systems

Conference

Conference2021 ACM Workshop on Body Centric Computing Systems, BodySys 2021
Country/TerritoryUnited States
CityVirtual, Online
Period06/24/21 → …

Keywords

  • Early event detection
  • Fitness monitoring
  • Mobile camera

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