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Updated: Sep 19, 2025
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Published on: August 8, 2019
Using wearable technology to measure adherence to intervention for upper extremity musculoskeletal conditions: A
Wan Ling Ng1, Sonya S Corea1, Marie Ansha Cruz1
1Department of Nursing & Allied Health, School of Health Sciences, Swinburne University of Technology, Hawthorn, VIC, Australia.
Background:
Measures of adherence usually rely on patient self-report, however, objective methods, such as the use of sensors and wearable devices are a growing area in enhancing personalized care and patient engagement in upper limb musculoskeletal intervention.
Purpose:
To identify and summarize evidence on the use of sensors and wearable devices to help us understand adherence to interventions in adults with upper extremity musculoskeletal pathology.
Study Design:
Scoping review.
Methods:
Database (CINAHL, Ovid MEDLINE, and Web of Science) and supplementary searches were conducted. Eighteen studies were included following title and abstract screening and full-text review. Studies were included into the final review if they (1) involved musculoskeletal conditions affecting the upper extremity; (2) incorporated the use of sensors and wearable devices; (3) included adult participants; and (4) provide insights into treatment adherence. Data from these studies were then extracted, analyzed, and synthesized as per the review aim.
Results:
Included papers were published between the years 1985 and 2024, with 12 focusing on shoulder pathology, three on flexor tendon injuries, two on distal radius fractures and one on wrist injuries. Sensors were primarily used for monitoring device wear time and adherence to exercise interventions.
Conclusions:
This scoping review maps the relevant literature on how sensors and wearable devices help us understand adherence to interventions for upper extremity musculoskeletal conditions. Findings highlight the value in using standardized tools for measuring and monitoring adherence to provide more consistent data for application in both research and clinical settings.
