Accuracy and Reliability of Wearable Devices, Image Analysis Software, and Smartphone Apps for Hand Goniometry: A Systematic Review

) but had low telehealth integration scores (TIS = 38 out of 50). Image analysis systems had high reliability (interclass correlation coefficient [ICC] > .67) and telehealth usability (TIS = 42) but lacked accuracy (MD 1°-35°). Similarly, smartphone apps had low accuracy (MD 1°-12°) but high reliability (ICC > 0.83). No single device class outperforms others across all metrics. Future studies should focus on creating technologies that combine the strengths of multiple device classes.

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Publication Details

Journal
Hand
Published
2026-04-06
DOI
https://doi.org/10.1177/15589447261433064
Primary Topic
Body Composition Measurement Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Accuracy and Reliability of Wearable Devices, Image Analysis Software, and Smartphone Apps for Hand Goniometry: A Systematic Review

Christopher J. Dy, Eshan Sane, David M. Brogan, Sundeep Chakladar et al.
Hand
Body Composition Measurement Techniques
article

Accuracy and Reliability of Wearable Devices, Image Analysis Software, and Smartphone Apps for Hand Goniometry: A Systematic Review

Christopher J. Dy, Eshan Sane, David M. Brogan, Sundeep Chakladar, Cole I. Davis
article en

Abstract

) but had low telehealth integration scores (TIS = 38 out of 50). Image analysis systems had high reliability (interclass correlation coefficient [ICC] > .67) and telehealth usability (TIS = 42) but lacked accuracy (MD 1°-35°). Similarly, smartphone apps had low accuracy (MD 1°-12°) but high reliability (ICC > 0.83). No single device class outperforms others across all metrics. Future studies should focus on creating technologies that combine the strengths of multiple device classes.

Hand
Washington University in St. Louis (US)
National Institute of Arthritis and Musculoskeletal and Skin Diseases
Openalex Percentile: Top 26%
Body Composition Measurement Techniques
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