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Accuracy and Reliability of Wearable Devices, Image Analysis Software, and Smartphone Apps for Hand Goniometry: A
Sundeep Chakladar1, Cole I Davis1, Eshan S Sane1
1Washington University School of Medicine in St. Louis, MO, USA.
Hand (New York, N.Y.)
|April 7, 2026
Summary
No single hand range of motion measurement device excels in accuracy, reliability, and telehealth. Wearable devices offer high accuracy, while apps and image systems provide better reliability and telehealth integration for remote patient monitoring.
Area of Science:
- Biomedical Engineering
- Rehabilitation Technology
- Digital Health
Background:
- Accurate hand range of motion (ROM) measurement is crucial for diagnosing and managing conditions.
- Existing technologies like wearable devices, image analysis systems, and smartphone apps aim to improve hand ROM assessment.
- Previous evaluations have focused on individual device performance, lacking comparative analysis across device types.
Purpose of the Study:
- To compare the accuracy, reliability, and telehealth applicability of different hand goniometry device classes.
- To identify the strengths and weaknesses of wearable devices, image analysis systems, and smartphone apps for hand ROM measurement.
- To inform the development of superior hand ROM assessment technologies.
Main Methods:
- Systematic literature search of PubMed, Embase, Scopus, and CINAHL databases.
- Inclusion of studies evaluating hand goniometry technologies directly compared against manual goniometry.
- Analysis of 13 studies encompassing 2 wearable devices, 7 image analysis systems, and 4 smartphone apps.
Main Results:
- Wearable devices demonstrated the highest accuracy (mean difference [MD] < 1°), but had lower telehealth integration scores (TIS = 38/50).
- Image analysis systems showed high reliability (interclass correlation coefficient [ICC] > 0.67) and telehealth usability (TIS = 42), but lower accuracy (MD 1°-35°).
- Smartphone apps exhibited high reliability (ICC > 0.83) but also low accuracy (MD 1°-12°).
Conclusions:
- No single class of hand goniometry devices outperforms others across all evaluated metrics (accuracy, reliability, telehealth).
- Each device class presents a unique profile of strengths and limitations for hand ROM assessment.
- Future research should aim to integrate the advantages of different device types to create comprehensive and effective hand ROM measurement solutions.
