Measurement of Upper Limb Range of Motion Using Wearable Sensors: A Systematic Review
Open accessAbstract
BACKGROUND: Wearable sensors are portable measurement tools that are becoming increasingly popular for the measurement of joint angle in the upper limb. With many brands emerging on the market, each with variations in hardware and protocols, evidence to inform selection and application is needed. Therefore, the objectives of this review were related to the use of wearable sensors to calculate upper limb joint angle. We aimed to describe (i) the characteristics of commercial and custom wearable sensors, (ii) the populations for whom researchers have adopted wearable sensors, and (iii) their established psychometric properties. METHODS: A systematic review of literature was undertaken using the following data bases: MEDLINE, EMBASE, CINAHL, Web of Science, SPORTDiscus, IEEE, and Scopus. Studies were eligible if they met the following criteria: (i) involved humans and/or robotic devices, (ii) involved the application or simulation of wearable sensors on the upper limb, and (iii) calculated a joint angle. RESULTS: Of 2191 records identified, 66 met the inclusion criteria. Eight studies compared wearable sensors to a robotic device and 22 studies compared to a motion analysis system. Commercial (n = 13) and custom (n = 7) wearable sensors were identified, each with variations in placement, calibration methods, and fusion algorithms, which were demonstrated to influence accuracy. CONCLUSION: Wearable sensors have potential as viable instruments for measurement of joint angle in the upper limb during active movement. Currently, customised application (i.e. calibration and angle calculation methods) is required to achieve sufficient accuracy (error < 5°). Additional research and standardisation is required to guide clinical application. TRIAL REGISTRATION: This systematic review was registered with PROSPERO ( CRD42017059935 ).
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Two systematic reviews have been conducted on the psychometric evidence relating to M/IMU validity.
“Two systematic reviews have been conducted to report on the psychometric evidence relating to M/IMU validity [11,12].”
From Validity and Reliability of Wearable Sensors for Joint Angle Estimation: A Systematic Review (2019) · cites this paper as [11]
Walmsley et al.'s results for the upper limbs are in agreement with those presented in this review.
“Their results for the upper limbs are in agreement with those presented here.”
From Validity and Reliability of Wearable Sensors for Joint Angle Estimation: A Systematic Review (2019) · cites this paper as [11]
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Kim, M., & Park, S. (2024) · Scientific Reports · doi:10.1038/s41598-024-59949-w · Cited by 14 · see citing works
- Authors
- Walmsley, C. P., Williams, S. A., Grisbrook, T., Elliott, C., Imms, C., & Campbell, A.
- Affiliations
- Curtin University (AU)
- University of Auckland (NZ)
- Australian Catholic University (AU)
- Corresponding author
- Imms, Christine
- ORCID
- Venue
- Sports Medicine - Open
- Published
- 2018-11-29
- Volume
- 4
- Issue
- 1
- Pages
- 53-53
- ISSN
- 2198-9761 (ISSN-L)
- 2199-1170
- PMC
- PMC6265374
- OpenAlex
- W2902349279
- Cited by
- 123
- References
- 94
- Citations by year
- 2026: 10 · 2025: 19 · 2024: 17 · 2023: 17 · 2022: 19 · 2021: 16 · 2020: 16 · 2019: 8 · 2018: 1
- FWCI
- 1.20
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sports Medicine - Open (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Bank (Australian Catholic University) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- eSpace (Curtin University) (submittedVersion, cc-by)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- ResearchSpace (University of Auckland) (submittedVersion, cc-by)
- Funders
- Australian Government Research Training Program Scholarship
- Perth Children's Hospital Foundation
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Health Sciences › Medicine › Rehabilitation › Musculoskeletal Disorders and Rehabilitation
- Physical Sciences › Engineering › Biomedical Engineering › Muscle activation and electromyography studies
- Keywords
- wearable sensors, upper limb range of motion, joint angle measurement, sensor calibration, sensor fusion algorithms, psychometric properties, measurement accuracy
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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