Inertial measurement systems for segments and joints kinematics assessment: towards an understanding of the variations in sensors accuracy
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BACKGROUND: Joints kinematics assessment based on inertial measurement systems, which include attitude and heading reference system (AHRS), are quickly gaining in popularity for research and clinical applications. The variety of the tasks and contexts they are used in require a deep understanding of the AHRS accuracy for optimal data interpretation. However, published accuracy studies on AHRS are mostly limited to a single task measured on a limited number of segments and participants. This study assessed AHRS sensors kinematics accuracy at multiple segments and joints through a variety of tasks not only to characterize the system's accuracy in these specific conditions, but also to extrapolate the accuracy results to a broader range of conditions using the characteristics of the movements (i.e. velocity and type of motion). Twenty asymptomatic adults ([Formula: see text] = 49.9) performed multiple 5 m timed up and go. Participants' head, upper trunk, pelvis, thigh, shank and foot were simultaneously tracked using AHRS and an optical motion capture system (gold standard). Each trial was segmented into basic tasks (sit-to-stand, walk, turn). RESULTS: At segment level, results revealed a mean root-mean-squared-difference [Formula: see text] varying between 1.1° and 5.5° according to the segment tracked and the task performed, with a good to excellent agreement between the systems. Relative sensor kinematics accuracy (i.e. joint) varied between 1.6° and 13.6° over the same tasks. On a global scheme, analysis of the effect of velocity on sensor kinematics accuracy showed that AHRS are better adapted to motions performed between 50°/s and 75°/s (roughly thigh and shank while walking). CONCLUSION: Results confirmed that pairing of modules to obtain joint kinematics affects the accuracy compared to segment kinematics. Overall, AHRS are a suitable solution for clinical evaluation of biomechanics under the multi-segment tasks performed although the variation in accuracy should be taken into consideration when judging the clinical meaningfulness of the observed changes.
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Ankle RMSE and correlation coefficients varied from 0.4 to 18.8° and 0.33 to 0.99.
“RMSE and correlation coefficients varied respectively from 0.4 to 18.8° and 0.33 to 0.99 [29,37,41,43,53,54,55,57,59,62,63].”
From Validity and Reliability of Wearable Sensors for Joint Angle Estimation: A Systematic Review (2019) · cites this paper as [41]
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- Authors
- Lebel, K., Boissy, P., Nguyen, H., & Duval, C.
- Affiliations
- Université de Sherbrooke (CA)
- Université du Québec à Montréal (CA)
- Corresponding author
- Boissy, Patrick
- Venue
- BioMedical Engineering OnLine
- Published
- 2017-05-15
- Volume
- 16
- Issue
- 1
- Pages
- 56-56
- ISSN
- 1475-925X (ISSN-L)
- PMC
- PMC5433074
- OpenAlex
- W2614348207
- Cited by
- 65
- References
- 49
- Citations by year
- 2026: 7 · 2025: 2 · 2024: 6 · 2023: 9 · 2022: 2 · 2021: 8 · 2020: 14 · 2019: 11 · 2018: 5 · 2017: 1
- FWCI
- 7.80
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- BioMedical Engineering OnLine (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Institute of Aging
- Canadian Institutes of Health Research
- Fonds de Recherche du Québec - Santé
- Topics
- Physical Sciences › Engineering › Aerospace Engineering › Inertial Sensor and Navigation
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Health Sciences › Health Professions › Physical Therapy, Sports Therapy and Rehabilitation › Balance, Gait, and Falls Prevention
- Keywords
- inertial measurement unit, attitude and heading reference system, joint kinematics, sensor accuracy, Timed Up and Go test, sit-to-stand, gait, movement speed, optical motion capture, wearable sensors
- MeSH terms
- Acceleration, Aged, Algorithms, Computer Simulation, Equipment Design, Female, Humans, Joints, Male, Models, Biological, Sensitivity and Specificity, Reproducibility of Results, Range of Motion, Articular, Equipment Failure Analysis, Actigraphy, Accelerometry
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