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The use of inertial sensors system for human motion analysis
Open accessAbstract
OBJECTIVE: The aim of this article is to review systematically and appraise critically the literature surrounding the research, comparing inertial sensors with any kind of gold standard; this gold standard has to be a tool for measuring human movement (e.g. electrogoniometry, optoelectronic systems, electromagnetic systems, etc.). METHOD: A MEDLINE, EMBASE, CINAHL, PEDRo and SCOPUS search of published English language articles was conducted, which focused on articles that compared inertial sensors to any kind of gold standard (e.g. electrogoniometry, optoelectronic systems, electromagnetic systems, etc.), from 2000 to 2010. Two independent reviewers completed the study selection, quality appraisal and data extraction. The Critical Appraisal Skills Programme Español tool was used to assess study quality, and a reliability comparison between the systems was made. RESULTS: Fourteen out of 242 articles were reviewed, which displayed a similar threat to validity, relating to sample selection and operator blinding. Other study limitations are discussed. A comparison between the different systems showed good agreement across a range of tasks and anatomical regions. CONCLUSIONS: This review concludes that inertial sensors can offer an accurate and reliable method to study human motion, but the degree of accuracy and reliability is site and task specific.
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“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 [12]
In the citing paper
“The other systematic review, published in 2018, focused only on the upper limb and provided only scarce details regarding the complexity of the tasks evaluated, a problem highlighted by the first systematic review as being one of the most challenging aspects for clinical evaluation.”
From Validity and Reliability of Wearable Sensors for Joint Angle Estimation: A Systematic Review (2019) · cites this paper as [12]
In the citing paper
“This is opposite to our results.”
From Validity and Reliability of Wearable Sensors for Joint Angle Estimation: A Systematic Review (2019) · cites this paper as [12]
In the citing paper
“The increasing number of studies in recent years that used complex movements to assess M/IMU validity and the focus made on the upper limb joint partially explain the different conclusions between these two systematic reviews and the present work [12].”
From Validity and Reliability of Wearable Sensors for Joint Angle Estimation: A Systematic Review (2019) · cites this paper as [12]
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Akins, J. S. (2013) · D-Scholarship@Pitt (University of Pittsburgh) · Cited by 1
Ho, S. F., Thomson, A., & Kerr, A. (2016) · International Conference for Students on Applied Engineering (ICSAE) · doi:10.1109/icsae.2016.7810233 · Cited by 1
Hollander, K., Hoenig, T., & Édouard, P. (2022) · Springer eBooks · doi:10.1007/978-3-662-65064-6_1 · Cited by 1
A Case Study in Upper Body Kinematics of an Elite Axe Thrower Using Sensor Technology
Evans, S., & Bini, R. R. (2023) · Research Directs in Strength and Performance · doi:10.53520/rdsp2023.10558 · Cited by 1
Head and Trunk Rotation in Roll during Turning in Agility Dogs
Higurashi, Y., Hattori, Y., & Wada, N. (2024) · Mammal Study · doi:10.3106/ms2023-0021 · Cited by 1
Donati, D., Nasuti, M., Marcovigi, A., Costantini, R. C., Tedeschi, R., Ricci, V., MANTOVANI, M., Farì, G., Benedetti, M. G., Tarallo, L., et al. (2025) · Minerva Orthopedics · doi:10.23736/s2784-8469.25.04495-5 · Cited by 1
González‐Sánchez, M., Cuesta‐Vargas, A., González, M. D. M. R., Díaz, E. A., Núñez, G. O., Galán-Mercant, A., & Belmonte, J. J. B. (2019) · BMC Geriatrics · doi:10.1186/s12877-019-1188-x · Cited by 1
Self-citationJair Burboa, G., Inostroza-Mondaca, M., Matías Bahamondes, F., Paloma Lillo, U., & Hinzpeter, J. (2019) · Journal of Sports and Exercise Medicine · doi:10.14302/issn.2694-2283.jsem-19-2938 · Cited by 1
Ward, rehabilitation, and clinic-based wearable devices
Parrington, L., Wilhelm, J., Pettigrew, N. C., Scanlan, K. T., & King, L. A. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-818914-6.00004-1 · Cited by 1
Validation study of low-cost sensors
Nandy, A., Chakraborty, S., Chakraborty, J., & Venture, G. (2021) · Elsevier eBooks · doi:10.1016/b978-0-323-85245-6.00005-9 · Cited by 1
Gait Biomechanics of Older Adults in Outdoor and Simulated Environments: A Scoping Review
Jendro, A. M., Talley, M. A., Gallagher, K. M., & Schmitt, A. C. (2025) · Journal of Aging and Physical Activity · doi:10.1123/japa.2024-0192 · Cited by 1
Roldán‐Jiménez, C., Martín‐Martín, J., Bennett, P. J., McPhail, S., Cuesta‐Vargas, A., & Kerr, G. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/398123 · Cited by 1
Self-citationRekant, J., & Chambers, A. J. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4002945 · Cited by 1
Metadata
- Authors
- Cuesta-Vargas, A. I., Galán-Mercant, A., & Williams, J. M.
- Affiliations
- Universidad de Málaga (ES)
- University of Roehampton (GB)
- Venue
- Physical Therapy Reviews
- Publisher
- Informa UK Limited
- Published
- 2010-12
- Volume
- 15
- Issue
- 6
- Pages
- 462-473
- ISSN
- 1083-3196 (ISSN-L)
- 1743-288X
- PMC
- PMC3566464
- OpenAlex
- W1994978432
- Cited by
- 369
- References
- 41
- Citations by year
- 2026: 19 · 2025: 23 · 2024: 33 · 2023: 30 · 2022: 33 · 2021: 47 · 2020: 39 · 2019: 35 · 2018: 33 · 2017: 29 · 2016: 10 · 2015: 16 · 2014: 15 · 2013: 5 · 2012: 2
- FWCI
- 2.60
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Physical Therapy Reviews (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- QUT ePrints (Queensland University of Technology) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Physical Sciences › Engineering › Aerospace Engineering › Inertial Sensor and Navigation
- Physical Sciences › Engineering › Biomedical Engineering › Lower Extremity Biomechanics and Pathologies
- Keywords
- inertial sensors, human motion analysis, gold standard comparison, electrogoniometry, optical motion capture, measurement validity, gait analysis
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