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The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Assessing proprioception: A critical review of methods

Open access
Han, Jia, Waddington, Gordon, Adams, Roger, Anson, Judith, Liu, Yu·2016·Journal of Sport and Health Science

Abstract

To control movement, the brain has to integrate proprioceptive information from a variety of mechanoreceptors. The role of proprioception in daily activities, exercise, and sports has been extensively investigated, using different techniques, yet the proprioceptive mechanisms underlying human movement control are still unclear. In the current work we have reviewed understanding of proprioception and the three testing methods: threshold to detection of passive motion, joint position reproduction, and active movement extent discrimination, all of which have been used for assessing proprioception. The origin of the methods, the different testing apparatus, and the procedures and protocols used in each approach are compared and discussed. Recommendations are made for choosing an appropriate technique when assessing proprioceptive mechanisms in different contexts.

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Crossref · 10.1016/j.jshs.2014.10.004

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Metadata

Authors
Han, J., Waddington, G., Adams, R., Anson, J., & Liu, Y.
Venue
Journal of Sport and Health Science
Publisher
Elsevier BV
Published
2016-03
Volume
5
Issue
1
Pages
80-90
ISSN
  • 2213-2961 (ISSN-L)
  • 2095-2546
OpenAlex
W2086760936
Cited by
629
References
3
FWCI
12.54
Type
journal article
Language
en
Open access
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CoChat. (2026). Citation check: Assessing proprioception: A critical review of methods. https://app.cochat.ai/papers/10.1016/j.jshs.2014.10.004
The paper
Han, J., Waddington, G., Adams, R., Anson, J., & Liu, Y. (2016). Assessing proprioception: A critical review of methods. Journal of Sport and Health Science. https://doi.org/10.1016/j.jshs.2014.10.004

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.