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Cited by 422

The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.

Proprioceptive Acuity Assessment Via Joint Position Matching: From Basic Science to General Practice

Goble, Daniel J.·2010·Physical Therapy

Abstract

Over the past several decades, studies of use-dependent plasticity have demonstrated a critical role for proprioceptive feedback in the reorganization, and subsequent recovery, of neuromotor systems. As such, an increasing emphasis has been placed on tests of proprioceptive acuity in both the clinic and the laboratory. One test that has garnered particular interest is joint position matching, whereby individuals must replicate a reference joint angle in the absence of vision (ie, using proprioceptive information). On the surface, this test might seem straightforward in nature. However, the present perspective article informs therapists and researchers alike of multiple insights gained from a recent series of position matching studies by the author and colleagues. In particular, 5 factors are outlined that can assist clinicians in developing well-informed opinions regarding the outcomes of tests of position matching abilities. This information should allow for enhanced diagnosis of proprioceptive deficits within clinical settings in the future.

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Metadata

Authors
Goble, D. J.
Venue
Physical Therapy
Published
2010-08-01
Volume
90
Issue
8
Pages
1176-1184
ISSN
  • 0031-9023 (ISSN-L)
  • 1538-6724
OpenAlex
W2119588720
Cited by
422
References
55
FWCI
4.71
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Proprioceptive Acuity Assessment Via Joint Position Matching: From Basic Science to General Practice. https://app.cochat.ai/papers/10.2522/ptj.20090399
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Goble, D. J. (2010). Proprioceptive Acuity Assessment Via Joint Position Matching: From Basic Science to General Practice. Physical Therapy. https://doi.org/10.2522/ptj.20090399

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.