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A reliable and efficient adaptive Bayesian method to assess static lower limb proprioception

View ORCID ProfileJonathan M Wood, View ORCID ProfileSusanne M Morton, View ORCID ProfileHyosub E Kim
doi: https://doi.org/10.1101/2023.01.23.525102
Jonathan M Wood
1Department of Physical Therapy, University of Delaware, Newark, DE 19711, United States
2Biomechanics and Movement Sciences Program, University of Delaware, Newark, DE 19711, United States
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  • For correspondence: jonwood@udel.edu
Susanne M Morton
1Department of Physical Therapy, University of Delaware, Newark, DE 19711, United States
2Biomechanics and Movement Sciences Program, University of Delaware, Newark, DE 19711, United States
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Hyosub E Kim
1Department of Physical Therapy, University of Delaware, Newark, DE 19711, United States
2Biomechanics and Movement Sciences Program, University of Delaware, Newark, DE 19711, United States
3Department of Psychological and Brain Sciences, University of Delaware, Newark, DE 19716, United States
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Abstract

Background Lower limb proprioception is critical for maintaining stability during gait and may impact how individuals modify their movements in response to changes in the environment and body state, a process termed “sensorimotor adaptation”. However, the connection between lower limb proprioception and sensorimotor adaptation during human gait has not been established. We suspect this gap is due in part to the lack of reliable, efficient methods to assess global lower limb proprioception in an ecologically valid context.

New Method We assessed static lower limb proprioception using an alternative forced choice task, administered twice to determine test-retest reliability. Participants stood on a dual-belt treadmill which passively moved one limb to stimulus locations selected by a Bayesian adaptive algorithm. At the stimulus locations, participants judged relative foot positions and the algorithm estimated the point of subjective equality (PSE) and the uncertainty of lower limb proprioception.

Results Using the Bland-Altman method, combined with Bayesian statistics, we found that both the PSE and uncertainty estimates had good reliability.

Comparison with Existing Method(s) Current methods assessing static lower limb proprioception do so within a single joint, in non-weight bearing positions, and rely heavily on memory. One exception assessed static lower limb proprioception in standing but did not measure reliability and contained confounds impacting participants’ judgments, which we experimentally controlled here.

Conclusions This efficient and reliable method assessing lower limb proprioception will aid future mechanistic understanding of locomotor adaptation and serve as a useful tool for basic and clinical researchers studying balance and falls.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://osf.io/g8nx4/

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted January 23, 2023.
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A reliable and efficient adaptive Bayesian method to assess static lower limb proprioception
Jonathan M Wood, Susanne M Morton, Hyosub E Kim
bioRxiv 2023.01.23.525102; doi: https://doi.org/10.1101/2023.01.23.525102
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A reliable and efficient adaptive Bayesian method to assess static lower limb proprioception
Jonathan M Wood, Susanne M Morton, Hyosub E Kim
bioRxiv 2023.01.23.525102; doi: https://doi.org/10.1101/2023.01.23.525102

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