Literature DB >> 31862606

Compensatory strategies of body-powered prosthesis users reveal primary reliance on trunk motion and relation to skill level.

Aïda M Valevicius1, Quinn A Boser2, Craig S Chapman3, Patrick M Pilarski2, Albert H Vette4, Jacqueline S Hebert5.   

Abstract

BACKGROUND: While body-powered prostheses are commonly used, the compensatory strategies required to operate body-powered devices are not well understood. Kinematic assessment in addition to standard clinical tests can give a comprehensive evaluation of prosthesis user function and skill. This study investigated the movement compensations of body-powered prosthesis users and determined whether a correlation is present between compensatory strategies and skill level, as measured by a standard clinical test.
METHODS: Five transradial body-powered prosthesis users completed two standardized upper limb tasks. A 12-camera motion capture system was used to obtain three-dimensional angular kinematics for eight degrees of freedom at the trunk, shoulder, and elbow. Range of motion was compared to a normative dataset. Pearson's correlation was used to assess the relationship between the Activities Measure for Upper Limb Amputees and range of motion for each degree of freedom.
FINDINGS: Participants displayed a statistically significant (P < .05) increase in range of motion at the trunk for both tasks. Shoulder flexion/extension range of motion was significantly reduced (P < .05) compared to normative values, but shoulder abduction/adduction range of motion did not show a consistent difference compared to norms. Skill level was correlated with range of motion for specific degrees of freedom at the trunk, shoulder, and elbow.
INTERPRETATION: Body-powered prosthesis users compensated with trunk movement and showed reduced motion for shoulder flexion/extension, with relatively normal shoulder abduction/adduction. Skill level was correlated with angular kinematic strategies, which may allow targeting of specific therapeutic interventions for reducing compensatory movements.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Body-powered prosthesis users; Clinical assessment; Compensatory strategies; Functional tasks; Motion capture; Upper limb kinematics

Year:  2019        PMID: 31862606     DOI: 10.1016/j.clinbiomech.2019.12.002

Source DB:  PubMed          Journal:  Clin Biomech (Bristol, Avon)        ISSN: 0268-0033            Impact factor:   2.063


  2 in total

1.  Application of machine learning to the identification of joint degrees of freedom involved in abnormal movement during upper limb prosthesis use.

Authors:  Sophie L Wang; Conor Bloomer; Gene Civillico; Kimberly Kontson
Journal:  PLoS One       Date:  2021-02-11       Impact factor: 3.240

2.  Myoelectric prosthesis users and non-disabled individuals wearing a simulated prosthesis exhibit similar compensatory movement strategies.

Authors:  Heather E Williams; Craig S Chapman; Patrick M Pilarski; Albert H Vette; Jacqueline S Hebert
Journal:  J Neuroeng Rehabil       Date:  2021-05-01       Impact factor: 4.262

  2 in total

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