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The Effect of Repeated Measurements Using an Upper Extremity Robot on Healthy Adults
Journal article   Open access   Peer reviewed

The Effect of Repeated Measurements Using an Upper Extremity Robot on Healthy Adults

Margaret A. Finley, Laura Dipietro, Jill Ohlhoff, Jill Whitall, Hermano I. Krebs and Christopher T. Bever
Journal of applied biomechanics, v 25(2), pp 103-110
01 May 2009
PMID: 19483254
url
https://europepmc.org/articles/pmc3535854View
Accepted (AM)Open Access (License Unspecified) Open

Abstract

orthopedic impairments outcomes rehabilitation
We are expanding the use of the MIT-MANUS robotics to persons with impairments due exclusively to orthopedic disorders, with no neurological deficits. To understand the reliability of repeated measurements of the robotic tasks and the potential for registering changes due to learning is critical. Purposes of this study were to assess the learning effect of repeated exposure to robotic evaluations and to demonstrate the ability to detect a change in protocol in outcome measurements. Ten healthy, unimpaired subjects (mean age = 54.1 ± 6.4 years) performed six repeated evaluations consisting of unconstrained reaching movements to targets and circle drawing (with and without a visual template) on the MIT-MANUS. Reaching outcomes were aiming error, mean and peak speed, movement smoothness and duration. Outcomes for circle drawing were axis ratio metric and shoulder–elbow joint angles correlation metric (was based on a two-link model of the human arm and calculated hand path during the motions). Repeated-measures ANOVA ( p ≤ .05) determined if difference existed between the sessions. Intraclass correlations ( R ) were calculated. All variables were reliable, without learning across testing sessions. Intraclass correlation values were good to high (reaching, R ≥ .80; circle drawing, R ≥ .90). Robotic measurement ability to differentiate between similar but distinct tasks was demonstrated as measured by axis ratio metric ( p < .001) and joint correlation metric ( p = .001). Outcome measures of the MIT-MANUS proved to be reliable yet sensitive to change in healthy adults without motor learning over the course of repeated measurements.

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11 citations in Scopus

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

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Collaboration types
Domestic collaboration
Web of Science research areas
Engineering, Biomedical
Sport Sciences
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