A metric for characterizing the arm nonuse workspace in poststroke individuals using a robot arm

Author:

Dennler Nathaniel1ORCID,Cain Amelia2ORCID,De Guzman Erica1,Chiu Claudia1ORCID,Winstein Carolee J.2ORCID,Nikolaidis Stefanos1,Matarić Maja J.1ORCID

Affiliation:

1. Department of Computer Science, University of Southern California, Los Angeles, CA, USA.

2. Department of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, CA, USA.

Abstract

An overreliance on the less-affected limb for functional tasks at the expense of the paretic limb and in spite of recovered capacity is an often-observed phenomenon in survivors of hemispheric stroke. The difference between capacity for use and actual spontaneous use is referred to as arm nonuse. Obtaining an ecologically valid evaluation of arm nonuse is challenging because it requires the observation of spontaneous arm choice for different tasks, which can easily be influenced by instructions, presumed expectations, and awareness that one is being tested. To better quantify arm nonuse, we developed the bimanual arm reaching test with a robot (BARTR) for quantitatively assessing arm nonuse in chronic stroke survivors. The BARTR is an instrument that uses a robot arm as a means of remote and unbiased data collection of nuanced spatial data for clinical evaluations of arm nonuse. This approach shows promise for determining the efficacy of interventions designed to reduce paretic arm nonuse and enhance functional recovery after stroke. We show that the BARTR satisfies the criteria of an appropriate metric for neurorehabilitative contexts: It is valid, reliable, and simple to use.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Artificial Intelligence,Control and Optimization,Computer Science Applications,Mechanical Engineering

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