Using a tablet to understand the spatial and temporal characteristics of complex upper limb movements in chronic stroke.

Autor: Austin DS; Graduate Program in Biomechanics and Movement Science (BIOMS), University of Delaware, Newark, Delaware, United States of America.; Department of Kinesiology and Applied Physiology, University of Delaware, Newark, Delaware, United States of America., Dixon MJ; Department of Kinesiology and Applied Physiology, University of Delaware, Newark, Delaware, United States of America., Hoh JE; Graduate Program in Biomechanics and Movement Science (BIOMS), University of Delaware, Newark, Delaware, United States of America.; Department of Kinesiology and Applied Physiology, University of Delaware, Newark, Delaware, United States of America., Tulimieri DT; Graduate Program in Biomechanics and Movement Science (BIOMS), University of Delaware, Newark, Delaware, United States of America.; Department of Kinesiology and Applied Physiology, University of Delaware, Newark, Delaware, United States of America., Cashaback JGA; Graduate Program in Biomechanics and Movement Science (BIOMS), University of Delaware, Newark, Delaware, United States of America.; Department of Kinesiology and Applied Physiology, University of Delaware, Newark, Delaware, United States of America.; Department of Biomedical Engineering, University of Delaware, Newark, Delaware, United States of America., Semrau JA; Graduate Program in Biomechanics and Movement Science (BIOMS), University of Delaware, Newark, Delaware, United States of America.; Department of Kinesiology and Applied Physiology, University of Delaware, Newark, Delaware, United States of America.; Department of Biomedical Engineering, University of Delaware, Newark, Delaware, United States of America.
Jazyk: angličtina
Zdroj: PloS one [PLoS One] 2024 Nov 18; Vol. 19 (11), pp. e0311773. Date of Electronic Publication: 2024 Nov 18 (Print Publication: 2024).
DOI: 10.1371/journal.pone.0311773
Abstrakt: Robotic devices are commonly used to quantify sensorimotor function of the upper limb after stroke; however, the availability and cost of such devices make it difficult to facilitate implementation in clinical environments. Tablets (e.g. iPad) can be used as devices to facilitate rehabilitation but are rarely used as assessment tools for the upper limb. The current study aimed to implement a tablet-based Maze Navigation Task to examine complex upper-limb movement in individuals with chronic stroke. We define complex upper-limb movement as reaching movements that require multi-joint coordination in a dynamic environment. We predicted that individuals with stroke would have more significant spatial errors, longer movement times, and slower speeds compared to controls with increasing task complexity. Twenty individuals with chronic stroke who had a variety of arm and hand function (Upper extremity Fugl-Myer 52.8 ± 18.3) and twenty controls navigated eight pseudorandomized mazes on an iPad using a digitizing stylus. The task was designed to elicit reaching movements engaging both the shoulder and elbow joints. Each maze became increasingly complex by increasing the number of 90° turns. We instructed participants to navigate each maze as quickly and accurately as possible while avoiding the maze's boundaries. Sensorimotor behavior was quantified using the following metrics: Error Time (time spent hitting or outside boundaries), Peak Speed, Average Speed, and Movement Time, Number of Speed Peaks. We found that individuals with stroke had significantly greater Error Time for all maze levels (all, p < 0.01), while both speed metrics, Movement Time and Number of Speed Peaks were significantly lower for several levels (all, p < 0.05). As maze complexity increased, the performance of individuals with stroke worsened only for Error Time while control performance remained consistent (p < 0.001). Our results indicate that a complex movement task on a tablet can capture temporal and spatial impairments in individuals with stroke, as well as how task complexity impacts movement quality. This work demonstrates that a tablet is a suitable tool for the assessment of complex movement after stroke and can serve to inform rehabilitation after stroke.
Competing Interests: The authors have declared that no competing interests exist.
(Copyright: © 2024 Austin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Databáze: MEDLINE
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