Bilateral assessment of functional tasks for robot-assisted therapy applications
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This article presents a novel evaluation system along with methods to evaluate bilateral coordination of arm function on activities of daily living tasks before and after robot-assisted therapy. An affordable bilateral assessment system (BiAS) consisting of two mini-passive measuring units modeled as three degree of freedom robots is described. The process for evaluating functional tasks using the BiAS is presented and we demonstrate its ability to measure wrist kinematic trajectories. Three metrics, phase difference, movement overlap, and task completion time, are used to evaluate the BiAS system on a bilateral symmetric (bi-drink) and a bilateral asymmetric (bi-pour) functional task. Wrist position and velocity trajectories are evaluated using these metrics to provide insight into temporal and spatial bilateral deficits after stroke. The BiAS system quantified movements of the wrists during functional tasks and detected differences in impaired and unimpaired arm movements. Case studies showed that stroke patients compared to healthy subjects move slower and are less likely to use their arm simultaneously even when the functional task requires simultaneous movement. After robot-assisted therapy, interlimb coordination spatial deficits moved toward normal coordination on functional tasks.
KeywordsActivities of daily living Bilateral coordination Interlimb coordination Robot-assisted therapy Reaching Grasping Stroke rehabilitation Upper limb
This study is supported in part by the National Institutes of Health—NINDS 5K25NS058577-03, Advancing a Healthier Wisconsin Grant #5520015 and the Medical College of Wisconsin Research Affairs Committee Grant# 3303017. We would like to acknowledge that this material is the result of work supported with resources and the use of facilities at the Clement J. Zablocki VA medical center, Milwaukee WI. We would also like to thank Rubing Xu, Rohit Ruparel, Dr Yasser Mallick for their assistance in recruitment and collecting the data. We would like to thank Rui Loureiro, PhD and William Harwin, PhD at the University of Reading Cybernetics department for their role in designing the tracker.
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