Validating the measurement of upper limb sensorimotor behavior utilizing a tablet in neurologically intact controls and individuals with chronic stroke

Abstract

Abstract Background Intact sensorimotor function of the upper extremity is essential for successfully performing activities of daily living. After a stroke, upper limb function is often compromised and requires rehabilitation. To develop appropriate rehabilitation interventions, sensitive and objective assessments are required. Current clinical measures often lack precision and technological devices (e.g. robotics) that are objective and sensitive to small changes in sensorimotor function are often unsuitable and impractical for performing home-based assessments. Here we developed a portable, tablet-based application capable of quantifying upper limb sensorimotor function after stroke. Our goal was to validate the developed application and accompanying data analysis against previously validated robotic measures of upper limb function in stroke. Methods Twenty individuals with stroke, twenty age-matched older controls, and twenty younger controls completed an eight-target Visually Guided Reaching (VGR) task using a Kinarm Robotic Exoskeleton and a Samsung Galaxy Tablet. Participants completed eighty trials of the VGR task on each device, where each trial consisted of making a reaching movement to one of eight pseudorandomly appearing targets. We calculated several outcome parameters capturing various aspects of sensorimotor behavior (e.g., Reaction Time, Initial Direction Error, Max Speed, and Movement Time) from each reaching movement, and our analyses compared metric consistency between devices. We used the previously validated Kinarm Standard Analysis (KSA) and a custom in-house analysis to calculate each outcome parameter. Results We observed strong correlations between the KSA and our custom analysis for all outcome parameters within each participant group, indicating our custom analysis accurately replicates the KSA. Minimal differences were observed for between-device comparisons (tablet vs. robot) in our outcome parameters. Additionally, we observed similar correlations for each device when comparing the Fugl-Meyer Assessment (FMA) scores of individuals with stroke to tablet-derived metrics, demonstrating that the tablet can capture clinically-based elements of upper limb impairment. Conclusions Tablet devices can accurately assess upper limb sensorimotor function in neurologically intact individuals and individuals with stroke. Our findings validate the use of tablets as a cost-effective and efficient assessment tool for upper-limb function after stroke.