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Background: Robotic devices have been used to quantify function, identify impairment, and rehabilitate motor function extensively in adults, but less-so in younger populations. The ability to perform motor actions improves as children grow. It is important to quantify this rate of change of the neurotypical population before attempting to identify impairment and target rehabilitation techniques. Objectives: For a population of typically developing children, this systematic review identifies and analyzes tools and techniques used with robotic devices to quantify upper-limb motor function. Since most of the papers also used robotic devices to compare function of neurotypical to pathological populations, a secondary objective was introduced to relate clinical outcome measures to identified robotic tools and techniques. Methods: Five databases were searched between February 2019 and August 2020, and 226 articles were found, 19 of which are included in the review. Results: Robotic devices, tasks, outcome measures, and clinical assessments were not consistent among studies from different settings but were consistent within laboratory groups. Fifteen of the 19 articles evaluated both typically developing and pathological populations. Conclusion: To optimize universally comparable outcomes in future work, it is recommended that a standard set of tasks and measures is used to assess upper-limb motor function. Standardized tasks and measures will facilitate effective rehabilitation.

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Motor development in children and youth occurs non-linearly; improvements are rapid at younger ages and decrease as they reach adulthood. There is also evidence that performance variability changes as children and youth age. Accurate models of typical performance are necessary to identify deficits in motor performance and to track the efficacy of therapies. Robotic devices have been used previously to measure motor performance in children and youth, and produce models of typical performance; however, power analyses on these models have not been explored. An algorithm was created to generate normative models of typical motor performance. The accuracy and repeatability of the algorithm were tested using simulated data that changed the number of data points, and the curvature and variability of the data. Two-hundred and eighty-eight participants who are typically developing (ages 5-18) completed a robotic point-to-point reaching task with the Kinarm Exoskeleton. Exponential curves were fit to reaction time measured by the Kinarm to model typical performance. The results of the simulations were used to generate confidence intervals on the models of typical performance. The simulations showed that number of datapoints had the largest impact on accuracy and repeatability of the models, and that repeatability was age-dependent. The simulations with the uniform and non-uniform datasets generated different confidence intervals; however, these differences were minimal when the number of datapoints at each age were matched between the two datasets. To ensure identification of deficits is accurately determined, there is a need to account for differences in repeatability when developing models of typical motor performance in children and youth. The results of our simulations can be used to assess repeatability of non-linear models of motor performance based on dataset size in the future.

General motor and executive functions are integral for tasks of daily living and are typically assessed when quantifying impairment of an individual. Robotic tasks offer highly repeatable and objective measures of motor and cognitive function. Additionally, robotic tasks and measures have been used successfully to quantify impairment of children with cerebral palsy (CP). Many robotic tasks include multiple performance parameters, so interpretation of results and identification of impairment can be difficult, especially when multiple tasks are completed. This study used exploratory factor analysis to investigate a potential set of quantitative models of motor and cognitive function in children, and compare performance of participants with CP to these models. The three calculated factors achieved strong differentiation between participants with mild CP and the typically developing population. This demonstrates the feasibility of these factors to quantify impairment and track improvements related to therapies.Clinical Relevance-This establishes a method to differentiate atypical motor performance related to CP using a robotic reversed visually guided reaching task.