Kinematic Assessment of Upper Limb Movements Using the ArmeoPower Robotic Exoskeleton

Abstract

After a neurological injury, neurorehabilitation aims to restore sensorimotor function of patients. Technological assessments can provide high-quality data on a patient’s performance and support clinical decision making towards the most appropriate therapy. In this study, the ArmeoPower, a robotic exoskeleton for the upper extremities, was used to assess 12 neurological patients and 31 non-disabled participants performing various standardized single joint and frontal plane game-like exercises. From the collected data, kinematic metrics (End-Point Error, Hand-Path Ratio, reaction time, stability, Number of Velocity Peaks, peak, and mean Velocity) and the game score, were calculated and analyzed according to three criteria: the reliability (a), the difference between patients and non-disabled participants (b), as well as the influence of robotic movement assistance (c). In total, 39 metrics were analyzed and the following five most promising assessment variables for different exercises could be identified based on the three above-mentioned criteria: smoothness (RainMug (wrist)), mean speed (RainMug (wrist)), reaction time (Goalkeeper), maximum speed (HighFlyer (elbow)) and accuracy (Connect the dots), with the former showing good validity (rho=0.82, p=0.02) when comparing to the patient’s severity level. The results demonstrate feasibility to extract and analyze various kinematic metrics from the ArmeoPower, which can provide quantitative information about human performance during training and therapy. The generated data increases the understanding of the patient’s movement and can be used in the future in clinical research for better performance evaluation and providing more feedback options, leading towards a more personalized and patient-centric therapy.