Investigating the feasibility of using visual feedback of biomechanical movement performance in sub-acute upper limb stroke rehabilitation

Introduction and aim: Stroke is the leading cause of severe adult disability in the developed world [1] and functional recovery of the upper limb is particularly poor. With a shift from hospital to community-based rehabilitation [2], novel solutions are needed to deliver the amount of quality therapy that is required for optimum recovery. 3D motion capture data can enhance a therapist's observational analysis of a patient's impairments however, clinically this is predominantly limited to use within a gait analysis laboratory. This study examined the use of portable motion capture technology and bespoke visualisation software to provide meaningful visual feedback of movement performance (Fig. 1) to patients, and their therapists, during upper limb stroke therapy sessions. We proposed this method would enhance understanding of correct movement patterns, of how improvements can be made during task orientated practice and thus enhance motor relearning to improve functional outcomes.