Reachable Workspace as a Clinical Outcome for Upper Extremity Function: A Narrative Review

Motion sensing technology can be utilized to capture detailed upper extremity (UE) motion to reconstruct an individual's three-dimensional (3D) reachable workspace (RWS). The RWS can be quantified as relative surface area (RSA), providing an innovative surrogate measure to assess UE mobility and function. Numerous studies have shown that RSA can reliably distinguish between healthy and impaired UE function and also is able to detect clinically relevant longitudinal changes, with sufficient sensitivity to detect small differences even in slowly-progressive conditions. After more than a decade of experience in clinical studies, RWS has been shown to be a valid, reliable, and sensitive UE clinical outcome assessment (COA) tool, with clinical utility in various neuromuscular diseases in which UE impairment is significant, including facioscapulohumeral dystrophy (FSHD), Duchenne muscular dystrophy (DMD), and amyotrophic lateral sclerosis (ALS). RWS and its performance outcome (PerfO) measure RSA have demonstrated strong associations with established clinical measures of disease severity, patient-reported outcomes (PROs), and functional performance, further supporting its clinical relevance. As an UE functional assessment tool, RWS has also shown its generalizable application in various other conditions with UE impairment, such as stroke, orthopedic conditions, and other musculoskeletal disorders. With significant body of work supporting sensor-based RWS as a clinically useful assessment of UE function, future developments incorporating increasingly-capable mobile sensing technologies for remote monitoring and applying machine learning and artificial intelligence (AI) approaches to the sensor-acquired motion data promise further exciting possibilities to enhance clinical studies and patient care.