• AI-Enabled Video Biomechanics: A New Frontier for Clinical Care and Trial Readiness in Neuromuscular Disease

    Nicoline B.M. Voet, M.D., Ph.D.

    Abstract

    The unpredictable course and subtle, variable impairments of facioscapulohumeral muscular dystrophy (FSHD) and myotonic dystrophy (DM) make conventional outcome measures, such as timed function tests and patient-reported outcome measures, inadequate for capturing clinically meaningful change in short trial time frames. In this issue of NEJM AI, Ruth et al. propose an alternative: AI-enabled video biomechanical analysis using OpenCap. In under 20 minutes per participant, they analyzed nine movements in 129 individuals, including 86 with FSHD or DM, extracting 34 clinically relevant kinematic features. These features showed high agreement with timed function tests (r>0.98) and better discrimination between disease groups (balanced accuracy 82%). The study uncovered subtle movement abnormalities, frequently missed by conventional tools, that can contribute to pain, inefficiency, and overuse injuries. Detecting such patterns early could inform the development of more personalized interventions. Furthermore, longitudinal research in FSHD has shown minimal detectable change over 5 years using conventional outcome assessments, making them unsuitable for shorter trials. Though similar long-term data are lacking in DM, the measurement challenges are comparable. By enabling scalable, objective, and clinically interpretable assessments outside specialized labs, video-based biomechanical analysis offers a promising approach to enhance both clinical care and trial readiness in neuromuscular disease.