MIT system ’sees’ the inner structure of the body during physical rehab

A system for monitoring motion and muscle engagement could aid the elderly and athletes during unsupervised physical rehabilitation for injuries or impaired mobility. A growing number of people are living with conditions that could benefit from physical rehabilitation - but there aren't enough physical therapists (PTs) to go around. The growing need for PTs is racing alongside population growth, and aging, as well as higher rates of severe ailments, are contributing to the problem. An upsurge in sensor-based techniques, such as on-body motion sensors, has provided some autonomy and precision for patients who could benefit from robotic systems to supplement human therapists. Still, the minimalist watches and rings that are currently available largely rely on motion data, which lack more holistic data a physical therapist pieces together, including muscle engagement and tension, in addition to movement. This muscle-motion language barrier recently prompted the creation of an unsupervised physical rehabilitation system, MuscleRehab, by researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) and Massachusetts General Hospital. There are three ingredients: motion tracking that captures motion activity, an imaging technique called electrical impedance tomography (EIT) that measures what the muscles are up to, and a virtual reality (VR) headset and tracking suit that lets a patient watch themselves perform alongside a physical therapist.