Biofeedback System for Shoulder Rehabilitation

Shoulder pain affects a large percentage of the US population, and while many seek physical therapy as rehabilitation, there are still problems that arise. Shoulder rehabilitation often suffers from muscle compensation and limited quantitative feedback, and additionally, a primary concern of a physical therapist is ensuring that the patients are performing the exercises correctly without the supervision of the clinician. Therefore, this project developed a dual-system electromyography (EMG) biofeedback platform to improve muscle awareness and tracking during shoulder exercises. The first system uses a Delsys Trigno EMG setup with a custom Python GUI for in-clinic use. The second system, built with Arduino Uno and MyoWare sensors, provides a low-cost, portable solution for at-home use. Both systems deliver real-time EMG signal visual feedback to patients, with the Arduino Unit achieving a sub-second latency and a total cost of under $200. This work offers a foundation for future clinical integration of EMG-based feedback systems for shoulder rehabilitation.