Remote Physiotherapy and Movement Assessment
Today, providing appropriate rehabilitation at home and finding ways to prevent injuries and chronic diseases caused by sedentary lifestyles and lack of movement is more important than ever. Monitoring and evaluating the patient’s home physiotherapy is vital to providing feedback to the user and facilitating faster, more realistic, and cost-effective recovery. A system has been developed to evaluate the user’s movements and performance during physiotherapy exercises. Not everyone has access to or can afford to go to gyms, physiotherapy clinics, or exercise with a trainer. Self-training is an additional option that involves recording the steps of a physiotherapy program beforehand without providing feedback. Posture estimation techniques can be used to define a person’s behavior by determining their position at key time intervals. This allows us to measure or evaluate a person’s movements and provide feedback.
AI-Based Exercise Tracking
A Temporal Convolutional Network (TCN) based exercise compliance detection model has been developed that enables the tracking and evaluation of remote physiotherapy exercises using artificial intelligence.
Performance Tracking and Feedback
During remote physiotherapy, assessing movement similarity in healthcare is important for maintaining patient motivation. Providing feedback can be very beneficial for both patients and physicians/clinicians. Tracking the user’s performance ensures that exercises are assigned or reassigned appropriately.
