Grant: Applied Research and Development Grants - Level 1

Telepresence for physiotherapy is an area of significant recent growth within healthcare for mobile computing. Applications typically use depth cameras to estimate the body pose of the user, so machine intelligence can assess and provide medically relevant feedback to achieve medical outcomes. Sheridan College and Lusens - a Canadian leader in interactive, touch, and gesture recognition software for commercial, retail and medical applications - seek to conduct collaborative applied research and development (R&D) focused on improving their existing GoPhysio product. GoPhysio uses proprietary technology to analyze and measure musculoskeletal positions and movements to provide remote assistance for physical therapy, rehabilitation and fitness. The proposed research will focus on development of innovative solutions for body pose estimation and scoring for both depth and RGB cameras via Machine Learning. The application of body pose estimation as a means for software to assess, critique and score patient movements and gestures in software requires specialized camera-to-skeleton calculations, algorithms for analyzing motion, and Artificial Intelligence to analyze the movements for predictive purposes. Lusens aims to apply the research results in the development of their industry-leading body pose estimation software and Sheridan Computer Science students engaged in the proposed project will benefit from experiential learning and practice of relevant skills applied to real-world innovation challenges.