The increasing demand concerning stroke rehabilitation and in-home exercise promotion requires objective methods to assess patients’ quality of movement, allowing progress tracking and promoting consensus among treatment regimens. In this work, we propose a method to detect diverse compensation patterns during exercise performance with 2D pose data to automate rehabilitation programs monitorization in any device with a 2D camera, such as tablets, smartphones, or robotic assistants.
