Abstract
Individualized rehabilitation sessions with a therapists are important to improve physical ability of a patient with neurological and musculoskeletal disorders. However, in-home rehabilitation regimens are often prescribed due to therapist’s limited availability. During in-home rehabilitation, patients might become confused whether they correctly follow rehabilitation regimens. To address this problem, this research aims to develop a Socially Assistive Robot that can interactively accommodate expert’s domain knowledge into a data-driven model to assess exercise performance and guide desirable joint positions for improvement.
Keywords
- Humans and AI: Human-AI Collaboration
- Robotics: Human Robot Interaction
- Humans and AI: Personalization and User Modeling
- Machine Learning Applications: Bio;Medicine
