An ℋ_∞ Approach for Human Torque Estimation and Assistive Robot Rehabilitation via LMI-based Convex Techniques

Interest in assistive robots for rehabilitation purposes has raised due to the increase of people affected by motor impairment. An important challenge in this context is the interaction between user and robot to realize a cooperative task, where knowing the participation of the patient is crucial to the rehabilitation protocol. A rising topic is the knowledge of human contribution for personalized assistance, as the current range of solutions include cumbersome measurement devices, therapist-on-the-loop approach and sensor-less estimation based on human movement. This proposal allows estimating the human contribution in a rehabilitation task, dealing with unexpected abrupt forces, i.e., a disease such as Parkinson. In addition, a robust LMI-based computed torque controller is tested and validated with an OpenSim model.