A Hybrid Controller with Chedoke-McMaster Stroke Assessment for Robot-Assisted Rehabilitation

Abstract

Amongst the major challenges in post-stroke rehabilitation are the repetitiveness nature of rehabilitation procedure, and the accessibility of therapists for long-term treatment. In manual rehabilitation procedure, the patient is subjected to repetitive mechanical movement of the affected limb by the therapist. In one of the techniques called active-assist exercise, the subject moves his affected limb along a specified trajectory with the therapist guiding the motion. The therapist gives some assistance to the subject to complete the course if deemed necessary and the procedure repeats. The significant advantages of using robots in assisting rehabilitation are its efficiency and it is fatigue free. The robots however need to be developed to have the capability of human therapist in providing the rehabilitation more naturally. In this paper, the work focuses on developing a new framework for the robot controller system. In particular, a low-level controller, which is in the form of force controller based on impedance control theory is discussed. The controller is capable of governing the active-assist exercise through autonomous guidance during the therapeutic procedure based on the Chedoke-McMaster stroke assessment method.