In this paper, we present a haptics-based rehabilitation system that uses kinematics of a haptic device to monitor a subject's participation in therapy. In robot-assisted therapy, it is crucial to monitor if the patient is actively performing the rehabilitation task and is not just passively following the robot's motions. In this paper, we have used position-tracking error patterns as a metric for identifying whether the subject is actively participating in the therapy. Using a single feature identification scheme, our method demonstrated a real-time classification accuracy of 80.04\% in separating active and passive participation during a therapy session.
Link to paper.