ADAPT - adaptive automated robotic task practice system for stroke rehabilitation

Younggeun Choi, James Gordon, Nicolas Schweighofer

Abstract: We propose a new robotic task practice system designed to enhance the recovery of upper extremity functions in patients with stroke. Our system, ADAPT (ADaptive and Automatic Presentation of Tasks), which was designed in accordance to current training guidelines for stroke rehabilitation, engages the patient intensively, actively, and adaptively in a variety of realistic functional tasks that require reaching and manipulation. A general-purpose robot simulates the dynamics of the functional tasks. Based on the subject’s performance, a task scheduler adaptively selects a task and sets the task difficulty. The tool changer selects the tool corresponding to the selected task, a doorknob for instance. The low-level controller then implements the selected task with the desired difficulty on the robot during the robot-patient interaction. Our preliminary experimental results demonstrate the feasibility of our system.