An adaptive impedance controller for upper limb rehabilitation based on estimation of patients' stiffness

Impedance control has been widely used in rehabilitation therapies. Especially the control strategies with adaptability are proved to be beneficial to patients. In this paper, we present an adaptive impedance controller for upper limb rehabilitation robots. Firstly, the stiffness and damping of the patients are estimated by the least square method. Then, a reward function is defined to encourage the patients' efforts and limit the tracking errors. To maximize the reward function, the optimal robot stiffness is determined based on the estimation of the patients' stiffness. In order to validate the performance of the proposed control method, a set of simulation experiments considering both the constant and varying patient stiffness are presented and the results have shown the adaptive impedance controller leads to a significantly greater reward than constant impedance controller.