Implementation of active training for an upper-limb rehabilitation robot based on impedance control

Abstract

Many rehabilitation robots have been designed to alleviate the conflict between increasing number of post-stroke patients and shortage of therapists. Active training is the main feature of advanced rehabilitation robots, which has been proved to be more effective than simple passive movement training. This paper presents the implementation of active training on a 2-DOF upper-limb rehabilitation robot, which can assist the shoulder and elbow joint rehabilitation training of post-stroke patients. The controller is built based on impedance control, which can provide a compliant human-robot reaction. The implementation of active training is combined with a virtual reality game, and the average error between the actual and target reaction force is 1.41 ± 0.79 N in the X axis, and 1.22 ± 0.91 N in the Y axis.