Adaptive control of a robotic exoskeleton for neurorehabilitation

Neurorehabilitation efficiency increases with therapy intensity and subject´s involvement during physical exercises. Robotic exoskeletons could bring both features, if they could adapt the level of assistance to patient´s motor capacities. To this aim, we developed an exoskeleton controller, based on adaptive techniques, that can actively modulate the stiffness of the robotic device in function of the subject´s activity. We tested this control law on one healthy subject with an upper-limb exoskeleton. The experiment consisted in learning a trajectory imposed by the robot. The early results show the different features allowed by our controller with respect to controllers commonly used for neurorehabilitation with exoskeletons.