Force control of a robot for wrist rehabilitation: Towards coping with human intrinsic constraints

This work proposes a mechatronic solution to increase the back-drivability of a state-of-the art robot for wrist neurorehabilitation. The final goal is to reduce robot mechanical impedance in order to cope with intrinsic kinematic constraints, which are adopted by the human brain to solve redundancy during pointing tasks with the wrist. The handle of the robot has been provided with a load cell and a direct force control scheme has been implemented to minimize the interaction forces/torques between the user and the robot. To this aim gravity, inertia and friction of the more proximal DOF of the robot (relative to Pronation/Supination (PS) movements) have been estimated and compensated for. The proposed solution resulted in a 70% reduction of the end-point perceived inertia in PS DOF as well as in a decrease of torques exerted by the user during both 1-DOF and 3-DOFs tasks. The average reduction of interaction torques is around 81% and 78% respectively. This work constitutes an important starting point for the analysis of the effect that different levels of robot transparency could have on the human neural constraints adopted during redundant tasks, such as pointing movements with the wrist.