Task-oriented active training based on adaptive impedance control with iLeg — A horizontal exoskeleton for lower limb rehabilitation

Abstract

A horizontal exoskeleton for lower limb rehabilitation called iLeg has been developed by our laboratory which consists of two 3-DOF (degrees of freedom) robotic leg orthoses. This paper proposes a position-based impedance control with the compensation of BP NNs (back propagation neural networks) for the exoskeleton. Based on the control scheme, the task-oriented active training is investigated where impedance parameters are self-adjusted to movement deviation and patient activities with fuzzy logic. An adaptive haptic interface of active compliance is ensured to provide positive feedback to patients when their effort is desired or negative otherwise, which encourages patients to practice the desired movement following the predefined directed path. Besides, the timing freedom is separated from spatial trajectory and determined by patients. Voluntary effort hence becomes a requirement during the exercises, no effort no movement, so that active contribution of patients is highly motivated. Simulation results have verified the feasibility of the control scheme and the training strategy. An active compliant environment is created with adaptive haptic interface for task-oriented patient-driven training of multi-joint coordination.