A Variable-Admittance Assist-As-Needed Controller for Upper-limb Rehabilitation Exoskeletons

Algorithms used for controlling upper limb rehabilitation exoskeletons need to promote active participation of patients in the training while preventing incorrect hand motion and arm posture. Any such framework should also be systematically customizable for individual users. Our work is motivated by the lack of such control frameworks for upper-limb rehabilitation exoskeletons. To address this shortcoming, we have proposed a method that consists of a two-port admittance controller in the task space which regulates the interaction between the exoskeleton and the user in both wrist and upper arm interaction points. Parameters of the virtual model in the wrist interaction port are dynamically adjusted based on both the performance and the intention of the subject, realizing a minimally intervening controller. The upper arm admittance model on the other hand, modulates how strictly reference shoulder-elbow synergies are enforced, making the proposed approach useful for various stages of rehabilitation. To achieve this, interaction forces measured between the exoskeleton and the upper-arm are used to modify the joint reference trajectories (generated by a model-based redundancy resolution strategy) in the null space of wrist motions.This paper presents a complete formulation of the introduced method, proof of the variable-admittance controller's passivity, and experimental results verifying the feasibility and performance of the proposed controller.