A Human-Robot Cooperative and Personalized Compliant Joint Controller for Upper-Limb Rehabilitation Robots: The Elbow Joint Validation

Abstract

Background: Appropriate training modalities for post-stroke upper-limb rehabil6 itation are key features for effective recovery after the acute event. This work presents a novel 7 human-robot cooperative control framework that promotes compliant motion and renders differ8 ent high-level human-robot interaction rehabilitation modalities under a unified low-level control 9 scheme. 10 Methods: The presented control law is based on a loadcell-based impedance controller provided 11 with positive-feedback compensation terms for disturbances rejection and dynamics compensation. 12 We developed an elbow flexion-extension experimental setup, and we conducted experiments to 13 evaluate the controller performances. Seven high-level modalities, characterized by different levels of 14 (i) impedance-based corrective assistance, (ii) weight counterbalance assistance, and (iii) resistance, 15 have been defined and tested with 14 healthy volunteers. 16 Results: The unified controller demonstrated suitability to promote good transparency and 17 render compliant and high-impedance behavior at the joint. Superficial electromyography results 18 showed different muscular activation patterns according to the rehabilitation modalities. Results 19 suggested to avoid weight counterbalance assistance, since it could induce different motor relearning 20 with respect to purely impedance-based corrective strategies. 21 Conclusion: We proved that the proposed control framework could implement different phys22 ical human-robot interaction modalities and promote the assist-as-needed paradigm, helping the 23 user to accomplish the task, while maintaining physiological muscular activation patterns. Future 24 insights involve the extension to multiple degrees of freedom robots and the investigation of an 25 adaptation control law that makes the controller learn and adapt in a therapist-like manner. 26