Physical Human-Robot Interaction Control of Variable Stiffness Exoskeleton With sEMG-Based Torque Estimation

• Published in: IEEE transactions on industrial informatics Vol. 19; no. 10; pp. 10601 - 10612
• Main Authors: Zhu, Yanghui, Wu, Qingcong, Chen, Bai, Zhao, Ziyue, Liang, Conghui
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.10.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Actuators; Algorithms; Assist-as-needed (AAN); Control algorithms; Estimation; Exoskeletons; Impedance; Joints (anatomy); Mechanical properties; physical human–robot interaction (pHRI); Pulleys; rehabilitation exoskeleton; Robot control; Robots; Springs; Stiffness; surface electromyography signal (sEMG); Torque; Torque sensors (robotics); variable stiffness actuator (VSA)
• ISSN: 1551-3203; 1941-0050
• DOI: 10.1109/TII.2023.3240749

Robotic exoskeleton assistance is an effective method for the treatment of patients with movement disorders. First, this article presents a variable stiffness knee exoskeleton robot, which can independently control stiffness and position and has a large stiffness range under low preload. Then, combined with the designed variable stiffness exoskeleton, a physical human-robot interaction (pHRI) control scheme based on joint torque estimation is proposed. Different from previous studies, this method uses the mechanical properties of the exoskeleton to achieve pHRI without complex control algorithms and force/torque sensors. Furthermore, the joint torque is estimated based on the surface electromyography signal and the Hill-based muscle model, and the exoskeleton can realize assist-as-needed function: when the subject trains with less effort, the exoskeleton maintains a high output physical impedance to provide high tracking accuracy; and when the subject trains with greater effort, the exoskeleton maintains a low output impedance to provide high physical compliance. Finally, we conducted experiments on three healthy subjects and two subjects with lower limb motor dysfunction to verify the effectiveness of the torque estimation method and the pHRI control scheme.