Impedance Reduction Control of a Knee Joint Human-Exoskeleton System

• Published in: IEEE transactions on control systems technology Vol. 27; no. 6; pp. 2541 - 2556
• Main Authors: Huo, Weiguang, Mohammed, Samer, Amirat, Yacine
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.11.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); Institute of Electrical and Electronics Engineers
• Subjects: Artificial Intelligence; Assistive robotics; Automatic; Computer Science; Damping; Electromyography; Engineering Sciences; Exoskeletons; Gravitation; human-exoskeleton interaction; Impedance; impedance reduction control (IRC); Joints (anatomy); Knee; Legged locomotion; Mechanical impedance; Muscles; Nonlinear control; Reduction; Rehabilitation robotics; Robotics; Sensors; Torquemeters; Uncertainty analysis; Walking; Human-exoskeleton interaction; Assistive robotics; Exoskeletons; Impedance reduction control (IRC)
• ISSN: 1063-6536; 1558-0865
• DOI: 10.1109/TCST.2018.2865768

Reducing human lower limb effort during walking is still a challenge for wearable exoskeletons. From the wearer's viewpoint, joint impedance increases while wearing the exoskeleton due to the fact that the exoskeleton's mass, friction, and gravity are added to those of the human lower limbs. Active impedance is required from the exoskeleton to compensate not only the exoskeleton's mechanical impedance but also that of the human limb. This paper presents a nonlinear impedance reduction control (IRC) approach applied to a knee joint exoskeleton during flexion/extension movements. The IRC approach ensures impedance adaptation of the human-exoskeleton system toward a desired level. The proposed method is an alternative to sensor-based impedance controllers where the human joint torque is estimated using electromyography (EMG) sensors, force/torque sensors, and so on. The performance of the proposed approach and its robustness with respect to modeling uncertainties are theoretically analyzed and discussed. Experiments were conducted with four healthy subjects to verify the effectiveness of human effort reduction. The root mean square of the EMG signals of the muscles involved in the flexion/extension was used as a metric. The experimental results show that EMG signal levels can be efficiently reduced by inertia, damping, and gravity compensation compared with those obtained without wearing the exoskeleton.