AUTHOR=Zhang Longbin , Liu Yixing , Wang Ruoli , Smith Christian , Gutierrez-Farewik Elena M. TITLE=Modeling and Simulation of a Human Knee Exoskeleton's Assistive Strategies and Interaction JOURNAL=Frontiers in Neurorobotics VOLUME=15 YEAR=2021 URL=https://www.frontiersin.org/journals/neurorobotics/articles/10.3389/fnbot.2021.620928 DOI=10.3389/fnbot.2021.620928 ISSN=1662-5218 ABSTRACT=

Exoskeletons are increasingly used in rehabilitation and daily life in patients with motor disorders after neurological injuries. In this paper, a realistic human knee exoskeleton model based on a physical system was generated, a human–machine system was created in a musculoskeletal modeling software, and human–machine interactions based on different assistive strategies were simulated. The developed human–machine system makes it possible to compute torques, muscle impulse, contact forces, and interactive forces involved in simulated movements. Assistive strategies modeled as a rotational actuator, a simple pendulum model, and a damped pendulum model were applied to the knee exoskeleton during simulated normal and fast gait. We found that the rotational actuator–based assistive controller could reduce the user's required physiological knee extensor torque and muscle impulse by a small amount, which suggests that joint rotational direction should be considered when developing an assistive strategy. Compared to the simple pendulum model, the damped pendulum model based controller made little difference during swing, but further decreased the user's required knee flexor torque during late stance. The trade-off that we identified between interaction forces and physiological torque, of which muscle impulse is the main contributor, should be considered when designing controllers for a physical exoskeleton system. Detailed information at joint and muscle levels provided in this human–machine system can contribute to the controller design optimization of assistive exoskeletons for rehabilitation and movement assistance.