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=Volume 15 - 2021 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 modelling 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 modelled 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.