Simulation of musculoskeletal systems using dynamic optimization is a powerful approach for studying the biomechanics of human movements and can be applied to human-robot interactions. The simulation results of human movements augmented by robotic devices may be used to evaluate and optimize the device design and controller. However, simulations are limited by the accuracy of the models which are usually simplified for computation efficiency. Typically, the powered robotic devices are often modeled as massless, ideal torque actuators that is without mass and internal dynamics, which may have significant impacts on the simulation results. This article investigates the effects of including the mass and internal dynamics of the device in simulations of assisted human movement. The device actuator was modeled in various ways with different detail levels. Dynamic optimization was used to find the muscle activations and actuator commands in motion tracking and predictive simulations. The results showed that while the effects of device mass and inertia can be small, the electrical dynamics of the motor can significantly impact the results. This outcome suggests the importance of using an accurate actuator model in simulations of human movement augmented by assistive devices. NOVELTY: Demonstrating the effects of including mass and internal dynamics of the actuator in simulations of assisted human movement A new OpenSim electric motor actuator class to capture the electromechanical dynamics for use in simulation of human movement assisted by powered robotic devices.
Keywords: DC motor; actuator dynamics; dynamic optimization; exoskeletons; predictive simulation; prostheses.
© 2020 John Wiley & Sons, Ltd.