Modeling and Analysis of a Coupled Human–Robot System With Walking Assistance by Exoskeletons

Systematic evaluation of an exoskeleton based on dynamics analysis is important for optimization of mechanical design and control strategy. Most existing evaluation methods are based on metabolic cost or Electromyography (EMG) signals. Both these kinds of methods do not directly provide whole body muscle force information from the human-exoskeleton coupled system, thus presenting limitations in revealing muscle-level dynamic mechanisms. In this work, we establish an inverse dynamics calculation approach of human-exoskeleton coupled systems by combining a human musculoskeletal model, an exoskeleton model, and a Kelvin-Voigt model. Human motion experiments at three walking speeds in unloaded condition and wearing a powered hip exoskeleton with transparent condition and three assistance conditions are also conducted. An optical motion capture, an EMG measurement device and a force sensing treadmill are used to collect motion data. The effects of exoskeleton assistance condition on human joint torques and muscle forces during specific gait phases are analyzed. Thus human-performance-augmentation exoskeletons can be evaluated based on muscle-level dynamics, which could be helpful in exploring insights into motion assistance mechanisms and optimizing the motion control strategy of exoskeletons.