下肢外骨骼人机耦合交互力特性分析

Objective: To propose a human-machine coupling dynamics modeling method based on virtual muscles, so as to quantitatively analyze the characteristics of human-computer interaction force and muscle activation of the musculoskeletal system. Methods: First, in the gait experiment of wearing exoskeleton, the human motion capture system and self-developed mechanical monitoring device were used to obtain the wearer's walking dynamics, electromyography (EMG) signals, exoskeleton drive status and local human-computer interaction information. The human-machine coupling model was established in modeling environment of the bone system, and the gait experiment data and the exoskeleton joint torques were used as driving information of the coupling model to perform inverse mechanical calculations. Finally, by adjusting strength and stiffness parameters of the virtual muscles, the real data of the model was compared with the experimental test result, to quantitatively evaluate effectiveness of the human-machine coupling model of the lower extremity exoskeleton. Results: The normal interaction force calculated by inverse dynamics of the coupled model and the activation of lower limb muscles had a good consistency in response curve trend compared with measurement results of the gait experiment, and the interaction force results had a high degree of correlation (r=0.931, P<0.01), the root mean square error was small, and the peak error of lower limb muscle activation was lower than 5%. Conclusions: The human-machine coupling model proposed in this study can effectively calculate the interaction force between human and exoskeleton. The establishment of the coupling model provides a theoretical basis for verification and iteration of the exoskeleton structure optimization and control algorithm, as well as performance evaluation on mobility assistance effects of the exoskeleton.