The modeling and simulation of coupled neuromusculoskeletal-exoskeletal systems play a crucial role in human biomechanical analysis, as well as in the design and control of exoskeletons. This study incorporates the integration of exoskeleton models into a reflex-based gait model, emphasizing human-exoskeleton interaction. Specifically, we introduce an optimization-based dynamic simulation framework that integrates a neuromusculoskeletal feedback loop, multibody dynamics, human-exoskeleton interaction, and foot-ground contact. The framework advances in human-exoskeleton interaction and muscle reflex model refinement. Without relying on experimental measurements or empirical data, our framework employs a stepwise optimization process to determine muscle reflex parameters, taking into account multidimensional criteria. This allows the framework to generate a full range of kinematic and biomechanical signals, including muscle activations, muscle forces, joint torques, etc., which are typically challenging to measure experimentally. To evaluate the validity of the framework, we compare the simulated results with experimental data obtained from a healthy subject wearing an exoskeleton while walking at different speeds (0.9, 1.0, and 1.1 m/s) and terrains (flat and uphill). The results demonstrate that our framework can capture the qualitative differences in muscle activity associated with different functions, as well as the evolutionary patterns of muscle activity and kinematic signals with respect to varying walking conditions, with the Pearson correlation coefficient R > 0.7. Simulations of the human walking with the exoskeleton in both passive mode and assisting mode at a peak torque of 20 N⋅m are further conducted to investigate the effect of exoskeleton assistance on human biomechanics. The simulation framework we propose has the potential to facilitate gait analysis and performance evaluation of coupled human-exoskeleton systems, as well as enable efficient and cost-effective testing of novel exoskeleton designs and control strategies.

神经肌肉骨骼-外骨骼耦合系统的建模和仿真在人体生物力学分析以及外骨骼的设计和控制中发挥着至关重要的作用。这项研究将外骨骼模型集成到基于反射的步态模型中，强调人与外骨骼的相互作用。具体来说，我们引入了一种基于优化的动态模拟框架，该框架集成了神经肌肉骨骼反馈回路、多体动力学、人体外骨骼交互和脚地接触。该框架在人类外骨骼交互和肌肉反射模型细化方面取得了进展。我们的框架不依赖实验测量或经验数据，采用逐步优化过程来确定肌肉反射参数，同时考虑多维标准。这使得该框架能够生成全方位的运动学和生物力学信号，包括肌肉激活、肌肉力量、关节扭矩等，这些信号通常很难通过实验测量。为了评估该框架的有效性，我们将模拟结果与佩戴外骨骼的健康受试者以不同速度（0.9、1.0 和 1.1 m/s）和地形（平坦和上坡）行走时获得的实验数据进行了比较。结果表明，我们的框架可以捕获与不同功能相关的肌肉活动的定性差异，以及不同步行条件下肌肉活动和运动信号的进化模式，皮尔逊相关系数 R > 0.7。进一步对峰值扭矩为 20 N·m 的外骨骼在被动模式和辅助模式下的人体行走进行模拟，以研究外骨骼辅助对人体生物力学的影响。我们提出的仿真框架有潜力促进耦合人外骨骼系统的步态分析和性能评估，并能够对新颖的外骨骼设计和控制策略进行高效且经济高效的测试。