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. However, conventional dynamic simulation frameworks have limitations due to their reliance on experimental data and their inability to capture comprehensive biomechanical signals and dynamic responses. To address these challenges, we introduce an optimization-based dynamic simulation framework that integrates a complete neuromusculoskeletal feedback loop, rigid-body dynamics, human-exoskeleton interaction, and foot-ground contact. 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 validate the effectiveness 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 effectively and accurately capture the qualitative differences in muscle activity associated with different functions, as well as the evolutionary patterns of muscle activity and kinematic signals under varying walking conditions. 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.

翻译：耦合神经肌肉骨骼-外骨骼系统的建模与仿真在人体生物力学分析以及外骨骼设计与控制中发挥着关键作用。然而，传统动态仿真框架因依赖实验数据且无法捕获全面的生物力学信号与动态响应而存在局限性。为解决这些挑战，我们提出了一种基于优化的动态仿真框架，该框架整合了完整的神经肌肉骨骼反馈回路、刚体动力学、人-外骨骼相互作用以及足-地接触。无需依赖实验测量或经验数据，我们的框架采用逐步优化过程来确定肌肉反射参数，并考虑多维度准则。这使得框架能够生成完整的运动学与生物力学信号，包括肌肉激活、肌肉力、关节力矩等——这些信号通常难以通过实验测量。为验证框架有效性，我们将仿真结果与一名健康受试者穿戴外骨骼在不同速度（0.9、1.0和1.1米/秒）和地形（平地与上坡）下行走的实验数据进行比较。结果表明，我们的框架能够有效且准确地捕获与不同功能相关的肌肉活动定性差异，以及不同行走条件下肌肉活动与运动学信号的演化模式。所提出的仿真框架有望促进人-外骨骼耦合系统的步态分析与性能评估，并支持新型外骨骼设计与控制策略的高效低成本测试。