A Comprehensive Dynamic Simulation Framework for Coupled Neuromusculoskeletal-Exoskeletal Systems

TL;DR

This paper presents an optimization-based simulation framework for coupled neuromusculoskeletal-exoskeletal systems that generates comprehensive biomechanical signals without experimental data, aiding in exoskeleton design and gait analysis.

Contribution

It introduces a novel simulation framework integrating feedback loops and optimization to produce detailed biomechanical signals without relying on empirical data.

Findings

Accurately captures muscle activity patterns across different walking conditions.

Demonstrates effective simulation of biomechanical signals matching experimental data.

Facilitates analysis and design of human-exoskeleton systems.

Abstract

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.