Zeng Wei, Hume Donald R, Lu Yongtao, Fitzpatrick Clare K, Babcock Colton, Myers Casey A, Rullkoetter Paul J, Shelburne Kevin B
Center for Orthopaedic Biomechanics, University of Denver, Denver, CO, United States.
Department of Mechanical Engineering, New York Institute of Technology, New York, NY, United States.
Front Bioeng Biotechnol. 2023 May 18;11:1153692. doi: 10.3389/fbioe.2023.1153692. eCollection 2023.
Skeletal muscles have a highly organized hierarchical structure, whose main function is to generate forces for movement and stability. To understand the complex heterogeneous behaviors of muscles, computational modeling has advanced as a non-invasive approach to evaluate relevant mechanical quantities. Aiming to improve musculoskeletal predictions, this paper presents a framework for modeling 3D deformable muscles that includes continuum constitutive representation, parametric determination, model validation, fiber distribution estimation, and integration of multiple muscles into a system level for joint motion simulation. The passive and active muscle properties were modeled based on the strain energy approach with Hill-type hyperelastic constitutive laws. A parametric study was conducted to validate the model using experimental datasets of passive and active rabbit leg muscles. The active muscle model with calibrated material parameters was then implemented to simulate knee bending during a squat with multiple quadriceps muscles. A computational fluid dynamics (CFD) fiber simulation approach was utilized to estimate the fiber arrangements for each muscle, and a cohesive contact approach was applied to simulate the interactions among muscles. The single muscle simulation results showed that both passive and active muscle elongation responses matched the range of the testing data. The dynamic simulation of knee flexion and extension showed the predictive capability of the model for estimating the active quadriceps responses, which indicates that the presented modeling pipeline is effective and stable for simulating multiple muscle configurations. This work provided an effective framework of a 3D continuum muscle model for complex muscle behavior simulation, which will facilitate additional computational and experimental studies of skeletal muscle mechanics. This study will offer valuable insight into the future development of multiscale neuromuscular models and applications of these models to a wide variety of relevant areas such as biomechanics and clinical research.
骨骼肌具有高度组织化的层次结构，其主要功能是产生运动和稳定所需的力量。为了理解肌肉复杂的异质性行为，计算建模已发展成为一种评估相关力学量的非侵入性方法。旨在改进肌肉骨骼预测，本文提出了一个用于对三维可变形肌肉进行建模的框架，该框架包括连续体本构表示、参数确定、模型验证、纤维分布估计以及将多个肌肉集成到系统层面以进行关节运动模拟。基于应变能方法和希尔型超弹性本构定律对被动和主动肌肉特性进行建模。使用被动和主动兔腿肌肉的实验数据集进行参数研究以验证模型。然后实施具有校准材料参数的主动肌肉模型，以模拟多个股四头肌在深蹲过程中的膝盖弯曲。利用计算流体动力学（CFD）纤维模拟方法估计每块肌肉的纤维排列，并应用内聚接触方法模拟肌肉之间的相互作用。单块肌肉的模拟结果表明，被动和主动肌肉的伸长响应均与测试数据范围相匹配。膝盖屈伸的动态模拟显示了该模型在估计主动股四头肌响应方面的预测能力，这表明所提出的建模流程对于模拟多种肌肉配置是有效且稳定的。这项工作为复杂肌肉行为模拟提供了一个有效的三维连续体肌肉模型框架，这将有助于对骨骼肌力学进行更多的计算和实验研究。这项研究将为多尺度神经肌肉模型的未来发展以及这些模型在生物力学和临床研究等广泛相关领域的应用提供有价值的见解。
