期刊论文详细信息
JOURNAL OF BIOMECHANICS 卷:84
A computationally efficient strategy to estimate muscle forces in a finite element musculoskeletal model of the lower limb
Article
Navacchia, Alessandro1,2  Hume, Donald R.1  Rullkoetter, Paul J.1  Shelburne, Kevin B.1 
[1] Univ Denver, Dept Mech & Mat Engn, Denver, CO 80208 USA
[2] Mayo Clin, Dept Orthoped Surg, 200 1st St SW, Rochester, MN 55905 USA
关键词: Musculoskeletal modeling;    Finite element;    Muscle forces;    Knee;    Multiscale;   
DOI  :  10.1016/j.jbiomech.2018.12.020
来源: Elsevier
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【 摘 要 】

Concurrent multiscale simulation strategies are required in computational biomechanics to study the interdependence between body scales. However, detailed finite element models rarely include muscle recruitment due to the computational burden of both the finite element method and the optimization strategies widely used to estimate muscle forces. The aim of this study was twofold: first, to develop a computationally efficient muscle force prediction strategy based on proportional-integral-derivative (PID) controllers to track gait and chair rise experimental joint motion with a finite element musculoskeletal model of the lower limb, including a deformable knee representation with 12 degrees of freedom; and, second, to demonstrate that the inclusion of joint-level deformability affects muscle force estimation by using two different knee models and comparing muscle forces between the two solutions. The PID control strategy tracked experimental hip, knee, and ankle flexion/extension with root mean square errors below 1, and estimated muscle, contact and ligament forces in good agreement with previous results and electromyography signals. Differences up to 11% and 20% in the vasti and biceps femoris forces, respectively, were observed between the two knee models, which might be attributed to a combination of differing joint contact geometry, ligament behavior, joint kinematics, and muscle moment arms. The tracking strategy developed in this study addressed the inevitable tradeoff between computational cost and model detail in musculoskeletal simulations and can be used with finite element musculoskeletal models to efficiently estimate the interdependence between muscle forces and tissue deformation. (C) 2018 Elsevier Ltd. All rights reserved.

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