Development and validation of a computational musculoskeletal model of the cat hind limb

D. Karabulut, Suzan Cansel Dogru, Y. Arslan, Yi-Chung Lin, M. Pandy, W. Herzog
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Abstract

The accurate prediction of individual muscle forces is a active area of Research in biomechanics. Theoretical calculation of muscle forces depends on solving the redundancy problem. Redundancy arises because the number of muscles which are active to realization of movement exceed the number of degrees of freedom of musculoskeletal model. The most preferred method to solving this problem is static optimization of musculoskeletal system. In this study, we developed a musculoskeletal model of the cat hind limb in Opensim and muscle forces were predicted using the static optimization toolbox of Opensim for a wide range of locomotor conditions. The muscle forces calculated using this model were compared with experimental muscle forces. It was observed that theoretical muscle forces were proximity to the experimental data. Taking into account these results, it has been observed that converging the experimental muscle forces can be achieved with musculoskeletal system models which will be developed by using Opensim and thus the analysis of deciding processes of the motor control mechanism of the body can be made more effectively.
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猫后肢计算肌肉骨骼模型的开发与验证
个体肌肉力量的准确预测是生物力学研究的一个活跃领域。肌肉力的理论计算取决于解决冗余问题。由于实现运动的活动肌肉数量超过了肌肉骨骼模型的自由度数量,从而产生冗余。解决这一问题的最佳方法是肌肉骨骼系统的静态优化。在这项研究中,我们在Opensim中建立了猫后肢的肌肉骨骼模型,并使用Opensim的静态优化工具箱预测了各种运动条件下的肌肉力。用该模型计算的肌力与实验肌力进行了比较。观察到理论肌肉力与实验数据接近。考虑到这些结果,我们已经观察到,将使用Opensim开发的肌肉骨骼系统模型可以实现实验肌肉力的收敛,从而可以更有效地分析身体运动控制机制的决定过程。
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