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首页> 外文期刊>Journal of Biomechanics >Femoral strain during walking predicted with muscle forces from static and dynamic optimization
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Femoral strain during walking predicted with muscle forces from static and dynamic optimization

机译：步行过程中的股骨菌株预测来自静态和动态优化的肌肉力

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Mechanical strain plays an important role in skeletal health, and the ability to accurately and non-invasively quantify bone strain in vivo may be used to develop preventive measures that improve bone quality and decrease fracture risk. A non-invasive estimation of bone strain requires combined musculoskeletal - finite element modeling, for which the applied muscle forces are usually obtained from static optimization (SO) methods. In this study, we compared finite element predicted femoral strains in walking using muscle forces obtained from SO to those obtained from forward dynamics (FD) simulation. The general trends in strain distributions were similar between FD and SO derived conditions and both agreed well with previously reported in vivo strain gage measurements. On the other hand, differences in peak maximum (epsilon(max)) and minimum (epsilon(min)) principal strain magnitudes were as high as 32% between FD (epsilon(max)/epsilon(min)=945/ - 1271 mu epsilon) and SO (epsilon(max)/epsilon(min)= 752/ - 859 mu epsilon). These large differences in strain magnitudes were observed during the first half of stance, where SO predicted lower gluteal muscle forces and virtually no co-contraction of the hip adductors compared to FD. The importance of these results will likely depend on the purpose/application of the modeling procedure. If the goal is to obtain a generalized strain distribution for adaptive bone remodeling algorithms, then traditional SO is likely sufficient. In cases were strain magnitudes are critical, as is the case with fracture risk assessment, bone strain estimation may benefit by including muscle activation and contractile dynamics in SO, or by using FD when practical. (C) 2016 Elsevier Ltd. All rights reserved.
机译：机械应变在骨骼健康中起重要作用，并且可以使用准确和非侵入性地量化体内骨菌株的能力来开发改善骨质质量并降低骨折风险的预防措施。骨菌株的非侵入性估计需要组合的肌肉骨骼 - 有限元建模，其中施加的肌肉力通常从静态优化（SO）方法获得。在这项研究中，我们将有限元预测股株使用从向前动力学（FD）模拟中获得的肌肉力进行行走。在FD和所以衍生的条件之间存在应变分布的一般趋势，并且在体内应变计测量中先前报道的两者都很好。另一方面，峰值最大值的差异（ε（max））和最小值（ε（min））主应变幅度高达FD（ε（MAX）/ epsilon（min）= 945 / - 1271μm之间的32％ ε）等（ε（max）/ epsilon（min）= 752 / - 859 mu epsilon）。在上半部分的上半部分期间观察到这些巨大差异，其中如此预测较低的衰弱肌力，并且与FD相比，几乎没有髋关节制剂的共收缩。这些结果的重要性可能取决于建模程序的目的/申请。如果目标是获得自适应骨改造算法的广义应变分布，那么传统的所以可能就足够了。在病例是应变幅度至关重要的，与骨折风险评估的情况一样，骨应变估计可以通过包括肌肉激活和收缩动力学，或者在实际使用FD时受益。 （c）2016 Elsevier Ltd.保留所有权利。

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