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Muscle optimization techniques impact the magnitude of calculated hip joint contact forces

机译:肌肉优化技术会影响计算得出的髋关节接触力的大小

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摘要

In musculoskeletal modelling, several optimization techniques are used to calculate muscle forces, which strongly influence resultant hip contact forces (HCF). The goal of this study was to calculate muscle forces using four different optimization techniques, i.e., two different static optimization techniques, computed muscle control (CMC) and the physiological inverse approach (PIA). We investigated their subsequent effects on HCFs during gait and sit to stand and found that at the first peak in gait at 15-20% of the gait cycle, CMC calculated the highest HCFs (median 3.9 times peak GRF (pGRF)). When comparing calculated HCFs to experimental HCFs reported in literature, the former were up to 238% larger. Both static optimization techniques produced lower HCFs (median 3.0 and 3.1 pGRF), while PIA included muscle dynamics without an excessive increase in HCF (median 3.2 pGRF). The increased HCFs in CMC were potentially caused by higher muscle forces resulting from co-contraction of agonists and antagonists around the hip. Alternatively, these higher HCFs may be caused by the slightly poorer tracking of the net joint moment by the muscle moments calculated by CMC. We conclude that the use of different optimization techniques affects calculated HCFs, and static optimization approached experimental values best. © 2014 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res.
机译:在肌肉骨骼建模中,使用了几种优化技术来计算肌肉力量,这些力量会极大地影响合成的髋部接触力(HCF)。这项研究的目的是使用四种不同的优化技术来计算肌肉力量,即两种不同的静态优化技术,即计算肌肉控制(CMC)和生理逆向方法(PIA)。我们研究了它们对步态在坐立时对HCF的后续影响,发现在步态的第一个高峰(步态周期的15-20%),CMC计算出了最高的HCF(中值是峰GRF(pGRF)的3.9倍)。当将计算得出的HCF与文献中报道的实验HCF进行比较时,前者最大可增加238%。两种静态优化技术均产生较低的HCF(中值3.0和3.1 pGRF),而PIA包括肌肉动力学,而HCF却没有过多增加(中值3.2 pGRF)。 CMC中HCF的增加可能是由于激动剂和拮抗剂在髋关节周围收缩引起的更高的肌肉力量引起的。或者,这些较高的HCF可能是由于CMC计算的肌肉力矩对净关节力矩的跟踪效果稍差所致。我们得出的结论是,使用不同的优化技术会影响所计算的HCF,而静态优化最接近实验值。 ©2014骨科研究学会。由Wiley Periodicals,Inc.出版。J Orthop Res。

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