Lamberto Giuliano, Martelli Saulo, Cappozzo Aurelio, Mazzà Claudia
Department of Mechanical Engineering, University of Sheffield, S1 3JD, United Kingdom; INSIGNEO Institute for in silico Medicine, University of Sheffield, United Kingdom.
Medical Device Research Institute, School of Computer Science, Engineering and Mathematics, Flinders University, Australia.
J Biomech. 2017 Sep 6;62:68-76. doi: 10.1016/j.jbiomech.2016.07.042. Epub 2016 Aug 24.
Musculoskeletal models are widely used to estimate joint kinematics, intersegmental loads, and muscle and joint contact forces during movement. These estimates can be heavily affected by the soft tissue artefact (STA) when input positional data are obtained using stereophotogrammetry, but this aspect has not yet been fully characterised for muscle and joint forces. This study aims to assess the sensitivity to the STA of three open-source musculoskeletal models, implemented in OpenSim. A baseline dataset of marker trajectories was created for each model from experimental data of one healthy volunteer. Five hundred STA realizations were then statistically generated using a marker-dependent model of the pelvis and lower limb artefact and added to the baseline data. The STA׳s impact on the musculoskeletal model estimates was finally quantified using a Monte Carlo analysis. The modelled STA distributions were in line with the literature. Observed output variations were comparable across the three models, and sensitivity to the STA was evident for most investigated quantities. Shape, magnitude and timing of the joint angle and moment time histories were not significantly affected throughout the entire gait cycle, whereas magnitude variations were observed for muscle and joint forces. Ranges of contact force variations differed between joints, with hip variations up to 1.8 times body weight observed. Variations of more than 30% were observed for some of the muscle forces. In conclusion, musculoskeletal simulations using stereophotogrammetry may be safely run when only interested in overall output patterns. Caution should be paid when more accurate estimated values are needed.
肌肉骨骼模型被广泛用于估计运动过程中的关节运动学、节段间负荷以及肌肉和关节接触力。当使用立体摄影测量法获取输入位置数据时,这些估计值可能会受到软组织伪影(STA)的严重影响,但肌肉和关节力的这一方面尚未得到充分表征。本研究旨在评估在OpenSim中实现的三种开源肌肉骨骼模型对STA的敏感性。根据一名健康志愿者的实验数据,为每个模型创建了一个标记轨迹的基线数据集。然后使用骨盆和下肢伪影的标记依赖模型统计生成500个STA实现,并将其添加到基线数据中。最后,使用蒙特卡洛分析量化STA对肌肉骨骼模型估计的影响。模拟的STA分布与文献一致。在这三个模型中观察到的输出变化具有可比性,并且对于大多数研究的量,对STA的敏感性是明显的。在整个步态周期中,关节角度和力矩时间历程的形状、大小和时间没有受到显著影响,而肌肉和关节力的大小变化则被观察到。不同关节的接触力变化范围不同,观察到髋关节的变化高达体重的1.8倍。一些肌肉力的变化超过了30%。总之,当只对总体输出模式感兴趣时,可以安全地运行使用立体摄影测量法的肌肉骨骼模拟。当需要更准确的估计值时,应谨慎行事。