Can a Priori Unknown Values of Biomechanical Parameters Be Determined with Sufficient Accuracy in MBS Using Sensitivity Analysis? Analyzing the Characteristics of the Interaction between Cervical Vertebra and Pedicle Screw

Ivanna Kramer, S. Bauer
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引用次数: 0

Abstract

Finite element (FE) modeling is a commonly used method to investigate the influence of medical devices, such as implants and screws, on the biomechanical behavior of the spine. Another simulation method is multibody simulation (MBS), where the model is composed of several non-deformable bodies. MBS solvers generally require a very short computing time for dynamic tasks, compared with an FE analysis. Considering this computational advantage, in this study, we examine whether parameters for which values are not known a priori can be determined with sufficient accuracy using an MBS model. Therefore, we propose a many-at-a-time sensitivity analysis method that allows us to approximate these a priori unknown parameters without requiring long simulation times. This method enables a high degree of MBS model optimization to be achieved in an iterative process. The sensitivity analysis method was applied to a simplified screw–vertebra model, consisting of an anterior anchor implant screw and vertebral body of C4. An experiment described in the literature was used as the basis for developing and assessing the potential of the method for sensitivity analyses and for validating the model’s action. The optimal model parameters for the MBS model were determined to be c = 823,224 N/m for stiffness and d = 488 Ns/m for damping. The presented method of parameter identification can be used in studies including more complex MBS spine models or to set initial parameter values that are not available as initial values for FE models.
在MBS中,生物力学参数的先验未知值能否通过灵敏度分析获得足够的准确性?颈椎与椎弓根螺钉相互作用特点分析
有限元(FE)建模是研究医疗器械(如植入物和螺钉)对脊柱生物力学行为影响的常用方法。另一种仿真方法是多体仿真(multibody simulation, MBS),即模型由多个不可变形体组成。与有限元分析相比,MBS求解器通常需要非常短的计算时间来处理动态任务。考虑到这种计算优势,在本研究中,我们研究了是否可以使用MBS模型以足够的精度确定先验值未知的参数。因此,我们提出了一种一次多灵敏度分析方法,使我们能够在不需要长时间模拟的情况下近似这些先验未知参数。该方法能够在迭代过程中实现MBS模型的高度优化。将敏感性分析方法应用于简化的螺钉-椎体模型,该模型由前牙锚钉植入螺钉和C4椎体组成。文献中描述的一个实验被用作开发和评估敏感性分析方法潜力和验证模型作用的基础。确定了MBS模型的最优模型参数为刚度c = 823,224 N/m,阻尼d = 488 Ns/m。所提出的参数识别方法可用于包括更复杂的MBS脊柱模型在内的研究,或用于设置FE模型无法提供的初始参数值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
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