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A Proposed Methodology for Setting the Finite Element Models Based on Healthy Human Intervertebral Lumbar Discs

机译:一种基于健康人椎间盘突出的有限元模型建立方法

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The human intervertebral lumbar disc is a fibrocartilage structure that is located between the vertebrae of the spine. This structure consists of a nucleus pulposus, the annulus fibrosus and the cartilage endplate. The disc may be subjected to a complex combination of loads. The study of its mechanical properties and movement are used to evaluate the medical devices and implants. Some researchers have used the Finite Element Method (FEM) to model the disc and to study its biomechanics. Estimating the parameters to correctly define these models has the drawback that any small differences between the actual material and the simulation model based on FEM can be amplified enormously in the presence of nonlinearities. This paper sets out a fully automated method to determine the most appropriate material parameters to define the behavior of the human intervertebral lumbar disc models based on FEM. The methodology that is proposed is based on experimental data and the combined use of data mining techniques, Genetic Algorithms (GA) and the FEM. Firstly, based on standard tests (compression, axial rotation, shear, flexion, extension and lateral bending), three-dimensional parameterized Finite Element (FE) models were generated. Then, considering the parameters that define the proposed parameterized FE models, a Design of Experiment (DoE) was completed. For each of the standard tests, a regression technique based on Support Vector Machines (SVM) with different kernels was applied to model the stiffness and bulges of the intervertebral lumbar disc when the parameters of the FE models are changed. Finally, the best combination of parameters was achieved by applying evolutionary optimization techniques that are based on GA to the best, previously obtained regression models.
机译:人椎间盘是位于脊椎椎骨之间的纤维软骨结构。这种结构由髓核,纤维环和软骨终板组成。光盘可能会承受复杂的载荷组合。对它的机械性能和运动的研究被用于评估医疗设备和植入物。一些研究人员已使用有限元方法(FEM)对光盘进行建模并研究其生物力学。估计参数以正确定义这些模型的缺点是,在存在非线性的情况下,实际材料与基于FEM的仿真模型之间的任何细微差异都可以被极大地放大。本文提出了一种全自动方法来确定最合适的材料参数,以定义基于FEM的人类椎间盘突出症模型的行为。提出的方法是基于实验数据以及数据挖掘技术,遗传算法(GA)和FEM的组合使用。首先,基于标准测试(压缩,轴向旋转,剪切,弯曲,延伸和横向弯曲),生成了三维参数化有限元(FE)模型。然后,考虑定义建议的参数化有限元模型的参数,完成了实验设计(DoE)。对于每个标准测试,当FE模型的参数发生更改时,将基于具有不同内核的支持向量机(SVM)的回归技术应用于对腰椎间盘的刚度和凸起进行建模。最后,通过将基于遗传算法的进化优化技术应用于最佳的,先前获得的回归模型,可以实现参数的最佳组合。

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