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

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.