Improvement in the process of designing a new artificial human intervertebral lumbar disc combining soft computing techniques and the finite element method

Abstract

Human intervertebral lumbar disc degeneration is painful and difficult to treat, and is often magnified when the patient is overweight. When the damage is excessive, the disc is replaced by a non-natural or artificial disc. Artificial discs sometimes have the disadvantage of totally different behavior from that of the natural disc. This affects substantially the quality of treated patient’s life. The Finite Element Method (FEM) has been used for years to design an artificial disc, but it involves a high computational cost. This paper proposes a methodology to design a new Artificial Human Intervertebral Lumbar Disc by combining FEM and soft computing techniques. Firstly, a three-dimensional Finite Element (FE) model of a healthy disc was generated and validated experimentally from cadavers by standard tests. Then, an Artificial Human Intervertebral Lumbar Disc FE model with a core of Polycarbonate Polyurethane (PCU) was modeled and parameterized. The healthy and artificial disc FE models were both assembled between lumbar vertebrae L4-L5, giving place to the Functional Spinal Unit (FSU). A Box-Behnken Design of Experiment (DoE) was generated that considers the parameters that define the geometry of the proposed artificial disc FE model and the load derived from the patient’s height and body weight. Artificial Neural Networks (ANNs) and regression trees that are based on heuristic methods and evolutionary algorithms were used for modeling the compression and lateral bending stiffness from the FE simulations of the artificial disc. In this case, ANNs proved to be the models that had the best generalization ability. Finally, the best geometry of the artificial disc proposed when the patient’s height and body weight were considered was achieved by applying Genetic Algorithms (GA) to the ANNs. The difference between the compression and lateral bending stiffness obtained from the healthy and artificial discs did not differ significantly. This indicated that the proposed methodology provides a powerful tool for the design and optimization of an artificial prosthesis.