Evaluation of the influences of various force magnitudes and configurations on scoliotic curve correction using finite element analysis

Mohammad Taghi Karimi, Mohammad Hossein Ebrahimi, Ali Mohammadi*, Anthony McGarry

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)
79 Downloads (Pure)

Abstract

Scoliosis is a lateral curvature in the normally straight vertical line of the spine, and the curvature can be moderate to severe. Different treatment can be used based on severity and age of subjects, but most common treatment for this disease is using orthosis. To design orthosis types of force arrangement can be varied, from transverse loads to vertical loads or combination of them. But it is not well introduced how orthoses control scoliotic curve and how to achieve the maximum correction based on force configurations and magnitude. Therefore, it was aimed to determine the effect of various loads configurations and magnitudes on curve correction of a degenerative scoliotic subject. A scoliotic subject participated in this study. The CT-Scan of the subject was used to produce 3D model of spine. The 3D model of spine was produced by Mimics software and the finite element analysis and deformation of scoliotic curve of the spine under seven different forces and in three different conditions was determined by ABAQUS software. The Cobb angle in scoliosis curve decreased significantly by applying forces. In each condition depends on different forces, different corrections have been achieved. It can be concluded that the configurations of the force application mentioned in this study is effective to decrease the scoliosis curve. Although it is a case study, it can be used for a vast number of subjects to predict the correction of scoliosis curve before orthotic treatment. Moreover, it is recommended that this method and the outputs can be compared with clinical findings.

Original languageEnglish
Number of pages6
JournalAustralasian Physical and Engineering Sciences in Medicine
Early online date28 Nov 2016
DOIs
Publication statusE-pub ahead of print - 28 Nov 2016

Keywords

  • computational modeling
  • finite element analysis
  • orthosis
  • scoliosis

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