A Model for Prediction of Bone Stiffness Using a Mechanical Approach of Composite Materials.
From: Department of Materials Science & Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA. dominique.perreux@univ-fcomte.fr
Journal of biomechanical engineering
- Publish Date: Aug 2007
- ISSN: 0148-0731
- Volume: 129
- Issue: 4
- Pages: 494-502
- Medium: Print
- Language: English
- Citation (JAMA): Perreux Dominique M, Johnson W Steven, et al. A Model for Prediction of Bone Stiffness Using a Mechanical Approach of Composite Materials.. Aug 2007;129:494-502
Abstract
A model to predict the bone stiffness is presented in this paper. The objective is to obtain a description of bone stiffness of a representative elementary volume (REV) based on a small set of physical parameters. The main idea is to use measurable information related to the orientation and the density of a basic elementary submicrostructure (ESMS). This ESMS is the first arrangement of the basic components. A simple rule-of-mixtures approach is used to provide the elastic properties for the ESMS. The basic properties are dependent on the volume fraction of the mineralized phase. The orientation and the density of the ESMS is described by a tensor and a scalar, respectively. The model is used to obtain the elastic properties of both the cortical and trabecular bones. Data from femoral bone are used to verify this approach.
Mesh Headings (Keywords): Animals, Biomechanics, Bone and Bones, Elasticity, Humans, Models, Biological
Check for Full Text / PubMed Unique Identifier (PMID): 17655470
This abstract is part of PubMed, a service of the U.S. National Library of Medicine. PubMed includes more than 17 million citations from MEDLINE and other life science journals for biomedical articles. See Copyright and Disclaimers.
Linked medical terms appearing on this page are added by Healia to help readers find more information and are not part of the original PubMed document.
The data herein was last updated on July 8th, 2008 and may not reflect the most current and accurate data available from NLM.
