Experimental Validation of a Finite Element Model of the Proximal Femur Using Digital Image Correlation and a Composite Bone Model

Journal of Biomechanical Engineering - Tập 133 Số 1 - 2011
Alexander Dickinson1, Andrew C. Taylor2, H. Öztürk1, M. Browne1
1Bioengineering Research Group, University of Southampton, Highfield, Southampton, Hants SO17 1BJ, UK
2Finsbury Development Limited, 13 Mole Business Park, Randalls Road, Leatherhead, Surrey KT22 0BA, UK

Tóm tắt

Computational biomechanical models are useful tools for supporting orthopedic implant design and surgical decision making, but because they are a simplification of the clinical scenario they must be carefully validated to ensure that they are still representative. The goal of this study was to assess the validity of the generation process of a structural finite element model of the proximal femur employing the digital image correlation (DIC) strain measurement technique. A finite element analysis model of the proximal femur subjected to gait loading was generated from a CT scan of an analog composite femur, and its predicted mechanical behavior was compared with an experimental model. Whereas previous studies have employed strain gauging to obtain discreet point data for validation, in this study DIC was used for full field quantified comparison of the predicted and experimentally measured strains. The strain predicted by the computational model was in good agreement with experimental measurements, with R2 correlation values from 0.83 to 0.92 between the simulation and the tests. The sensitivity and repeatability of the strain measurements were comparable to or better than values reported in the literature for other DIC tests on tissue specimens. The experimental-model correlation was in the same range as values obtained from strain gauging, but the DIC technique produced more detailed, full field data and is potentially easier to use. As such, the findings supported the validity of the model generation process, giving greater confidence in the model’s predictions, and digital image correlation was demonstrated as a useful tool for the validation of biomechanical models.

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