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C4–C5 segment finite element model development, validation, and load-sharing investigation

Authors
Journal
Journal of Biomechanics
0021-9290
Publisher
Elsevier
Publication Date
Volume
42
Issue
4
Identifiers
DOI: 10.1016/j.jbiomech.2008.11.036
Keywords
  • Cervical Spine
  • Motion Segment
  • Finite Element Model
  • Load Sharing
Disciplines
  • Biology

Abstract

Abstract Detailed cervical spine models are necessary to better understand cervical spine response to loading, improve our understanding of injury mechanisms, and specifically for predicting occupant response and injury in auto crash scenarios. The focus of this study was to develop a C4–C5 finite element model with accurate representations of each tissue within the segment. This model incorporates more than double the number of elements of existing models, required for accurate prediction of response. The most advanced material data available were then incorporated using appropriate nonlinear constitutive models to provide accurate predictions of response at physiological levels of loading. This tissue-scale segment model was validated against a wide variety of experimental data including different modes of loading (axial rotation, flexion, extension, lateral bending, and translation), and different load levels. In general, the predicted response of the model was within the single standard deviation response corridors for both low and high load levels. Importantly, this model demonstrates that appropriate refinement of the finite element mesh, representation at the tissue level, and sufficiently detailed material properties and constitutive models provide excellent response predictions without calibration of the model to experimental data. Load sharing between the disc, ligaments, and facet joints was investigated for various modes of loading, and the dominant load-bearing structure was found to correlate with typical anatomical injury sites for these modes of loading. The C4–C5 model forms the basis for the development of a full cervical spine model. Future studies will focus on tissue-level injury prediction and dynamic response.

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