Neck injury remains a significant societal problem with large financial costs and personal suffering. The cervical spine is vulnerable to severe injury in settings ranging from automotive crashes to athletic accidents. While cadaveric studies conducted here at Duke University's Injury and Orthopaedic Biomechanics Laboratory have provided valuable insights into cervical spine injury, the limitations of cadaveric experimentation have precluded a comprehensive study of the numerous variables influencing injury risk. Use of computational models to study injury has eliminated the interspecimen variability, technical challenges, and expense inherent to cadaveric experimentation. The reliability of model predictions critically hinges on an appropriate mechanical representation of the component tissues and validation of model performance against experimental data.

The Duke head and neck computational model is a hybrid lumped parameter ligamentous cervical spine with eight joints, each consisting of three discrete element pairs, connecting a finite element viscoelastic head with eight rigid body vertebrae (Hypermesh from Altair Engineering Inc., LS-INGRID, LS-DYNA, LS-PREPOST from LSTC, Livermore, CA). Each discrete element pair is comprised of a nonlinear spring and linear damper in parallel. While geometrically accurate in three dimensions, neck behavior is only modeled in the sagittal plane with two translational elements (in compression-tension and anteroposterior shear) and one rotational element (in flexion-extension) that couple the superior vertebra to the next inferior vertebra. The joint kinetics is defined about the center of rotation, a node connected to the superior body.

Neck musculature is modeled using two nonlinear springs in parallel, one for the passive and the other for the active muscle properties. The modeled muscles are based on a comprehensive set of anthropometric parameters. Using optimization to minimize muscle fatigue or maximize force in these muscles produced initial conditions representing both a relaxed and tensed muscle activation scheme respectively in which the head and neck were stable under the action of gravity. Further developments to the Duke head and neck computational model will include enhancing the muscles to follow neck curvature during bending and creating a series of pediatric models of different representative age groups.