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Experimental and Computational Characterization of Three-Dimensional Cervical Spine Flexibility
Technical Paper
2000-01-SC11
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English
Abstract
Cervical spine behavior for generalized loading is often
characterized using a full three-dimensional flexibility matrix.
While experimental studies have been aimed at determining cervical
motion segment behavior, their accuracy and utility have been
limited both experimentally and analytically. For example, the
nondiagonal terms, describing coupled motions, of the matrices have
often been omitted. Flexibility terms have been primarily
represented as constants despite the known nonlinear stiffening
response of the spine. Moreover, there is presently no study
validating the flexibility approach for predicting vertebral
motions; nor have the effects of approximations and simplifications
to the matrix representations been quantified. Yet, the flexibility
matrix currently forms the basis for all multibody dynamics models
of cervical spine motion. Therefore, the purpose of this study is
to fully quantify the flexibility relationships for cervical motion
segments, examine the diagonal and nondiagonal components of the
flexibility matrix, and determine the extent to which multivariable
relationships improve cervical spine motion prediction. To that
end, using unembalmed human cervical spine motion segments, a full
battery of flexibility tests were performed for a neutral
orientation and also following an axial pretorque. Primary and
coupled matrix components were described using linear and piecewise
nonlinear incremental constants. An additional approach utilized
multivariable incremental relationships to describe matrix terms.
Measured motions were predicted using structural flexibility
methods and were evaluated using RMS error of the difference
between the predicted and measured responses. Results of this study
provide a full set of flexibility relationships describing primary
and coupled motions for C3-C4 and C5-C6 motion segment levels.
Analysis of these data indicates that a flexibility matrix using
incremental responses describing primary and coupled motions offers
improved predictions over using linear methods (p<0.01).
However, there is no significant improvement using more generalized
nonlinear terms represented by the multivariable functional
approach (p<0.2). Based on these findings, it is suggested that
a multivariable approach for flexibility is more demanding
experimentally and analytically while not offering improved motion
prediction.
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