SENSITIVITY ANALYSIS FOR EVALUATING NONLINEAR MODELS OF LUNG-MECHANICS

We present a combined theoretical and numerical procedure for sensitiv ity analyses of lung mechanics models that are nonlinear in both state variables and parameters. We apply the analyses to a recently propose d nonlinear lung model which incorporates a wide range of potential no nlinear identification conditions including nonlinear viscoelastic tis sues, airway inhomogeneities via a parallel airway resistance distribu tion function, and a nonlinear block-structure paradigm. Additionally, we examine a system identification procedure which fits time-and freq uency-domain data simultaneously. Model nonlinearities motivate sensit ivity analyses involving numerical approximation of sensitivity coeffi cients. Examination of the normalized sensitivity coefficients provide s direct insight on the relative importance of each model parameter, a nd hence the respective mechanism. More formal quantification of param eter uniqueness requires approximation of the paired and multidimensio nal parameter confidence regions. Combined with parameter estimation, we use the sensitivity analyses to justify tissue nonlinearities in mo deling of lung mechanics for healthy and airway constricted conditions , and to justify both airway inhomogeneities and tissue nonlinearities during broncoconstriction. The tools in this paper are general and ca n be applied to a wide class of nonlinear models. (C) 1998 Biomedical Engineering Society.