A frequency domain approach to nonlinear and structure identification for long memory systems: Application to lung mechanics

From the input-output point of view, many nonlinear biological systems disp lay long memory characteristics which can become a critical issue using non parametric time-domain kernel identification due to inevitable truncation o f memory length. To avoid these limitations, we present an alternative appr oach in the frequency domain with application to lung mechanics. Generally, if the system is excited with a periodic wave form, the response will appr oach a steady state which dominates the long memory transients. Thus, we hy pothesized that the kernels at discrete frequencies will not be significant ly affected by memory truncation. To test this, we extended the Frequency k ernel analysis of Victor and Shapley (Biophys. J. 29:459-484, 1980) to a no nwhite input spectrum and developed a new structure test in the frequency d omain to differentiate between Wiener and Hammerstein models. These techniq ues were applied to measured pressure-flow data of isolated lung lobes. The results showed that (1) the important nonlinearities in the pressure-flow relation are of second order, (2) the frequency kernels of the lobes were s imilar for flat and ventilatory-like input spectra, and (3) the structure t est strongly suggested that the pressure-flow relationship during tidal-lik e excursions is consistent with a Wiener structure. (C) 1999 Biomedical Eng ineering Society. [S0090-6964(99)00101-0].