Modeling of respiratory system impedances in dogs
- 1 February 1987
- journal article
- research article
- Published by American Physiological Society in Journal of Applied Physiology
- Vol. 62 (2) , 414-420
- https://doi.org/10.1152/jappl.1987.62.2.414
Abstract
Mechanical impedances between 4 and 64 Hz of the respiratory system in dogs have been reported (A.C. Jackson et al. J. Appl. Physiol. 57: 34–39, 1984) previously by this laboratory. It was observed that resistance (the real part of impedance) decreased slightly with frequency between 4 and 22 Hz then increased considerably with frequency above 22 Hz. In the current study, these impedance data were analyzed using nonlinear regression analysis incorporating several different lumped linear element models. The five-element model of Eyles and Pimmel (IEEE Trans. Biomed. Eng. 28: 313–317, 1981) could only fit data where resistance decreased with frequency. However, when the model was applied to these data the returned parameter estimates were not physiologically realistic. Over the entire frequency range, a significantly improved fit was obtained with the six-element model of DuBois et al. (J. Appl. Physiol. 8: 587–594, 1956), since it could follow the predominate frequency-dependent characteristic that was the increase in resistance. The resulting parameter estimates suggested that the shunt compliance represents alveolar gas compressibility, the central branch represents airways, and the peripheral branch represents lung and chest wall tissues. This six-element model could not fit, with the same set of parameter values, both the frequency-dependent decrease in Rrs and the frequency-dependent increase in resistance. A nine-element model recently proposed by Peslin et al. (J. Appl. Physiol. 39: 523–534, 1975) was capable of fitting both the frequency-dependent decrease and the frequency-dependent increase in resistance. However, the data only between 4 and 64 Hz was not sufficient to consistently determine unique values for all nine parameters.This publication has 17 references indexed in Scilit:
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