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J Appl Physiol 81: 2274-2286, 1996;
8750-7587/96 $5.00
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Journal of Applied Physiology
Vol. 81, No. 5, pp. 2274-2286, November 1996
CONTROL OF BREATHING, CIRCULATION, AND TEMPERATURE

modeling in physiology

Statistical properties of breath-to-breath variations in ventilation at constant PETCO2 and PETO2 in humans

Pei-Ji Liang, Jaideep J. Pandit, and Peter A. Robbins

University Laboratory of Physiology, Parks Road, Oxford OX1 3PT, United Kingdom

Received 29 March 1995; accepted in final form 12 July, 1996.

Liang, Pei-Ji, Jaideep J. Pandit, and Peter A. Robbins. Statistical properties of breath-to-breath variations in ventilation at constant PETCO2 and PETO2 in humans. J. Appl. Physiol. 81(5): 2274-2286, 1996.---The purpose of this study was to provide a statistical description of the breath-to-breath variations in ventilation during steady breathing in both rest and during light exercise, with the end-tidal gases controlled by using an end-tidal forcing system. Sixty data sets were studied, only one of which was white (i.e., did not show autocorrelation). Three simple autoregressive moving average (ARMA) models, i.e., AR1, AR2, and AR1MA1, and one simple state-space model were fitted to the data and resulted in white residuals in 15, 31, 46, and 48 out of 60 occasions, respectively. Evolutionary spectral analysis revealed that only 13 data sets had a constant power spectrum, although 50 were uniformly modulated. An autoregressive estimate of variance could be used to "demodulate" the data in most cases, but the results were not significantly affected by fitting the model to the demodulated data. The results indicate that 1) both simple ARMA models and a simple state-space model can describe the autocorrelation present; 2) variations in spectral power were present in the data that cannot be described by these models; and 3) these variations were often due to a uniform modulation and did not significantly affect the coefficients for the models. For these kinds of data, a heteroscedastic form of state-space model provides an attractive theoretical structure for the noise processes.

time-series models; state-space model; constant power spectrum; uniform modulation; heteroscedastic form; end-tidal partial pressure of oxygen; end-tidal partial pressure of carbon dioxide

0161-7567/96 $5.00 Copyright © 1996 the American Physiological Society




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