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This study examined the statistical properties of breath-to-breath variations in the inspiratory and expiratory volumes and times during rest and light exercise. Sixty data sets were analyzed. Initial data and residuals after fitting time-series models were examined for 1) sustained periodicities with use of spectral analysis, 2) temporal changes in signal power with use of evolutionary spectral analysis, and 3) auto- and cross correlations with use of a portmanteau test. The major findings were as follows: 1) no sustained periodic components were detected; 2) temporal changes in signal power were normally present, but these did not affect significantly the results from time-series modeling; 3) for all variables, a simple autoregressive moving average (ARMA) AR1MA1 model generally described the autocorrelation; 4) considerable cross correlation remained between residuals from the AR1MA1 model; 5) relationships between variables could be described by using a multivariate time-series model; 6) residual fluctuations in end-tidal PCO2 had little influence; and 7) responses were broadly similar between rest and exercise, although some quantitative differences were found. The multivariate model provides a description of the structure of the interrelationships between cycle variables in a quantitative and a qualitative form.

Original publication




Journal article


J Appl Physiol (1985)

Publication Date





2287 - 2296


Carbon Dioxide, Data Interpretation, Statistical, Humans, Models, Biological, Multivariate Analysis, Oxygen Consumption, Regression Analysis, Respiratory Function Tests, Respiratory Mechanics