Estimation of the gas exchange threshold in humans: a time series approach

An autoregressive moving average model is presented for detecting the gas e xchange threshold (GET) from gas exchange response data taken during an inc remental exercise test. The approach has the advantage of modelling the ser ial correlation in the noise between observations from the same subject. Th e model is fitted by maximum likelihood and a breakpoint or threshold in th e mean function is the estimated GET. It is shown how an estimate of standa rd error can be obtained by bootstrapping the residuals from the fitted mod el. To evaluate the approach, gas exchange data on 14 healthy subjects duri ng a ramp exercise test (20 W.min(-1)) to the limits of tolerance, were ana lysed. The results are compared to the v-slope method and to the method of maximum likelihood assuming independent noise.