Modelling the Breath by Breath Variability in Respiratory Data

摘要: The spontaneous temporal variability in respiratory data, sampled at each breath or by other uniform sampling means, has been shown to consist of a non-random structure (1,2,3), along with stochastic variations. Attempts identify the periodic characteristics, if any, have made help Fourier methods frequency domain and autocorrelation time (2,4). Limitations discrete transform and, more importantly, nonstationary character periodicities data makes it difficult place confidence results analysis these methods.