APPLICATION OF THE CORRELATION INTEGRAL TO RESPIRATORY DATA OF INFANTS DURING REM-SLEEP

Non-linear time sequence analysis has been performed on infant sleep m easurement data in order to obtain more information about the respirat ory processes. As a first step, respiration data during REM sleep were analysed with methods from non-linear dynamics, especially, the corre lation integral and the slope of its log-log plot, representing the co rrelation dimension. Before calculation of the correlation integral, a special kind of filtering has to be applied to the data. This filteri ng algorithm is a state space and singular value decomposition-based n oise reduction method, and it is used to separate the noise and signal subspaces. The dynamics of a signal (in our case data from the respir atory process) and its degrees of freedom can be characterised by the correlation integral and by the correlation dimension, respectively. T he main result of this study is that the highly irregular-looking brea thing patterns during REM sleep could be described by a deterministic system, and finally the physiological significance of this finding is discussed.