Application of nonlinear methods to respiratory data of infants during sleep

Non-linear time sequence analysis has been performed on infants sleep measurement data in order to get better insight into the respiration processes. As a first step, respiration data during different sleep stages are analyzed with nonlinear dynamic methods. Especially, the correlation integral and its slope are computed. The correlation integral characterizes the dynamics of the signal (respiration) and estimates its degrees of freedom. Changes of the dimension during sleep could be used as an indication of a high SIDS-risc (Sudden Infant Death Syndrom).