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...

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Bibliographic Details
Published in1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Vol. 6; pp. 2620 - 2621
Main Authors Pilgram, B., Schappacher, W., Pfurtscheller, G.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.1992
Subjects
Correlation
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Summary: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).
ISBN:0780307852
9780780307858
DOI:10.1109/IEMBS.1992.5761617