Sleep-disordered breathing: statistical characteristics of joint recurrent indicators in EEG activity

Anton O. Selskii, Evgeniy N. Egorov,Rodion Ukolov, Anna A. Orlova, Evgeniya E. Drozhdeva, Sergei A. Mironov, Yurii V. Doludin,Mikhail V. Agaltsov, Oxana M. Drapkina

RUSSIAN OPEN MEDICAL JOURNAL(2023)

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Abstract
The purpose of this study was to identify promising candidates for the role of biomarkers associated with different degrees of the apnea-hypapnea index in patients using polysomnographic recordings.Material - The study used polysomnography data recorded in 30 patients with nocturnal respiratory dysfunction in the form of obstructive sleep apnea syndrome.Methods - Analysis of polysomnographic recordings was carried out using a joint recurrent indicator, for which further statistical characteristics were assessed: average value, geometric mean, cubic mean, median, dispersion, standard deviation, the coefficient of variation, asymmetry indicator, kurtosis indicator.Results - For all polysomnographic recordings, joint recurrence diagrams were calculated to identify time points corresponding to specific sleep events in patients with high and low apnea-hypnea index. Based on the statistical characteristics of such events, possible candidates for the role of biomarkers to diagnose apnea syndrome are introduced.Conclusion - The article presents clustering parameters and the efficiency of dividing into clusters of statistical characteristics for two groups of patients -with high and low apnea-hypnea index. Characteristics have been identified that are promising candidates for the role of biomarkers associated with the apnea-hypnea index value.
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Key words
polysomnography,EEG,apnea,recurrence analysis,biomarkers
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