Wavelet singularity analysis for CAP sleep delineation
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abstract
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Sleep is an essential process in our life, which covers 1/3 of our lifetime. But this process can be affected by disorders producing serious consequences at physiological and behavioral level. One of the major indexes connected to the sleep disorders is the dynamic of the sleep macrostructure that is used for the assessment of sleep quality. Beyond sleep macrostructure, recently attention is also given to a finer structure of sleep called Cyclic Alternating Pattern (CAP). CAP is composed by short cortical events (A-phases), where some transition processes can be observed. With the aim to unveil properties of this transition phenomenon, in this work, we present a wavelet singularity analysis of the EEG signal during the onset and offset of A-phases. The results showed that EEG signal presents significant differences between A-phases and activity of background when the average singularity is considered. This finding can help both in better delineating the A-phases of CAP sleep and in understanding the mechanisms behind the CAP dynamics. © 2019 IEEE.
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A-phase; CAP sleep; Hölder exponent; Singularity Bioinformatics; Wavelet analysis; A-phase; Behavioral level; CAP sleep; Macrostructures; Singularity; Transition phenomenon; Transition process; Wavelet singularity; Sleep research
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