https://doi.org/10.1140/epjs/s11734-023-01047-5
Regular Article
Statistical analysis of local fluctuations in the signal profile: application to electrocorticograms
1
Saratov State University, Astrakhanskaya Str. 83, 410012, Saratov, Russia
2
Regional Scientific and Educational Mathematical Center “Mathematics of Future Technologies”, 410012, Saratov, Russia
Received:
27
August
2023
Accepted:
21
November
2023
Published online:
1
December
2023
Local fluctuations in the profile can vary significantly for nonstationarity signals produced, e.g., by physiological systems. To correctly identify distinctions between the states of such systems, these fluctuations should be processed thoroughly. In the current study, we apply extended detrended fluctuation analysis (EDFA) to simulated data with various signal distortions and to electrical activity signals in the brains of mice under normal conditions and after one day of sleep deprivation. We show that the latter states can be distinguished by several EDFA scaling exponents, but their performance is scale dependent. The maximum differences between the states quantified by conventional and extended fluctuation analysis may be associated with different scale ranges. We conclude that the statistical analysis of local fluctuations in the signal profile is useful for developing diagnostically significant markers of the system state.
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© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
