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Linear and Non-linear Analysis of EEG During Sleep Deprivation in Subjects with and Without Epilepsy

Marino, Silvia
•
Silveri, Giulia
•
Bonanno, Lilla
altro
Accardo, Agostino
2020
  • conference object

Abstract
EEG has a central role in the diagnosis of epileptiform abnormalities helpful in diagnosing epilepsy. Since irregularities are random and sporadic events, easily activated in the initial phase of sleep but difficult to observe in a standard EEG examination, sleep deprivation is a frequent condition to be used. Thus, in this study the EEG monitoring of 44 subjects, 14 without epilepsy and 30 with epilepsy, afferent to the IRCCS Centro Neurolesi “Bonino Pulejo” of Messina were examined after sleep deprivation the day before performing the registration. EEGs were recorded according to the international setting system using nineteen channels. The normalized power spectral densities in delta (2– 4 Hz), theta (4–8 Hz), alpha (8–13 Hz) and beta (13–30 Hz) band were computed and the non-linear parameters such as beta exponent, fractal dimension and zero crossing were considered. The differences between the sleep and awake were significant in almost all the channels in the beta band and in posterior areas for beta exponent, fractal dimension and zero crossing in normal subjects. In epileptic patients they were significant in all the channels in the delta band and for the non-linear parameters, and in several ones in theta and beta bands. Even if in posterior areas all the spectral and the non-linear parameters showed different values between epileptic and healthy subjects, no significant differences were found. The results suggest that analysis of spectral power as well as of complexity, obtained by non-linear parameters, could be used to identify differences between healthy and epileptic patients.
DOI
10.1007/978-3-030-31635-8_15
WOS
WOS:000582693600015
Archivio
http://hdl.handle.net/11368/2951139
info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85075898765
Diritti
open access
license:copyright editore
license:copyright editore
license:digital rights management non definito
FVG url
https://arts.units.it/request-item?handle=11368/2951139
Soggetti
  • EEG

  • Epilepsy

  • Sleep deprivation

Web of Science© citazioni
0
Data di acquisizione
Mar 27, 2024
Visualizzazioni
2
Data di acquisizione
Apr 19, 2024
Vedi dettagli
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