Approximate Entropy of the Electroencephalogram in Healthy Awake Subjects and Absence Epilepsy Patients

Naoto Burioka, Germaine G Cornelissen-Guillaume, Yoshihiro Maegaki, Franz Halberg, Daniel T. Kaplan, Masanori Miyata, Yasushi Fukuoka, Masahiro Endo, Hisashi Suyama, Yutaka Tomita, Eiji Shimizu

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

The approximate entropy (ApEn) of signals in the electroencephalogram (EEG) was evaluated in 8 healthy volunteers and in 10 patients with absence epilepsy, both during seizure-free and seizure intervals. We estimated the nonlinearity of each 3-sec EEG segment using surrogate data methods. The mean (± SD) ApEn in EEG was 0.83 ± 0.22 in healthy subjects awake with eyes closed. It was significantly lower during epileptic seizures (0.48 ± 0.05) than during seizure-free intervals (0.80 ± 0.13) (P<0.001). Nonlinearity was clearly detected in EEG signals from epileptic patients during seizures but not during seizure-free intervals or in EEG signals from healthy subjects. The ApEn of EEG signals estimated over consecutive intervals could serve to determine pathological brain activity such as that occurring during absence epilepsy.

Original languageEnglish (US)
Pages (from-to)188-193
Number of pages6
JournalClinical EEG and Neuroscience
Volume36
Issue number3
DOIs
StatePublished - Jul 2005

Bibliographical note

Copyright:
Copyright 2016 Elsevier B.V., All rights reserved.

Keywords

  • Absence Epilepsy
  • Approximate Entropy
  • Electroencephalography
  • Surrogate Data

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