title: Chapter 2. Mechanisms of changes in dynamic complexity of EEG patterns in epileptic brain injury
metadata.name: dc.contributor.author
metadata.value: Dik, Olga E.
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Nozdrachev, Alexander D.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2020-12-02T09:11:31Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2020-12-02T09:11:31Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2019
metadata.lang: -
metadata.name: dc.identifier.other
metadata.value: https://doi.org/10.21638/11701/9785288059322.03
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/21148
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: The second chapter is devoted to elucidating the mechanisms underlying the changes in the dynamic complexity of EEG patterns in disorders of the functional state of the brain associated with
  epileptic injuries, and modeling the possibility of automatic detection of epileptic discharges based
  on a comparative study of changes in wavelet spectra and the degree of multifractality of EEG patterns in patients with partial symptomatic epilepsy before, during and after epileptic discharges, as
  well as when opening the eyes and during hyperventilation during periods of absence of epileptic
  discharges. Comparative analysis of changes in wavelet spectra and in degree of multifractality of
  EEG patterns in patients with partial symptomatic epilepsy before, during and after epileptic discharges, as well as during covering the eyes and with hyperventilation during periods of absence
  of epileptic discharges, proved that changes in the values of multifractal parameters and the maximum of the global energy of the EEG wavelet spectrum can be used to automatically distinguish
  between periods before, during and after an epileptic discharge. Using multifractal analysis, it was
  found that the mechanism of changes in the dynamic complexity of EEG patterns during the occurrence of epileptic discharges is based on an increase in the contribution of weak fluctuations
  of successive EEG values, leading to an increase in their correlation and a significant increase in
  the energy of the wavelet spectrum and the degree of multifractality of the pattern in the preictal
  period.
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: ru
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: multifractality degree
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: EEG
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: epileptic discharges
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: ictal period
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: Chapter 2. Mechanisms of changes in dynamic complexity of EEG patterns in epileptic brain injury
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Book chapter
metadata.lang: en_GB
resources.filename: 36-49.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/21148/1/36-49.pdf
resources.format: Adobe PDF
resources.size: 2,24 MB