Evaluation of selected recurrence measures in discriminating pre-ictal and inter-ictal periods from epileptic EEG data

Eulalie Joelle Ngamga, Stephan Bialonski, Norbert Marwan, Jürgen Kurths, Christian Geier, Klaus Lehnertz

Research output: Contribution to journalArticle

21 Citations (Scopus)
2 Downloads (Pure)

Abstract

We investigate the suitability of selected measures of complexity based on recurrence quantification analysis and recurrence networks for an identification of pre-seizure states in multi-day, multi-channel, invasive electroencephalographic recordings from five epilepsy patients. We employ several statistical techniques to avoid spurious findings due to various influencing factors and due to multiple comparisons and observe precursory structures in three patients. Our findings indicate a high congruence among measures in identifying seizure precursors and emphasize the current notion of seizure generation in large-scale epileptic networks. A final judgment of the suitability for field studies, however, requires evaluation on a larger database.
Original languageEnglish
Pages (from-to)1419-1425
Number of pages7
JournalPhysics Letters A
Volume380
Issue number16
Early online date20 Feb 2016
DOIs
Publication statusPublished - 1 Apr 2016

Keywords

  • nlin.CD
  • physics.data-an
  • physics.med-ph

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