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Neurological Sciences

, Volume 29, Issue 1, pp 3–9 | Cite as

Permutation entropy to detect vigilance changes and preictal states from scalp EEG in epileptic patients. A preliminary study

  • Angela A. Bruzzo
  • Benno Gesierich
  • Maurizio Santi
  • Carlo Alberto Tassinari
  • Niels Birbaumer
  • Guido Rubboli
Original Article

Abstract

Permutation entropy (PE) was recently introduced as a very fast and robust algorithm to detect dynamic complexity changes in time series. It was also suggested as a useful screening algorithm for epileptic events in EEG data. In the present work, we tested its efficacy on scalp EEG data recorded from three epileptic patients. With a receiver operating characteristics (ROC) analysis, we evaluated the separability of amplitude distributions of PE resulting from preictal and interictal phases. Moreover, the dependency of PE on vigilance state was tested by correlation coefficients. A good separability of interictal and preictal phase was found, nevertheless PE was shown to be sensitive to changes in vigilance state. The changes of PE during the preictal phase and at seizure onset coincided with changes in vigilance state, restricting its possible use for seizure prediction on scalp EEG; this finding however suggests its possible usefulness for an automated classification of vigilance states.

Keywords

Drug-resistant focal epilepsy Permutation entropy Preictal phase Scalp-electroencephalogram Seizure prediction State of vigilance 

Sommario

È stato recentemente introdotto un algoritmo denominato Permutation Entropy (PE) a cui gli autori Bandt e Pompe (2002) attribuiscono due caratteristiche interessanti: la robustezza e la relativa rapidità di implementazione, proprietà entrambe utili nell’individuazione delle variazioni di complessità in serie temporali. Sulla scia di un iniziale ottimismo, la PE è stata suggerita come un possibile ausilio di ricerca su dati elettroencefalografici relativi a crisi epilettiche. Un primo obiettivo del nostro studio era testare l’efficacia dell’algoritmo, su dati elettroencefalografici di scalpo, registrati da 3 pazienti epilettici. Mediante l’applicazione di una ROC (Receiver Operating Characteristics) analisi abbiamo valutato la separabilità delle distribuzioni delle ampiezze di PE, rispettivamente per la fase preictale per quella interictale, su ogni registrazione di scalpo. Il secondo obiettivo è stato quello di indagare le eventuali correlazioni sussistenti fra l’andamento della PE e gli stati di vigilanza. Troviamo una buona separabilità fra le curve di dati preictali e interictali di ciascun paziente, seppure è evidente che la PE sia sensibile al cambio di stati di vigilanza, poiché spesso l’inizio di un evento accessuale era concomitante a cambi di stati di vigilanza. Alla luce di queste osservazioni, concludiamo che al momento non è possibile valutare l’affidabilità della PE come algoritmo predittore di crisi su dati elettroencefalografici di superficie, mentre appare sicuramente più attendibile come classificatore automatico degli stati di vigilanza.

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Copyright information

© Springer-Verlag Italia 2008

Authors and Affiliations

  • Angela A. Bruzzo
    • 1
    • 3
    • 4
  • Benno Gesierich
    • 2
  • Maurizio Santi
    • 3
  • Carlo Alberto Tassinari
    • 3
  • Niels Birbaumer
    • 4
    • 5
  • Guido Rubboli
    • 3
  1. 1.Department of PsychologyUniversity of BolognaBolognaItaly
  2. 2.Center for Mind/Brain SciencesUniversity of TrentoRoveretoItaly
  3. 3.Department of NeurosciencesUniversity of Bologna Bellaria HospitalBolognaItaly
  4. 4.Institute of Medical Psychology and Behavioral NeurobiologyEberhard Karls University of TübingenTübingenGermany
  5. 5.Cortical Physiology UnitNational Institutes of Health (NIH) NINDSBethesdaUSA

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