• DocumentCode
    1370572
  • Title

    Extraction of spatio-temporal signatures from depth EEG seizure signals based on objective matching in warped vectorial observations

  • Author

    Wendling, Fabrice ; Bellanger, Jean-Jacques ; Badier, Jean-Michel ; Coatrieux, Jean-Louis

  • Author_Institution
    Lab. Traitement du Signal et de l´´Image, Rennes I Univ., France
  • Volume
    43
  • Issue
    10
  • fYear
    1996
  • Firstpage
    990
  • Lastpage
    1000
  • Abstract
    In the field of epilepsy, the analysis of stereoelectroencephalographic (SEEG) signals recorded with depth electrodes provides major information on interactions between brain structures during seizures. A comprehensive methodology of comparing SEEG seizure recordings is presented. It proceeds in three steps: 1) segmentation of SEEG signals; 2) characterization and labeling of segments; and 3) comparison of observations coded as sequences of symbol vectors. The third step reports a vectorial extension of the Wagner and Fischer´s algorithm to first, quantify similarities between observations and second, extract invariant sequences of events, referred to as spatio-temporal signatures. The study shows that two observations of nonequal duration can be matched by deforming the first one to optimally fit the second, under cost constraints. Results show that the methodology allows to exhibit signatures occurring during epileptic seizures and to point out different types of seizure patterns. The study brings objective results on reproducible interactions between brain structures during ictal periods and may help in the understanding of epileptogenic networks.
  • Keywords
    electroencephalography; medical signal processing; sequences; vectors; Wagner-Fischer algorithm; brain structures; depth EEG seizure signals; electrodiagnostics; epileptic seizures; ictal periods; invariant event sequences; nonequal duration observations; objective matching; seizure patterns; signals segmentation; spatiotemporal signatures extraction; stereoelectroencephalographic signals analysis; vectorial extension; warped vectorial observations; Biomedical monitoring; Brain; Computed tomography; Diseases; Electrodes; Electroencephalography; Epilepsy; Magnetic resonance imaging; Neurons; Signal processing; Algorithms; Electroencephalography; Epilepsy, Temporal Lobe; Humans; Pattern Recognition, Automated; Reproducibility of Results; Seizures; Signal Processing, Computer-Assisted;
  • fLanguage
    English
  • Journal_Title
    Biomedical Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9294
  • Type

    jour

  • DOI
    10.1109/10.536900
  • Filename
    536900