Characterization of epileptic seizure dynamics using Gabor atom density

Objective: The study of epileptic electroencephalograph (EEG) dynamics can potentially provide insights into seizure onset, evolution and termination. We propose a new synthetic measure based on time–frequency decomposition to provide detailed characterization of these dynamic changes. Methods: The...

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Veröffentlicht in:Clinical neurophysiology 2003-03, Vol.114 (3), p.426-437
Hauptverfasser: Jouny, Christophe C., Franaszczuk, Piotr J., Bergey, Gregory K.
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Sprache:eng
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Zusammenfassung:Objective: The study of epileptic electroencephalograph (EEG) dynamics can potentially provide insights into seizure onset, evolution and termination. We propose a new synthetic measure based on time–frequency decomposition to provide detailed characterization of these dynamic changes. Methods: The matching pursuit (MP) method allows for continuous time–frequency decomposition. We have developed a derivative of the MP method, the Gabor atom density method (GAD) that facilitates interpretation during the dynamic ictal period. The GAD analysis was applied to intracranial recordings of complex partial seizures ( n=43) of mesial temporal origin in 7 patients. Results: Complex partial seizure occurrence is systematically associated with a GAD increase of 400±150%. The GAD increase coincides with the electrographical evidence of seizure onset. The similarity between seizures in a given patient is very high with uniform onset slope, maximum level and termination pattern. Global GAD responses over all channels can reveal detailed seizure propagation patterns including secondary independent foci and secondary generalization. Conclusions: The GAD measure based on the MP decomposition is a reliable tool to detect seizure occurrence in long-term recordings, to differentiate seizures from artifacts on a multi-channel basis and to examine patterns of seizure propagation. The reproducible GAD pattern suggests consistent changes in signal inner structure and may provide new clues about seizure dynamics and evolution. Significance: The GAD method can provide information about seizure dynamics that can contribute to methods of seizure detection. These analyses may lead to better understanding of seizure termination and help facilitate application of responsive seizure control devices in humans.
ISSN:1388-2457
1872-8952
DOI:10.1016/S1388-2457(02)00344-9