A physiologically motivated ECoG segmentation method for epileptic seizure onset zone detection.
In this paper we propose a novel segmentation method based on the relative frequency contributions of ictal multichannel ECoG data. Segments with predominant [[see text]]-activity are classified as epileptic. The seizure onset zone is determined by the temporal delay of the epileptic [[see text]]-activity (4-9Hz) on the different channels. We apply this methodology to three seizures of one patient suffering from focal epilepsy. The resulting segments reflect the visual characteristics of the ictal ECoG well. The seizure onset zone identified by the proposed method is in very good accordance with the clinical findings.
Institute for Mathematical Methods in Economics, Vienna University of Technology, Vienna, Austria. andreas.graef@tuwien.ac.at
Andreas
A
Graef
Christoph
C
Flamm
Susanne
S
Pirker
Manfred
M
Deistler
Christoph
C
Baumgartner
D004569:Electroencephalography / Q000379:methods*; D004827:Epilepsy / Q000503:physiopathology*; D006801:Humans; D012815:Signal Processing, Computer-Assisted