title: Automatic detection of the seizure onset zone based on ictal EEG.
abstract: In this paper we show a proof of concept for novel automatic seizure onset zone detector. The proposed approach utilizes the Austrian Institute of Technology (AIT) seizure detection system EpiScan extended by a frequency domain source localization module. EpiScan was proven to detect rhythmic epileptoform seizure activity often seen during the early phase of epileptic seizures with reasonable high sensitivity and specificity. Additionally, the core module of EpiScan provides complex coefficients and fundamental frequencies representing the rhythmic activity of the ictal EEG signal. These parameters serve as input to a frequency domain version of the Minimum Variance Beamformer to estimate the most dominant source. The position of this source is the detected seizure onset zone. The results are compared to a state of the art wavelet transformation approach based on a manually chosen frequency band. Our first results are encouraging since they coincide with those obtained with the wavelet approach and furthermore show excellent accordance with the medical report for the majority of analyzed seizures. In contrast to the wavelet approach our method has the advantage that it does not rely on a manual selection of the frequency band.
authors.affiliation: Austrian Institute of Technology, Donau-City-Strasse 1, 1220 Vienna, Austria.
authors.forename: G
authors.initials: G
authors.lastname: Gritsch
authors.forename: M M
authors.initials: MM
authors.lastname: Hartmann
authors.forename: H
authors.initials: H
authors.lastname: Perko
authors.forename: F
authors.initials: F
authors.lastname: Fürbass
authors.forename: P
authors.initials: P
authors.lastname: Ossenblok
authors.forename: T
authors.initials: T
authors.lastname: Kluge
mesh_terms: D000465:Algorithms; D001331:Automation; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D012640:Seizures / Q000503:physiopathology*