DocumentCode
2485343
Title
Automatic detection of the seizure onset zone based on ictal EEG
Author
Gritsch, G. ; Hartmann, M.M. ; Perko, H. ; Fürbass, F. ; Ossenblok, P. ; Kluge, T.
Author_Institution
Austrian Inst. of Technol., Vienna, Austria
fYear
2011
fDate
Aug. 30 2011-Sept. 3 2011
Firstpage
3901
Lastpage
3904
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.
Keywords
electroencephalography; frequency-domain analysis; medical disorders; medical signal detection; wavelet transforms; AIT seizure detection system; Austrian Institute of Technology; EpiScan; Minimum Variance Beamformer; automatic detection; frequency domain source localization module; ictal EEG; rhythmic epileptoform seizure activity; seizure onset zone; wavelet transformation approach; Brain modeling; Electrodes; Electroencephalography; Epilepsy; Frequency domain analysis; Lead; Temporal lobe; Algorithms; Automation; Electroencephalography; Humans; Seizures;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location
Boston, MA
ISSN
1557-170X
Print_ISBN
978-1-4244-4121-1
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/IEMBS.2011.6090969
Filename
6090969
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