DocumentCode
2938861
Title
Automatic classification of penicillin-induced epileptic EEG spikes
Author
Kortelainen, Jukka ; Silfverhuth, Minna ; Suominen, Kalervo ; Sonkajärvi, Eila ; Alahuhta, Seppo ; Jäntti, Ville ; Seppänen, Tapio
Author_Institution
Dept. of Electr. & Inf. Eng., Univ. of Oulu, Oulu, Finland
fYear
2010
fDate
Aug. 31 2010-Sept. 4 2010
Firstpage
6674
Lastpage
6677
Abstract
Penicillin-induced focal epilepsy is a well-known model in epilepsy research. In this model, epileptic activity is generated by delivering penicillin focally to the cortex. The drug induces interictal electroencephalographic (EEG) spikes which evolve in time and may later change to ictal discharges. This paper proposes a method for automatic classification of these interictal epileptic spikes using iterative K-means clustering. The method is shown to be able to detect different spike waveforms and describe their characteristic occurrence in time during penicillin-induced focal epilepsy. The study offers potential for future research by providing a method to objectively and quantitatively analyze the time sequence of interictal epileptic activity.
Keywords
electroencephalography; iterative methods; medical disorders; medical signal processing; neurophysiology; physiological models; signal classification; automatic classification; electroencephalography; focal epilepsy; ictal discharges; interictal epileptic activity; iterative K-means clustering; penicillin-induced epileptic EEG spikes; Brain modeling; Classification algorithms; Clustering algorithms; Data mining; Discharges; Electroencephalography; Epilepsy; Algorithms; Animals; Electroencephalography; Epilepsies, Partial; Humans; Magnetic Resonance Imaging; Penicillins;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location
Buenos Aires
ISSN
1557-170X
Print_ISBN
978-1-4244-4123-5
Type
conf
DOI
10.1109/IEMBS.2010.5627154
Filename
5627154
Link To Document