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
fDate :
Aug. 31 2010-Sept. 4 2010
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;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2010 Annual International Conference of the IEEE
Conference_Location :
Buenos Aires
Print_ISBN :
978-1-4244-4123-5
DOI :
10.1109/IEMBS.2010.5627154