DocumentCode :
2207927
Title :
Directed epileptic network from scalp and intracranial EEG of epileptic patients
Author :
Amini, L. ; Jutten, Christian ; Achard, S. ; David, O. ; Soltanian-Zadeh, H. ; Hossein-Zadeh, G.A. ; Kahane, P. ; Minotti, L. ; Vercueil, L.
Author_Institution :
GIPSA-Lab., Grenoble INP, Grenoble, France
fYear :
2009
fDate :
1-4 Sept. 2009
Firstpage :
1
Lastpage :
6
Abstract :
We proposed recently the computation of epileptic connectivity graphs based on wavelet correlation coefficients between EEG signals. The suspected epileptiform electrodes are recognized using the clustering of the topological properties of the graph that can be useful for pre-surgical studies. Here, we present a method for comparing epileptic networks estimated from scalp and intracranial EEG (IEEG) in partial epilepsy patients. The results are presented for a patient with left temporal epilepsy. Good spatial correspondence between the IEEG and the scalp EEG epileptic graphs is obtained. These results are consistent with the patient´s clinical diagnosis.
Keywords :
biomedical electrodes; directed graphs; electroencephalography; medical signal processing; directed epileptic network; epileptic connectivity graph; epileptic patients; epileptiform electrodes; intracranial EEG; scalp EEG; wavelet correlation coefficients; Control systems; Electrodes; Electroencephalography; Epilepsy; Indium phosphide; Process control; Radio control; Scalp; Surgery; Time frequency analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning for Signal Processing, 2009. MLSP 2009. IEEE International Workshop on
Conference_Location :
Grenoble
Print_ISBN :
978-1-4244-4947-7
Electronic_ISBN :
978-1-4244-4948-4
Type :
conf
DOI :
10.1109/MLSP.2009.5306245
Filename :
5306245
Link To Document :
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