DocumentCode
2488540
Title
Analysis of absence seizure EEG via Permutation Entropy spatio-temporal clustering
Author
Mammone, Nadia ; Lay-Ekuakille, Aime ; Morabito, Francesco C. ; Massaro, Alessandro ; Casciaro, Sergio ; Trabacca, Antonio
Author_Institution
Dept. DIMET, Mediterranean Univ. of Reggio Calabria, Reggio Calabria, Italy
fYear
2011
fDate
30-31 May 2011
Firstpage
532
Lastpage
535
Abstract
The genesis of epileptic seizures is nowadays still mostly unknown. The hypothesis that most of scientist share is that an abnormal synchronization of different groups of neurons seems to trigger a recruitment mechanism that leads the brain to the seizure in order to reset this abnormal condition. If this is the case, a gradual transformation of the characteristics of the EEG can be hypothesized. It is therefore necessary to find a parameter that is able to measure the synchronization level in the EEG and, since the spatial dimension has to be taken into account if we aim to find out how the different areas in the brain recruit each other to develop the seizure, a spatio-temporal analysis of this parameter has to be carried out. In the present paper, a spatio-temporal analysis of EEG synchronization in 24 patients affected by absence seizure is proposed and the results are hereby reported and compared to the results obtained with a group of 40 healthy subjects. The spatio-temporal analysis is based on Permutation Entropy (PE). We found out that, ever since the interictal stages, fronto-temporal areas appear constantly associated to PE levels that are higher compared to the rest of the brain, whereas the parietal/occipital areas appear associated to low-PE. The brain of healthy subjects seems to behave in a different way because we could not see a recurrent behaviour of PE topography.
Keywords
electroencephalography; medical disorders; neurophysiology; spatiotemporal phenomena; synchronisation; EEG synchronization; abnormal synchronization; absence seizure EEG; brain; epileptic seizures; fronto-temporal areas; interictal stages; neurons; occipital area; parietal area; permutation entropy spatio-temporal clustering; spatial dimension; spatio-temporal analysis; topography; Clustering algorithms; Complexity theory; Electrodes; Electroencephalography; Entropy; Synchronization; Time series analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Medical Measurements and Applications Proceedings (MeMeA), 2011 IEEE International Workshop on
Conference_Location
Bari
Print_ISBN
978-1-4244-9336-4
Type
conf
DOI
10.1109/MeMeA.2011.5966762
Filename
5966762
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