Paper Info
Title
Entropy spatial clustering in epileptic EEG
Abstract
Works in literature analyse neuronal electrical source distribution on human brain cortex from noninvasive measurements of electric potentials at multichannel scalp electrodes (Electroencephalography). In this paper a new technique, based on entropy, is introduced to study the synchronization of the electric activity of neuronal sources in the brain. An abnormal synchronization (abnormal interactions between the electrodes) can result in an epileptic seizure and Renyi's entropy topography and its spatial clustering are proposed to measure this interaction and to provide a spatial picture of its distribution over the cortex. Three EEG dataset from patients affected by partial epilepsy were analysed. Entropy showed a very steady spatial distribution and a clear relationship with the region of seizure onset. Entropy mapping was compared with the standard power mapping that was much less stable and selective. A SOM based spatial clustering of entropy topography showed that the critical electrodes were coupled together long time before the seizure onset.
Year
DOI
Venue
2009
10.1109/IJCNN.2009.5178871
IJCNN
Keywords
Field
DocType
bioelectric potentials,electroencephalography,entropy,medical computing,pattern clustering,Renyi entropy topography,electric potentials,epileptic EEG,epileptic seizure,human brain cortex,multichannel scalp electrodes,neuronal electrical source distribution,spatial clustering,Electroencephalography,Epilepsy,Reny's Entropy,SOM
Synchronization,Pattern recognition,Computer science,Epilepsy,Epileptic seizure,Human brain,Artificial intelligence,Artificial neural network,Cluster analysis,Cellular neural network,Electroencephalography,Machine learning
Conference
ISSN
Citations 
PageRank 
2161-4393
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Nadia Mammone113619.69
Giuseppina Inuso2143.93
Fabio La Foresta39315.69
Mario Versaci45115.70
Francesco C. Morabito5175.46