Electroencephalographic source localization based on enhanced empirical mode decomposition

dc.creatorBueno-López, Maximiliano
dc.creatorMunoz-Gutierrez, Pablo A.
dc.creatorGiraldo, Eduardo
dc.creatorMolinas, Marta
dc.date2019-05-01T07:00:00Z
dc.date.accessioned2022-10-13T13:35:34Z
dc.date.available2022-10-13T13:35:34Z
dc.identifierhttps://ciencia.lasalle.edu.co/scopus_unisalle/153
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4157482
dc.descriptionIn this work, a novel identification method of relevant Intrinsic Mode Functions, obtained from Electroencephalographic signals, by using an entropy criteria is proposed. The idea is to reduce the number of Intrinsic Mode Functions that are necessary for the electroencephalographic source reconstruction. An entropy cost function is applied on the Intrinsic Mode Functions generated by the Empirical Mode Decomposition for automatic IMF selection. The resulting Enhanced Empirical Mode Decomposition is evaluated in simulated and real data bases containing normal and epileptic activity by means of a relative error measure. The proposed approach shows to improve the electroencephalographic source reconstruction specifically for epileptic seizure detection.
dc.sourceIAENG International Journal of Computer Science
dc.source228
dc.subjectBrain mapping
dc.subjectEmpirical-Mode-Decomposition
dc.subjectEpileptic seizures
dc.subjectSeizure detection
dc.titleElectroencephalographic source localization based on enhanced empirical mode decomposition
dc.typeArticle


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