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dc.creatorGómez A.
dc.creatorQuintero O.L.
dc.creatorLopez-Celani N.
dc.creatorVilla L.F.
dc.descriptionThis paper addresses the cerebral cortex maps construction from EEG signals getting an information simplification method for an emotional state phenomenon description. Bi-dimensional density distribution of main signal features are identified and a comparison to a previous approach is presented. Feature extraction scheme is performed via windowed EEG signals Stationary Wavelet Transform with the Daubechies Family (1-10); nine temporal and spectral descriptors are computed from the decomposed signal. Recursive feature selection method based on training a Random forest classifier using a one-vs-all scheme with the full features space, then a ranking procedure via gini importance, eliminating the bottom features and restarting the entire process over the new subset. Stopping criteria is the maximum accuracy. The main contribution is the analysis of the resulting subset features as a proxy for cerebral cortex maps looking for the cognitive processes understanding from surface signals. Identifying the common location of different emotional states in the central and frontal lobes, allowing to be strong parietal and temporal lobes differentiators for different emotions. © 2020, Springer Nature Switzerland AG.
dc.sourceIFMBE Proceedings
dc.subjectCerebral cortex
dc.subjectFeature selection
dc.subjectBiomedical engineering
dc.subjectDecision trees
dc.subjectDiscrete wavelet transforms
dc.subjectSignal processing
dc.subjectCerebral cortex
dc.subjectDensity distributions
dc.subjectFeature selection methods
dc.subjectRandom forest classifier
dc.subjectSimplification method
dc.subjectStationary wavelet transforms
dc.subjectFeature extraction
dc.titleCerebral Cortex Atlas of Emotional States Through EEG Processing
dc.typeConference Papereng
dc.publisher.programIngeniería de Sistemas
dc.publisher.facultyFacultad de Ingenierías
dc.affiliationGómez, A., Mathematical Modelling, Universidad EAFIT, Medellín, Colombia; Quintero, O.L., Mathematical Modelling, Universidad EAFIT, Medellín, Colombia; Lopez-Celani, N., Gabinete de Tecnologia Medica - CONICET, Universidad Nacional de San Juan, San Juan, Argentina; Villa, L.F., Arkadius, Universidad de Medellín, Medellín, Colombia
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