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dc.creatorGómez A.
dc.creatorQuintero O.L.
dc.creatorLopez-Celani N.
dc.creatorVilla L.F.
dc.date2020
dc.date.accessioned2020-04-29T14:53:52Z
dc.date.available2020-04-29T14:53:52Z
dc.identifier.isbn9783030306472
dc.identifier.issn16800737
dc.identifier.urihttp://hdl.handle.net/11407/5747
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.language.isoeng
dc.publisherSpringer
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85075694660&doi=10.1007%2f978-3-030-30648-9_19&partnerID=40&md5=6541319a548e588e0d7f8ff1c717af63
dc.sourceIFMBE Proceedings
dc.subjectAtlas
dc.subjectCerebral cortex
dc.subjectEEG
dc.subjectEmotion
dc.subjectFeature selection
dc.subjectBiomedical engineering
dc.subjectBiophysics
dc.subjectDecision trees
dc.subjectDiscrete wavelet transforms
dc.subjectElectroencephalography
dc.subjectSignal processing
dc.subjectAtlas
dc.subjectCerebral cortex
dc.subjectDensity distributions
dc.subjectEmotion
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.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.publisher.programIngeniería de Sistemas
dc.identifier.doi10.1007/978-3-030-30648-9_19
dc.relation.citationvolume75
dc.relation.citationstartpage138
dc.relation.citationendpage144
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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dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.type.driverinfo:eu-repo/semantics/article


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