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Emotional Networked maps from EEG signals

dc.creatorGomez A.
dc.creatorQuintero O.L.
dc.creatorLopez-Celani N.
dc.creatorVilla L.F.
dc.date2020
dc.date.accessioned2021-02-05T14:58:13Z
dc.date.available2021-02-05T14:58:13Z
dc.identifier.isbn9781728119908
dc.identifier.issn1557170X
dc.identifier.urihttp://hdl.handle.net/11407/5950
dc.descriptionThe EEG has showed that contains relevant information about recognition of emotional states. It is important to analyze the EEG signals to understand the emotional states not only from a time series approach but also determining the importance of the generating process of these signals, the location of electrodes and the relationship between the EEG signals. From the EEG signals of each emotional state, a functional connectivity measurement was used to construct adjacency matrices: lagged phase synchronization (LPS), averaging adjacency matrices we built a prototype network for each emotion. Based on these networks, we extracted a set node features seeking to understand their behavior and the relationship between them. We found through the strength and degree, the group of representative electrodes for each emotional state, finding differences from intensity of measurement and the spatial location of these electrodes. In addition, analyzing the cluster coefficient, degree, and strength, we find differences between the networks from the spatial patterns associated with the electrodes with the highest coefficient. This analysis can also gain evidence from the connectivity elements shared between emotional states, allowing to cluster emotions and concluding about the relationship of emotions from EEG perspective. © 2020 IEEE.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.isversionofhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85091012600&doi=10.1109%2fEMBC44109.2020.9175935&partnerID=40&md5=ae27cc7bc66d990e79ba8002aea434b9
dc.sourceProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
dc.titleEmotional Networked maps from EEG signals
dc.typeConference Papereng
dc.rights.accessrightsinfo:eu-repo/semantics/restrictedAccess
dc.publisher.programIngeniería de Sistemasspa
dc.identifier.doi10.1109/EMBC44109.2020.9175935
dc.subject.keywordGraph structureseng
dc.subject.keywordAdjacency matriceseng
dc.subject.keywordCluster coefficientseng
dc.subject.keywordEEG signalseng
dc.subject.keywordEmotional stateeng
dc.subject.keywordFunctional connectivityeng
dc.subject.keywordLagged phaseeng
dc.subject.keywordSpatial locationeng
dc.subject.keywordSpatial patternseng
dc.subject.keywordElectrodeseng
dc.relation.citationvolume2020-July
dc.relation.citationstartpage34
dc.relation.citationendpage37
dc.publisher.facultyFacultad de Ingenieríasspa
dc.affiliationGomez, A., Universidad Eafit, Mathematical Modelling, Medellín, Colombia
dc.affiliationQuintero, O.L., Universidad Eafit, Mathematical Modelling, Medellín, Colombia
dc.affiliationLopez-Celani, N., Universidad Nacional de San Juan, Gabinete de Tecnologia Medica-CONICET, San Juan, Argentina
dc.affiliationVilla, L.F., Universidad de Medellín, Arkadius, Medellín, Colombia
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dc.type.versioninfo:eu-repo/semantics/publishedVersion
dc.type.driverinfo:eu-repo/semantics/other


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