Design of an EEG analytical methodology for the analysis and interpretation of cerebral connectivity signals

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dc.contributor.authorCórdova, Felisa M.
dc.contributor.authorCifuentes, Hugo F.
dc.contributor.authorDíaz, Hernán A.
dc.contributor.authorYanine, Fernando
dc.contributor.authorPereira, Robertino
dc.date.accessioned2022-11-15T14:15:38Z
dc.date.available2022-11-15T14:15:38Z
dc.date.issued2022-02-20
dc.description.abstractThe objective of this study is to design an Electroencephalographic (EEG) analytic methodology that allows to develop a variety of analysis and interpretations of brain signals. The initial phase considers the acquisition and filtering of EEG signals, the division into bands in data ranges, and the storage of EEG signals in a cloud data base. Then, an analytical phase considering descriptive, predictive and prescriptive analysis is accomplished. A sequence of analytic intermediate processing steps is done in order to render a graphic visualization of significant correlations between pairs of EEG channels. Pearson correlation is utilized to detect synchronic connectivity through the brain areas. Time series in nearly instantaneous time lapses are treated by using Hilbert Huang Transform. An experimental design by submitting a set of students to an abbreviated version Raven visual test is made providing results in correlation maps of cerebral connectivityes
dc.identifier.citationProcedia Computer Science, Vol. 199, (2022) p.1401-1408.en
dc.identifier.doihttps://doi.org/10.1016/j.procs.2022.01.177
dc.identifier.issn1877-0509
dc.identifier.orcidhttps://orcid.org/0000-0003-1086-0840es
dc.identifier.urihttp://hdl.handle.net/20.500.12254/2607
dc.language.isoenen
dc.publisherElsevieren
dc.rightsAtribución-NoComercial-CompartirIgual 3.0 Chile (CC BY-NC-SA 3.0 CL)
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/cl/
dc.subject.otherAnalytic methodologyen
dc.subject.otherSignal analysisen
dc.subject.otherCerebral connectivityen
dc.titleDesign of an EEG analytical methodology for the analysis and interpretation of cerebral connectivity signalsen
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