dc.creator | Quesada Tabares, Roylán | es |
dc.creator | Molina Cantero, Alberto Jesús | es |
dc.creator | Escudero Fombuena, José Ignacio | es |
dc.creator | Merino Monge, Manuel | es |
dc.creator | Gómez González, Isabel María | es |
dc.creator | Lebrato Vázquez, Clara | es |
dc.creator | Castro García, Juan Antonio | es |
dc.date.accessioned | 2021-03-11T09:42:12Z | |
dc.date.available | 2021-03-11T09:42:12Z | |
dc.date.issued | 2018 | |
dc.identifier.citation | Quesada Tabares, R., Molina Cantero, A.J., Escudero Fombuena, J.I., Merino Monge, M., Gómez González, I.M., Lebrato-Vázquez, C. y Castro García, J.A. (2018). Looking for Emotions on a Single EEG Signal. En PhyCS 2018: 5th International Conference on Physiological Computing Systems (78-92), Sevilla, España: Springer. | |
dc.identifier.isbn | 978-3-030-27949-3 | es |
dc.identifier.issn | 0302-9743 | es |
dc.identifier.uri | https://hdl.handle.net/11441/105896 | |
dc.description.abstract | This work aims at demonstrating that it is possible to detect
emotions using a single EEG channel with an accuracy that is comparable
to that obtained in studies carried out with devices that have a
high number of channels. In this article the Neurosky Maindwave device,
which only a single electrode at the FP1 position, the MatLab and the
IBM SPSS Modeler were used to acquire, process and classify the signals
respectively. It is remarkable the accuracy achieved in relation to the
inexpensive hardware employed for the acquisition of the EEG signal.
The result of this study allows us to determine when the brain response
is more intense after undergoing the subject, in the experimentation,
to the stimuli that generate those emotions. This let us decide which
brain power bands are most significants and which moments are the
most appropriate to carry out this detection of emotions. | es |
dc.format | application/pdf | es |
dc.format.extent | 15 | es |
dc.language.iso | eng | es |
dc.publisher | Springer | es |
dc.relation.ispartof | PhyCS 2018: 5th International Conference on Physiological Computing Systems (2018), pp. 78-92. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Emotions | es |
dc.subject | Signal processing | es |
dc.subject | Single EEG channel | es |
dc.subject | Classification analysis | es |
dc.subject | Dynamic properties | es |
dc.title | Looking for Emotions on a Single EEG Signal | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/submittedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Tecnología Electrónica | es |
dc.relation.publisherversion | https://link.springer.com/chapter/10.1007/978-3-030-27950-9_5 | es |
dc.identifier.doi | 10.1007/978-3-030-27950-9_5 | es |
dc.publication.initialPage | 78 | es |
dc.publication.endPage | 92 | es |
dc.eventtitle | PhyCS 2018: 5th International Conference on Physiological Computing Systems | es |
dc.eventinstitution | Sevilla, España | es |
dc.relation.publicationplace | Cham, Switzerland | es |
dc.identifier.sisius | 21857192 | es |