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Mining EEG scalp maps of independent components related to HCT tasks

dc.contributor.authorTeixeira, Ana
dc.contributor.authorSantos, I.M.
dc.contributor.authorLang, E.W.
dc.contributor.authorTome, A.M.
dc.date.accessioned2023-10-23T10:11:16Z
dc.date.available2023-10-23T10:11:16Z
dc.date.issued2019
dc.description.abstractThis work presents an unsupervised mining strat- egy, applied to an independent component analysis (ICA) of segments of data collected while participants are answering to the items of the Halstead Category Test (HCT). This new methodology was developed to achieve signal components at trial level and therefore to study signal dynamics which are not available within participants’ ensemble average signals. The study will be focused on the signal component that can be elicited by the binary visual feedback which is part of the HCT protocol. The experimental study is conducted using a cohort of 58 participants.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.1109/EMBC.2019.8857600pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.26/47389
dc.language.isoengpt_PT
dc.publisherIEEEpt_PT
dc.titleMining EEG scalp maps of independent components related to HCT taskspt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.endPage3891pt_PT
oaire.citation.startPage3888pt_PT
oaire.citation.title[41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society]pt_PT
person.familyNameTeixeira
person.givenNameAna
person.identifier.ciencia-idD619-A151-8BE2
person.identifier.orcid0000-0002-8120-0148
person.identifier.ridA-3100-2014
person.identifier.scopus-author-id7202385348
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationc1ff686d-c3d3-4658-96c6-a1f62a52777a
relation.isAuthorOfPublication.latestForDiscoveryc1ff686d-c3d3-4658-96c6-a1f62a52777a

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