EEG datasets for healthcare: A scoping review

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dc.contributor.authorPeres da Silva, Carolineen
dc.contributor.authorTedesco, Salvatoreen
dc.contributor.authorO’Flynn, Brendanen
dc.contributor.funderScience Foundation Irelanden
dc.contributor.funderEuropean Regional Development Funden
dc.date.accessioned2024-03-27T15:44:43Z
dc.date.available2024-03-27T15:44:43Z
dc.date.issued2024-03-11en
dc.description.abstractThe rapidly evolving landscape of artificial intelligence (AI) and machine learning has placed data at the forefront of healthcare innovation. Electroencephalography (EEG) has gained significant attention for its potential to revolutionize healthcare applications. However, the effective utilization of EEG data in advancing medical diagnoses and treatment hinges on the availability and quality of relevant datasets. In this context, we conducted a scoping review to explore the wealth of EEG datasets designed for healthcare applications. This review serves as a critical exploration of the current landscape, aiming to identify datasets related to healthcare conditions while assessing their reusability. Our findings highlight both the opportunities and limitations in the wealth of open access EEG datasets. Available. As AI increasingly relies on high-quality, well labelled data, barriers impeding the sharing and utilization of EEG data for healthcare (such as lack of comprehensive documentation or adherence to FAIR principles) must be addressed so as to leverage the potential of advanced deep learning models to unlock new possibilities for diagnosis and analysis of a wide array of medical conditions.en
dc.description.sponsorshipScience Foundation Ireland (12/RC/2289-P2)en
dc.description.statusPeer revieweden
dc.description.versionPublished Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationPeres da Silva, C., Tedesco, S. and O’Flynn, B. (2024) 'EEG datasets for healthcare: A scoping review', IEEE Access, 12, pp. 39186-39203. https://doi.org/10.1109/ACCESS.2024.3376254en
dc.identifier.doihttps://doi.org/10.1109/ACCESS.2024.3376254en
dc.identifier.eissn2169-3536en
dc.identifier.endpage39203en
dc.identifier.journaltitleIEEE Accessen
dc.identifier.startpage39186en
dc.identifier.urihttps://hdl.handle.net/10468/15714
dc.identifier.volume12en
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres Programme::Phase 1/16/RC/3918/IE/Confirm Centre for Smart Manufacturing/en
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Centres for Research Training Programme::Data and ICT Skills for the Future/18/CRT/6223/IE/SFI Centre for Research Training in Artificial Intelligence/en
dc.relation.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/13/RC/2077/IE/CONNECT: The Centre for Future Networks & Communications/en
dc.rights© 2024, the Authors. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subjectElectroencephalographyen
dc.subjectEEGen
dc.subjectDeep learningen
dc.subjectOpen accen
dc.subjectData setsen
dc.titleEEG datasets for healthcare: A scoping reviewen
dc.typeArticle (peer-reviewed)en
oaire.citation.volume12en
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