Exploring the Possibilities of Determining Fitness For Duty Using commercial EEG device

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dc.contributor.authorJung, Yeachanko
dc.contributor.authorYim, Man-Sungko
dc.contributor.authorKim, Tae Ryounko
dc.date.accessioned2022-09-07T08:00:11Z-
dc.date.available2022-09-07T08:00:11Z-
dc.date.created2022-07-25-
dc.date.issued2022-07-11-
dc.identifier.citation44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society-
dc.identifier.urihttp://hdl.handle.net/10203/298434-
dc.description.abstractAn increase in personal negative emotions (stress, depression, anxiety) and an increase in consuming alcohol may threaten personal health, and worker performance in highly reliability organizations, causing serious accidents. This study suggests a method to integrate conveniently measurable commercial EEG (Electroencephalography) devices and machine learning to assess FFD (Fitness For Duty) as well as a worker's mental health.-
dc.languageEnglish-
dc.publisherIEEE-
dc.titleExploring the Possibilities of Determining Fitness For Duty Using commercial EEG device-
dc.typeConference-
dc.type.rimsCONF-
dc.citation.publicationname44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society-
dc.identifier.conferencecountryUK-
dc.identifier.conferencelocationGlasgow, Scotland-
dc.contributor.localauthorYim, Man-Sung-
dc.contributor.nonIdAuthorJung, Yeachan-
dc.contributor.nonIdAuthorKim, Tae Ryoun-
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NE-Conference Papers(학술회의논문)
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