Modeling of brain cortical activity during relaxation and mental workload tasks based on EEG signal collection

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cris.lastimport.scopus2025-04-17T03:14:12Z
dc.abstract.enCoronavirus disease 2019 (COVID-19) has caused everything from daily hassles, relationship issues, and work pressures to health concerns and debilitating phobias. Relaxation techniques are one example of the many methods used to address stress, and they have been investigated for decades. In this study, we aimed to check whether there are differences in the brain cortical activity of participants during relaxation or mental workload tasks, as observed using dense array electroencephalography, and whether these differences can be modeled and then classified using a machine learning classifier. In this study, guided imagery as a relaxation technique was used in a randomized trial design. Two groups of thirty randomly selected participants underwent a guided imagery session; other randomly selected participants performed a mental task. Participants were recruited among male computer science students. During the guided imagery session, the electroencephalographic activity of each student’s brain was recorded using a dense array amplifier. This activity was compared with that of a group of another 30 computer science students who performed a mental task. Power activity maps were generated for each participant, and examples are presented and discussed to some extent. These types of maps cannot be easily interpreted by therapists due to their complexity and the fact that they vary over time. However, the recorded signal can be classified using general linear models. The classification results as well as a discussion of prospective applications are presented.
dc.affiliationInstytut Psychologii
dc.affiliationWydział Psychologii w Warszawie
dc.contributor.authorZemla, Katarzyna
dc.contributor.authorWójcik, Grzegorz M.
dc.contributor.authorPostepski, Filip
dc.contributor.authorWróbel, Krzysztof
dc.contributor.authorKawiak, Andrzej
dc.contributor.authorSędek, Grzegorz
dc.date.access2023-03-31
dc.date.accessioned2023-12-27T10:04:40Z
dc.date.available2023-12-27T10:04:40Z
dc.date.created2023-03-27
dc.date.issued2023-03-31
dc.description.abstract<jats:p>Coronavirus disease 2019 (COVID-19) has caused everything from daily hassles, relationship issues, and work pressures to health concerns and debilitating phobias. Relaxation techniques are one example of the many methods used to address stress, and they have been investigated for decades. In this study, we aimed to check whether there are differences in the brain cortical activity of participants during relaxation or mental workload tasks, as observed using dense array electroencephalography, and whether these differences can be modeled and then classified using a machine learning classifier. In this study, guided imagery as a relaxation technique was used in a randomized trial design. Two groups of thirty randomly selected participants underwent a guided imagery session; other randomly selected participants performed a mental task. Participants were recruited among male computer science students. During the guided imagery session, the electroencephalographic activity of each student’s brain was recorded using a dense array amplifier. This activity was compared with that of a group of another 30 computer science students who performed a mental task. Power activity maps were generated for each participant, and examples are presented and discussed to some extent. These types of maps cannot be easily interpreted by therapists due to their complexity and the fact that they vary over time. However, the recorded signal can be classified using general linear models. The classification results as well as a discussion of prospective applications are presented.</jats:p>
dc.description.accesstimeat_publication
dc.description.issue7
dc.description.physical1-13
dc.description.versionfinal_published
dc.description.volume13
dc.identifier.doi10.3390/app13074472
dc.identifier.issn2076-3417
dc.identifier.urihttps://share.swps.edu.pl/handle/swps/244
dc.identifier.weblinkhttps://www.mdpi.com/2076-3417/13/7/4472
dc.languageen
dc.pbn.affiliationpsychologia
dc.rightsCC-BY
dc.rights.questionYes_rights
dc.share.articleOPEN_JOURNAL
dc.subject.enguided imagery
dc.subject.enrelaxation
dc.subject.enEEG
dc.subject.enGLM
dc.swps.sciencecloudnosend
dc.titleModeling of brain cortical activity during relaxation and mental workload tasks based on EEG signal collection
dc.title.journalApplied Sciences
dc.typeJournalArticle
dspace.entity.typeArticle