Implementation of Brain Computer Interface for Stress Management

dc.contributor.authorWeerasinghe, P
dc.contributor.authorWeerasekara, M.K.
dc.contributor.authorWickramaarachchi, W.A.S.M.
dc.date.accessioned2025-11-13T04:30:06Z
dc.date.issued2018-08-25
dc.description.abstractThis paper presents a stress identification system implementation, which contains an EEG Headset, a non invasive type of brain – to – machine interfacing on which the brainwave patterns such as attention, meditation, and eye blink is acquired directly on the person’s scalp. Electroencephalography (EEG) is also being examined at the time of detection where the Gamma, Beta, Alpha, Theta, and Delta brain waves are considered. The system implementation consists of two main functional modules:stress detection unit and stress visualization unit. The stress detection unit based on the analysis of EEG waves using Neurosky Mindwave EEG, Sri Lanka decisions and exercise critical thinking. They get support to develop skills and abilities along with a more positive self image. This is also referred to as ‘patient empowerment.’ Thus, this research work also contribute to expand the horizons of ICT supported stress management interventions through brain computer interfacing approach. The captured waves are then transferred to the stress visualization unit where it displays the signals in the form of a virtual fish tank, programmed to change the swimming position of a fish according to the stress levels. The development of this type of system is not only convenient but also it is portable and affordable.
dc.identifier.citationWeerasinghe, P & Weerasekara, M.K. & Wickramaarachchi, W.A.S.M(2018) Implementation of Brain Computer Interface for Stress Management , International Conference On Business Innovation (ICOBI), NSBM Green University, Sri Lanka. P.111-114
dc.identifier.issn2651-0111
dc.identifier.urihttps://nspace.nsbm.ac.lk/handle/123456789/42
dc.language.isoen
dc.publisherNSBM Green University
dc.subjectBrain Computer Interaction
dc.subjectstress
dc.subjectEEG
dc.titleImplementation of Brain Computer Interface for Stress Management
dc.typeArticle

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