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dc.contributor.authorYunyong Punsawaden_US
dc.contributor.authorYodchanan Wongsawaten_US
dc.contributor.otherSilpakorn Universityen_US
dc.contributor.otherMahidol Universityen_US
dc.identifier.citationIFMBE Proceedings. Vol.63, (2018), 567-571en_US
dc.description.abstract© Springer Nature Singapore Pte Ltd. 2018. This paper proposed a self-paced emotional imagery based noninvasive Brain-computer interface (BCI) system. Electroencephalography (EEG) was used to observe brain phenomenon and regions during imagery positive and negative emotions. Absolute power at peak frequency of EEG bands from quantitative EEG analysis was used to create a parameter two classes of emotion by using Linear discriminant analysis (LDA) classifier. The study of brain response via EEG supports previously proposed EEG-based emotion recognition. The results showed the proposed algorithms achieved averaged accuracy rate of 53.3–83.3%. The proposed system can be used for real-time BCI. The aim is an assistive devices and emotion monitoring based on BCI that can practically use in clinical applications.en_US
dc.rightsMahidol Universityen_US
dc.subjectChemical Engineeringen_US
dc.titleSelf-paced emotional imagery-based brain computer interface systemen_US
dc.typeConference Paperen_US
Appears in Collections:Scopus 2018

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