Cited time in webofscience Cited time in scopus

Full metadata record

DC Field Value Language Kwon, Hyeong Oh - Kang, Won Seok - Yun, Sang Hun - 2021-04-26T04:36:43Z - 2021-04-26T04:36:43Z - 2018-03-29 - 2014 -
dc.identifier.citation Global Journal on Technology, v.5, pp.53 - 58 -
dc.identifier.issn 2147-5369 -
dc.identifier.uri -
dc.identifier.uri -
dc.description.abstract In this paper, we proposes an emotion classification method based on Bayesian Belief Networks (BBN) to classify
the EEG signals which are induced by the olfactory stimuli. In order to stimulate the olfactory organ, the citralva
is used as the pleasant smell and 2-melcaptoethanol is used as the unpleasant smell. We placed the 4-channel
EEG electrodes on F3, F4 at frontal lobe and T3, T4 at temporal lobe to acquire EEG signals in according to the
standard electrode placement, which is called international 10-20 system. The participants are five high school
students (4 male and 1 female) whose ages are from 17 to 18. To extract features from EEG signals, the timefrequency
analysis is performed by using the Event-Related Spectral Perturbation (ERSP). The average values of
relative power of the frequency in each time domain are used as the features for the BBN classifier. To evaluate
the performance of the proposed method, we compared the performance of the BBN and Naïve Bayesian
Networks (BN). As a result of the comparison, we confirm that the classification rate of the BBN is increased by
approximately 11%.
dc.language English -
dc.publisher Academic World Education & Research Center -
dc.title EEG-based Emotion Classification using Bayesian Belief Networks in Pleasant and Unpleasant Odorant Stimuli -
dc.type Article -
dc.type.local Article(Overseas) -
dc.type.rims ART -
dc.description.journalClass 1 -
dc.citation.publicationname Global Journal on Technology -
dc.contributor.nonIdAuthor Kwon, Hyeong Oh -
dc.identifier.citationVolume 5 -
dc.identifier.citationStartPage 53 -
dc.identifier.citationEndPage 58 -
dc.identifier.citationTitle Global Journal on Technology -
dc.description.isOpenAccess N -
dc.contributor.affiliatedAuthor Kwon, Hyeong Oh -
dc.contributor.affiliatedAuthor Kang, Won Seok -
dc.contributor.affiliatedAuthor Yun, Sang Hun -
Files in This Item:

There are no files associated with this item.

Appears in Collections:
ETC 1. Journal Articles
Division of Electronics & Information System 1. Journal Articles


  • twitter
  • facebook
  • mendeley

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.