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Kim, Sung-Phil
Brain-Computer Interface (BCI) Lab
Research Interests
  • Brain-computer interface, Statistical Signal Processing, Neural Code, Neuromarketing


A Review on the Computational Methods for Emotional State Estimation from the Human EEG

DC Field Value Language Kim, Min-Ki ko Kim, Miyoung ko Oh, Eunmi ko Kim, Sung-Phil ko 2014-12-22T00:06:49Z - 2014-12-19 ko 2013 ko
dc.identifier.citation COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE, v.2013, pp.1 - 13 ko
dc.identifier.issn 1748-670X ko
dc.identifier.uri -
dc.description.abstract A growing number of affective computing researches recently developed a computer system that can recognize an emotional state of the human user to establish affective human-computer interactions. Various measures have been used to estimate emotional states, including self-report, startle response, behavioral response, autonomic measurement, and neurophysiologic measurement. Among them, inferring emotional states from electroencephalography (EEG) has received considerable attention as EEG could directly reflect emotional states with relatively low costs and simplicity. Yet, EEG-based emotional state estimation requires well-designed computational methods to extract information from complex and noisy multichannel EEG data. In this paper, we review the computational methods that have been developed to deduct EEG indices of emotion, to extract emotion-related features, or to classify EEG signals into one of many emotional states. We also propose using sequential Bayesian inference to estimate the continuous emotional state in real time. We present current challenges for building an EEG-based emotion recognition system and suggest some future directions. ko
dc.description.statementofresponsibility open -
dc.language 영어 ko
dc.title A Review on the Computational Methods for Emotional State Estimation from the Human EEG ko
dc.type ARTICLE ko
dc.identifier.wosid 000317197900001 ko
dc.type.rims ART ko
dc.description.wostc 2 * 2015-05-06 *
dc.identifier.doi 10.1155/2013/573734 ko
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