Classification of the Emotional States Based on the EEG Signal Processing

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F09%3A00159618" target="_blank" >RIV/68407700:21230/09:00159618 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Classification of the Emotional States Based on the EEG Signal Processing
Original language description
The paper proposes a method for the classification of EEG signal based on machine learning methods. We analyzed the data from an EEG experiment consisting of affective picture stimuli presentation, and tested automatic recognition of the individual emotional states from the EEG signal using Bayes classifier. The mean accuracy was about 75 percent, but we were not able to select universal features for classification of all subjects, because of interindividual differences in the signal. We also identifiedcorrelation between the classification error and the extroversion-introversion personality trait measured by EPQ-R test. Introverts have lower excitation threshold so we are able to detect the differences in their EEG activity with better accuracy. Furthermore, the use of Kohonen's self-organizing map for visualization is suggested and demonstrated on one subject.
Czech name
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Czech description
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Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of 9th Intrenational Conference on Information Technology and Applications in Biomedicine
ISBN
978-1-4244-5378-8
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
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Publisher name
IEEE
Place of publication
Piscataway
Event location
Larnaca
Event date
Nov 5, 2009
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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