METHODS OF CLASSIFICATION OF ELECTROENCEPHALOGRAM DATA FOR IDENTIFICATION OF HUMAN EMOTIONAL STATE
DOI:
https://doi.org/10.30888/2709-2267.2025-31-00-016Ключові слова:
electroencephalogram, emotion recognition, cluster analysis, statistical analysis, barycenter signatureАнотація
The developed methods for classifying electroencephalogram (EEG) signals enable the identification of brain responses to emotional stimuli, which serves as the foundation for constructing neurointerface systems. The result of the classification process isMetrics
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Посилання
Bota, P., Wang, C., & Leu, M. C. (2019). Electroencephalogram-Based Emotion Recognition: A Comparative Analysis of Different Feature Extraction Methods. Cognitive Neurodynamics, 13(5), 421–434.
Egger, M., Ley, M., & Hanke, S. (2019). Emotion Recognition from EEG Signals with Different Feature Extraction Techniques. Procedia Computer Science, 159, 31–38.
Lin, Y., & Li, Y. (2023). A Review on EEG-Based Emotion Recognition: Methods and Applications. Frontiers in Neuroscience, 17, 123456.
Опубліковано
2025-05-30
Як цитувати
Holoborodko, V., & Lyfar, V. (2025). METHODS OF CLASSIFICATION OF ELECTROENCEPHALOGRAM DATA FOR IDENTIFICATION OF HUMAN EMOTIONAL STATE. Sworld-Us Conference Proceedings, 1(usc31-00), 27–30. https://doi.org/10.30888/2709-2267.2025-31-00-016
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