METHODS OF INTELLIGENT ELECTROENCEPHALOGRAM DATA ANALYSIS FOR CLASSIFYING HUMAN EMOTIONAL STATES
DOI:
https://doi.org/10.30890/2709-1783.2025-42-00-011Keywords:
artificial intelligence, data analysis, knowledge bases, clustering, EEGAbstract
The paper presents a method for classifying human psycho-emotional states (positive and negative) based on the intelligent analysis of electroencephalogram (EEG) data. The proposed approach is an extension of the k-nearest neighbors method and is based onReferences
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M. R. Islam et al., "Emotion Recognition From EEG Signal Focusing on Deep Learning and Shallow Learning Techniques," in IEEE Access, vol. 9, pp.94601-94624, 2021, https://doi.org/10.1109/ACCESS.2021.3091487
Ismael, A.M., Alçin, Ö.F., Abdalla, K.H. et al. Two-stepped majority voting for efficient EEG-based emotion classification. Brain Inf. 7, 9 (2020). https://doi.org/10.1186/s40708-020-00111-3
Pillalamarri, R., Shanmugam, U. A review on EEG-based multimodal learning for emotion recognition. Artif Intell Rev 58, 131 (2025). https://doi.org/10.1007/s10462-025-11126-9
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