IJLTEMAS International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS) IJLTEMAS 2278-2540 IJLTEMAS 281 10.51583/IJLTEMAS.2026.150800087 Education Multi Class Emotion Classification using PSD and CNN Kumawat Ramprasad Department of Electrical and Electronics Engineering (Mandsaur University) Mandsaur, India India Jain Virendra Department of Electrical and Electronics Engineering (Mandsaur University) Mandsaur, India India Das Bairagi Tapan Department of Electrical and Electronics Engineering (Mandsaur University) Mandsaur, India India 15 8 1213 1220 30 08 2026 04 09 2026 16 09 2026 CNN EEG emotion recognition PSD SEED_IV Abstract

Emotion identification based on electroencephalography (EEG) data has become a popular area of study in human-machine interactions. Conventional machine learning techniques employ carefully created classifiers using hand-made features that may be restricted to domain expertise. We suggested a convolutional neural network (CNN) model to automatically extract the spatiotemporal information from power spectral density (PSD) features extracted from EEG signals, motivated by the exceptional performance of deep learning techniques in recognition tests. The proposed model achieves a high accuracy rate of 90% using the preprocessing method with baseline signals, for the four-class classification task in the SEED_IV dataset. We have achieved a standard deviation of 4.3% in multiple trials

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