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EEG-Based Emotion Recognition System by Panos Lionas is a document available to read on EtoBox.

This document summarizes a study on recognizing emotions from human brain activity measured by EEG signals. The researchers collected EEG data from participants who viewed emotionally evocative images and rated their feelings. They analyzed features of the EEG signals like frequency band power and cross-correlations. Using these features, their system classified the EEG data into 5 emotion categories related to valence and arousal, achieving accuracy of 32-37% via cross-validation. Classification was more a

Author

Panos Lionas

Language

EN