Emotion Detection Using EEG Signals

Rustem Popa

Abstract


In this paper we propose some new methods for detecting emotions in EEG signals, using both time analysis and frequency analysis of signals. In the last section of the paper we present a method of classifying EEG signals using a feedforward neural network. EEG signals were acquired on a single channel, using a laboratory equipment produced by BIOPAC, and the subject was relaxed with his eyes open or in one of the states of joy, anger, and music listening for about 60 seconds. Separate analyzes were also performed for the 4 frequency bands of the EEG signals: alpha, beta, theta and delta waves.


Keywords


electroencephalography, zero crossings, discrete cosine transform, neural networks, emotion detection

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DOI: http://dx.doi.org/10.52155/ijpsat.v24.1.2459

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