Emotion Recognition based on EEG Signals

Rustem Popa


In this paper we propose some methods for analyzing EEG signals in order to recognize emotions, using the representation of signals on Poincaré plots and the calculation of the fractal dimension. 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.


electroencephalography, chaos, fractal dimension, nonlinear dynamics, emotion recognition

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DOI: http://dx.doi.org/10.52155/ijpsat.v22.2.2089


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