Simulation About Accurate Extraction of Emotional EEG

doi:10.3969/j.issn.1006-2475.2017.01.025

Abstract

Abstract: EEG signal is a kind of microvolt signal. Collected from the scalp, EEG signals contain EOG signals, ECG signals as well as a variety of environmental noise. For the problem how the emotion recognition does effectively deal with EEG signals, firstly, the collected EEG signals from experiments are pretreated for removing interferences by using wavelet analysis and independent component analysis; secondly, in order to effectively extract EEG signal features, the amplitude histogram and standard difference are used to find qualitatively in time domain the differences in brain power of two kinds of emotion; lastly, the power spectrum is used to analyze the two emotional EEG gamma wave rhythm. The experimental simulation results show that it is feasible to use the gamma wave rhythm of EEG signals for emotion recognition.

Key words: emotion recognition, EEG, ICA, wavelet analysis, feature extraction

CLC Number:

TP391.4

TAN Zhi-wei, XIE Yun, SU Jing. Simulation About Accurate Extraction of Emotional EEG[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2017.01.025.

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