Classification model of arousal and valence mental states by EEG signals analysis and Brodmann correlations

@inproceedings{Aguiaga2015ClassificationMO,
  title={Classification model of arousal and valence mental states by EEG signals analysis and Brodmann correlations},
  author={Adrian Rodriguez Agui{\~n}aga and Miguel Angel Lopez},
  year={2015}
}
This paper proposes a methodology to perform emotional states classification by the analysis of EEG signals, wavelet decomposition and an electrode discrimination process, that associates electrodes of a 10/20 model to Brodmann regions and reduce computational burden. The classification process were performed by a Support Vector Machines Classification process, achieving a 81.46 percent of classification rate for a multi-class problem and the emotions modeling are based in an adjusted space… CONTINUE READING
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