Emotion Classification Based On Gamma-Band Eeg
2009 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-20(2009)
摘要
In this paper, we use EEG signals to classify two emotions happiness and sadness. These emotions are evoked by showing subjects pictures of smile and cry facial expressions. We propose a frequency band searching method to choose an optimal band into which the recorded EEG signal is filtered. We use common spatial patterns (CSP) and linear-SVM to classify these two emotions. To investigate the time resolution of classification, we explore two kinds of trials with lengths of 3s and is. Classification accuracies of 93.5% +/- 6.7% and 93.0% +/- 6.2% are achieved on 10 subjects for 3s-trials and 1s-trials, respectively. Our experimental results indicate that the gamma band (roughly 30-100 Hz) is suitable for EEG-based emotion classification.
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关键词
psychology,frequency,electroencephalography,facial expressions,support vector machine,emotion classification,spatial resolution,support vector machines,facial expression,common spatial pattern,neuroscience
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