TY - JOUR
AU - Lu, Bao-Liang
AB - 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 1s. 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.
TI - Emotion classification based on gamma-band EEG.
JF - Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
DO - 10.1109/IEMBS.2009.5334139
DA - 2010-04-22
UR - https://www.deepdyve.com/lp/pubmed/emotion-classification-based-on-gamma-band-eeg-6L2r0ySwem
SP - 1323
EP - 6
VL - 2009
IS - 
DP - DeepDyve
ER -