Classification of Emotion in Chinese Words Based on EEG

• 作 者: MinminCheng;HaixianWang;ZuhongLu;
• 机 构: Key Laboratory of Child Development and Learning Science of Ministry of Education Research Center fo
• 出 处: 儿童早期发展前沿研究国际会议(International Symposium on cutting-edge resea
• 发表日期: 2014年期

　　To classify the emotion induced by human language, this study used EEG signals from the brain to identify the emotional and non-emotional two-character Chinese words.The power spectrums in theta, alpha and beta frequency bands are extracted by short time Fourier transform (STFT).Principal component analysis (PCA) is employed for dimensionality reduction.The mean accuracy rate of LDA classifier is about 63% for 4 subjects.The result demonstrates the identifiability of emotion in Chinese words.