EEG-based Emotion Recognition Using Recurrence Plot Analysis and K Nearest Neighbor Classifier
محل انتشار: بیستمین کنفرانس مهندسی پزشکی ایران
سال انتشار: 1392
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 920
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شناسه ملی سند علمی:
ICBME20_093
تاریخ نمایه سازی: 25 فروردین 1394
چکیده مقاله:
Electroencephalogram (EEG)-based emotion recognition has been a rapidly growing field. However, accurate and sufficient performance rates are yet to be obtained. This paper presents the classification of EEG correlates on emotion using the relatively new non-linear feature extraction method, namely, Recurrence Plot analysis to extract thirteen non-linear features. This method is compared with feature extraction method based on spectral power analysis. The K nearest neighbor is applied to classify extracted features into the emotional states based on arousal-valence (high/low arousal, valence) plane with the addition of liking axis (positive/negative). Leading to performance rates of 58.05%, 64.56% and 67.42% for 3 classes of valence, arousal and liking; which confirm the advantage of a non-linear feature extraction method over previous frequency based feature extraction techniques
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نویسندگان
Fatemeh Bahari
Department of Biomedical Engineering Amirkabir University of Technology Tehran, Iran
Amin Janghorbani
Department of Biomedical Engineering Amirkabir University of Technology Tehran, Iran