Statistical Approach for a Complex Emotion Recognition Based on EEG Features

被引：6

作者：

Handayani, Dini ^{[1
]}

Yaacob, Hamwira ^{[1
]}

Wahab, Abdul ^{[1
]}

Alshaikli, Imad Fakhri Taha ^{[1
]}

机构：

[1] Int Islamic Univ Malaysia, Kuliyyah Informat & Commun Technol, Dept Comp Sci, Kuala Lumpur, Malaysia

来源：

2015 4TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER SCIENCE APPLICATIONS AND TECHNOLOGIES (ACSAT) | 2015年

关键词：

emotion recognition; mood recognition; normal distribution; Mel-frequency cepstral coefficients; multilayer perceptron; MOOD;

D O I：

10.1109/ACSAT.2015.54

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper presents electroencephalogram (EEG) signals and normal distribution technique to recognize the complex emotion. In the recent years, there has been a trend towards recognizing human emotions, however not many researcher aware that human can recognize more than one emotion at one time. Thus, in this study, normal distribution is utilized to recognize the expected emotion. The feature extraction and classification were obtained using a Mel frequency cepstral coefficients (MFCC) and multilayer perceptron (MLP). The correlation between human emotion and mood is also the essential point, since the mood can affected to the human emotion. The results show that the human emotions is strongly influenced by his initial mood.

引用

页码：202 / 207

页数：6

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