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Detection Of Emotions Based On Signals Using Wavelet Transform And Support Vector Machine Classification Method

عنوان مقاله: Detection Of Emotions Based On Signals Using Wavelet Transform And Support Vector Machine Classification Method
شناسه ملی مقاله: CEITCONF01_134
منتشر شده در کنفرانس ملی کامیپوتر،فناوری اطلاعات و کاربردهای هوش مصنوعی در سال 1396
مشخصات نویسندگان مقاله:

Manizheh Zare - Faculty member, Department of Computer Engineering, Islamic Azad University Zabol Branch, Zabol, Sistan and Baluchestan Province, Iran
Aliakbar Kikhajavan - Faculty member, Department of Electronic, Islamic Azad University Zabol Branch, Zabol, Sistan and Baluchestan Province, Iran

خلاصه مقاله:
Emotion represents a psychological state of the human mind. Researchers from different domains have diverse opinions about the developmental process of emotion. Detection of emotions has recently played a key role in human life, and most researches have greatly used physical parameters such as facial expressions, body movements, and heart signals, but few have used EEG brain signaling. In this paper, it has been attempted to identify emotions based on brain signals using wavelet transform coefficients as an attribute and SVM classification method to categorize such emotions. In this classification which was performed for four categories of feelings: joy, hatred, excitement,and fear, the obtained accuracy level was about %76. The results are better than the results of other papers that measure fewer feelings or use other classification methods.

کلمات کلیدی:
brain signals, support vector machine, wavelet transform, emotions

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/762597/