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http://dx.doi.org/10.7840/kics.2014.39C.2.122

The Classification Algorithm of Users' Emotion Using Brain-Wave  

Lee, Hyun-Ju (세종대학교 컴퓨터공학과 멀티미디어 인터넷 연구실)
Shin, Dong-Il (세종대학교 컴퓨터공학과 멀티미디어 인터넷 연구실)
Shin, Dong-Kyoo (세종대학교 컴퓨터공학과 멀티미디어 인터넷 연구실)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.39C, no.2, 2014 , pp. 122-129 More about this Journal
Abstract
In this study, emotion-classification gathered from users was performed, classification-experiments were then conducted using SVM(Support Vector Machine) and K-means algorithm. Total 15 numbers of channels; CP6, Cz, FC2, T7. PO4, AF3, CP1, CP2, C3, F3, FC6, C4, Oz, T8 and F8 among 32 members of the channels measured were adapted in Brain signals which indicated obvious the classification of emotions in previous researches. To extract emotion, watching DVD and IAPS(International Affective Picture System) which is a way to stimulate with photos were applied and SAM(Self-Assessment Manikin) was used in emotion-classification to users' emotional conditions. The collected users' Brain-wave signals gathered had been pre-processing using FIR filter and artifacts(eye-blink) were then deleted by ICA(independence component Analysis) using. The data pre-processing were conveyed into frequency analysis for feature extraction through FFT. At last, the experiment was conducted suing classification algorithm; Although, K-means extracted 70% of results, SVM showed better accuracy which extracted 71.85% of results. Then, the results of previous researches adapted SVM were comparatively analyzed.
Keywords
Brain-wave; Emotion; Classification; FIR; ICA; FFT; SVM; K-means;
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