WT feature based emotion recognition from multi-channel physiological signals with decision fusion
J Xie, X Xu, L Shu - 2018 first asian conference on affective …, 2018 - ieeexplore.ieee.org
J Xie, X Xu, L Shu
2018 first asian conference on affective computing and intelligent …, 2018•ieeexplore.ieee.orgEmotion recognition has become a hot research topic in the field of human-computer
interaction (HCI), while the recognition accuracy is still not adequate for real applications. In
this paper, a new emotion recognition framework based on multi-channel physiological
signals including ECG, EMG and SCL using the dataset of Bio Vid Emo DB was proposed. A
series of feature selection methods and fusion methods had been evaluated, through which
wavelet transform features and SVM classifier were adopted. An improved accuracy of …
interaction (HCI), while the recognition accuracy is still not adequate for real applications. In
this paper, a new emotion recognition framework based on multi-channel physiological
signals including ECG, EMG and SCL using the dataset of Bio Vid Emo DB was proposed. A
series of feature selection methods and fusion methods had been evaluated, through which
wavelet transform features and SVM classifier were adopted. An improved accuracy of …
Emotion recognition has become a hot research topic in the field of human-computer interaction (HCI), while the recognition accuracy is still not adequate for real applications. In this paper, a new emotion recognition framework based on multi-channel physiological signals including ECG, EMG and SCL using the dataset of Bio Vid Emo DB was proposed. A series of feature selection methods and fusion methods had been evaluated, through which wavelet transform features and SVM classifier were adopted. An improved accuracy of 94.81% was achieved by fusing the classifiers of ECG and EMG, which was adequate for real applications and better than relevant studies.
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