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This paper aims to explore the neural patterns between Chinese and Germans for electroencephalogram (EEG)-based emotion recognition. Both Chinese and German subjects, wearing electrode caps, watched video stimuli that triggered positive, neutral, and negative emotions. Two emotion classifiers are trained on Chinese EEG data and German EEG data, respectively. The experiment results indicate that: a)...
EEG signals, which can record the electrical activity along the scalp, provide researchers a reliable channel for investigating human emotional states. In this paper, a new algorithm, manifold regularized extreme learning machine (MRELM), is proposed for recognizing human emotional states (positive, neutral and negative) from EEG data, which were previously evoked by watching different types of movie...
This study aims at finding the relationship between EEG signals and human emotions. EEG signals are used to classify two kinds of emotions, positive and negative. First, we extracted features from original EEG data and used a linear dynamic system approach to smooth these features. An average test accuracy of 87.53% was obtained by using all of the features together with a support vector machine....
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