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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Dan Nie Xiao-Wei Wang Li-Chen Shi Bao-Liang Lu |
| Copyright Year | 2011 |
| Description | Author affiliation: Dept. of Comput. Sci. & Eng., Shanghai Jiao Tong Univ., Shanghai, China (Dan Nie; Xiao-Wei Wang; Li-Chen Shi; Bao-Liang Lu) |
| Abstract | 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. Next, we reduced the dimension of features through correlation coefficients. The top 100 and top 50 subject-independent features were achieved, with average test accuracies of 89.22% and 84.94%, respectively. Finally, a manifold model was applied to find the trajectory of emotion changes. |
| Sponsorship | Nat. Sci. Found. |
| Starting Page | 667 |
| Ending Page | 670 |
| File Size | 967427 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424441402 |
| ISSN | 19483554 |
| DOI | 10.1109/NER.2011.5910636 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-04-27 |
| Publisher Place | Mexico |
| Access Restriction | Subscribed |
| Rights Holder | M Akay and K. Tippit. |
| Subject Keyword | Manifolds Emotion recognition Accuracy Humans Motion pictures Electroencephalography Trajectory |
| Content Type | Text |
| Resource Type | Article |
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