The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
EEG-based emotion recognition during watching movies
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.
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Cites
A Global Geometric Framework for Nonlinear Dimensionality Reduction
Tenenbaum, J. B., Silva, V. D., & Langford, J. C. (2000) · Science · doi:10.1126/science.290.5500.2319 · Cited by 13,585
Measuring emotion: The self-assessment manikin and the semantic differential
Bradley, M. M., & Lang, P. J. (1994) · Journal of Behavior Therapy and Experimental Psychiatry · doi:10.1016/0005-7916(94)90063-9 · Cited by 9,538
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
Zeng, Z., Pantic, M., Roisman, G. I., & Huang, T. S. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2008.52 · Cited by 2,797
Cited by
EmotionMeter: A Multimodal Framework for Recognizing Human Emotions
Zheng, W.-L., Liu, W., Lu, Y., Lu, B.-L., & Cichocki, A. (2019) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2018.2797176 · Cited by 1,276
Self-citationEmotions Recognition Using EEG Signals: A Survey
Alarcao, S. M., & Fonseca, M. J. (2019) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2017.2714671 · Cited by 1,201
Feature Extraction and Selection for Emotion Recognition from EEG
Jenke, R., Peer, A., & Buss, M. (2014) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2014.2339834 · Cited by 1,081
Identifying Stable Patterns over Time for Emotion Recognition from EEG
Zheng, W.-L., Zhu, J.-Y., & Lu, B.-L. (2019) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2017.2712143 · Cited by 990
Self-citationA review of emotion recognition using physiological signals
Shu, L., Xie, J., Yang, M., Li, Z., Li, Z., Liao, D., Xu, X., & Yang, X. (2018) · Sensors · doi:10.3390/s18072074 · Cited by 923
Metadata
- Authors
- Nie, D., Wang, X.-W., Shi, L.-C., & Lu, B.-L.
- Venue
- 2011 5th International IEEE/EMBS Conference on Neural Engineering
- Publisher
- IEEE
- Published
- 2011-04
- Pages
- 667-670
- ISSN
- 1948-3554 (ISSN-L)
- OpenAlex
- W2109773980
- Cited by
- 360
- References
- 3
- FWCI
- 24.02
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Nie, D., Wang, X.-W., Shi, L.-C., & Lu, B.-L. (2011). EEG-based emotion recognition during watching movies. 2011 5th International IEEE/EMBS Conference on Neural Engineering. https://doi.org/10.1109/ner.2011.5910636
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