Human Emotion Classification from Brain EEG Signal Using Multimodal Approach of Classifier-Reference-Cited by-同舟云学术

Human Emotion Classification from Brain EEG Signal Using Multimodal Approach of Classifier

Published:2018 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2018 International Conference on Intelligent Information Technology - ICIIT 2018
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Author:

Kimmatkar Nisha Vishnupant¹,Babu Vijaya B.¹

Affiliation:

1. Department of CSE, K L University, Vaddeshwaram, Guntur, AP

Publisher

ACM Press

Reference13 articles.

1. Palus, Milan. 1996. Nonlinearity in normal human EEG: cycles, temporal asymmetry, nonstationarity and randomness, not chaos. Biological cybernetics. 75. 389--96. 10.1007/s004220050304.

2. http://bcmi.sjtu.edu.cn/~seed/index.html.

3. Zheng, Wei-Long, and Bao-Liang Lu. 2015. Investigating critical frequency bands and channels for EEG-based emotion recognition with deep neural networks. IEEE Transactions on Autonomous Mental Development 7.3. 162--175.

4. Duan, Ruo-Nan, Jia-Yi Zhu, and Bao-Liang Lu. 2013. Differential entropy feature for EEG-based emotion classification. Neural Engineering (NER), 2013 6th International IEEE/EMBS Conference on. IEEE.

5. Li, Mu, and Bao-Liang Lu. 2009. Emotion classification based on gamma-band EEG. Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE.

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