Abstract
This chapter proposes an emotion recognition system based on time domain analysis of the bio-signals for emotion features extraction. Three different types of emotions (happy, relax and sad) are classified and results are compared using five different algorithms based on RVM, MLP, DT, SVM and Bayesian techniques. Experimental results show the potential of using the time domain analysis for real-time application.
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First several seconds of signal recording is invalid as per specifications of the EEG equipment manufacturer.
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Acknowledgments
This work has been partially supported by NEDO (New Energy and Industrial Technology Development Organization) of Japan. The authors would like to thank Professor Kazuya Takeda of Nagoya University, Japan for his support and timely advises.
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© 2009 Springer Science+Business Media, LLC
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Li, M., Chai, Q., Kaixiang, T., Wahab, A., Abut, H. (2009). EEG Emotion Recognition System. In: Takeda, K., Erdogan, H., Hansen, J.H.L., Abut, H. (eds) In-Vehicle Corpus and Signal Processing for Driver Behavior. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-79582-9_10
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DOI: https://doi.org/10.1007/978-0-387-79582-9_10
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