Abstract
Recognition of user felt emotion is an exciting field because visual, verbal and facial communications can be falsified more easily than ‘inner’ emotions. Non-invasive EEG-based human emotion recognition entails the classification of discrete emotions using EEG data. These emotions can be defined by the arousal-valence dimensions. We performed real-time emotion classification for four categories of emotional states, namely: pleasant, sad, happy and frustrated. Higuchi’s Fractal Dimension was applied on EEG data and used as a feature extraction method and Support Vector Machine was used for classification. This paper documents a comparative study of classification accuracy achieved by collecting raw EEG data from 3 electrode locations vs. collection from 8 electrode locations.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Liu, Y., Sourina, O., Nguyen, M.K.: Real-time EEG-based Human Emotion Recognition and Visualization
Lin, Y.P., Wang, C.H., Wu, T.L., Jeng, S.K., Chen, J.H.: EEG-based emotion recognition in music listening: A comparison of schemes for multiclass support vector machine. In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Taipei, pp. 489–492 (2009)
Bos, D.O.: EEG-based emotion recognition (2006). http://hmi.ewi.utwente.nl/verslagen/capitaselecta/CS-Oude_Bos-Danny.pdf
Russell, J.A.: Affective space is bipolar. J. Pers. Soc. Psychol. 37, 345–356 (1979)
Higuchi, T.: Approach to an irregular time series on the basis of the fractal theory
Liu, Y., Sourina, O., Nguyen, M.K.: Real-time EEG-based Human Emotion Recognition and Visualization
Lin, Y.P., Wang, C.H., Wu, T.L., Jeng, S.K., Chen, J.H.: EEG-based emotion recognition in music listening: A comparison of schemes for multiclass support vector machine. In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Taipei, pp. 489–492 (2009)
Bos, D.O.: EEG-based emotion recognition (2006). http://hmi.ewi.utwente.nl/verslagen/capitaselecta/CS-Oude_Bos-Danny.pdf
Russell, J.A.: Affective space is bipolar. J. Pers. Soc. Psychol. 37, 345–356 (1979)
Higuchi, T.: Approach to an irregular time series on the basis of the fractal theory
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Javaid, M.M., Yousaf, M.A., Sheikh, Q.Z., Awais, M.M., Saleem, S., Khalid, M. (2015). Real-Time EEG-based Human Emotion Recognition. In: Arik, S., Huang, T., Lai, W., Liu, Q. (eds) Neural Information Processing. ICONIP 2015. Lecture Notes in Computer Science(), vol 9492. Springer, Cham. https://doi.org/10.1007/978-3-319-26561-2_22
Download citation
DOI: https://doi.org/10.1007/978-3-319-26561-2_22
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-26560-5
Online ISBN: 978-3-319-26561-2
eBook Packages: Computer ScienceComputer Science (R0)