The role of empirical mode decomposition on emotion classification using stimulated eeg signals

Anwesha Khasnobish, Saugat Bhattacharyya, Garima Singh, Arindam Jati, Amit Konar, D. N. Tibarewala, R. Janarthanan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

An efficient scheme of emotion recognition using EEG signals is an initiation to our quest for developing emotionally intelligent systems and devices, in order to enhance the performance quality of the same. Classification of emotions, both euphoric and negative, using stimulated EEG signals acquired from subjects whose different emotional states were elicited using audio-visual stimuli. The underlying strategy involved the extraction of Power spectral density(PSD) and empirical mode decomposition (EMD) features from the raw EEG data and their classification using linear discriminant analysis (LDA) and linear support vector machine (SVM) thereby classifying the emotions into their respective emotion classes: neutral, happy and sad, with an average classification accuracy of 76.46%,where the neutral state has been classified most efficiently, with an average classification accuracy of 80.86%. The classification accuracy increases with EMD features with reduction in time and computational complexity. LDA is found to perform better than LSVM with EMD features.

Original languageEnglish
Title of host publicationAdvances in Computing and Information Technology- Proceedings of the 2nd International Conference on Advances in Computing and Information Technology, ACITY 2012- Volume 3
EditorsNatarajan Meghanathan, Nabendu Chaki, Dhinaharan Nagamalai
PublisherSpringer Verlag
Pages55-62
Number of pages8
ISBN (Electronic)978-3-642-31600-5
ISBN (Print)9783642315992
DOIs
Publication statusPublished - 1 Jan 2013
Event2nd International Conference on Advances in Computing and Information Technology, ACITY 2012 - Chennai, India
Duration: 13 Jul 201215 Jul 2012

Publication series

NameAdvances in Intelligent Systems and Computing
Volume178
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference2nd International Conference on Advances in Computing and Information Technology, ACITY 2012
CountryIndia
CityChennai
Period13/07/1215/07/12

Keywords

  • EEG
  • EMD
  • Emotion recognition
  • LDA
  • PSD
  • SVM

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    Khasnobish, A., Bhattacharyya, S., Singh, G., Jati, A., Konar, A., Tibarewala, D. N., & Janarthanan, R. (2013). The role of empirical mode decomposition on emotion classification using stimulated eeg signals. In N. Meghanathan, N. Chaki, & D. Nagamalai (Eds.), Advances in Computing and Information Technology- Proceedings of the 2nd International Conference on Advances in Computing and Information Technology, ACITY 2012- Volume 3 (pp. 55-62). (Advances in Intelligent Systems and Computing; Vol. 178). Springer Verlag. https://doi.org/10.1007/978-3-642-31600-5_6