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Pattern Analysis and Applications

, Volume 21, Issue 1, pp 81–89 | Cite as

Emotion recognition from EEG signals by using multivariate empirical mode decomposition

Theoretical Advances

Abstract

This paper explores the advanced properties of empirical mode decomposition (EMD) and its multivariate extension (MEMD) for emotion recognition. Since emotion recognition using EEG is a challenging study due to nonstationary behavior of the signals caused by complicated neuronal activity in the brain, sophisticated signal processing methods are required to extract the hidden patterns in the EEG. In addition, multichannel analysis is another issue to be considered when dealing with EEG signals. EMD is a recently proposed iterative method to analyze nonlinear and nonstationary time series. It decomposes a signal into a set of oscillations called intrinsic mode functions (IMFs) without requiring a set of basis functions. In this study, a MEMD-based feature extraction method is proposed to process multichannel EEG signals for emotion recognition. The multichannel IMFs extracted by MEMD are analyzed using various time and frequency domain techniques such as power ratio, power spectral density, entropy, Hjorth parameters and correlation as features of valance and arousal scales of the participants. The proposed method is applied to the DEAP emotional EEG data set, and the results are compared with similar previous studies for benchmarking.

Keywords

Empirical mode decomposition Multivariate empirical mode decomposition Emotion recognition Electroencephalogram 

Notes

Acknowledgments

This work was partially supported by The Research Fund of The University of Istanbul, Project numbers 45259 and 54959.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© Springer-Verlag London 2016

Authors and Affiliations

  1. 1.Department of Mechatronics EngineeringBursa Technical UniversityYildirim, BursaTurkey
  2. 2.Department of Electrical and Electronics EngineeringIstanbul UniversityAvcilar, IstanbulTurkey

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