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Optimized Echo State Network with Intrinsic Plasticity for EEG-Based Emotion Recognition

  • Rahma Fourati
  • Boudour Ammar
  • Chaouki Aouiti
  • Javier Sanchez-Medina
  • Adel M. Alimi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10635)

Abstract

Reservoir Computing (RC) is a paradigm for efficient training of Recurrent Neural Networks (RNNs). The Echo State Network (ESN), a type of RC paradigm, has been widely used for time series forecasting. Whereas, few works exist on classification with ESN. In this paper, we shed light on the use of ESN for pattern recognition problem, i.e. emotion recognition from Electroencephalogram (EEG). We show that the reservoir with its recurrence is able to perform the feature extraction step directly from the EEG raw. Such kind of recurrence rich of nonlinearities allows the projection of the input data into a high dimensional state space. It is well known that the ESN fails due to the poor choices of its initialization. Nevertheless, we show that pretraining the ESN with the Intrinsic Plasticity (IP) rule remedies the shortcoming of randomly initialization. To validate our approach, we tested our system on the benchmark DEAP containing EEG signals of 32 subjects and the results were promising.

Keywords

Echo state network Intrinsic plasticity Feature extraction Classification Electroencephalogram Emotion recognition 

Notes

Acknowledgment

The research leading to these results has received funding from the Ministry of Higher Education and Scientific Research of Tunisia under the grant agreement number LR11ES48.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Rahma Fourati
    • 1
  • Boudour Ammar
    • 1
  • Chaouki Aouiti
    • 2
  • Javier Sanchez-Medina
    • 3
  • Adel M. Alimi
    • 1
  1. 1.REGIM-Lab.: REsearch Groups in Intelligent Machines, National Engineering School of Sfax (ENIS)University of SfaxSfaxTunisia
  2. 2.Research Units of Mathematics and Applications UR13ES47, Department of Mathematics, Faculty of Sciences of BizertaUniversity of CarthageBizertaTunisia
  3. 3.CICEI: Innovation Center for the Information SocietyUniversity of Las Palmas de Gran CanariaLas Palmas de Gran CanariaSpain

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