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Neurological Classifier Committee Based on Artificial Neural Networks and Support Vector Machine for Single-Trial EEG Signal Decoding

  • Konstantin SonkinEmail author
  • Lev Stankevich
  • Yulia Khomenko
  • Zhanna Nagornova
  • Natalia Shemyakina
  • Alexandra Koval
  • Dmitry Perets
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9719)

Abstract

This study aimed to finding effective approaches for electroencephalographic (EEG) multiclass classification of imaginary movements. The combined classifier of EEG signals based on artificial neural network (ANN) and support vector machine (SVM) algorithms was applied. Effectiveness of the classifier was shown in 4-class imaginary finger movement classification. Nine right-handed subjects participated in the study. The mean decoding accuracy using combined heterogeneous classifier committee was −60 ± 10 %, max: 77 ± 5 %, while application of homogeneous classifier based on committee of ANNs −52 ± 9 % and 65 ± 5 % correspondingly. This work supports the feasibility of the approach, which is presumed suitable for imaginary movements decoding of four fingers of one hand. These results could be used for development of effective non-invasive BCI with enlarged amount of degrees of freedom.

Keywords

Electroencephalography Classifier committee Artificial neural network Support vector machine Imaginary finger movements 

Notes

Acknowledgements

The study was supported by the RFBR foundation grant № 13-01-12059 ofi-m.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Konstantin Sonkin
    • 1
    Email author
  • Lev Stankevich
    • 1
  • Yulia Khomenko
    • 2
  • Zhanna Nagornova
    • 3
  • Natalia Shemyakina
    • 3
  • Alexandra Koval
    • 1
  • Dmitry Perets
    • 1
  1. 1.St. Petersburg State Polytechnic UniversitySt. PetersburgRussia
  2. 2.N.P. Bechtereva Institute of Human BrainRussian Academy of SciencesSt. PetersburgRussia
  3. 3.I.M. Sechenov Institute of Evolutionary Physiology and BiochemistryRussian Academy of SciencesSt. PetersburgRussia

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