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Motor Imagery Task Classification in EEG Signals with Spiking Neural Network

  • Carlos D. Virgilio G
  • Humberto SossaEmail author
  • Javier M. Antelis
  • Luis E. Falcón
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11524)

Abstract

We report the development and evaluation of brain signal classifiers, specifically Spiking Neuron based classifiers. The proposal consists of two main stages: feature extraction and pattern classification. The EEG signals used represent four motor imagery tasks: Left Hand, Right Hand, Foot and Tongue movements. In addition, one more class was added: Rest. These EEG signals were obtained from a database provided by the Technological University of Graz. Feature extraction stage was carried out by applying two algorithms: Power Spectral Density and Wavelet Decomposition. The tested algorithms were: K-Nearest Neighbors, Multilayer Perceptron, Single Spiking Neuron and Spiking Neural Network. All of them were evaluated in the classification between two Motor Imagery tasks; all possible pairings were made with the 5 mental tasks (Rest, Left Hand, Right Hand, Tongue and Foot). In the end, a performance comparison was made between a Multilayer Perceptron and Spiking Neural Network.

Keywords

EEG signals Motor Imagery Power Spectral Density Wavelet Decomposition Neural networks Multi layer perceptron Spiking Neural Network 

Notes

Acknowledgements

We would like to express our sincere appreciation to the Instituto Politécnico Nacional and the Secretaria de Investigación y Posgrado for the economic support provided to carry out this research. This project was supported economically by SIP-IPN (numbers 20180730 and 20190007) and the National Council of Science and Technology of Mexico (CONACyT) (65 Frontiers of Science, numbers 268958 and PN2015-873).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Carlos D. Virgilio G
    • 1
  • Humberto Sossa
    • 1
    • 2
    Email author
  • Javier M. Antelis
    • 2
  • Luis E. Falcón
    • 2
  1. 1.Centro de Investigación en ComputaciónInstituto Politécnico NacionalMexico CityMexico
  2. 2.Tecnológico de Monterrey, Escuela de Ingeniería y CienciasZapopanMexico

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