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Appling of Neural Networks to Classification of Brain-Computer Interface Data

  • Malgorzata Plechawska-WojcikEmail author
  • Piotr Wolszczak
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 613)

Abstract

The paper presents application of neural networks to the construction of a brain-computer interface (BCI) based on the Motor Imagery paradigm. The BCI was constructed for ten electroencephalographic (EEG) signals collected and analysed in real time.The filtered signals were divided into three groups corresponding to the information displayed to users on the screen during the experiments. ANOVA analysis and automatic construction of a neural network (NN) classification were also performed. Results of the ANOVA analysis were confirmed by the neural networks efficiency analysis. The efficiency of NN classification of the left and right hemisphere activities reached almost 70 %.

Keywords

Neural networks Brain-computer interface EEG data ANOVA 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Lublin University of TechnologyLublinPoland

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