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2016 | OriginalPaper | Buchkapitel

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

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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 %.

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Metadaten
Titel
Appling of Neural Networks to Classification of Brain-Computer Interface Data
verfasst von
Malgorzata Plechawska-Wojcik
Piotr Wolszczak
Copyright-Jahr
2016
DOI
https://doi.org/10.1007/978-3-319-34099-9_37

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