Artificial Neural Network Classification of Motor-Related EEG: An Increase in Classification Accuracy by Reducing Signal Complexity

We apply artificial neural network (ANN) for recognition and classification of electroencephalographic (EEG) patterns associated with motor imagery in untrained subjects. Classification accuracy is optimized by reducing complexity of input experimental data. From multichannel EEG recorded by the set...

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Bibliographic Details
Main Authors: Vladimir A. Maksimenko, Semen A. Kurkin, Elena N. Pitsik, Vyacheslav Yu. Musatov, Anastasia E. Runnova, Tatyana Yu. Efremova, Alexander E. Hramov, Alexander N. Pisarchik
Format: Article
Language:English
Published: Wiley 2018-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2018/9385947
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