Classification of EEG Records for the Cursor Movement with the Convolutional Neural Network

Turk, OmerOzerdem, Mehmet Sirac2024-04-242024-04-242018978-1-5386-7786-5https://hdl.handle.net/11468/20630Innovations in Intelligent Systems and Applications Conference (ASYU) -- OCT 04-06, 2018 -- Adana, TURKEYNowadays, very successful results are obtained with deep learning architectures which can be applied to many fields. Because of the high performances it provides in many areas, deep learning has come to a central position in machine learning and pattern recognition. In this study, electroencephalogram (EEG) signals related to up and down cursor movements were represented as image pattern by using obtained approximation coefficients after wavelet transform. The Obtained image patterns were classified by applying Convolutional Neural Network. In this study, EEG records related to cursor movements were classified and classification accuracy was obtained as 88.13%.trinfo:eu-repo/semantics/closedAccessConvolutional Neural NetworkEegWavelet TransformClassification of EEG Records for the Cursor Movement with the Convolutional Neural NetworkClassification of EEG Records for the Cursor Movement with the Convolutional Neural NetworkConference Object2932WOS:0004555928000352-s2.0-85059975910N/AN/A