1-D Cursor Movement using Brain Computer Interface

Abstract: The main idea of the current work is to use a wireless Electroencephalography (EEG) signal as a remote control for the mouse cursor of a personal computer. The proposed system uses EEG signals as a communication link between brains and computers. Signal records obtained from the PhysioNet EEG dataset were analyzed using the Coif lets wavelets and many features were extracted using PSD. The extracted features were inputted into machine learning algorithms to generate the decision rules required for our application. The suggested online system was tested and very good performance was achieved. This system could be helpful for disabled people as they can control computer applications via the imagination of 1D-cursor movement.

Keywords: EEG; BCI; Data Mining; Machine Learning; SVMs; NNs; DWT; Feature Extraction.