%0 Journal Article
%T Classifying the EEG Signal through Stimulus of Motor Movement Using New Type of Wavelet
%A Endro Yulianto
%A Adhi Susanto
%A Thomas Sri Widodo
%A Samekto Wibowo
%J IAES International Journal of Artificial Intelligence (IJ-AI)
%D 2012
%I Institute of Advanced Engineering and Science (IAES)
%R 10.11591/ij-ai.v1i3.843
%X Brain Computer Interface (BCI) refers to a system designed to translate the brain signal in controlling a computer application.  The most widely used brain signal is electroencephalograph (EEG) for using the non-invasive method, and having a quite good resolution and relatively affordable equipments. This research purposively is to obtain the characteristics of EEG signals using the motor movement of ¡°turn right¡± and ¡°turn left¡± that is by moving the simulation of steering wheel. The characteristic of signal obtained is subsequently used as a reference to create a new type of wavelet for classification. The signal processing, including a 4 ¨C 20 Hz bandpass filter, signal segmentation in 1 to 2 seconds after stimuli and signal correlation,  is used to obtain the characteristic of EEG signal; namely Event¨CRelated Synchronization/Desynchronization (ERS/ERD). The result of test data classification to two new types of wavelet shows that each volunteer has a higher correlation value towards the new type of wavelet that has been designed with various wavelet scales for each individuals.
%U http://www.iaesjournal.com/online/index.php/IJAI/article/view/843