IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 1, No 3: September 2012

Classifying the EEG Signal through Stimulus of Motor Movement Using New Type of Wavelet

Endro Yulianto (Gadjah Mada University)
Adhi Susanto (Gadjah Mada University)
Thomas Sri Widodo (Gadjah Mada University)
Samekto Wibowo (Gadjah Mada University)



Article Info

Publish Date
13 Sep 2012

Abstract

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 – 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–Related 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.DOI: http://dx.doi.org/10.11591/ij-ai.v1i3.843

Copyrights © 2012






Journal Info

Abbrev

IJAI

Publisher

Subject

Computer Science & IT Engineering

Description

IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like ...