SSVEP-based Brain-computer Interface for Computer Control Application Using SVM Classifier

Sutjiadi, Raymond and Pattiasina, Timothy John and Lim, Resmana (2018) SSVEP-based Brain-computer Interface for Computer Control Application Using SVM Classifier. International Journal of Engineering & Technology, 7 (4). pp. 2722-2728. ISSN 2227-524X

[img]
Preview
Text (Article)
IJET-16139.pdf - Published Version

Download (783kB) | Preview
[img] Text (Hasil Cek Similarity)
(report) Paper SSVEP IJET.pdf - Supplemental Material
Restricted to Repository staff only

Download (354kB)
[img] Text (Peer Review Bapak Timothy John Pattiasina)
Peer Review SSVEP.pdf - Supplemental Material
Restricted to Repository staff only

Download (697kB)
Official URL: https://www.sciencepubco.com/index.php/ijet/articl...

Abstract

In this research, a Brain Computer Interface (BCI) based on Steady State Visually Evoked Potential (SSVEP) for computer control appli-cations using Support Vector Machine (SVM) is presented. For many years, people have speculated that electroencephalographic activi-ties or other electrophysiological measures of brain function might provide a new non-muscular channel that can be used for sending messages or commands to the external world. BCI is a fast-growing emergent technology in which researchers aim to build a direct channel between the human brain and the computer. BCI systems provide a new communication channel for disabled people. Among many different types of the BCI systems, the SSVEP based has attracted more attention due to its ease of use and signal processing. SSVEPs are usually detected from the occipital lobe of the brain when the subject is looking at a twinkling light source. In this paper, SVM is used to classify SSVEP based on electroencephalogram data with proper features. Based on the experiment utilizing a 14-channel Electroencephalography (EEG) device, 80 percent of accuracy can be reached by our SSVEP-based BCI system using Linear SVM Kernel as classification engine.

Item Type: Article
Uncontrolled Keywords: Brain Computer Interface, Brain Waves, Electroencephalography, Steady State Visually Evoked Potential, Support Vector Machine
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Information Technology
Faculty of Information Technology > Informatics Department
Faculty of Information Technology > Information System Department
Depositing User: P3M IKADO
Date Deposited: 27 Sep 2018 06:44
Last Modified: 16 Jul 2020 03:08
URI: http://repository.ikado.ac.id/id/eprint/62

Actions (login required)

View Item View Item