2024 21st International Conference on Electrical Engineering Electronics Computer Telecommunications and Information Technology Ecti Con 2024 , 01/01/2024
EEG-based Brain-Computer Interface System via Time-Locked Visual Attention for Assistive Device Control
Abstract
This work proposes a brain-computer interface system using visual attention paradigm. We used count-down numbers for different periods of attention to command creation from EEG signals. Electrode positions and feature extraction algorithm were verified. By using four number and the proposed simple classification method can produce four commands. The results showed that EEG from the occipital region using an alpha-beta ratio achieved an average classification accuracy of 80. 56% and 62.06% for two and four commands, respectively. The proposed system can be used for severely physically disabled people for control and communication in the future. However, the proposed needs to improve for higher efficiency by session training and using complex algorithms and classifiers.
Document Type
Conference Paper
Source Type
Conference Proceeding
ISBN
[9798350381559]
ISSN
Keywords
Brain-Computer InterfaceElectroencephalogramVisual attention
Funding Agency
Walailak University
Tohkhwan, N., Bouyam, C., Saichoo, T., Siribunyaphat, N., Borirakarawin, M., & Punsawad, Y. (2024). EEG-based Brain-Computer Interface System via Time-Locked Visual Attention for Assistive Device Control. 2024 21st International Conference on Electrical Engineering Electronics Computer Telecommunications and Information Technology Ecti Con 2024doi:10.1109/ECTI-CON60892.2024.10594880