Detection of eye movements based on EEG signals and the SAX algorithm

• Main Authors: Shanmuga, P. M. M., Lau, Sian Lun *, Jou, Chichang.
• Format: Conference or Workshop Item
• Language: English
• Published: 2018
• Subjects: QA76 Computer software
• Online Access: http://eprints.sunway.edu.my/1691/1/Lau%20Sian%20Lun%20Detection%20of%20eye%20movements.pdf; http://eprints.sunway.edu.my/1691/
• Institution: Sunway University

For patients with disabilities, particularly those with motor disabilities and difficulties to interact with computer and devices, Human-Machine Interaction (HMI) research may provide them new ways to solve this problem. In this paper, we propose the Brain-Computer Interface (BCI) approach as a potential technique. The patients may use a portable electroencephalography (EEG) device to give instruction to a computing device via eye movements. Classification algorithms have been investigated in past research to allow detection of eye movement. We would like to investigate another technique, namely the Symbolic Aggregate Approximation (SAX) algorithm, to find out its suitability and performance against known classification algorithms such as Support Vector Machine (SVM), k-Nearest Neighbour (KNN) and Decision Tree (DT).