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

Shanmuga, P. M. M. and Lau, Sian Lun * and Jou, Chichang. (2018) Detection of eye movements based on EEG signals and the SAX algorithm. In: 2nd International Conference on Intelligent and Interactive Computing (IIC2018), 8-9 August 2018, Melaka, Malaysia. (Unpublished)

Lau Sian Lun Detection of eye movements.pdf - Accepted Version
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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).

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Brain-computer Interface; SAX; Eye movement
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Others > Non Sunway Academics
Sunway University > School of Engineering and Technology [formerly School of Science and Technology until 2020] > Dept. Computing and Information Systems
Depositing User: Dr Janaki Sinnasamy
Related URLs:
Date Deposited: 29 Mar 2021 02:43
Last Modified: 29 Mar 2021 02:43

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