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

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 pote...

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Main Authors: Shanmuga, P. M. M., Lau, Sian Lun *, Jou, Chichang.
Format: Conference or Workshop Item
Language:English
Published: 2018
Subjects:
Online Access:http://eprints.sunway.edu.my/1691/
http://eprints.sunway.edu.my/1691/1/Lau%20Sian%20Lun%20Detection%20of%20eye%20movements.pdf
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author Shanmuga, P. M. M.
Lau, Sian Lun *
Jou, Chichang.
author_facet Shanmuga, P. M. M.
Lau, Sian Lun *
Jou, Chichang.
author_sort Shanmuga, P. M. M.
building SU Institutional Repository
collection Online Access
description 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).
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language English
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spelling sunway-16912021-03-29T02:43:51Z http://eprints.sunway.edu.my/1691/ Detection of eye movements based on EEG signals and the SAX algorithm Shanmuga, P. M. M. Lau, Sian Lun * Jou, Chichang. QA76 Computer software 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). 2018 Conference or Workshop Item PeerReviewed text en cc_by_nc_nd_4 http://eprints.sunway.edu.my/1691/1/Lau%20Sian%20Lun%20Detection%20of%20eye%20movements.pdf 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)
spellingShingle QA76 Computer software
Shanmuga, P. M. M.
Lau, Sian Lun *
Jou, Chichang.
Detection of eye movements based on EEG signals and the SAX algorithm
title Detection of eye movements based on EEG signals and the SAX algorithm
title_full Detection of eye movements based on EEG signals and the SAX algorithm
title_fullStr Detection of eye movements based on EEG signals and the SAX algorithm
title_full_unstemmed Detection of eye movements based on EEG signals and the SAX algorithm
title_short Detection of eye movements based on EEG signals and the SAX algorithm
title_sort detection of eye movements based on eeg signals and the sax algorithm
topic QA76 Computer software
url http://eprints.sunway.edu.my/1691/
http://eprints.sunway.edu.my/1691/1/Lau%20Sian%20Lun%20Detection%20of%20eye%20movements.pdf