淡江大學機構典藏:Item 987654321/115343
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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/115343


    Title: Detection of Eye Movements based on EEG Signals and the SAX algorithm
    Authors: Shanmuga Pillai Murutha Muthu;Sian Lun Lau;Chichang Jou
    Keywords: Brain-computer Interface;SAX;Eye movement
    Date: 2018-08-08
    Issue Date: 2018-10-23 12:11:51 (UTC+8)
    Abstract: 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).
    Relation: NA
    Appears in Collections:[Graduate Institute & Department of Information Management] Proceeding

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