• DocumentCode
    2445413
  • Title

    Automatic Determination of Sleep-Wake States from EOG Signals using Fusion Technique

  • Author

    Hendi, S. Farshad ; Hussain, Aini ; Samad, Salina Abdul ; Chieh, Thum Chia ; Mustafa, Mohd Marzuki

  • Author_Institution
    Dept. of Electr. Electron. & Syst. Eng., Nat. Univ. of Malaysia, Bangi
  • Volume
    1
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1165
  • Lastpage
    1169
  • Abstract
    This paper deals with an alternative method in contrast to common classifiers that use very complex methods such as statistical pattern recognition, fuzzy system and neural networks for determining sleep-wake states from the electrooculogram signals (EOG). The method involves a straight forward EOG based signal processing and feature extraction algorithm based on Lissajous-like plots. This novel method was presented along with a case study to show its performance
  • Keywords
    electro-oculography; feature extraction; medical signal processing; sleep; EOG based signal processing; Lissajous-like plots; electrooculogram signal; feature extraction; fusion technique; sleep-wake state; Cornea; Electrodes; Electroencephalography; Electrooculography; Fatigue; Humans; Monitoring; Neural networks; Road accidents; Signal processing algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Communication Technologies, 2006. ICTTA '06. 2nd
  • Conference_Location
    Damascus
  • Print_ISBN
    0-7803-9521-2
  • Type

    conf

  • DOI
    10.1109/ICTTA.2006.1684539
  • Filename
    1684539