• DocumentCode
    2871422
  • Title

    EOG guidance of a wheelchair using neural networks

  • Author

    Barea, Rafael ; Boquete, Luciano ; Mazo, Manuel ; López, Elena ; Bergasa, L.M.

  • Author_Institution
    Electron. Dept., Univ. of Alcala, Madrid, Spain
  • Volume
    4
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    668
  • Abstract
    Presents a method to control and guide mobile robots. In this case, to send different commands we have used electrooculography (EOG) techniques, so that, control is made by means of the ocular position (eye displacement into its orbit). A neural network is used to identify the inverse eye model, therefore the saccadic eye movements can be detected and where the user is looking can be determined. This control technique can be useful in multiple applications, but in this work it is used to guide an autonomous robot (wheelchair) as a system to help to people with severe disabilities. The system consists of a standard electric wheelchair with an on-board computer, sensors and graphical user interface running on a computer
  • Keywords
    bioelectric potentials; eye; graphical user interfaces; handicapped aids; mobile robots; radial basis function networks; EOG guidance; autonomous robot; electric wheelchair; electrooculography techniques; eye displacement; inverse eye model; ocular position; severe disabilities; Application software; Computer interfaces; Control systems; Displacement control; Electrooculography; Inverse problems; Mobile robots; Neural networks; Robot sensing systems; Wheelchairs;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2000. Proceedings. 15th International Conference on
  • Conference_Location
    Barcelona
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-0750-6
  • Type

    conf

  • DOI
    10.1109/ICPR.2000.903006
  • Filename
    903006