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
Link To Document