Detection of Eyes Position Based on Electrooculography Signal Analysis
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
Robust Recognition of Reading Activity in Transit Using Wearable Electrooculography
Pervasive '08 Proceedings of the 6th International Conference on Pervasive Computing
Detection of saccadic eye movements using the order statistic constant false alarm rate technique
BioMED '08 Proceedings of the Sixth IASTED International Conference on Biomedical Engineering
A semi-autonomous wheelchair towards user-centered design
ICCHP'06 Proceedings of the 10th international conference on Computers Helping People with Special Needs
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This paper presents a new 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 know where user is looking. 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.