EOG based interface for people with physical disabilities

• Autorzy: Chodak, J.
• Języki publikacji: EN

Abstrakty

EN

In this paper EOG (electrooculography) based interface for people with physical disabilities has been described. The interface was implemented using an AC amplifier (EEG device) and four electrodes made of gold. The electrode placement was planned in such way that it would be possible in the future to install them in glasses. Eight selections operations were realized by circular interface displayed on a screen monitor which was divided into eight parts. Each part may be selected by targeting sight into one of the eight defined directions: up, up-right, right, bottom-right, down, down, left, left, up and left. This interface is an alternative for people, whose disability prevents them from using interfaces designed for physically fit person. The interface configuration allows assigning different functions to the parts of circle, what allows using it in different circumstances. Virtual keyboard or a on / off switch for household appliances are examples of practical application of the described interface.

Słowa kluczowe

EN

electrooculography (EOG); human-computer interface­ (HCI); artificial neural networks; signal processing

• Czasopismo: Bio-Algorithms and Med-Systems
• Rocznik: 2010
• Tom: Vol. 6, no. 12
• Strony: 81--84
• Opis fizyczny: Bibliogr. 5 poz., rys., wykr.

Twórcy

autor

Chodak, J.

• Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Kraków, Poland,

Bibliografia

• [1] Malmivuo J., Plonsey R. (1995) Bioelectromagnetism: Principles and Applications of Bioelectric and Biomagnetic Fields. Oxford University Press New York.
• [2] Braintronics ISO-1032CE Amplifier. http://www.braintronics.nl/DocumentDatabase/860107.pdf
• [3] Goto S., Yamada A., Hashimoto W., Sugi T., Nakamura M. (2007), Determination of Target Position of Meal Assistance Orthosis. Using EOG Signal and Dish Image. Saga University, Saga.
• [4] Coughlin M.J., Cutmore T.R.H., Hine T.J. (2004) Automated eye tracking system calibration using artificial neural networks. Computer Methods and Programs in Biomedicine 76.
• [5] Yamagishi K., Hori J., Miyakawa M. (2006) Development of EOG-Based Communication System Controlled by Eight-Directional Movements. Proceedings of the 28th IEEE, EMBS Annual International Conference.