DocumentCode :
3101859
Title :
EOG-based signal detection and verification for HCI
Author :
Deng, Lawrence Y. ; Hsu, Chun-Liang ; Lin, Tzu-ching ; Tuan, Jui-sen ; Chen, Yung-Hui
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., St. John´´s Univ., Taipei, Taiwan
Volume :
6
fYear :
2009
fDate :
12-15 July 2009
Firstpage :
3342
Lastpage :
3348
Abstract :
In this paper, we proposed an eye-movement tracking system. Based on electro-oculography (E.O.G) technology we detected the signal with different directions in eye-movements and then analyzed to understand what they represented about (e.g. horizontal direction or vertical direction). We converted the analog signal to digital signal and then used as the control signals for human computer interface (HCI). In order to make the system ldquorobustrdquo, several applications with EOG-based HCI had been designed. Our preliminary results revealed more than 90% accuracy rate for examining the eye-movement that may become a new useful human-machine user interface in the near future.
Keywords :
electro-oculography; human computer interaction; signal detection; user interfaces; HCI; analog signal; digital signal; electro-oculography; eye-movements; horizontal direction; human computer interface; human-machine user interface; signal detection; signal verification; vertical direction; Application software; Coils; Cornea; Cybernetics; Diseases; Electrooculography; Eyes; Human computer interaction; Machine learning; Signal detection; Amyotrophic Lateral Sclerosis; Electro-Oculography (E.O.G); Eye-Movement; Human-Machine/Computer Interface (HMI/HCI); Motor Neuron Disease;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
Type :
conf
DOI :
10.1109/ICMLC.2009.5212752
Filename :
5212752
Link To Document :
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