Publication: Directional eye movement detection system for virtual keyboard controller
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Issued Date
2012
Resource Type
File Type
application/pdf
Other identifier(s)
2-s2.0-84875086684
Rights Holder(s)
มหาวิทยาลัยศรีนครินทรวิโรฒ
Bibliographic Citation
5th 2012 Biomedical Engineering International Conference, BMEiCON 2012. Vol , No. (2012), p.-
Suggested Citation
Tangsuksant W., Aekmunkhongpaisal C., Cambua P., Charoenpong T., Chanwimalueang T. Directional eye movement detection system for virtual keyboard controller. 5th 2012 Biomedical Engineering International Conference, BMEiCON 2012. Vol , No. (2012), p.-. doi:10.1109/BMEiCon.2012.6465432 Retrieved from: https://hdl.handle.net/20.500.14740/6875
Abstract
several researches concerning electrooculography interface for Human Computer Interface (HCI) have been developed in recent years. For applications of disabled person such as lock-in, and Motor Neuron disease, a simple and effective technology for communication is necessary. Eye blink is defined as a selection command in existing research. Problem of current research is occurred when user blinks his eye involuntarily. To resolve this problem, in this paper, we develop a new electrooculography based system for typing words via virtual keyboard by using voltage threshold algorithm. EOG signal with different direction of eye movement in horizontal and vertical directions are detected. EOG signal is measured by two channels with six electrodes. Measurement circuit consists of three major processes: instrument amplifier, filter and signal conditioning amplifier processes. These circuits filter noise out, pass frequencies in ranges of EOG signal and then amplify the signal. The voltage threshold algorithm is then used to classify the EOG signal. Selection command is defined by closing eye in a short period of use to avoid eye blink involuntary. To test the performance of method, typing rate and accuracy are measured. Typing rate on virtual keyboard 25.94 seconds/letter and its accuracy is 95.2%. The results show the feasibility of proposed method. ©2012 IEEE.
Subject(s)
Component
Human computer interfaces
Instrument amplifiers
Measurement circuit
Motor neuron disease
Movement detection
Threshold algorithms
Virtual Keyboards
Algorithms
Biomedical engineering
Computer keyboards
Electrooculography
Handicapped persons
Human computer interaction
Neurons
Research
Eye movements
Human computer interfaces
Instrument amplifiers
Measurement circuit
Motor neuron disease
Movement detection
Threshold algorithms
Virtual Keyboards
Algorithms
Biomedical engineering
Computer keyboards
Electrooculography
Handicapped persons
Human computer interaction
Neurons
Research
Eye movements