• Journal of rehabilitation welfare engineering & assistive technology
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• v.5 no.1
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• pp.87-93
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• 2011

This paper proposes a method for extraction of the gaze point on display using EOG(Electrooculography) signal. Based on the linear property of EOG signal, the proposed method corrects scaling difference, rotation difference and origin difference between coordinate of using EOG signal and coordinate on display, without adjustment using the head movement. The performance of the proposed method was evaluated by measuring the difference between extracted gaze point and displayed circle point on the monitor with 1680*1050 resolution. Experimental results show that the average distance errors at the gaze points are 3%(56pixel) on x-axis, 4%(47pixel) on y-axis, respectively. This method can be used to human computer interface of pointing device for general paralysis patients or HCI for VR game application.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1356-1363
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• 1999

In this paper, a new method for controlling the pointing device using EOG(electrooculogram) signal generated from eye movement was suggested. The basic idea of the method is to control the direction of pointer, as using the results of measuring each component of the horizontal EOG and the vertical EOG by angle of eye-gaze. As a practical example, pointing device controlling the personal computer's pointer is manufactured. The designed pointing device consists of pre-amplifier, A/D converter, serial transmission device and PC program. That is, first, the EOG is amplified by pre-amplifier. Secondly, the amplified EOG is digitized and transmitted to personal computer by PIC16C74A. Finally, the software for controlling the pointer on personal computer is programed. As the result, the measured horizontal EOG and vertical EOG by eye-gaze angle had high linearity; the correlation coefficients of the regression line were 0.998 and 0.996 respectively. And the developed pointing device is able to control the personal computer's pointer, and the average of the errors between the objective value and the observed value had 3.77% for horizontal axis and 5.85% for vertical axis. The pointing device developed in this study is able to control personal computer's pointer by subject's eye movement, that is, the user's intention. Furthermore, the algorithm of this study is applicable for many field, such as a new method remote control, a new wheelchair control and so forth.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.604-606
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• 1998

As a basic study for Man-Machine interfacing technics, this paper purposed the vertorization of EOG(electrooculogram) that is generated by eye movement. EOG is electric potential difference between the positive potential of cornea and the negative potential of retina. The magnitude and the polarity are depend on the direction of eye movement and degree of gaze angle. In order to vectorize EOG, EOG signal is measured about vertical and horizontal movement of eyes. This vectorization of EOG is expected to help Man-Machine Interfacing technics and development of other useful equipment.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2012.05a
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• pp.15-16
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• 2012

• Korean Journal of Applied Biomechanics
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• v.18 no.1
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• pp.39-43
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• 2008

The purpose of this study was to develop EOG system for collecting eye movement patterns to investigate visual function and position and the level of balancing. This small and partable wireless EOG system was enabled to collect stable signals without hindering any kind of sports movement. This system was consist of four parts: amplifier, main process with wireless transmitter, receiver, and display. Three EOG electrodes were used and placed on right(+), left(-) sides of eyes, and between eyes as a reference. This system was possible to measure signals for relatively long duration but the degeneration of electrodes may magnify measurement errors when collecting time was getting longer. Thus, dry electrodes may be applied to the system when long term measurement is needed for future studies.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.133-141
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• 2006

Recently many wearable computers have been developed. But they still have many user interface problems from both an input and output perspective. This paper presents a wearable user interface based on EOG(electrooculogram) sensing circuit and marker recognition. In the proposed user interface, the EOG sensor circuit which tracks the movement of eyes by sensing the potential difference across the eye is used as a pointing device. Objects to manipulate are represented human readable markers. And the marker recognition system detects and recognize markers from the camera input image. When a marker is recognized, the corresponding property window and method window are displayed to the head mounted display. Users manipulate the object by selecting a property or a method item from the window. By using the EOG sensor circuit and the marker recognition system, we can manipulate an object with only eye movement in the wearable computing environment.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.755-762
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• 2004

In this research, EOG(Electrooculogram) signal was analyzed to predict the subject's intention using a fuzzy classifier. The fuzzy classifier is built automatically using the EOG data and evolutionary algorithms. An assistant robot manipulator in redundant configuration has been developed, which operates according to the EOG signal classification results. For automatic fuzzy model construction without any experts' knowledge, an evolutionary algorithm with the new representation scheme, design of adequate fitness function and evolutionary operators, is proposed. The proposed evolutionary algorithm can optimize the number of fuzzy rules, the number of fuzzy membership functions, parameter values for the each membership functions, and parameter values for the consequent parts. It is shown that the fuzzy classifier built by the proposed algorithm can classify the EOG data efficiently. Intelligent motion planner that consists of several neural networks are used for control of robot manipulator based upon EOG classification results.

• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.167-175
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• 2003

In this paper, a new electrode configuration and EOG removal method are proposed in order to measure EEG effectively on the frontal lobe and remove EOG in the measured raw EEG. The method of measuring EEG is proposed using four electrodes and a ground electrode on the frontal lobe with a reference electrode at the left earlobe. And also, the separation method using ICA is proposed for EOG removal from the measured EEG, Through the experiments of measuring EEG it was demonstrated that a subject can attach the electrodes by himself easily to measure his own EEG without any assistant and the proposed methods were suitable for removing EOG signal from the measured EEG.

• The Journal of the Korea Contents Association
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• v.5 no.1
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• pp.19-26
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• 2005

This paper introduces a new design method of realizing the machine control interface by using bio-signals(EEG/EOG). This method can be further expanded to be applied to the computer system responding to EEG or EOG signals and the general bio-feedback system. For this reason, we made the remotely controlled toy system controlled by the EEG spectrums, their combination indexes, and EOG parameters. And the headset that has bio-signal processing modules built-in offers convenience for users, and this make much more advanced system than any other existing BCI and BMI system.

• Journal of Biomedical Engineering Research
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• v.28 no.4
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• pp.477-483
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• 2007

We have measured EOG and fMRI simultaneously to investigate whether eye movement (blinking mechanism) might influence functional magnetic resonance imaging (fMRI) signal response in the primary visual cortex. $T2^*-weighted$ Echo-Planar Imaging (EPI) with concurrent electrooculogram (EOG) was acquired in four subjects while they viewed a fixation point and a checkerboard with a flickering rate of 8Hz. With the help of EOG information we divided the experimental blocks into two different conditions: fixation and moving eye. We have compared the fMRI data of these two conditions. Our results have shown that there is no difference between these two conditions. This might suggest that eye blinking does not affect BOLD signal changes in the primary visual cortex. This means further that eye blinking can be ignored in data processing.