• Smart Media Journal
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• v.13 no.4
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• pp.94-103
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• 2024

The eyeball input system is a text input system designed based on 'eye tracking technology' and 'virtual keyboard character-input technology'. The current virtual keyboard structure used is a rectangular QWERTY array optimized for a multi-input method that simultaneously utilizes all 10 fingers on both hands. However, since 'eye-tracking technology' is a single-input method that relies solely on eye movement, requiring only one focal point for input, problems arise when used in conjunction with a rectangular virtual keyboard structure designed for multi-input method. To solve this problem, first of all, previous studies on the shape, type, and movement of muscles connected to the eyeball were investigated. Through the investigation, it was identified that the principle of eye movement occurs in a circle rather than in a straight line. This study, therefore, proposes a new key arrangement wherein the keys are arranged in a circular structure suitable for rotational motion rather than the key arrangement of the current virtual keyboard which is arranged in a rectangular structure and optimized for both-hand input. In addition, compared to the existing rectangular key arrangement, a performance verification experiment was conducted on the circular key arrangement, and through the experiment, it was confirmed that the circular arrangement would be a good replacement for the rectangular arrangement for the virtual keyboard.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.205-208
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• 2001

본 논문은 Biometrics분야 중 다른 생체학적 특징보다도 정확도면에서 가장 뛰어난 특징인 안구의 홍채 패턴을 이용하여 사용자를 인증 하는 시스템에 관한 연구이다. 입력된 안구 영상으로부터 전처리과정을 거쳐 극좌표 변환을 통해 홍채 패턴을 추출한 후 웨이블릿 변환을 이용하여 특징패턴을 압축하였으며, PCA(Principal Component Analysis:주성분 해석)의 한 종류인 GHA(Generalized Hebbian Algorithm)를 사용하여 등록된 사용자의 패턴 DB 에서 Basis 배열을 추출하고, 구축된 Basis 배열과 입력 영상 패턴과의 비교 Matching을 통하여 사용자를 인증하는 시스템을 제안한다.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1333-1337
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• 1987

본 연구는 머리운동 제어 시스템에 대한 생체 물리학적인 모델링과 시뮬레이션을 통하여 모델의 동특성을 조사하였으며, 생체운동(머리-안구)의 상호 관계를 비교하였다. 결과를 요약하면 다음과 같다. 1) 시스템을 구성하고 있는 매개변수의 변화가 출력에 미치는 영향을 조사하기 위해 감도해석법을 써서 감도계수를 구한 결과, 입력 제어신호의 펄스높이(PH), 동근의 펄스폭(PW1), 길항근의 펄스폭(PW2)이, 시스템의 출력특성을 결정하는 가장 중요한 매개변수 임을 알 수 있었다. 2) 비 선형 제어모델의 선형화를 통하여 선형모델의 응답특성과 크나큰 차이가 없음을 알았다. 3) Main-Sequence도를 작성하여 실험 데이터와 비교한 결과, 거의 일치함으로서 모델의 타당성을 입증하였다. 4) 머리운동이 시간최적으로 응답하기 위해서는 bang-bang 제어법칙이 적용되어야 함을 알았다. 5) 머리운동이 목표점에 도달하는 순간에는 길항근의 역제통 펄스가 가해 짐으로서, 길항근이 궤적의 마지막 부분을 지배함을 알았다. 6) 머리-안구운동의 main-sequence도를 비교 함으로서 상호관계를 규명하였다. 앞으로는 이 모델링 법을 개선확장하면, 비행시 파일럿의 생체 시뮬레이션, 헬멧 조준 사격 시스템등의 항공공학, 생체의용공학 연구 및 제어입력을 생체신호로 하는 로봇틱스 연구에 본 연구 방법은 유용하리라 생각된다.

• Smart Media Journal
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• v.10 no.1
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• pp.9-15
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• 2021

The eye tracking system designed in this paper is an eye-based computer input device designed to give an easy access for those who are uncomfortable with Lou Gehrig's or various muscle-related diseases. It is an eye-based-computer-using device for users whose potential demand alone amounts to 30,000. Combining the number of Lou Gehrig's patients in Korea estimated at around 1,700, and those who are unable to move their bodies due to various accidents or diseases. Because these eye input devices are intended for a small group of users, many types of commercial devices are available on the market. It is making them more expensive and difficult to use for these potential users, less accessible. For this reason, each individual's economic situation and individual experience with smart devices are slightly different. Therefore, making it difficult to access them in terms of cost or usability to use a commercial eye tracking system. Accordingly, attempts to improve accessibility to IT devices through low-cost but easy-to-use technologies are essential. Thus, this paper proposes a complementary superior performance eye tracking system that can be conveniently used by far more people and patients by improving the deficiencies of the existing system. Through voluntary VoCs(Voice of Customers) of users who have used different kinds of eye tracking systems that satisfies it through various usability tests, and we propose a reduced system that the amount of calculation to 1/15th, and eye-gaze tracking error rate to 0.5~1 degree under.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.1122-1125
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• 2014

본 연구에서는 전신마비 환자들이 안구 마우스를 사용하여 전등, 선풍기, 창문 제어 및 침대 각도 조절을 할 수 있고, 보호자에게 소변통 알림과 응급메시지 알림을 보낼 수 있는 홈 네트워크 시스템을 설계하고 구현한다. 또한 전신마비 환자들뿐만 아니라 일반 사용자들도 이용할 수 있도록 동일한 기능을 모바일 어플리케이션으로 구현한다. 본 연구의 입력장치인 안구 마우스는 삼성전자 창의개발연구소에서 개발한 eyeCan을 사용하였다. 전체적인 시스템은 Arduino를 사용하여 제어하고, 무선 통신은 Xbee모듈을 사용하여 구현하였다. 기존의 홈 네트워크 시스템은 일반 사용자들만 이용할 수 있지만, 본 연구에서는 루게릭 환자처럼 전신을 움직이지 못하는 환자들에게 최적화된 홈 네트워크 시스템을 구축하여 소외계층의 스마트 기기에 대한 접근성을 높이고, 자립심을 키울 수 있도록 도와준다는 점에서 의의가 있다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.5
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• pp.57-64
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• 2004

We proposed the eye gaze tracking system under natural head movements, which consists of one narrow-view field CCD camera, two mirrors which of reflective angles are controlled and active infra-red illumination. The mirrors' angles were computed by geometric and linear algebra calculations to put the pupil images on the optical axis of the camera. Our system allowed the subjects head to move 90cm horizontally and 60cm vertically, and the spatial resolutions were about 6$^{\circ}$ and 7$^{\circ}$, respectively. The frame rate for estimating gaze points was 10～15 frames/sec. As gaze mapping function, we used the hierarchical generalized regression neural networks (H-GRNN) based on the two-pass GRNN. The gaze accuracy showed 94% by H-GRNN improved 9% more than 85% of GRNN even though the head or face was a little rotated. Our system does not have a high spatial gaze resolution, but it allows natural head movements, robust and accurate gaze tracking. In addition there is no need to re-calibrate the system when subjects are changed.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.1
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• pp.25-31
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• 2004

This paper is research about the improvement of recognition rate of the biometrics user identification system using the data previously stored in the non contact Ic smart card. The proposed system identifies the user by analyzing the iris pattern his or her us. First, after extracting the area of the iris from the image of the iris of an eye which is taken by CCD camera, and then we save PCA Coefficient using GHA(Generalized Hebbian Algorithm) into the Smart Card. When we confirmed the users, we compared the imformation of the biometrics of users with that of smart card. In case two kinds of information was the same, we classified the data by using SVM(Support Vector Machine). The Experimental result showed that this system outperformed the previous developed system.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.5
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• pp.171-180
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• 2023

The three major sleep disorders in Korea are snoring, sleep apnea, and insomnia. Lack of sleep is the root of all diseases. Some of the most serious potential problems associated with sleep deprivation are cardiovascular problems, cognitive impairment, obesity, diabetes, colitis, prostate cancer, etc. To solve these problems, the Korean government provided low-cost national health insurance benefits for polysomnography tests in July 2018. However, insomnia patients still have problems getting treated in terms of time, space, and economic perspectives. Therefore, it would be better for insomnia patients to be allowed to test at home. The measuring device can measure six biosignals (eye movement, tossing and turning, body temperature, oxygen saturation, heart rate, and audio). A gyroscope sensor (MPU9250, InvenSense, USA) was used for eye movement, tossing, and turning. The input range of the sensor was in 258°/sec to 460°/sec, and the data range was in the input range. Body temperature, oxygen saturation range, and heart rate were measured by a sensor (MAX30102, Analog Devices, USA). The body temperature was measured in 30 ℃ to 45 ℃, and the oxygen saturation range was 0% for the unused state and 20 % to 90 % for the used state. The heart rate measurement range was in 40 bpm to 180 bpm. The measurement of audio signal was performed by an audio sensor (AMM2742-T-R, PUIaudio, USA). The was -42 dB ±1 dB frequency range was 20 Hz to 20 kHz. The measured data was successfully received in wireless network conditions. The system configuration was consisted of a PC and a mobile app for bio-signal measurement and data collection. The measured data was collected by mobile phones and desktops. The data collected can be used as preliminary data to determine the stage of sleep and perform the screening function for sleep induction and sleep disturbances. In the future, this convenient sleep measurement device could be beneficial for treating insomnia.