• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.463-471
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• 2014

In this paper, emotion classification was performed by using four ocular features extracted from near-infrared camera image. According to comparing with previous work, the proposed method used more ocular features and each feature was validated as significant one in terms of emotion classification. To minimize side effects on ocular features caused by using visual stimuli, auditory stimuli for causing two opposite emotion pairs such as "positive-negative" and "arousal-relaxation" were used. As four features for emotion classification, pupil size, pupil accommodation rate, blink frequency, and eye cloased duration were adopted which could be automatically extracted by using lab-made image processing software. At result, pupil accommodation rate and blink frequency were statistically significant features for classification arousal-relaxation. Also, eye closed duration was the most significant feature for classification positive-negative.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.90-94
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• 2002

이전연구에서 가상현실에 몰입하는 동안 넓은 시야 (Field of view: 150$^{\circ}$)와 빠른 운행속도 (70 km/sec)가 사이버멀미를 심화시킨다는 결과를 얻었다: 피험자의 90%가 좁은 시야 (50$^{\circ}$)와 느린 운행속도 (30 km/sec)에서 사이버멀미 증상이 적었다. 본 실험에서는 피험자가 생리적인 동요를 경험할 때마다 바이오피드백 방법을 사용해서 사이버멀미 감소 가상환경 (cybersickness alleviating virtual environment, CAVE)을 제시한 후, 그 효과를 관찰하였다. 피부전도도, 말초체온, 말초혈류량, 심박률, 눈 깜박임, 뇌전위의 변수들을 입력으로 하는 인공신경망으로 구성된 실시간 멀미 탐지 시스템과 CAVE-제시 피드백 시스템을 구축하였다. 이 시스템은 생리적 측정치들이 사이버멀미의 출현을 신호할 때마다 피드백 출력으로 좁은 화면과 감소된 운행속도를 일시적으로 제공했다. 36명의 피험자를 대상으로 SSQ (simulator sickness questionnaires)와 자기보고를 이용하여 사이버멀미의 빈도와 심각도를 조사하였다. 모든 피험자는 한달 간격으로 CAVE 조건과 non-CAVE 조건에서 두 번 가상현실을 경험하였다. 사이버멀미의 빈도와 심각도는 non-CAVE 조건보다 CAVE 조건에서 유의미하게 감소하였다. 즉, 전기생리학적 특징들에 기반한 인공신경망에 의해 제공된 좁은 시야와 느린 운행의 가상환경은 사이버멀미 증상들을 의미있게 감소시켰다. 이러한 결과들은 생체신호 피드백 시스템을 이용하여 인간 친화적 가상환경을 구축할 수 있는 가능성을 보인 것이다.

• Journal of Korean Ophthalmic Optics Society
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• v.19 no.4
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• pp.533-538
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• 2014

Purpose: This study is to investigate correlation between eye fatigue and letter contrast according to letter contrast changes on monitor display. Methods: Reading speed test were carried out for 53 subjects (mean age: $22.68{\pm}1.85$ years) who have over Best-corrected visual acuity (BCVA) 1.0, and 45 subjects, who could read over 123 out of 163 letters among 53 subjects were selected. They were asked to read the letters which were composed of Black (contrast 100%), Dark gray (contrast 80%), Gray (contrast 80%), Light gray (contrast 30%) randomly. The change of their eye fatigue by letter contrast on monitor display was measured by monitoring their eyes with an eye-tracker while they were reading letters. Results: Event Duration (sec) was 33.635 for Black, 32.266 Dark gray, 33.936 for Gray, and 34.848 for Light gray. Average of Fixation Duration (sec) was 0.224 for Black, 0.218 for Dark gray, 0.239 for Gray and 0.243 for Light gray. Average of Pupil diameter (mm) was 41.133 mm for Black, 41.160 mm for Dark gray, 40.880 mm for Gray and 40.459 mm for Light gray. Frequency (blinks/sec) was 0.211 for Black, 0.206 for Dark gray, 0.221 for Gray, and 0.238 for Light gray. Conclusions: Event Duration and average of Fixation Duration were the shortest for Dark gray and the longest for Light gray. In average Pupil diameter was the biggest Dark gray and the smallest for Light gray. Blink Frequency (blinks/sec) was the lowest for Dark gray and the highest for Light gray. Visual fatigue by brightness of letters on monitor display was the least for Dark gray followed by Black, Gray and Light gray.

• Science of Emotion and Sensibility
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• v.5 no.2
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• pp.29-34
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• 2002

Our previous studies investigated that narrow field of view (FOV : 50˚) and slow navigation speed decreased the frequency of occurrence and severity of cybersickness during immersion in the virtual reality (VR). It would cause a significant reduction of cybersickness if it were provided cybersickness alleviating virtual environment (CAVE) using biofeedback method whenever subject underwent physiological agitation. For verifying the hypothesis, we constructed a real-time cybersickness detection and feedback system with artificial neural network whose inputs are electrophysiological parameters of blood pulse volume, skin conductance, eye blink, skin temperature, heart period, and EEG. The system temporary provided narrow FOV and decreased speed of navigation as feedback outputs whenever physiological measures signal the occurrence of cybersickness. We examined the frequency and severity of cybersickness from simulator sickness questionnaires and self-report in 36 subjects. All subjects experienced VR two times in CAVE and non-CAVE condition at one-month intervals. The frequency and severity of cybersickness were significantly reduced in CAVE than non-CAVE condition. Virtual environment of narrow FOV and slow navigation provided by electrophysiological features based artificial neural network caused a significant reduction of cybersickness symptoms. These results showed that efficiency of a cybersickness detection system we developed was relatively high and subjects expressed more comfortable in the virtual navigation environment.