• Proceedings of the Korea Society of Design Studies Conference
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• 2005.10a
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• pp.86-87
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• 2005

모든 인간은 빛과 함께 할 때, 보다 편안함을 느낄 수 있으며, 안정된 마음으로 아름다움과 행복을 추구하려는 본능을 가지게 된다. 더구나 태양빛의 스펙트럼 특성과 하루의 빛의 리듬, 계절적인 빛의 변화에 모든 동식물들은 다양한 생리적 반응을 일으키도록 되어 있는 만큼 색온도의 심적인 효과를 조명계획에 의도적으로 사용하는 것은 공간을 한층 더 쾌적하게 만드는 수단이 될 수 있다. 이런 이유로 현대인들이 가장 많은 시간을 보내는 실내 공간에서 감성조명이 필요하다. 이미 조명은 빛을 발하는 단순 기능에서 벗어나 생활과 사회 전 분야에 걸쳐 하나의 예술문화로 자리매김했다. 감성조명은 이러한 시대 요구에 부응하고, Well-Being을 추구하는 현대인들에게 꼭 필요한 기술이다.

• Science of Emotion and Sensibility
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• v.22 no.3
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• pp.35-46
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• 2019

Artificial intelligence (AI) technology has been evolving to recognize and learn the languages, voice tones, and facial expressions of users so that they can respond to users' emotions in various contexts. Many AI-based services of particular importance in communications with users provide emotional interaction. However, research on nonverbal interaction as a means of expressing emotion in the AI system is still insufficient. We studied the effect of lighting on users' emotional interaction with an AI device, focusing on color and flickering motion. The AI device used in this study expresses emotions with six colors of light (red, yellow, green, blue, purple, and white) and with a three-level flickering effect (high, middle, and low velocity). We studied the responses of 50 men and women in their 20s and 30s to the emotions expressed by the light colors and flickering effects of the AI device. We found that each light color represented an emotion that was largely similar to the user's emotional image shown in a previous color-sensibility study. The rate of flickering of the lights produced changes in emotional arousal and balance. The change in arousal patterns produced similar intensities of all colors. On the other hand, changes in balance patterns were somewhat related to the emotional image in the previous color-sensibility study, but the colors were different. As AI systems and devices are becoming more diverse, our findings are expected to contribute to designing the users emotional with AI devices through lighting.

• Science of Emotion and Sensibility
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• v.17 no.3
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• pp.29-38
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• 2014

The purpose of this study was to verify human physiological responses to emotional lighting system using LED (light emitting diode) flat lighting. Subjects were ten males in their twenties without medical history to eyes. Colors of LED lighting are red, orange, yellow, green, blue, purple and colorless (white). They were stimulated by LED lighting for 5 minutes. We measured body temperature, heart rate variability (HRV) and electroencephalogram (EEG) before and after color stimulus. In case of EEG analysis, relative power ${\alpha}$ wave ratio decreased in the groups of colorless, red and orange color light. Also, sympathetic nerve was more activated than parasympathetic nerve and the body temperature was increased in the groups of colorless, red, orange, yellow color light. On the other hand, relative power ${\alpha}$ wave ratio increased and parasympathetic nerve was more activated than sympathetic nerve and the body temperature was decreased in the groups of green, blue and purple color light. The results imply that the LED color lighting system in the realistic experiment environment. In the future, studies with compounded both colors and modes according to situation or auditory as nature sound or olfactory as aroma will be required.

• Journal of the Korea Fashion and Costume Design Association
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• v.17 no.3
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• pp.1-11
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• 2015

This study comparatively analyzed the images and preference of lighting space using the emotion-based technique in order to effectively use it in clothing shops and fashion marketing. In terms of color temperature for light sources, 2,800K of lamp color, 6,500K of daylight color and 4,200K of white color were used. For the assessment, sensory evaluation technique was used. Then, the study found the followings: In terms of the image of lighting space by light source, different images were observed by light source with significant difference by the evaluation category. For factor analysis by the evaluation category, 7 factors were extracted. Among them, evaluation on lighting space was influenced by the following three images: modern space, elegant space and classical space. In particular, the modern space comprised of the following adjectives had the biggest effect on the assessment of the image of lighting space ('refreshing,' 'transparent,' 'bluish,' 'bright' and 'non-classical') (primary evaluation 30.13%). According to assessment on the preference of lighting space, the respondents' most favorite lighting space was 4,200K while their least favorable one was 6,500K in terms of color temperature. In terms of preference by the image of lighting space, they didn't like 'non-elegant' and 'non-beige' images even though they had the images of modern space. Therefore, it was confirmed that beige and elegant space images have an effect on the preference of lighting space.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.8
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• pp.1637-1642
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• 2015

Next-generation applications using technology IT fused to biological signals from the emotional state to extract a lot of research has been, and the sensitivity of the human sensory functions influences the physiological condition known to be the fact that. In this paper, Propose an Emotional-lighting control algorithm using bio-signals. LED lighting for Emotion light is environmentally friendly and has a high efficiency and long life. In particular, LED lights are different colors represent the possible single light sphere advantages. And, Human sensitivity for determining a more accurate biological signals using EEG was collected using EEG equipment sensitivity was determined to analyze the EEG.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.102-108
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• 2011

The existing vessels lighting control system has several problems, which are complexity of construction and high cost of establishment and maintenance. In this paper, We designed low cost and high performance lighting control system at digital vessel environment. We proposed a system which recognize the user's emotions after obtaining the biological informations about user's bio information(pulse sensor, blood pressure sensor, blood sugar sensor etc) through wireless sensors controls the LED Lights. This system classified emotions using backpropagation algorithm. We chose 3,000 data sets to train the backpropagation algorithm. As a result, obtained about 88.7% accuracy. And the classified emotions find the most appropriate point in the method of controlling the waves or frequencies to the red, green, blue LED Lamp comparing with the 20-color-emotion models in the HP's 'The meaning of color' and control the brightness or contrast of the LED Lamp. In this method, the system saved about 20% of the electricity consumed.

• Science of Emotion and Sensibility
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• v.14 no.3
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• pp.371-384
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• 2011

Three experiments were carried out to examine how LED lighting hues influence to the rating and recognition of affective stimuli. In Experiment 1 and 2, IAPS affective pictures were used and an affective rating(valence and arousal) task and a recognition memory task were conducted under red, green, blue, and white hue LED lightings in Experiment 1 and cyan, magenta, yellow, and white ones in Experiment 2, respectively. In Experiment 3, affective words were used and the same two tasks were conducted under red, green, blue, and white hue LED lightings. According to the results of affective rating tasks, when primary hues(RGB) were used, red LED lighting elicited an excitement at the arousal dimension and green LED lighting evoked pleasantness at the valence one. When secondary hues(CMY) were used, magenta and cyan showed the similar but weaker patterns of responses comparing to red and green. The results of recognition memory task showed that the responses to the picture stimuli presented at green and cyan hue lightings tended to be a bit faster comparing to the stimuli presented at the other conditions but the difference was insignificant. In Experiment 3, however, recognition memory responses to the affective words presented at green hue lighting were faster significantly. These results indicate that warm colors like red and magenta elicit unpleasantness or excitement while cool colors like green and cyan evoke pleasantness or relaxation, and the primary hues provoke more positive or negative affectivity than secondary ones do. Particularly, the result of recognition memory task in Experiment 3 suggests that green hue LED lighting might be advantageous at the memory performance of language stimuli rather than visual ones.

• Journal of the Ergonomics Society of Korea
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• v.31 no.3
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• pp.427-435
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• 2012

The aim of this study is to investigate facial temperature changes induced by facial expression and emotional state in order to recognize a persons emotion using facial thermal images. Background: Facial thermal images have two advantages compared to visual images. Firstly, facial temperature measured by thermal camera does not depend on skin color, darkness, and lighting condition. Secondly, facial thermal images are changed not only by facial expression but also emotional state. To our knowledge, there is no study to concurrently investigate these two sources of facial temperature changes. Method: 231 students participated in the experiment. Four kinds of stimuli inducing anger, fear, boredom, and neutral were presented to participants and the facial temperatures were measured by an infrared camera. Each stimulus consisted of baseline and emotion period. Baseline period lasted during 1min and emotion period 1~3min. In the data analysis, the temperature differences between the baseline and emotion state were analyzed. Eyes, mouth, and glabella were selected for facial expression features, and forehead, nose, cheeks were selected for emotional state features. Results: The temperatures of eyes, mouth, glanella, forehead, and nose area were significantly decreased during the emotional experience and the changes were significantly different by the kind of emotion. The result of linear discriminant analysis for emotion recognition showed that the correct classification percentage in four emotions was 62.7% when using both facial expression features and emotional state features. The accuracy was slightly but significantly decreased at 56.7% when using only facial expression features, and the accuracy was 40.2% when using only emotional state features. Conclusion: Facial expression features are essential in emotion recognition, but emotion state features are also important to classify the emotion. Application: The results of this study can be applied to human-computer interaction system in the work places or the automobiles.

• Science of Emotion and Sensibility
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• v.18 no.2
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• pp.37-44
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• 2015

LED lighting has an advantage of adjusting color temperature. This change of color temperature may derive change in behavioral and physiological responses of the visual perception for indoor environments. This research examined the changes of behavioral and physiological responses caused by the color temperature. The environment was configured that the indoor temperature was 20 degrees centigrade or less as the perceived uncomfortable environment in winter. Then, the comfortable sensation vote (CSV) and the results of 3-back working memory test were measured as behavioral responses. In addition, the Electrodermal Activity (EDA) and Electrocardiogram (ECG) were measured as the responses of autonomics nervous system (ANS) in the three conditions of color temperature (red: 3862K, white: 5052K, blue: 11,460K). As a result, behavioral responses were not significant by the condition of color temperature, but the tendency of occupants' physiological relaxation appeared in the blue color temperature condition compared with the white color temperature condition. Although the color temperature of LED lighting might be a small factor in terms of the characteristics of indoor environment, it suggests that the color temperature could have an impact on the physiological changes in the parasympathetic nervous system.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.310-313
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• 2002

본 연구는 공간특성이 서로 다른 두 공간, 주거/사무공간의 조명환경에 대한 평가구조를 비교 검토하고 각 공간의 행위에 적합한 조명환경을 제시하고자 슬라이드 사진을 이용한 평가실험을 실시하였다. 평가대상 슬라이드수는 주거공간이 28장, 사무공간이 26장이다 실험은 각 공간별로 분위기항목과 행위항목에 대해 각각 실시하였다. 평가항목은 분위기항목이 21가지, 행위항목이 14가지이다. 각 공간의 평정치를 이용하여 인자분석을 실시한 결과, 주거공간과 사무공간 모두 <활동성>,<안정감),<고급감)의 3인자축이 추출되었다. 그러나, 주거공간의 경우는 <활동성>인자축이 평가축을 이루었으며, 사무공간의 경우는 <고급감>인자축이 평가축을 이루었다. 행위항목의 인자분석 결과는 주거공간의 경우, <작업행위>,<휴식행위>,<단란행위>의 3인자축이, 사무공간의 경우 <작업행위),<휴식행위>의 2인자축이 추출되어 주거공간의 경우, 활동성 평가가 높은 조명환경은 작업행위에 적합하며 반대로 활동성평가가 낮은 조명환경일수록 휴식행위에 적합한 것으로 나타났다 사무공간의 경우도 마찬가지로 작업행위에 가장 큰 영향을 미치는 분위기 인자는 활동성으로 나타나 활동성평가 높을수록 작업행위에 적합하며, 후식행위는 평가성 평가가 높은 조명환경에 적합한 것으로 나타났다.