• Science of Emotion and Sensibility
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• v.20 no.4
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• pp.79-88
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• 2017

As the age in which the importance of sensitivity has increased, education for the future generation regarding emotion engineering, affective recognition and cognitive science have taken center stage. We measure human's emotion quantitatively, analyze evaluation and apply them to various services in life, which are based on human technology. Therefore, we need the education which is related to emotion science to cultivate talented people. The goal of this paper is to suggest the possibility of emotion science education and effective methods through development of the STEAM (Science, Technology, Engineering, Arts, Mathematics) program which can teach emotion science to early elementary school students by applying it to pilot classes. For this study, first, we build a program, 'The mind made by figure' for student of early elementary school. The method of STEAM was used in this program, because it is an effective system to educate the emotion science. We recognize the needs and value of this program development through theory and benchmarking of STEAM related to emotion science. And then the contents of class, activities, course book and kit are designed with elementary school textbook of pertinent grade. Secondly, we analyze the result which is applied in two pilot classes of second grade by satisfaction survey and teacher interview. As a result, the average of satisfaction level was very high (4.40/5), Class participation was especially high. Third, we discuss the ability, value and limits of this program based on the result of analysis. The outcome of this research shows that students of early elementary school who have difficulty in understanding science can approach the education program related to emotion science with ease and interest. We hope this education will help students understand emotion science effectively, and to train people to lead the emotion centered era.

• Science of Emotion and Sensibility
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• v.1 no.1
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• pp.1-2
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• 1998

• Science of Emotion and Sensibility
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• v.21 no.1
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• pp.177-186
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• 2018

The mechanism of emotion is complex and influenced by a variety of factors, so that it is crucial to analyze emotion in broad and diversified perspectives. In this study, we classified neutral and negative emotions(sadness, fear, surprise) using arousal evaluation, which is one of the psychological evaluation scales, as well as physiological signals. We have not only revealed the difference between physiological signals coupled to the emotions, but also assessed how accurate these emotions can be classified by our emotional recognizer based on neural network algorithm. A total of 146 participants(mean age $20.1{\pm}4.0$, male 41%) were emotionally stimulated while their physiological signals of the electrocardiogram, blood flow, and dermal activity were recorded. In addition, the participants evaluated their psychological states on the emotional rating scale in response to the emotional stimuli. Heart rate(HR), standard deviation(SDNN), blood flow(BVP), pulse wave transmission time(PTT), skin conduction level(SCL) and skin conduction response(SCR) were calculated before and after the emotional stimulation. As a result, the difference between physiological responses was verified corresponding to the emotions, and the highest emotion classification performance of 86.9% was obtained using the combined analysis of arousal and physiological features. This study suggests that negative emotion can be categorized by psychological and physiological evaluation along with the application of machine learning algorithm, which can contribute to the science and technology of detecting human emotion.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2003.11a
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• pp.1211-1212
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• 2003

본 연구에서는 감성 변화가 빈번하게 일어나는 오라인 포커 게임을 대상으로 EEG를 이용하여 게임 중 발생 할 수 있는 감성 변화를 알아내고자 하는 연구를 수행하였다. 포커 게임에서 나타날 수 있는 사용자의 감성과 행동을 Task Analysis를 이용하여 구분하였고 전두엽 표면 뇌파를 측정하여 Neural Network 및 통계적 처리를 이용하여 분석하였다. 이후 분석될 뇌파에서 인간의 감성상태를 구분할 수 있는 Index를 찾아내었다. 향후 ECG를 추가적으로 연구하여 감성상태를 더 정확하게 파악하는 연구가 진행될 것이다.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.79-86
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• 2020

In this paper, we propose an efficient emotional relaxation framework using Dijkstra algorithm based on anisotropic features. Emotional relaxation is as important as emotional analysis. This is a framework that can automatically alleviate the person's depression or loneliness. This is very important for HCI (Human-Computer Interaction). In this paper, 1) Emotion value changing from facial expression is calculated using Microsoft's Emotion API, 2) Using these differences in emotion values, we recognize abnormal feelings such as depression or loneliness. 3) Finally, emotional mesh based matching process considering the emotional histogram and anisotropic characteristics is proposed, which suggests emotional relaxation to the user. In this paper, we propose a system which can recognize the change of emotion easily by using face image and train personal emotion by emotion relaxation.

• Science of Emotion and Sensibility
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• v.14 no.1
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• pp.157-164
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• 2011

Emotion science is one of the rapidly expanding engineering/scientific disciplines which has a major impact on human society. Such growing interests in emotion science and engineering owe the recent trend that various academic fields are being merged. In this paper we propose the potential importance of the biochip technology in which the human emotion can be precisely measured in real time using body fluids such as blood, saliva and sweat. We firstly and newly name such a biochip an Emotion-On-a-Chip (EOC). EOC consists of biological markers to measure the emotion, electrode to acquire the signal, transducer to transfer the signal and display to show the result. In particular, microfabrication techniques made it possible to construct nano/micron scale sensing parts/chips to accommodate the biological molecules to capture the emotional bio-markers and gave us a new opportunities to investigate the emotion precisely. Future developments in the EOC techniques will be able to help combine the social sciences and natural sciences, and consequently expand the scope of studies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1557-1564
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• 2010

In this paper, we propose a maximum entropy-based emotion recognition model using the individual average difference of emotional signal, because an emotional signal pattern depends on each individual. In order to accurately recognize a user's emotion, the proposed model utilizes the difference between the average of the input emotional signals and the average of each emotional state's signals(such as positive emotional signals and negative emotional signals), rather than only the given input signal. With the aim of easily constructing the emotion recognition model without the professional knowledge of the emotion recognition, it utilizes a maximum entropy model, one of the best-performed and well-known machine learning techniques. Considering that it is difficult to obtain enough training data based on the numerical value of emotional signal for machine learning, the proposed model substitutes two simple symbols such as +(positive number)/-(negative number) for every average difference value, and calculates the average of emotional signals per second rather than the total emotion response time(10 seconds).

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1997.11a
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• pp.1-5
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• 1997

• Science of Emotion and Sensibility
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• v.15 no.1
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• pp.121-132
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• 2012

Recently, interest in emotional technology has escalated and its application has extended to many fields, from both an industrial (product) and service (culture, tourism, medical, education, advertising) perspective. Moreover, culture has become a fundamental aspect of modern industry, playing key roles in: gaming, exhibitions, performances, sports, tourism, design, edutainment, as well as various content distribution industries. The prospect of applying emotional technology for cultural content industries makes up for more than half of the 'plan-manufacture-distribution-marketing' process, and thereby also serves as driving force for the growth of a nation. The primary objective of the following research is analyze successful cases from the past through utilization of emotional technology, and to speculate on efficient directions for future research into developing emotional contents. To achieve this, some of the key terms have been defined and elaborated for the sake of clarity. The terms are as follows: emotion, emotion engineering, science of emotion, emotional technology, and emotional contents. Furthermore, studies were conducted based on the six different fields surrounding CT R&D to observe how projects involving emotional technology have succeeded both on a national and global scale. Based on this analysis, this research aims to develop personalized 'Concierge' service-providing contents, contents designed to maximize performance ability of humans, and contents that could be controlled simply via emotion to effectively spread the culture of Korea by focussing on 'fusion' content development. The following research data may hopefully serve as a basic reference to industries navigating towards emotional content development.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.130-133
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• 2004

인간의 감정을 정의하거나 분류하는 것은 매우 어려운 일이다. 이러한 애매모호한 인간의 감정은 어느 한 감정만 나타나는 것이 아니고 다양한 감정의 복합으로, 눈에 띄는 강정이 드러나는 것이다. 인간의 애매모호한 감정 상태와 유사한 감성을 표현하는 알고리즘으로 dynamic emotion Space를 이용한 감성 표현 알고리즘을 제안한다. 기존의 감성 표현 아바타들이 키리 설정된 몇개의 감정만을 데이터 베이스에서 불러와 표현하는 반면에, 본 논문에서 제안하는 감성 표현 시스템은 동적으로 변화하는 감성 공간을 이용하여 감성을 표현함으로써 무수히 다양한 표정을 표현할 수 있다. 실제로 인간의 복합적이고 다양한 표정을 표현할 수 있는지를 알아보기 위해 실제 구현 및 실험을 수행하고, dynamic emotion space를 이용한 감성 표현 시스템의 성능을 입증한다.