• Journal of the Ergonomics Society of Korea
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• v.31 no.2
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• pp.271-279
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• 2012

Objective: This study classified three different emotional states(boredom, pain, and surprise) using physiological signals. Background: Emotion recognition studies have tried to recognize human emotion by using physiological signals. It is important for emotion recognition to apply on human-computer interaction system for emotion detection. Method: 122 college students participated in this experiment. Three different emotional stimuli were presented to participants and physiological signals, i.e., EDA(Electrodermal Activity), SKT(Skin Temperature), PPG(Photoplethysmogram), and ECG (Electrocardiogram) were measured for 1 minute as baseline and for 1~1.5 minutes during emotional state. The obtained signals were analyzed for 30 seconds from the baseline and the emotional state and 27 features were extracted from these signals. Statistical analysis for emotion classification were done by DFA(discriminant function analysis) (SPSS 15.0) by using the difference values subtracting baseline values from the emotional state. Results: The result showed that physiological responses during emotional states were significantly differed as compared to during baseline. Also, an accuracy rate of emotion classification was 84.7%. Conclusion: Our study have identified that emotions were classified by various physiological signals. However, future study is needed to obtain additional signals from other modalities such as facial expression, face temperature, or voice to improve classification rate and to examine the stability and reliability of this result compare with accuracy of emotion classification using other algorithms. Application: This could help emotion recognition studies lead to better chance to recognize various human emotions by using physiological signals as well as is able to be applied on human-computer interaction system for emotion recognition. Also, it can be useful in developing an emotion theory, or profiling emotion-specific physiological responses as well as establishing the basis for emotion recognition system in human-computer interaction.

• Korean Journal of Cognitive Science
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• v.18 no.1
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• pp.57-68
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• 2007

This study explores children's categories of emotion understanding from facial expressions onto two dimensional structure of emotion. Children of 89 from 3 to 5 years old were required to those facial expressions related the fourteen emotion terms. Facial expressions applied for experiment are used the photographs rated the degree of expression in each of the two dimensions (pleasure-displeasure dimension and arousal-sleep dimension) on a nine-point scale from 54 university students. The experimental results showed that children indicated the greater stability in arousal dimension than stability in pleasure-displeasure dimension. Emotions about sadness, sleepiness, anger and surprise onto two dimensions was understand very well, but emotions about fear, boredom were showed instability in pleasure-displeasure dimension. Specifically, 3 years old children indicated highly the perception in a degree of arousal-sleep than perception of pleasure-displeasure.

• Science of Emotion and Sensibility
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• v.14 no.4
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• pp.605-616
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• 2011

The present study examined memory accuracy for faces with positive, negative and neutral emotional expressions to test whether their emotional content can affect visual working memory (VWM) performance. Participants remembered a set of face pictures in which facial expressions of the faces were randomly assigned from pleasant, unpleasant and neutral emotional categories. Participants' task was to report presence or absence of an emotion change in the faces by comparing the remembered set against another set of test faces displayed after a short delay. The change detection accuracies of the pleasant, unpleasant and neutral face conditions were compared under two memory exposure duration of 500ms vs. 1000ms. Under the duration of 500ms, the accuracy in the pleasant condition was higher than both unpleasant and neutral conditions. However the difference disappeared when the duration was extended to 1000ms. The results indicate that a positive facial expression can improve VWM accuracy relative to the negative or positive expressions especially when there is not enough time for forming durable VWM representations.

• Journal of Families and Better Life
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• v.29 no.6
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• pp.55-69
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• 2011

The purpose of this study was to explore the effects of difficult temperament and mothers' reactions to child negative emotion on child emotion regulation strategies. Mothers of 253 preschoolers(Mage=4.04yrs.) responded to questionnaires on child temperament, mothers' reactions to child negative emotion, and child emotion regulation strategy. The results of regression analysis revealed that; 1) child difficult temperament positively predicted child's aggressive or outburst/appealing strategies whereas negatively predicted avoidance/none strategy; 2) child difficult temperament was not the variable predicting positive coping strategy, but mothers' emotion-focused or problem-focused reactions predicted child positive coping strategy whereas punitive or distress reactions predicted either aggressive or avoidance/none strategy; 3) child temperament moderated the link between mothers' reactions to child's negative emotion expression and child emotion regulation strategies. In particular, children with higher difficult temperament showed higher aggressive strategy under mothers' higher distress or punitive reaction and lower emotion focused or problem focused reaction. On the other hand, children with lower difficult temperament only showed avoidance/ none strategy when mothers showed higher minimization or punitive reaction. The results of current study underscore both child temperament, mothers' reactions and their interactions in predicting child emotion regulation strategies.

• Journal of Families and Better Life
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• v.28 no.3
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• pp.13-26
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• 2010

This study investigates the effects of parent-adolescent communication, emotional intelligence and parentification on the psychological well-being of adolescents. Participants were 712 middle and high school students from Seoul. The collected data were analyzed through a Cronbach's $\alpha$, two-way ANOVA, Pearson's correlation and stepwise multiple regression. The results are as follows: 1) While parent-adolescent communication, parentification, and psychological well-being differed by grade, emotional intelligence did not differ by grade. 2) Father-adolescent communication, regulation of emotion, expression of emotion, practice of emotion, recognition of emotion and mother-adolescent communication were significant predictors of the psychological well-being of middle school students. 3) The recognition of emotion, father-adolescent communication, practice of emotion, regulation of emotion, and mother-adolescent communication were significant predictors of the psychological well-being of high school students. 4) Emotional intelligence played a partially mediating role in the relationship between parent-adolescent communication and psychological well-being.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.2
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• pp.91-101
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• 2008

For a friendly interaction between human and robot, emotional interchange has recently been more important. So many researchers who are investigating the emotion generation model tried to naturalize the robot's emotional state and to improve the usability of the model for the designer of the robot. And also the various emotion generation of the robot is needed to increase the believability of the robot. So in this paper we used the hybrid emotion generation architecture, and defined the generalized context input of emotion generation model for the designer to easily implement it to the robot. And we developed the personality and loyalty model based on the psychology for various emotion generation. Robot's personality is implemented with the emotional stability from Big-Five, and loyalty is made of familiarity generation, expression, and learning procedure which are based on the human-human social relationship such as balance theory and social exchange theory. We verify this emotion generation model by implementing it to the 'user calling and scheduling' scenario.

• 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.

• Proceedings of the Korea Society of Design Studies Conference
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• 2005.10a
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• pp.32-33
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• 2005

• Review of Korea Contents Association
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• v.11 no.2
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• pp.34-39
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• 2013

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1128-1141
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• 2009

Graphical expressions are continuously improving, spurred by the astonishing growth of the game technology industry. Despite such improvements, users are still demanding a more natural gaming environment and true reflections of human emotions. In real life, people can read a person's moods from facial color and expression. Hence, interactive facial colors in game characters provide a deeper level of reality. In this paper we propose a facial color adaptive technique, which is a combination of an emotional model based on human emotion theory, emotional expression pattern using colors of animation contents, and emotional reaction speed function based on human personality theory, as opposed to past methods that expressed emotion through blood flow, pulse, or skin temperature. Experiments show this of expression of the Facial Color Model based on facial color adoptive technique and expression of the animation contents is effective in conveying character emotions. Moreover, the proposed Facial Color Adaptive Technique can be applied not only to 2D games, but to 3D games as well.