• Journal of the Korean Home Economics Association
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• v.44 no.7 s.221
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• pp.99-111
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• 2006

This study was conducted to investigate children's emotional response, emotion regulation strategy, and emotion regulation effect (regulation effect of strategies), and to determine the relationships among emotion regulation strategy, emotion regulation effect and children's psychological well-being in anger, (ear, and disappointment situations. Emotion regulation strategy recomposed four strategies through factor analysis based on the children's direct answers to the question inquiring on the method used to regulate anger, fear, and disappointment. A total of 359 elementary school children in glades 5 or 6 selected one strategy use to regulate anger, fear, and disappointment. The effect of that selected strategy were estimated. Psychological well-being is evaluated by a questionnaire. The results of this study showed that most of elementary school children used the attention evocation strategy to regulate anger, fear, and disappointment, and this strategy was confirmed to be the most effective. Children's psychological well-being was associated with only emotion regulation effect in anger, fear, and disappointment situations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.9
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• pp.1294-1299
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• 2014

The emotion is deeply affected by human behavior and cognitive process, so it is important to do research about the emotion. However, the emotion is ambiguous to clarify because of different ways of life pattern depending on each individual characteristics. To solve this problem, we use not only physiological signal for objective analysis but also hybrid unsupervised-supervised learning classifier for automatic emotion detection. The hybrid emotion classifier is composed of K-means, genetic algorithm and support vector machine. We acquire four different kinds of physiological signal including electroencephalography(EEG), electrocardiography(ECG), galvanic skin response(GSR) and skin temperature(SKT) as well as we use 15 features extracted to be used for hybrid emotion classifier. As a result, hybrid emotion classifier(80.6%) shows better performance than SVM(31.3%).

• Science of Emotion and Sensibility
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• v.17 no.1
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• pp.63-70
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• 2014

Emotion regulation has been suggested as a pathway through which personality traits (e.g., extraversion or neuroticism) affect psychological well-being. However, the pathway needs further investigation across cultures due to variations in parts of the relationship reported in recent culture research. With an aim of improving current understanding of the pathway, we investigated the role of emotion regulation mediating the link between personality traits and well-being across two college samples from different cultural backgrounds: Korea and the United States (US). Results of mediation analysis revealed that the extraversion-well-being relationship was fully mediated by the degree to which individuals regulate negative emotions in both Korean and US samples. However, the neuroticism-well-being relationship was partially mediated by emotion regulation in the US sample, while it was fully mediated in the Korean sample. The role of emotion regulation differently functioning across cultures suggests the importance of investigating cultural-specific mechanism of psychological processes.

• International Journal of Advanced Culture Technology
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• v.5 no.1
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• pp.26-31
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• 2017

In this study, Emotion-DNA is constructed in the same way asthat the human DNA constructs the human body. Emotion-DNA is copied and translated in the same way as that the human DNA copies and translates itself. We made an attempt to embody the mind by Emotion-DNA like the symbols "A, T, G, C, U" that make up the chromosome of the human body. This is a diagram of the flow of emotions that the human body operates by literary works. These schemes present new directions for the therapeutic analysis of literary works and for the creation of therapeutic literary works. In this study, we analyzed the nominal Emotion-syllables as a framework of the structuring of emotional DNA. As a result, through the structuring of the emotional DNA, it was judged that the therapeutic action of the human body, which is included in the Rated Sijo among the literary works, can be more concrete and powerful than the works of other genres.

• Journal of Oriental Neuropsychiatry
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• v.33 no.3
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• pp.227-239
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• 2022

Objectives: The purpose of this study was to develop a standardization manual for Emotion To Emotion therapy. In this study, the processes and categories derived through literature search related to the Emotion To Emotion treatments, were revised and supplemented by the expert FGI (Focus Group Interview). Afterwards, the expert Delphi was conducted, to develop a standard manual for the disease types, purpose, and method of Emotion To Emotion therapy. Methods: In this study, literature analysis and expert Delphi, as a quantitative research method, were conducted, and the expert Focus Group Interview (FGI) was conducted as a qualitative study. The manual was completed by leading the consensus, on the standardization manual for Emotion To Emotion therapy. After that, a clinical expert Delphi was conducted to test the reliability as well as validity of the manual, through quantitative consensus on the manual of the Emotion To Emotion therapy. Results: First, as a result of literature studies, to date, studies related to Emotion To Emotion therapy have been qualitatively and quantitatively limited, as comparative literature related to clinical cases. Second, through expert FGI, the manual was structured with eight sub-factors for the indication diagnosis, six sub-factors for the implementation method, and 13 detailed factors. Third, through an expert Delphi, the consensus did the factor of indication, implementation methods, and implementation process, and developed a standardization manual for Emotion To Emotion therapy ver 1.0. Conclusions: Through literature analysis, expert FGI, and expert Delphi, the Emotion To Emotion therapy standardization manual ver 1.0 was completed, and will proceed with the revision and improvement report.

• Science of Emotion and Sensibility
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• v.15 no.1
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• pp.97-104
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• 2012

Recently, a big text data has been produced by users, an opinion mining to analyze information and opinion about users is becoming a hot issue. Of the opinion mining, especially a sentiment analysis is a study for analysing emotions such as a positive, negative, happiness, sadness, and so on analysing personal opinions or emotions for commercial products, social issues and opinions of politician. To analyze the sentiment analysis, previous studies used a mapping method setting up a distribution of emotions using two dimensions composed of a valence and arousal. But previous studies set up a distribution of emotions arbitrarily. In order to solve the problem, we composed a distribution of 12 emotions through carrying out a survey using Korean emotion words list. Also, certain emotional states on two dimension overlapping multiple emotions, we proposed a selection method with Roulette wheel method using a selection probability. The proposed method shows to classify a text into emotion extracting emotion terms from a text.

• 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.20 no.3
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• pp.13-22
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• 2017

Emotion has a direct influence such as decision-making, perception, etc. and plays an important role in human life. For the convenient and accurate recognition of high-arousal negative emotion, the purpose of this paper is to design an algorithm for analysis using the bio-signal. In this study, after two emotional induction using the 'normal' / 'fear' emotion types of videos, we measured the Galvanic Skin Response (GSR) signal which is the simple of bio-signals. Then, by decomposing Tonic component and Phasic component in the measured GSR and decomposing Skin Conductance Very Slow Response (SCVSR) and Skin Conductance Slow Response (SCSR) in the Phasic component associated with emotional stimulation, extracting the major features of the components for an accurate analysis, we used a discrete wavelet transform with excellent time-frequency localization characteristics, not the method used previously. The extracted features are maximum value of Phasic component, amplitude of Phasic component, zero crossing rate of SCVSR and zero crossing rate of SCSR for distinguishing high-arousal negative emotion. As results, the case of high-arousal negative emotion exhibited higher value than the case of low-arousal normal emotion in all 4 of the features, and the more significant difference between the two emotion was found statistically than the previous analysis method. Accordingly, the results of this study indicate that the GSR may be a useful indicator for a high-arousal negative emotion measurement and contribute to the development of the emotional real-time rating system using the GSR.

• Korean Journal of Human Ecology
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• v.19 no.2
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• pp.285-294
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• 2010

This study examined the relationship between children's school adjustment and their emotion regulation. The subjects were 122 1st grade students selected from one elementary school in Incheon. Teachers rated each child using the Emotion Regulation Scale (Lee, 1997) and School Adjustment Scale (Chi & Jung, 2006). The data were analyzed by using descriptive statistics, t-test, correlation analysis, and stepwise regressions. The children's emotion regulation and school adjustment were differed by sex of the child. The girls were assessed to be better adapted in emotion regulation and school adjustment than the boys. The children's emotion regulation was positively related to the children's school adjustment. In addition, the children's emotion regulation predicted how well they would adjust to school life.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.2
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• pp.64-70
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• 2012

This paper presents a statistical analysis method for the selection of electroencephalogram (EEG) electrode positions and spectral features to recognize emotion, where emotional valence and arousal are classified into three and two levels, respectively. Ten experiments for a subject were performed under three categorized IAPS (International Affective Picture System) pictures, i.e., high valence and high arousal, medium valence and low arousal, and low valence and high arousal. The electroencephalogram was recorded from 12 sites according to the international 10~20 system referenced to Cz. The statistical analysis approach using ANOVA with Tukey's HSD is employed to identify statistically significant EEG electrode positions and spectral features in the emotion recognition.