• Journal of the Ergonomics Society of Korea
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• v.30 no.1
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• pp.179-186
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• 2011

Objective: This study is to review three representative psychological perspectives that explain scientific construct of emotion, that are the discrete emotion model, appraisal model, and dimensional model. Background: To develop emotion sensitive interface is the fusion area of emotion and scientific technology, it is necessary to have a balanced mixture of both the scientific theory of emotion and practical engineering technology. Extensional theories of the emotional structure can provide engineers with relevant knowledge in functional application of the systems. Method: To achieve this purpose, firstly, literature review on the basic emotion model and the circuit model of discrete emotion model as well as representative theories was done. Secondly, review on the classical and modern theories of the appraisal model emphasizing cognitive appraisal in emotion provoking events was conducted. Lastly, a review on dimensional theories describing emotion by dimensions and representative theories was conducted. Results: The paper compared the three models based on the prime points of the each model. In addition, this paper also made a comment on a need for a comprehensive model an alternative to each model, which is componential model by Scherer(2001) describing numerous emotional aspects. Conclusion: However, this review suggests a need for an evolved comprehensive model taking consideration of social context effect and discrete neural circuit while pinpointing the limitation of componential model. Application: Insight obtained by extensive scientific research in human emotion can be valuable in development of emotion sensitive interface and emotion recognition technology.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1999.03a
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• pp.11-15
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• 1999

The discrete state theory on emotion postulated that there existed discrete emotions, such as happiness, anger, fear, disgust, and so forth. Many investigators who emphasized discreteness of emotions have suggested that discrete emotions entailed their specific activities in the autonomic nervous system. The purposes of this study were to develop a model of emotion-specific physiological response patterns. The study postulated six emotions (i.e., happiness, sadness, anger, disgust, fear, and surprise) as the basic discrete emotions. Thirty eight college students participated in the present study. Twelve slides (2 for each emotion category) were presented to the subjects in random order. During resting period of 30 s prior to the presentation of each slide, four presentation of each slide, four physiological measures (EEG, ECG, EDA, and respiration) were recorded to establish a baseline. The same physiological measures were recorded while each slide was being presented for 60 s (producing an emotional sate). Then, the subjects were asked to rate the degree of emotion induced by the slide on semantic differential scales. This procedure was repeated for every slide. Based upon the results, a model of emotion-specific physiological response patterns was developed: four emotion (fear, disgust, sadness, and anger) were classified according to the characteristics of EEG and autonomic responses. However, emotions of happiness and surprise were not distinguished by any combination of the physiological measures employed in this study, suggesting another appropriate measure should be adopted for differentiation.

• 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.

• Asian Journal for Public Opinion Research
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• v.2 no.4
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• pp.248-278
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• 2015

Despite the proliferation of studies on emotion, little attention has been paid to the effects of discrete emotion on political participation. Using a representative survey conducted on a sample of South Korean citizens in the aftermath of the Sewol ferry accident, the current survey explored how anger and sadness, as well as the ways people express those emotions, influence the orientation of their response in social environments and, ultimately, their voting intention. The results partially supported the discrete effects of sadness and anger in eliciting reactions of approach or avoidance. Anger was found to provoke an approach action tendency in independent voters and supporters of the opposition, while also eliciting an avoidance action tendency with a varying effect size across all three groups of respondents. Sadness also prompted an approach action tendency in independents and supporters of the incumbent party, while it manifested a negative association with the avoidance action tendency in supporters of the opponent party. An interpretation of the findings and proposed directions for future research are presented.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.1-11
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• 2014

This paper addresses the emotion computing model for software affective agents. In this paper, emotion is represented in valence-arousal-dominance dimensions instead of discrete categorical representation approach. Firstly, a novel emotion model architecture for affective agents is proposed based on Scherer's componential theories of human emotion, which is one of the well-known emotion models in psychological area. Then a fuzzy logic is applied to determine emotional statuses in the emotion model architecture, i.e., the first valence and arousal, the second valence and arousal, and dominance. The proposed methods are implemented and tested by applying them in a virtual training system for children's neurobehavioral disorders.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.1
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• pp.1-6
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• 2005

In this paper, we propose an emotion recognition method using the facial images and speech signals. Six basic emotions including happiness, sadness, anger, surprise, fear and dislike are investigated. Facia] expression recognition is performed by using the multi-resolution analysis based on the discrete wavelet. Here, we obtain the feature vectors through the ICA(Independent Component Analysis). On the other hand, the emotion recognition from the speech signal method has a structure of performing the recognition algorithm independently for each wavelet subband and the final recognition is obtained from the multi-decision making scheme. After merging the facial and speech emotion recognition results, we obtained better performance than previous ones.

• The Journal of the Acoustical Society of Korea
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• v.23 no.3E
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• pp.85-90
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• 2004

This paper presents two kinds of new approaches, one of which is concerned with recognition of emotional speech such as anger, happiness, normal, sadness, or surprise. The other is concerned with emotion recognition in speech. For the proposed speech recognition system handling human speech with emotional states, total nine kinds of prosodic features were first extracted and then given to prosodic identifier. In evaluation, the recognition results on emotional speech showed that the rates using proposed method increased more greatly than the existing speech recognizer. For recognition of emotion, on the other hands, four kinds of prosodic parameters such as pitch, energy, and their derivatives were proposed, that were then trained by discrete duration continuous hidden Markov models(DDCHMM) for recognition. In this approach, the emotional models were adapted by specific speaker's speech, using maximum a posteriori(MAP) estimation. In evaluation, the recognition results on emotional states showed that the rates on the vocal emotions gradually increased with an increase of adaptation sample number.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1997.11a
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• pp.224-227
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• 1997

The International Affective Picture System (IAPS) developed by Lang and colleagues[1] is a world-widely adopted tool in studices relating a variety of physiological indices to subjective emotions induced by the presentation of standardized pictures of which subjective ratings are well established in the three dimensions of pleasure, arousal and dominance. In the present stuey we investigated whether distinctive EEG characteristics for six discrete emotions can be discernible using 12 IAPS pictures that scored highest subjective ratings for one of the 6 categorical emotions, i. e., happiness, sadness, fear, anger, disgust, and surprise (Two slides for each emotion). These pictures as visual stimuli were randomly given to 38 right-handed college students (20-26 years old) with 30 sec of exposure time and 30sec of inter-stimulus interval for each picture while EEG signals were recorded from F3, F4, O1, and O2 referenced to linked ears. The FFT technoque were used to analyze the acquired EEG data. There were significant differences in RP value changes of EEG bands, most prominent in theta, between positive positive and negative emotions, and partial also among negative emotions. This result is in agreement with previous studies[2, 3]. However, it requires further studied to decided whether IAPS could be a useful tool for catigorical approaches to emotion in addition to its traditional uwe, namely dimensional to emotion.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1998.11a
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• pp.143-147
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• 1998

Autonomic and EEG responses of 38 college students were studied during 60-sec long presentation of International Affective Picture System (IAPS )slides evoking, according to subjective reports, negative (disgust, sadness, surprise) and positive (happiness, exciting) emotional. states. Observed were significant heart rate (HR) deceleration, large skin conductance responses (SCR), moderate respiration frequency slowing, reduction of frontal (F 3, F 4 ) and occipital (O 1, O 2 ) fast alpha, and increases of theta, delta and beta relative spectral power values during the first 30 sec of exposure of IAPS pictures. Analysis carried out to differentiate emotion categories according to autonomic responses indicated that observed HR deceleration was larger in magnitude in surprise and sadness than in disgust, SCR amplitude higher in sadness than in disgust. EEC showed significant differences in theta (F 3, F 4 ) and delta (O 1) power increase in disgust vs. happiness, fast alpha (F 3, F 4 ) power was lower in surprise than in happiness, and slow beta power higher. in happiness than in disgust (0 1). Despite some differences. observed within discrete emotion conditions, overall responses pattern of monitored parameters exhibited similar profiles with few variations, most. obvious. in disgust state, which suggests that affective visual stimulation elicits stereotypical responses in a given passive viewing paradigm. However, the magnitude of physiological responses may vary to certain extent across discrete emotional states making it possible to differentiate among particular experimentally-induced emotional states, e.g., disgust vs. sadness by ANS responses or disgust vs. happiness by EEG measures.

• Journal of KIISE:Software and Applications
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• v.31 no.6
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• pp.799-807
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• 2004

In this paper, we deal with an emotion recognition method using facial images and speech signal. Six basic human emotions including happiness, sadness, anger, surprise, fear and dislike are investigated. Emotion recognition using the facial expression is performed by using a multi-resolution analysis based on the discrete wavelet transform. And then, the feature vectors are extracted from the linear discriminant analysis method. On the other hand, the emotion recognition from speech signal method has a structure of performing the recognition algorithm independently for each wavelet subband and then the final recognition is obtained from a multi-decision making scheme.