• Science of Emotion and Sensibility
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• v.26 no.2
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• pp.25-38
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• 2023

Among the discussions on affective representation, the first is to explain the affective representation in the dimensions, and the second is to explain the affective representation according to the modality. In previous studies, to explain affective representation, valence models (signed valence, unsigned valence) and Modality-generality models (modality-general, modality-specific) were presented. In this study, we compared models presented in the previous study using the recently published ASMR to confirm which models explain affective representation well. The data used in this study were behavioral rating values collected by Kim & Kim (2022), and these were obtained for ASMR stimuli that were divided into three affective types (negative, neutral, and positive) and two modalities (auditory and audiovisual). Then, a multidimensional scaling, a representational similarity analysis with a two-way repeated measures ANOVA, and a multiple regression analysis with a two-way repeated measures ANOVA were performed. The results revealed that signed valence and modality-general distinguished between affective types of stimuli better than unsigned valence and modality-specific. Similar to the results of multidimensional scaling, the results of a representational similarity analysis and a multiple regression also showed that the signed valence and modality-general significantly explained affective representation better than the unsigned valence and the modality-specific. These results suggest that the model in which positive and negative are located at the opposite ends of the one dimension explains the affective representation of ASMR well, and that the affective representation was consistent regardless of modality.

• Proceedings of the KSPS conference
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• 2007.05a
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• pp.67-70
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• 2007

The present paper focuses on the interaction between lexical-semantic information and affective prosody. The previous studies showed that the influence of lexical-semantic information on the affective evaluation of the prosody was relatively clear, but the influence of emotional prosody on the word evaluation remains still ambiguous. In the present, we explore whether affective prosody influence on the evaluation of affective meaning of a word and vice versa, using more ecological stimulus (sentences) than simple words. We asked participants to evaluate the emotional valence of the sentences which were recorded with affective prosody (negative, neutral, and positive) in Experiment 1 and the emotional valence of their prosodies in Experiment 2. The results showed that the emotional valence of prosody can influence on the emotional evaluation of sentences and vice versa. Interestingly, the positive prosody is likely to be more responsible to this interaction.

• Korean Journal of Cognitive Science
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• v.28 no.1
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• pp.43-64
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• 2017

The purpose of the current study is to investigate how task-irrelevant affective priming affects higher cognitive function. In the study, we selected prime stimuli from International Affective Picture System(IAPS) and examined if they influence participants' performance of syllogistic reasoning task when they are task-irrelevant. In Experiment 1, arousal of IAPS stimuli was controlled while valence of the stimuli was manipulated. In Experiment 2, valence of IAPS stimuli was controlled while arousal of stimuli was manipulated. In both experiments, task-irrelevant affective primes were followed by syllogistic reasoning tasks consisting of three sentences and measured accuracies of task performance. The results showed that valence of affective prime affected logical validity of reasoning and belief-bias whereas arousal of affective primes did not yield any difference. That is, positive valence facilitated logical and analytic processing by reducing belief-bias while arousal did not affect reasoning task performance. These results suggest that dimensions of valence and arousal independently influence higher cognitive function.

• 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.

• Healthcare Informatics Research
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• v.24 no.4
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• pp.309-316
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• 2018

Objectives: Both the valence and arousal components of affect are important considerations when managing mental healthcare because they are associated with affective and physiological responses. Research on arousal and valence analysis, which uses images, texts, and physiological signals that employ deep learning, is actively underway; research investigating how to improve the recognition rate is needed. The goal of this research was to design a deep learning framework and model to classify arousal and valence, indicating positive and negative degrees of emotion as high or low. Methods: The proposed arousal and valence classification model to analyze the affective state was tested using data from 40 channels provided by a dataset for emotion analysis using electrocardiography (EEG), physiological, and video signals (the DEAP dataset). Experiments were based on 10 selected featured central and peripheral nervous system data points, using long short-term memory (LSTM) as a deep learning method. Results: The arousal and valence were classified and visualized on a two-dimensional coordinate plane. Profiles were designed depending on the number of hidden layers, nodes, and hyperparameters according to the error rate. The experimental results show an arousal and valence classification model accuracy of 74.65 and 78%, respectively. The proposed model performed better than previous other models. Conclusions: The proposed model appears to be effective in analyzing arousal and valence; specifically, it is expected that affective analysis using physiological signals based on LSTM will be possible without manual feature extraction. In a future study, the classification model will be adopted in mental healthcare management systems.

• Journal of Digital Convergence
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• v.15 no.3
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• pp.107-117
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• 2017

This study examined the conditional indirect effect of EEG (electroencephalogram) arousal on the relationship among affective valence, visual attention, perceived self-relevance, and attitudes toward campaign issues in the context of public service announcements (PSAs). Using SPSS macro (No. 14) of conditional process model, the findings in this current study indicated that the perceived self-relevance mediates the relationship between affective valence of PSA and attitudes toward issues and, in turn, is moderated by EEG arousal, indicating goodness-of-fit of the moderated mediation of psychophysiological arousal on PSAs. The results suggested that management of PSAs should be considered the strategic combination between affective valence and perceived self-relevance in advertising appeals.

• The Journal of the Acoustical Society of Korea
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• v.42 no.1
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• pp.75-82
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• 2023

The purpose of this study was to investigate listener's affective responses to different vocal registers and modes in terms of valence (i.e., negative to positive affect) and arousal (i.e., low to high energy level). The data were collected from four different conditions (i.e., higher and lower registers paired with major and minor modes). A total of 188 female college students participated in the survey online and rated their perceived valence and arousal levels on a visual analogue scale after listening to each excerpt. The two-way analysis of variance (ANOVA) was administered for data analysis. The results revealed that there were significant differences in the affective responses to the two vocal registers, showing that the arousal was more affected by the register than the valence. Secondly, mode had statistically significant impact on both valence and arousal while weighing more on valence. Further, there was significant interaction effect of vocal register and mode on valence, but not on arousal. Results also displayed that listeners had the most negative valence when listening to the excerpt of minor mode in higher register, while having the lowest arousal when listening to the excerpt of minor mode in lower register. These findings imply that it is important to consider the vocal range as well as the musical mode when selecting music for appreciation.

• Sleep Medicine and Psychophysiology
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• v.25 no.1
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• pp.21-26
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• 2018

Objectives: The current study aims to develop Korean Social Affective Visual Stimuli (K-SAVS) to arouse social affect. Methods: K-SAVS is composed of pictures of social situations among East Asians. Each picture contains a negative, positive, or neutral affect. Positive and negative stimuli were presented to one group of subjects. Negative and neutral stimuli were presented to another group of subjects. All subjects were required to fill out Affective Valence and Arousal Manikin. Results: In the initial test, 18 positive affective stimuli pictures (1 set) and 36 negative affective stimuli pictures (2 sets) were chosen from 95 stimuli pictures. Positive affective stimuli pictures showed higher valence (p < 0.001) and lower arousal (p < 0.001) than negative affective stimuli pictures. In the confirmatory test, 18 neutral stimuli pictures (1 set) were additionally selected out of the total of 79 pictures of neutral stimuli pictures and the pictures used in the former experiment. Neutral stimuli pictures showed higher valence (p < 0.001) and lower arousal (p < 0.001) than negative affective stimuli pictures. Conclusion: K-SAVS can be a valid and useful tool for inducing specific social affects of Koreans.

• Science of Emotion and Sensibility
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• v.3 no.2
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• pp.29-40
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• 2000

Autonomic and EEG responses were analyzed in 32 college students exposed to visual stimulation with Korean Affective Picture System (KAPS) and 36 students exposed to the International Affective Picture System (IAPS). Cardiac, electrodermal, and electrocortical measures were recorded during 30 sec of viewing affective pictures. The slides intended to elicit basic emotions (fear, anger, surprise, disgust, and sadness) were presented to subjects via Kodak slide-projector. The aim of the study was to differentiate autonomic and EEG responses associated with the same negative valence emotions elicited by KAPS and IAPS stimulation and to identify the influence of cultural relevance on physiological reactivity. The analysis of obtained results revealed significant differences in physiological responsiveness to emotionally negative valence slides from KAPS and IAPS. The typical response profile for all emotions elicited by the KAPS included HR acceleration (except surprise), and increase of electrodermal activity, slow and fast alpha blocking and fast beta power increase in EEG, which was not associated with significant asymmetry (except fast alpha in sadness). Stimulation with the IAPS evoked HR deceleration, specific electrodermal responses with relatively high tonic electrodermal activation, alpha-blocking and fast beta increase, and was accompanied also by theta power increase and marked frontal asymmetry (e.g., fast beta, theta asymmetries in sadness, fast alpha in fear). Physiological responses to fear and anger-eliciting slides from the IAPS were significantly less profound and were accompanied by autonomic and EEG changes more typical for attention rather than negative affect. Higher cardiovascular and electrodermal reactivity to fear emotion observed in the KAPS, e.g., as compared to data with the IAPS as stimuli, can be explained by cultural relevance and higher effectiveness of the KAPS in producing certain emotions such as fear in Koreans.

• 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.