• Science of Emotion and Sensibility
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• v.14 no.3
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• pp.371-384
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• 2011

Three experiments were carried out to examine how LED lighting hues influence to the rating and recognition of affective stimuli. In Experiment 1 and 2, IAPS affective pictures were used and an affective rating(valence and arousal) task and a recognition memory task were conducted under red, green, blue, and white hue LED lightings in Experiment 1 and cyan, magenta, yellow, and white ones in Experiment 2, respectively. In Experiment 3, affective words were used and the same two tasks were conducted under red, green, blue, and white hue LED lightings. According to the results of affective rating tasks, when primary hues(RGB) were used, red LED lighting elicited an excitement at the arousal dimension and green LED lighting evoked pleasantness at the valence one. When secondary hues(CMY) were used, magenta and cyan showed the similar but weaker patterns of responses comparing to red and green. The results of recognition memory task showed that the responses to the picture stimuli presented at green and cyan hue lightings tended to be a bit faster comparing to the stimuli presented at the other conditions but the difference was insignificant. In Experiment 3, however, recognition memory responses to the affective words presented at green hue lighting were faster significantly. These results indicate that warm colors like red and magenta elicit unpleasantness or excitement while cool colors like green and cyan evoke pleasantness or relaxation, and the primary hues provoke more positive or negative affectivity than secondary ones do. Particularly, the result of recognition memory task in Experiment 3 suggests that green hue LED lighting might be advantageous at the memory performance of language stimuli rather than visual ones.

• Science of Emotion and Sensibility
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• v.20 no.4
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• pp.41-54
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• 2017

Physical activity has positive effects on cognitive functions by aging. However, it is rare to find research that have scientifically investigated the effects on the affective-cognitive function. Thus, this study aims to brain-scientifically research its effects of physical activity on the affective-cognitive function of adults in adolescence and senescence. As subjects of this study, a total of 60 males adults in D region were selected, and then equally divided into four groups of young exercise group(25~35y/o), young non-exercise group(26~35y/o), old exercise group(60~70y/o), and old non-exercise group(60~70y/o). As experiment tools, the EEG measuring equipment and International Affective Picture System(IAPS) were used. The experiment of this study used an affective-cognitive task where subjects pressed a button depending on emotional valence(positive, neutral, negative) shown in the pictures. During the task, EEG measured eight areas(Fp1, Fp2, Fz, C3, C4, Cz, T3, T4) out of brain areas in accordance with the international 10-20 electrode system, EEG was measured. For statistical analysis, a three-way ANOVA on $4(group){\times}3(stimulus){\times}8(area)$ was conducted. The results showed main effects of group in both reaction time and accuracy, and also in the latency of P3. And there was an interaction between group and stimulus the amplitude of P3. In conclusion, Physical activity has positive effects on the affective-cognitive function of people in adolescence and senescence.

• Proceedings of the ESK Conference
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• 1997.10a
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• pp.473-476
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• 1997

Human visual emotion were investigated by analyzing HRV from ECG signals, which were varied by the visual stimuli. In this paper, twelve university students experienced visual emotion by pictures from IAPS. ECG and subjective rating were obtained for human emotion evaluation. For determination of HRV, ECG was extracted into HF and LF via power spectrum analysis. The results showed that HRV is good for discrimination between positive and negative emotions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.2
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• pp.122-129
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• 2014

In this study, emotion-classification gathered from users was performed, classification-experiments were then conducted using SVM(Support Vector Machine) and K-means algorithm. Total 15 numbers of channels; CP6, Cz, FC2, T7. PO4, AF3, CP1, CP2, C3, F3, FC6, C4, Oz, T8 and F8 among 32 members of the channels measured were adapted in Brain signals which indicated obvious the classification of emotions in previous researches. To extract emotion, watching DVD and IAPS(International Affective Picture System) which is a way to stimulate with photos were applied and SAM(Self-Assessment Manikin) was used in emotion-classification to users' emotional conditions. The collected users' Brain-wave signals gathered had been pre-processing using FIR filter and artifacts(eye-blink) were then deleted by ICA(independence component Analysis) using. The data pre-processing were conveyed into frequency analysis for feature extraction through FFT. At last, the experiment was conducted suing classification algorithm; Although, K-means extracted 70% of results, SVM showed better accuracy which extracted 71.85% of results. Then, the results of previous researches adapted SVM were comparatively analyzed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.1
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• pp.155-161
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• 2014

This study presents the real-time emotion image contents player to induce the user's emotion efficiently. The emotion image contents player was designed to efficiently induce by giving a change in the color, brightness, saturation of image contents corresponded to the user's emotion. In the emotion recognition module, physiological signal of pulse, skin temperature, skin resistance which based on autonomic nervous system were used. The emotion recognition part used physiological signal of pulse, skin temperature, skin resistance based on autonomic nervous system. The image as emotional contents was used with the 9 kinds emotion area classified in international affective picture system(IAPS). As experimental results, the use's emotion that match the image's emotion with the emotion image contents player was derived 10% more accurately. The emotion contents player is expected to increase emotional feeling between users's emotion and contents emotion duo to the real-time emotion reflection.

• Science of Emotion and Sensibility
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• v.15 no.4
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• pp.575-584
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• 2012

Decades of psychological research have shown that emotion brings users various kinds of physical and psychological advantages and disadvantages. Moreover, this also impacts human decision-making. However, in spite of the weight of emotion, combined with HCI, relevant research is still insufficient. We hypothesized that the user's temporal emotion could influence the product evaluation, especially in terms of product usability. Two studies were carried out to investigate the effect of induced priming on user evaluations. In exp1, we manipulated participants' temporal emotions using positive and negative images from IAPS. In our results, we saw image priming had a statistically significant effect, with the positive condition group giving the product high ratings for usability. In exp2, emotional image manipulation was conducted with valence and arousal. As a result, we found that the variables of valence and arousal had some interaction effects. These studies have demonstrated that temporally induced emotion could affect users' emotion in different ways, in addition to influencing product evaluations.

• Korean Journal of Cognitive Science
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• v.21 no.2
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• pp.387-408
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• 2010

This study examined the effects of emotional content on the encoding process of emotional stimuli and the effects of emotional context on those of neutral stimuli. It was examined whether the superior memory of emotional stimuli is due to attentional resource allocation. This study were performed an emotional picture and a neutral word were presented in succession at every trials. The results of recognition judgement showed superior memory of emotional pictures than neutral pictures, but showed poorer memory of neutral words in emotional context than those in neutral context. LPC(Late Positive Complex) of ERP results showed the similar pattern: higher amplitude by emotional pictures than neutral pictures, and lower amplitude by neutral words in emotional context than those in neutral context. This result is considered to support attention allocation hypothesis.

• 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.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.11a
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• pp.73-80
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• 2000

The paper is addressed to the topic of physiological response-specificity in disgust induced by visual stimulation. The purpose of this study was to evaluate reproducibility of physiological reactivity pattern during disgust elicited by the International Affective Pictures System (IAPS) in 2 experiments. Twenty-nine subjects participated in the first experiment with 3 visual stimulation sessions with disgust-eliciting slides (3 slides in each 1 min long session). In the second experiment disgust-eliciting slides from the IAPS were presented to 42 subjects in 2 sessions (one slide for 1 min). Spectral power of frontal EEG, skin conductance (SCL, SCR and NS.SCR), heart rate(HR), heart period variability(HPV) and respiration rate were recorded. Visual stimulation evoked 1:.n deceleration, higher power of high frequency component of HPV, increased SCL and NS.SCR frequency, frontal slow alpha blocking and moderate increase in fast beta power in most of the sessions in both experiments. However in the second experiment the EEG pattern associated with disgust showed inconsistent shifts in fast alpha and slow beta bands, but was marked by higher power of theta activity. Our data in both experiments emphasizes presence of disgust-specific profiles of autonomic and at the less extent EEG responses in visual stimulation context. Discussed are potential behavioral mechanisms leading to observed physiological manifestations in disgust elicited by visual stimulation. The results support the consideration that disgust is an withdrawal type negative valence emotion associated with relatively low autonomic arousal (low HR, low amplitude SCRs with relatively high NS.SCR frequency) and moderate EEG activation signs. Obtained data showed more consistent reproducibility of disgust-specific autonomic rather than EEG response patterns during visual stimulation design.

• Science of Emotion and Sensibility
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• v.20 no.1
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• pp.75-82
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• 2017

We propose a novel method for modeling emotional dimensions using expansion of Russell's (1980) emotional dimensions (Circumplex Model). The Circumplex Model represents emotional words in two axes (Arousal, Valence). However, other researchers have insisted that location of word in Russell's model which is expressed by single point could not represent exact position. Consequently, it is difficult to apply this model in engineering fields (such as Science of Emotion & Sensibility, Human-Computer-Interaction, Ergonomics, etc.). Therefore, we propose a new modeling method which expresses emotional word not as a single point but as a region. We conducted survey to obtain actual data and derived equations using ellipse formula to represent emotional region. Furthermore, we applied ANEW and IAPS which are commonly used in many studies to our emotional model using pattern recognition algorithm. Using our method, we could solve problems with Russell's model and our model is easily applicable to the field of engineering.