• Science of Emotion and Sensibility
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• v.18 no.3
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• pp.63-70
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• 2015

This study identified heart response of participants while listening to sounds which have 1/f fluctuations with exponent ${\alpha}$ gradient. The participants were engaged in emotional stress work. Prior studies related to 1/f fluctuation sound have reported that sound source can alleviate psychological and physiological state of users. Subjects of this study were exposed to sound with three levels of ${\alpha}$ gradient. Heart response of subjects were measured with Photoplethysmography(PPG) sensor simultaneously. The dependent variables of this study were beat per minute(BPM), very low frequency percent of pulse rate variability (VLF percent), the standard deviation of all normal RR intervals (SDNN), and high frequency power(HF power). Subject showed arousal response when exposed to sound with exponent ${\alpha}$ gradient of 3 whereas the sound with exponent ${\alpha}$ gradient of 1 and 2 resulted in relax effect. The characteristic of 1/f fluctuation sounds can be applied to alleviate stress for employers under emotional labor.

• Journal of Korea Game Society
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• v.17 no.2
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• pp.27-34
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• 2017

The study is to drive right users' attitude of internet and smart phones by providing the rewards. It consisted of 4 different types of no compensation, praise card, achievement sticker and cash and its effect on user's behavior was statistically tested. 24 children in grades four through six participated in the study. The task in this study was game of mathematical calculation. The subjective satisfaction about the reward and heart response during the game task were measured. As the results, inactivation of sympathetic and parasympathetic was observed in the case of no compensation while activation in the case of praise card. Therefore, the praise card was observed in greater commitment and satisfaction than the other rewards. The difference between non-compensation and compensation was significant in the subjective satisfaction, but not difference between compensations.

• Journal of the Korea Computer Graphics Society
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• v.22 no.5
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• pp.37-47
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• 2016

This study evaluate user feedback such as physiological response and facial expression when subjects play a social decision making game with interactive virtual agent partners. In the social decision making game, subjects will invest some of money or credit in one of projects. Their partners (virtual agents) will also invest in one of the projects. They will interact with different kinds of virtual agents which behave reciprocated or unreciprocated behavior while expressing socially affective facial expression. The total money or credit which the subject earns is contingent on partner's choice. From this study, I observed that subject's appraisal of interaction with cooperative/uncooperative (or friendly/unfriendly) virtual agents in an investment game result in increased autonomic and somatic response, and that these responses were observed by physiological signal and facial expression in real time. For assessing user feedback, Photoplethysmography (PPG) sensor, Galvanic skin response (GSR) sensor while capturing front facial image of the subject from web camera were used. After all trials, subjects asked to answer to questions associated with evaluation how much these interaction with virtual agents affect to their appraisals.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.4
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• pp.93-102
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• 2019

As interest in wellness grows, There is a lot of research about monitoring individual health using wearable devices. Accordingly, a variety of methods have been studied to distinguish exercise from daily activities using wearable devices. Most of these existing studies are machine learning methods. However, there are problems with over-fitting on individual person's learning, data discontinuously recognition by independent segmenting and fake activity. This paper suggests a detection method for exercise activity based on the physiological response principle of heart rate up and down during exercise. This proposed method calculates activity intensity and heart rate from triaxial and photoplethysmography sensor to determine a heart rate recovery, then detects exercise by estimating activity intensity or detecting a heart rate rising state. Experimental results show that our proposed algorithm has 98.64% of averaged accuracy, 98.05% of averaged precision and 98.62% of averaged recall.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.1-7
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• 2023

The advent of deep learning technologies has led to the development of various medical applications, making healthcare services more convenient and effective. Among these applications, heart rate estimation is considered a vital method for assessing an individual's health. Traditional methods, such as photoplethysmography through smart watches, have been widely used but are invasive and require additional hardware. Recent advancements allow for contactless heart rate estimation through facial image analysis, providing a more hygienic and convenient approach. In this paper, we propose a lightweight methodology capable of accurately estimating heart rate in mobile environments, using a specialized 2-channel network structure based on 2D convolution. Our method considers both subtle facial movements and color changes resulting from blood flow and muscle contractions. The approach comprises two major components: an Encoder for analyzing image features and a regression layer for evaluating Blood Volume Pulse. By incorporating both features simultaneously our methodology delivers more accurate results even in computing environments with limited resources. The proposed approach is expected to offer a more efficient way to monitor heart rate without invasive technology, particularly well-suited for mobile devices.

• Science of Emotion and Sensibility
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• v.14 no.4
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• pp.503-512
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• 2011

Recently in HCI research, emotion recognition is one of the core processes to implement emotional intelligence. There are many studies using bio signals in order to recognize human emotions, but it has been done merely for the basic emotions and very few exists for the other emotions. The purpose of present study is to confirm the difference of autonomic nervous system (ANS) response in three emotions (boredom, pain, and surprise). There were totally 217 of participants (male 96, female 121), we presented audio-visual stimulus to induce boredom and surprise, and pressure by using the sphygmomanometer for pain. During presented emotional stimuli, we measured electrodermal activity (EDA), skin temperature (SKT), electrocardiac activity (ECG) and photoplethysmography (PPG), besides; we required them to classify their present emotion and its intensity according to the emotion assessment scale. As the results of emotional stimulus evaluation, emotional stimulus which we used was shown to mean 92.5% of relevance and 5.43 of efficiency; this inferred that each emotional stimulus caused its own emotion quite effectively. When we analyzed the results of the ANS response which had been measured, we ascertained the significant difference between the baseline and emotional state on skin conductance response, SKT, heart rate, low frequency and blood volume pulse amplitude. In addition, the ANS response caused by each emotion had significant differences among the emotions. These results can probably be able to use to extend the emotion theory and develop the algorithm in recognition of three kinds of emotions (boredom, surprise, and pain) by response measurement indicators and be used to make applications for differentiating various human emotions in computer system.