• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.985-987
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• 2010

In this paper, we propose a maximum entropy-based emotion recognition model using individual average difference. In order to accurately recognize an user' s emotion, the proposed model utilizes the difference between the average of the given input physiological signals and the average of each emotion state' signals rather than only the input signal. For the purpose of alleviating data sparse -ness, the proposed model substitutes two simple symbols such as +(positive number)/-(negative number) for every average difference value, and calculates the average of physiological signals based on a second rather than the longer total emotion response time. With the aim of easily constructing the model, it utilizes a simple average difference calculation technique and a maximum entropy model, one of well-known machine learning techniques.

• Journal of Korea Multimedia Society
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• v.25 no.9
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• pp.1251-1256
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• 2022

Auscultation of heart sounds using a stethoscope is the basic method to diagnose the cardiovascular disease and observation of abnormalities. However, the heart sound transmitted to the ear through the stethoscope is greatly affected by internal sounds such as organ movement or breathing. In addition, the user's experience significantly influences the accuracy of the auscultation result. Therefore, in this paper, we developed a wearable device that simultaneously measures heart sound and PPG signals for cardiac condition monitoring. The structure of the proposed device is designed to simultaneously measure heart sound and PPG signals when worn on a finger and placed on the chest. A prototype was implemented according to the design structure, and it was confirmed that the performance of measurements and collection for physiological signals was excellent through experiments.

• Science of Emotion and Sensibility
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• v.11 no.4
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• pp.637-644
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• 2008

Human emotion has been tried to be recognized by physiological measurements in developing emotion machine enabling to understand and react to user's emotion. This study is to find the time-dependent physiological measurements and their variation characteristics for discriminating emotions according to dimensional emotion model. Ten university students were asked to watch sixteen prepared images to evoke different emotions. Their subjective emotions and autonomic nervous responses such as ECG (electrocardiogram), PPG (photoplethysmogram), GSR (Galvanic skin response), RSP (respiration), and SKT(skin temperature) were measured during experiment. And these responses were analyzed into HR(Heart Rate), Respiration Rate, GSR amplitude average, SKT amplitude average, PPG amplitude, and PTT(Pulse Transition Time). TDPs(Time dependent parameters) defined as the delay, the activation, the half recovery and the full recovery of respective physiological signal in this study have been determined and statistically compared between variations from different emotions. The significant tendencies in TDP were shown between emotions. Therefore, TDP may provide useful measurements with emotion recognition.

• The Journal of the Korea Contents Association
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• v.15 no.7
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• pp.591-600
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• 2015

Recently high interest in health and fitness has led to vibrant researches for the active fitness system to learn and enjoy the exercise program for oneself. In this paper, we design and implement the active spinning training system which enables user to have self-learning and experience of customized spinning training program by the biometric and movement information acquired from user's physiological signals. The proposed system provides the appropriate difficulty of spinning program which reflects the concordance rate of spinning dance gestures and the amount of exercising by analyzing the physical status of participant from his brain and pulse waves and recognizing the skeletal movement in real time. For the higher exercise effect, the system offers a virtual personal trainer to show the correct poses and controls the level of difficulty depending on the concordance rate of participant's motions. The experiment with various participants through the proposed system shows that it is able to help users in getting the available exercise effect in comparatively short time.

• Journal of Korea Game Society
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• v.15 no.2
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• pp.105-114
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• 2015

We propose a real time user interface that utilizes emotion recognition by physiological signals. To improve the problem that was low accuracy of emotion recognition through the traditional EEG(ElectroEncephaloGram), We developed a physiological signals-based emotion recognition system mixing relative power spectrum values of theta/alpha/beta/gamma EEG waves and autonomic nerve signal ratio of ECG (ElectroCardioGram). We propose both a data map and weight value modification algorithm to recognize six emotions of happy, fear, sad, joy, anger, and hatred. The datamap that stores the user-specific probability value is created and the algorithm updates the weighting to improve the accuracy of emotion recognition corresponding to each EEG channel. Also, as we compared the results of the EEG/ECG bio-singal complex data and single data consisting of EEG, the accuracy went up 23.77%. The proposed interface system with high accuracy will be utillized as a useful interface for controlling the game spaces and smart spaces.

• Korean Journal of Oriental Medicine
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• v.2 no.1
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• pp.84-103
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• 1996

The physiological signals measured by Oriental Medicine instruments have been analyzed quantitatively in the view of the rule of promoting and counteracting relation of five evolutive phases theory. We tried to reduce the physiological signals measured by EAV(Elec-tro-Acupuncture according to Voll) and IR thermography to the representation of five evelutive phases. The EAV index and local skin temperature on acupuncture points of each phases measured and normalized so that the total value of five phases became unity. We assumed that the normalized EAV index and local skin temperature mean the deficiency or excess of Qi for each phases. The state of Qi distribution for each phases were approximately agree with the diagnostic pattern of O. M. doctor. Taking account of the Qi distribution state of·or the five evolutive phases, we performed a proper needle insertion on acupuncture points to induce the distinct change of Qi for each phases. We compared the measured results with the predictions of Qi variation by the rule of pro- moting and counteracting relation over the five evolutive phases. For all cases, the variation of Qi in the own phase on which a needle insertion was performed were exactly same to the theoretical prediction and partial agreement was shown for the other four phases. The same analysis was carried to the results of skin temperature measurements at accupoints. We found that the local skin temperature at accupoints of each phases shelved a finite change by the needle insertion and the behavior- of its change were strongly correlated to the rule of promoting and counteracting relation of five evolutive phases.

• Journal of Physiology & Pathology in Korean Medicine
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• v.19 no.5
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• pp.1154-1161
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• 2005

Yin Yang theory is the first and the last one to interpret diseases apply to treatment in oriental medicine. So it is regarded as the way of heaven and earth, the discipline of all things, the origin of change, the beginning of giving birth and death, the source of spirit. These regulatory passages are needed to compare with western medical physiology and analyzed whether it has scientific bases or not. The Yin Yang theory of traditional oriental medicine are summerized from the descriptions of Scripture of Documents, Ying Wei theory of Huangdi Neijing. Meanwhile up-to-date neurobiological and molecular genetic theories on circadian physiology are reviewed in western medicine. Sunshine is transferred through RGC to SCN, herein the central circadian rhythm is made by zeitgeber and interaction of melatonin secreted from pineal body and orexin from mp pan of hypothalamus. So HPA axis is activated and controlled under the circadian rhythm and affects peripheral tissues and cells of whole body through glucocorticoid hormones. First of all, the circadian rhythm makes the basic patterns of human life in biological and sociological meaning. It is almost same context with the record of the Scripture of Documents. Also the Ying Qi and Wei Qi is basically same with the sleep-awake mechanism, that is melatonin/orexin signal or per/clk/bmal/cry genes with circadian activation and activity of each organ's physiological function. Conclusively it can be said that Yin Yang is a priori principle of living things and the beginning of giving birth and death for activation of them biologically, as is described in Huangdi Neijing.

• 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.

• Journal of Radiation Industry
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• v.5 no.3
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• pp.259-266
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• 2011

When plants undergo stress, Reactive oxygen species (ROS) which remove bad elements such as mildew and virus is activated in plant body. However, if ROS is excessively increased, plant will be harmed itself by destruction of cell and signal system and phenomenon of lipid peroxidation. In order to identify content of lipid peroxidation and activity of some enzymes scavenging ROS, phenotypical and physiological analysis was performed with two mutant lines, Till-II-877 and Till-II-894, comparing with cv. Dongan (WT). In phenotype analysis, two mutant lines give to well-conditioned growth better than WT in since 5 days after salt treatment. In enzyme activities, there was a modest difference in the content of catalase (CAT) and peroxidase (POD) between Till-II-877 and Till-II-894, two mutant lines showed high levels in CAT contents than WT. However, they express low levels in POD contents. In MDA analysis, the content of Till-II-877 was higher than that of WT, but Till-II-894 was lower. This result indicates that two mutants have different mechanism against salt stress.

• 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.