• 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.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.11a
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• pp.160-163
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• 2009

본 연구는 생리신호에 의한 집중된 시선과 집중하지 않는 시선을 분류하고자 한다. 이를 검증하기 위해 시각적으로 높은 집중과 낮은 집중을 요구하는 두가지 과제를 피실험자에게 제시하고 PPG(Photoplethysmogram), GSR(Galvanic Skin Response) 그리고 SKT(Skin Temperature)센서를 사용한 자율신경계 반응과 시선 움직임을 측정하였다. 과제는 $3{\times}3$으로 화면 구역을 나누고 각 구역에 문자를 제시하고 역방향 문자를 찾도록 하였다. 실험에는 20 명의 대학생이 참여하였으며, 1 번의 실험에 12 종류의 다른 문자배열을 제시 받았으며 1 번의 연습을 포함하여 총 5 회 실시후 데이터를 분석하였다. 높은 집중일 경우와 낮은 집중일 경우를 T-test 분석 결과, 자율신경계에서는 높은 집중일 경우 PPG 주파수가 증가하고 GSR과 SKT는 감소한 결과를 보였다. 따라서 시선의 집중도에 따라 다른 자율신경계 반응과 시선반응을 보이는 것을 확인하였다.

• Science of Emotion and Sensibility
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• v.7 no.3
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• pp.27-35
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• 2004

This study has investigated a psychological status of optimal and pleasant driving condition by measuring various physiological signals using SCR(skin conductance response), PPG(peripheral plethysmograph), SKT(skin temperature) and HR(heart rate). The physiological response was measured during various simulated driving conditions. We developed a hardware and algorithm to measure and analyze the physiological response. The physiological signals has reflected the level of driver's tension or relaxation as well as the heart rate. The emotional responses of drivers were also measured and analyzed in this experiment. The result of the study can be used to design a system to enhance the driver's emotional satisfaction as well as to monitor the driver's safety and health condition.

• Science of Emotion and Sensibility
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• v.20 no.3
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• pp.169-180
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• 2017

Individuals with high trait anxiety try to suppress their anger expression, thus there are limits in measuring their anger using subjective behavioral evaluation. In order to overcome this limitation, this study attempted to identify the difference in the autonomic nervous system responses induced by anger in individuals with high trait anxiety. Participants were divided into two groups, anxiety and control groups. Electrocardiogram (ECG), respiration (RESP), electrodermal activity (EDA), and skin temperature (SKT) were measured while participants were presented with an anger-inducing stimulus. Heart rate (HR), standard deviation of NN interval (SDNN), root mean square of successive difference (RMSSD), low frequency (LF), high frequency (HF), LF/HF ratio, respiration rate (RR), skin conductance level (SCL), and maximum skin temperature (maxSKT) were calculated before and after presenting the stimulus. Anxiety group reported greater anger by the anger-inducing stimulus compared to the control group. Anxiety group also showed significant increase in SDNN and LF, and decrease in HF, LF/HF ratio, and RR. These results suggest that the autonomic nervous system responses may be used as objective indicators of anger experiences in individuals with high trait anxiety.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1131-1135
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• 2010

The development of modern civilization result from the abundance of material. Yet modern people live with chronic mild stress. Excessive chronic mild stress leads to various diseases. From the risk of the disease in order to protect our bodies need to manage chronic mild stress. The purpose of this study is to inspection the effectiveness of detecting in chronic mild stress using the Multi-sensor system. The Multi-sensor system is designed that can be measure three kinds of vital signals of chronic mild stress for the detection. First Photoplethysmogram(PPG), second Electro Dermal Activity(EDA), third Skin Temperature(SKT). The ages and occupations exposed to chronic mild stress, people often use out of this system was applied to dairy products(Pen). In addition, vital signals that occur when the variety of noise was used to remove the accelerometer. Chronic mild stress by the analysis of measured vital signals from Multi-sensor system to the measurement information to a PC to a wireless transmission(Bluetooth). In this study, using Multi-sensor system writing conditions and a variety of situations in the movement to measure vital signals and measurement results verified the accuracy and reliability. Through this measure chronic mild stress in everyday life and managing to maintain will help more healthy lifestyle.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.269-273
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• 1999

Combination of mental stress task with noise background is a traditional tool employed in psychophysiology. However, intensity of background noise is a factor affecting both performance on test and psychophysiological responses associated with stress evoked by mental load in noisy environment. In the current study on 7 subjects we analyzed the influence of white noise (WN) intensity (55, 70, and 85 dB[A] ) on psychophysiological responses during word recognition test performed on noise background. There were recorded following physiological variables: electrodermal activity (EDA) , namely, skin conductance level (SCL), skin conductance response (SCR) amplitude (SCR-A), rise time and total number of SCRs (N-SCR); cardiovascular activity, e.g., heart rate (HR), respiratory sinus arrhythmia (RSA) index, pulse transit time (PTT), finger pulse volume (PV), skin temperature (SKT) and respiratory activity, such as respiration rate (RESP-R) and inspiration wane amplitude (RESP-A) during baseline resting state and 40 s long performance on 3 similar Korean word recognition tests with different WN intensity (55, 70, and 85 dB). Electrodermal responses (SCR-A, SCL, N-SCR) demonstrated gradual increment with increased intensity of noise, and this increase of response magnitude with higher intensity of noise was typical also for r skin temperature (phasic SKT decrease) and pulse volume (phasic and tonic PV decrease). However, some cardiovascular and respiratory responses did not exhibit same tendency of gradual increase of reactivity , namely HR, as well as RESP-R and RESP-A showed decrement of response magnitudes. Important finding in terms of cardiovascular reactivity was that 55 and 70dB evoked similar profiles, while 85dB WN resulted in significantly different profile of reactions, suggesting that there exists a threshold level after which intensive auditory stimulation elicits psychophyslological responses pattern of different quality. There are discussed potential autonomic mechanism involved in mediation of observed physiological responses.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.9
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• pp.1294-1299
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• 2014

The emotion is deeply affected by human behavior and cognitive process, so it is important to do research about the emotion. However, the emotion is ambiguous to clarify because of different ways of life pattern depending on each individual characteristics. To solve this problem, we use not only physiological signal for objective analysis but also hybrid unsupervised-supervised learning classifier for automatic emotion detection. The hybrid emotion classifier is composed of K-means, genetic algorithm and support vector machine. We acquire four different kinds of physiological signal including electroencephalography(EEG), electrocardiography(ECG), galvanic skin response(GSR) and skin temperature(SKT) as well as we use 15 features extracted to be used for hybrid emotion classifier. As a result, hybrid emotion classifier(80.6%) shows better performance than SVM(31.3%).

• Science of Emotion and Sensibility
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• v.15 no.1
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• pp.133-140
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• 2012

We designed a novel individualization process for improving personal emotion recognitions in real time. The designed individualization process was performed by a neutralization algorithm of physiological signals, a subjective emotion reflection of a user updated by personal emotion rules in real time. The physiological signals such as PPG(Photoplethysmography), GSR(Galvanic skin reflex), and SKT(Skin temperature) were measured and analyzed to estimate an emotion states of users. Regulating the emotion status using by emotion rules was performed by reflecting subjective evaluations. The agreement of emotion recognition between of individualization and non-individualization method was estimated by 10 undergraduates (5 females, mean age: $22.1{\pm}2.2$) of Sangmyung University. During the emotion recognition test, 45 images were randomly presented to each participant five times. In results, the proposed individualization process showed the agreement of 71.67 % which was five times higher than when the process was not applied. Therefore, in this study, we demonstrated that the individualization process was significantly useful for customizing emotion recognitions of personal users in real time. The individualization process will be able to improve satisfactions in various emotion related applications and services in the nearer future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.8
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• pp.3925-3932
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• 2013

Emotion is closely related to the life of human, so has effect on many parts such as concentration, learning ability, etc. and makes to have different behavior patterns. The purpose of this paper is to extract important features based on physiological signals to recognize negative emotion. In this paper, after acquisition of electrocardiography(ECG), electroencephalography(EEG), skin temperature(SKT) and galvanic skin response(GSR) measurements based on physiological signals, we designed an accurate and fast algorithm using combination of linear discriminant analysis(LDA) and genetic algorithm(GA), then we selected important features. As a result, the accuracy of the algorithm is up to 96.4% and selected features are Mean, root mean square successive difference(RMSSD), NN intervals differing more than 50ms(NN50) of heart rate variability(HRV), ${\sigma}$ and ${\alpha}$ frequency power of EEG from frontal region, ${\alpha}$, ${\beta}$, and ${\gamma}$ frequency power of EEG from central region, and mean and standard deviation of SKT. Therefore, the features play an important role to recognize negative emotion.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.11a
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• pp.87-90
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• 2009

본 연구는 HMD(Head Mounted Display), 적외선 카메라, 웹 카메라, 데이터 글러브, 그리고 생리신호 측정 센서를 이용한 증강현실 게임 플랫폼 설계를 목적으로 하고 있다. HMD 는 사용자의 머리의 움직임을 파악하고, 사용자에게 가상 물체를 디스플레이화면에 제공한다. 적외선 카메라는 HMD 하단에 부착하여 사용자의 시선을 추적한다. 웹 카메라는 HMD 상단에 부착하여 전방 영상을 취득 후, 현실영상을 HMD 디스플레이를 통하여 사용자에게 제공한다. 데이터 글러브는 사용자의 손동작을 파악한다. 자율신경계반응은 GSR(Galvanic Skin Response), PPG(PhotoPlethysmoGraphy), 그리고 SKT(SKin Temperature) 센서로 측정한다. 측정된 피부전기반응, 맥파, 그리고 피부온도는 실시간 데이터분석을 통하여 집중 정도를 파악하게 된다. 사용자의 머리 움직임, 시선, 그리고 손동작은 직관적 인터랙션에 사용되고, 집중 정도는 직관적 인터랙션과 결합하여 사용자의 의도파악에 사용된다. 따라서, 본 연구는 멀티모달 인터랙션을 이용하여 직관적 인터랙션 구현과 집중력 분석을 통하여 사용자의 의도를 파악할 수 있는 새로운 증강현실 게임 플랫폼을 설계하였다.