• Science of Emotion and Sensibility
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• v.14 no.1
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• pp.147-156
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• 2011

Basic emotions such as happiness, sadness, anger, fear, and disgust have been widely used to investigate emotion-specific autonomic nervous system activity in many studies. On the contrary, surprise emotion, Suggested also as one of the basic emotions suggested by Ekman et al. (1983), has been least investigated. The purpose of this study was to provide a description of cardiovascular responses on surprise stimulus using electrocardiograph (ECG) and photoplethysmograph (PPG). ECG and PPG were recorded from 76 undergraduate students, as they were exposed to a visuo-acoustic surprise stimulus. Heart rate (HR), standard deviation of R-R interval (SD-RR), root mean square of successive R-R interval difference (RMSSD-RR), respiratory sinus arrhythmia (RSA), finger blood volume pulse amplitude (FBVPA), and finger pulse transit time (FPTT) were calculated before and after the stimulus presentation. Results show significant increase in HR, SD-RR, and RMSSD-RR, decreased FBVPA, and shortened FPTT. Evidence suggests that surprise emotion can be characterized by vasoconstriction and accelerated heart rate, sympathetic activation, and increased heart rate variability, parasympathetic activation. These results can be useful in developing an emotion theory, or profiling surprise-specific physiological responses, as well as establishing the basis for emotion recognition system in human-computer interaction.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.30 no.2
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• pp.44-54
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• 2022

An empirical analysis was conducted on the workload of helicopter pilots flying in high-risk flight environments such as ground obstacles and weather effects at low altitudes. To evaluate the workload, an independent sample t-test was performed using the NASA-TLX evaluation method most suitable for the aviation field, and the workload score was calculated by applying the analytical stratification method (AHP) to compare and analyze private and commercial pilots. There is a significant difference in mean between private and commercial pilots and the result of work load was obtained over 70%. This paper studied the 'surprise and startle effect' on the helicopter field for the first time. In the future, it is intended to contribute to the safe operation of helicopters by presenting a method for effective safety management by utilizing it in the field of education and training for helicopter pilots and providing basic data for preventing accidents caused by human error.

• Sleep Medicine and Psychophysiology
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• v.4 no.1
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• pp.107-119
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• 1997

Objectives: The psychophysiologic response pattern between healthy subjects and patients with generalized anxiety disorder, and the relationship among anxiety rating scales and those patterns in patients were examined. Methods: Twenty-three patients with generalized anxiety disorder(AD) and 23 healthy subjects were evaluated by Hamilton Rating Scale for Anxiety(HRSA) and State-Trait Anxiety Inventory before baseline stressful tasks. Subjective Units of Distress were evaluated just before baseline period, immediately after stressful tasks, at the end of the entire procedure, and psychophysiologic measures, i.e., skin temperature(ST), electromyographic activity(EMG), heart rate(HR), electrodermal response(EDR) during baseline & rest and during two psychologically stressful tasks (mental arithmetic, TM; talk about a stressful event, TT) were also evaluated. Results: 1) AD group showed significantly higher EMG level during rest after stressful tasks and higher HR level during all period except TM compared to control group. 2) AD group showed lower change in the startle response(SR) of ST, in the SR & the recovery response(RR) of EMG during TM, and in the RR of EDR immediately after TM than control group. AD group showed that the RR of EDR was significantly lower than the SR during stressful tasks. 3) We found that there was significantly negative correlation between state anxiety and the RR of EDR after TT in AD group. We also found that there were significantly positive correlations between HRSA score and the SRs of EDR during stressful tasks, and between state anxiety and the SR of EDR during TT. Conclusion: Our results suggest that patients with generalized anxiety disorder show higher autonomic arousal than healthy subjects and decreased physiologic flexibility or reduced autonomic flexibility.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.11a
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• pp.96-103
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• 2001

그동안 정서의 실험적 유도의 어려움과 많은 제약으로 인해 성인 위주로만 이루어져 오던 정서연구가 최근 수 년 간의 정서연구에 대한 방법론의 발달로 아동에게까지 그 범위가 확대되고 있다. 본 연구에서는 아동의 다섯 가지 정서 (기쁨, 분노, 슬픔, 스트레스, 놀람)에 의해 유발되는 아동의 자율신경계 패턴을 확인하고자 한다. 놀람 정서를 추가한 "아동용 정서유발 프로토콜 (양경혜 등, 2000)"을 사용하여 아동에게 정서를 유발시키고, 정서가 유발되는 도안의 자율신경계 반응(KST, ECG, EDA, PPG)을 측정하였다. 초등학교 1, 2 학년인 34명(남: 18, 여:16)의 아동이 실험에 참여하였다. 실험 결과 다섯 가지 정서가 아동들에게 적절하고 효과적으로 유발되었으며, 정서에 따른 생리반응 변화가 관찰되었다. 분석에 사용된 12개 생리반응 변수 중 8개 변수에서 정서에 따른 차이가 발견되었으며, 정서에 따라 다른 자율신경계 반응 패턴을 얻을 수 있었다. 또한, 동일한 방법으로 수행한 본 연구실의 선행 연구와도 일치하는 결과를 보였다. 이는 아동용 정서유발 프로토콜이 표준화된 아동정서 유발자극으로 사용될 수 있으며, 생리반응 주형(template)을 이용하여 아동정서를 구분할 수 있음을 제시한다.

• The Journal of the Korea Contents Association
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• v.14 no.9
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• pp.476-483
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• 2014

The purpose of this study was to make a suitable images for korean emotional expressions. KSFI(Korean Standard Facial Image)-AUs was produced from korean standard apperance and FACS(Facial Action coding system)-AUs. For the objectivity of KSFI, the survey was examined about emotion recognition rate and contribution of emotion recognition in facial elements from six-basic emotional expression images(sadness, happiness, disgust, fear, anger and surprise). As a result of the experiment, the images of happiness, surprise, sadness and anger which had shown higher accuracy. Also, emotional recognition rate was mainly decided by the facial element of eyes and a mouth. Through the result of this study, KSFI contents which could be combined AU images was proposed. In this future, KSFI would be helpful contents to improve emotion recognition rate.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.4
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• pp.28-36
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• 2021

Surprise and Startle are often cited as potential or contributing factors in the cause of aircraft accidents because they can negatively affect pilots' situational awareness and decision-making. Accordingly, it is necessary to more clearly understand the effect on flight safety through the psychological and physiological reactions that occur to the pilots. Therefore, this study empirically analyzed the effects of Surprise and Startle on the pilot's psychological and physiological responses using a helicopter flight training device for the first time in Korea. As a result of the analysis, the ratio of recognition of Startle and Surprise, heart rate, and respiration rate showed a high difference between private pilots and commercial pilots. This is analyzed as the difference between long-term flight experience and flight time. In addition to presenting effective information for improving the education and training field of helicopter pilots in the future, it is intended to provide basic data for related research.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.179-184
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• 2023

본 연구는 우울감을 느끼거나 대화 상대 부재로 어려움을 겪는 사용자와 정서 교감형 시스템간의 대화로 구성된 한국어 데이터 셋을 구축하고 이때 시스템이 사용할 수 있는 효과적인 응대 전략을 제안하는데 목적이 있다. 데이터셋은 사용자와 시스템 간의 대화 쌍을 기본 단위로 하며, 사용자의 7가지 기본 감정(행복, 슬픔, 공포, 놀람, 분노, 혐오, 중립)과 시스템의 4가지 응대 전략(명료화, 공감적 응대, 제안, 페르소나)에 따라 주석이 된다. 이 중, 공감적 응대 전략은 10가지 독특한 반응 유형(수용적 경청, 후행 발화 요청, 승인/동의, 비승인/재고 요청, 놀람, 격려, 느낌 표시, 상대 발화 반복, 인사, 의견 제시) 및 4가지 후행 발화 요청 유형(무엇, 왜, 어떻게, 그밖에)을 포함하는 구조로 구체화되었다. 이러한 주석은 시스템이 사용자의 다양한 감정을 식별하고 적절한 공감 수준을 나타내는 응답을 생성하는 데 있어 연구적인 의의가 있으며, 필요시 사용자가 부정적 감정을 극복할 수 있는 활동을 제안하는 데 도움을 줄 수 있다는 점에서 실제적인 의의가 있다.

• 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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.528-531
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• 2004

본 논문에서는 칼라 영상을 이용하여 인간의 감성을 인식할 수 있는 방법을 제안한다. 먼저 칼라 영상으로부터 피부색 추출방법을 이용하여 얼굴을 추출한다 그 다음, 추출된 얼굴 영상으로부터 인간 얼굴의 특징 점(눈썹, 눈, 코, 입)들을 추출하는 방법과 각 특징 점들 간의 구조적인 관계로부터 인간의 감성(기쁨, 놀람, 슬픔, 분노)을 인식하는 방법을 제안한다. 본 논문에서 제안한 방법은 퍼지 추론을 기반으로 하여 인간의 감성을 인식한다. 마지막으로, 제안된 방법은 실험을 통해 그 응용 가능성을 확인한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.115-118
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• 2008

본 논문에서는 음성으로부터 감정을 인식하고 감성적인 운율로 음성 출력을 산출해 내는 시스템을 제안 한다. 음성적인 운율로부터 감정을 인식하기 위해서 퍼지룰(rule)을 이용한다. 본 논문에서 감정 인식 시스템은 음성 샘플들로 학습 데이터를 구축하고 이를 기반으로 하여 추출된 20개의 특징 집합으로부터 가장 중요한 특징들을 자동적으로 선택한다. 화남, 놀람, 행복, 슬픔, 보통의 5가지 감정 상태를 구분하기 위하여 접근법에 기반한 퍼지를 이용하였다.