• 로봇학회논문지
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• 제5권1호
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• pp.7-13
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• 2010

This paper presents the sound-based emotion estimation method and the growing HRI (human-robot interaction) system for a Mon-E robot. The method of emotion estimation uses the musical element based on the law of harmony and counterpoint. The emotion is estimated from sound using the information of musical elements which include chord, tempo, volume, harmonic and compass. In this paper, the estimated emotions display the standard 12 emotions including Eckman's 6 emotions (anger, disgust, fear, happiness, sadness, surprise) and the opposite 6 emotions (calmness, love, confidence, unhappiness, gladness, comfortableness) of those. The growing HRI system analyzes sensing information, estimated emotion and service log in an edutainment robot. So, it commands the behavior of the robot. The growing HRI system consists of the emotion client and the emotion server. The emotion client estimates the emotion from sound. This client not only transmits the estimated emotion and sensing information to the emotion server but also delivers response coming from the emotion server to the main program of the robot. The emotion server not only updates the rule table of HRI using information transmitted from the emotion client and but also transmits the response of the HRI to the emotion client. The proposed system was applied to a Mon-E robot and can supply friendly HRI service to users.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2000년도 춘계 학술대회 및 국제 감성공학 심포지움 논문집 Proceeding of the 2000 Spring Conference of KOSES and International Sensibility Ergonomics Symposium
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• pp.99-103
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• 2000

There are two approaches in the study of emotion in the physiological psychology. The first is to clarify the brain mechanism of emotion, and the second is to evaluate objectively emotions using physiological responses along with our feeling experience. The method presented here belongs to the second one. Our method is based on the "level-crossing point detection" method. which involves the analysis of frequency fluctuations of EEG and is characterized by estimation of emotionality using coefficients of slopes in the log-power spectra of frequency fluctuation in alpha waves on both the left and right frontal lobe. In this paper we introduce a new theory of estimation on an individual's emotional state by using our non-invasive and easy measurement apparatus.

• 산업경영시스템학회지
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• 제37권1호
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• pp.1-8
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• 2014

This paper proposes an emotion classifier from EEG signals based on Bayes' theorem and a machine learning using a perceptron convergence algorithm. The emotions are represented on the valence and arousal dimensions. The fast Fourier transform spectrum analysis is used to extract features from the EEG signals. To verify the proposed method, we use an open database for emotion analysis using physiological signal (DEAP) and compare it with C-SVC which is one of the support vector machines. An emotion is defined as two-level class and three-level class in both valence and arousal dimensions. For the two-level class case, the accuracy of the valence and arousal estimation is 67% and 66%, respectively. For the three-level class case, the accuracy is 53% and 51%, respectively. Compared with the best case of the C-SVC, the proposed classifier gave 4% and 8% more accurate estimations of valence and arousal for the two-level class. In estimation of three-level class, the proposed method showed a similar performance to the best case of the C-SVC.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2008년도 추계학술대회
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• pp.143-146
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• 2008

The objectives of this study were to evaluate color sensation for yellowish natural dye fabrics using magnitude estimation to determine physical colorimetric factors significantly related to human sensibility by establishing power function in psychophysical analysis. Fourteen different yellowish fabrics dyed with natural colorants were selected as stimuli and subjective color sensations including brightness, heaviness, softness, strength, warmth, activeness, classicalness, femininity, and pleasantness for each stimulus were evaluated. As results, yellowish natural dye fabrics in general seemed to evoke feeling of brightness, femininity, and pleasantness more strongly than that of heaviness and classicalness. Most of color sensation were significantly related with more than one of physical color properties, which leads to establishing reliable power functions between them. In the power functions, these relationships could be utilized to design color-sensible natural dye textiles.

• 전기학회논문지P
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• 제67권2호
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• pp.100-105
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• 2018

In this paper, we determined the driver's stress and fatigue level through physiological signals of a driver in the connected car environment, accordingly designing and implementing the architecture of the connected cars' platforms needed to provide services to make the driving environments comfortable and reduce the driver's fatigue level. It includes a gateway between AVN and ECU for the vehicle control, a framework for native applications and web applications based on AVN, and a sensing device and an emotion estimation engine for application services. This paper will provide the element technologies for the connected car-based convergence services and their implementation methods, and reference models for the service design.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2004년도 추계학술대회 논문집
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• pp.16-16
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• 2004

• 음성과학
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• 제12권4호
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• pp.53-70
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• 2005

A Vowel of speech signals are multicomponent signals composed of AM-FM components whose instantaneous frequency and instantaneous amplitude are time-varying. The changes of emotion states cause the variation of the instantaneous frequencies and the instantaneous amplitudes of AM-FM components. Therefore, it is important to estimate exactly the instantaneous frequencies and the instantaneous amplitudes of AM-FM components for the extraction of key information representing emotion states and changes in speech signals. In tills paper, firstly a method decomposing speech signals into AM - FM components is addressed. Secondly, the fundamental frequency of vowel sound is estimated by the simple method based on the spectrogram. The estimate of the fundamental frequency is used for decomposing speech signals into AM-FM components. Thirdly, an estimation method is suggested for separation of the instantaneous frequencies and the instantaneous amplitudes of the decomposed AM - FM components, based on Hilbert transform and the demodulation property of the extended Fourier transform. The estimates of the instantaneous frequencies and the instantaneous amplitudes can be used for modification of the spectral distribution and smooth connection of two words in the speech synthesis systems based on a corpus.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 1998년도 춘계학술발표 논문집
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• pp.171-175
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• 1998

This work presents an estimation for stress status using biosignal and fuzzy theory. Stress is estimated by 'coin-build' experiment with two type, relax and stress status. The estimator uses five biosignals, fuzzy logic to combine these signals and physiological knowledge. The system was tested in 10 records of healthy indivisuals and acheived a template of a stress progress. This work presents an estimation for stress status using biosignal and fuzzy theory. Stress is estimated by 'coin-build' experiment with two type, relax and stress status. The estimator uses five biosignals, fuzzy logic to combine these signals and physiological knowledge. The system was tested in 10 records of healthy indivisuals and acheived a template of a stress progress.

• 감성과학
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• 제20권2호
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• pp.161-170
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• 2017

감정은 학습능력, 행동, 판단력 등 삶의 많은 부분에 영향을 끼치므로 인간의 본질을 이해하는 데 중요한 역할을 한다. 그러나 감정은 개인이 느끼는 강도가 다르며, 시각 영상 자극을 통해 감정을 유도하는 경우 감정이 지속적으로 유지되지 않는다. 이러한 문제점을 극복하기 위하여 총 4가지 감정자극(행복, 슬픔, 공포, 보통) 시 생체신호(뇌전도, 맥파, 피부전도도, 피부 온도)를 획득하고, 이로부터 특징을 추출하여 분류기의 입력으로 사용하였다. 감정 패턴을 확률적으로 해석하여 다른 공간으로 매핑시켜주는 역할을 하는 Restricted Boltzmann Machine (RBM)과 Multilayer Neural Network (MNN)의 은닉층 노드를 이용하여 비선형적인 성질의 감정을 구별하는 Deep Belief Network (DBN) 감정 패턴 분류기를 설계하였다. 그 결과, DBN의 정확도(약 94%)는 오류 역전파 알고리즘의 정확도(약 40%)보다 높은 정확도를 가지며 감정 패턴 분류기로서 우수성을 가짐을 확인하였다. 이는 향후 인지과학 및 HCI 분야 등에서 활용 가능할 것으로 사료된다.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2003년도 춘계학술대회 논문집
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• pp.41-46
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• 2003

In recently, Is inhabiting more than 70％ indoors during a day in case of company employee and ordinary people which is looking at usual business. Therefore Thermal comfort of human body about indoor temperature and air flow acting very heftily. When intestine temperature is fallen for external low temperature and air flow in winter in case enter into heated room feel comfort by effect of temperature and feel comfort or discomfort by room heating condition gradually. Therefore it is important that grasp thermal comfort about temperature and air flow in heating to keep continuous comfort in indoor dwelling. Temperature and thermal comfort factor of emotion ＆ sensitivity image exert fair effect since heating middle although thermal comfort change greatly effect on sensation about temperature at actuality heating early. Need much study yet in vantage point of emotion ＆ sensitivity although much study were held about thermal and comfort sensibility and when heat in existing research until now. Therefore this study is targeting that evaluate thermal comfort through introduction of estimation method by emotion ＆ sensibility image real and synthetic sensibility about thermal environment that is becoming winter heating.