• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2699-2701
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• 2004

This paper describes a new algorithm for human sensibility evaluation using two personality-group templates of electroencephalogram (EEG) signals. EEG signals of two groups arc collected in relaxed state, comfortable state and uncomfortable state. First of all, the characteristics of EEGs in relaxed state for two groups are compared. After verification of the results, an algorithm for sensibility evaluation is developed. In comparison of the characteristics for two personality-group EEG signals. there are distinct difference between the EEG patterns of the extrovert and the introvert. Upon these findings, the algorithm for human sensibility evaluation is designed. The results of the algorithm showed 90.0% of coincidence with given tasks. This seems to be compromising results for subject independent sensibility evaluation using EEG signal.

• Journal of the Ergonomics Society of Korea
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• v.26 no.3
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• pp.17-25
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• 2007

'Emotional value' has been a buzz word for design and ergonomics in the era of business innovation. However, the complication of 'emotion' in terms of literal and practical meaning has made it a challenging but confusing task for designers to develop a new product with emotional value. 'Sensibility' and 'emotion' are interchangeable terms to describe human feeling ('gamsung' in Korean). The confusion reached at its peak with Korean terms. Even scholars in Korean language, psychologists, ergonomists, and designers are bewildered at the choice of proper expression for human feeling in both Korean and English. The difficulty could explain the problems in 'sensibility ergonomics' in Korea. The purpose of this paper is to provide both fundamental and satisfying information with people in the area of 'sensibility ergonomics'. Therefore, in this paper, a number of articles and books on sensibility, psychology, sensibility ergonomics, and design were reviewed to clarify the meaning of sensibility and relationship among similar words that have been used with unintentional misunderstanding. Also many adjectives on human sensibility were collected and complied for the use of sensibility evaluation.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.184-186
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• 2001

This paper describes a method of human sensibility evaluation for pleasant and unpleasant environments. Conditions of the environment are room temperature and humidity. Changing the conditions, 10-channel EEG signals for 4 subjects are collected. Linear predictor coefficients of the recorded EEGs are extracted as the feature parameter of human sensibility. A neural network-based human sensibility estimation algorithm is developed. The developed algorithm showed good performance in the pleasantness evaluation. The neural network output produced accurate states of pleasantness sensibility. Subject-independent test showed similar results with subject-dependent test.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.2010-2012
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• 2008

This study describes a system for human sensibility evaluation using PPG(photoplethysmogram) signal and biofeedback algorithm to respond the bad(negative) mood. For this objective, PPG signals for two emotional states(positive/negative) are collected. To evoke the test emotions, happy(or joyful) and sad(or irritating) movie files are collected and played in subjects' monitor. From the acquired PPG signal, the heart rate variability(HRV) is calculated. Using the HRV and its FFT spectra, the human sensibility is evaluated. Since the heart is a representative organ which is controlled by the autonomic nervous system(ANS), the ANS may reflect the changes in emotion. The biofeedback algorithm is designed with motion image player interacting with the results of the sensibility evaluation. It was shown that HRV was changed according to the subject's emotions. Accordingly, the sensibility evaluation test showed feasibility of the our method.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2959-2961
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• 2005

This study presents a human sensibility evaluation algorithm based on the personality-group templates of EEGs. For this objective, 16-channel EEG signals of 10 adults are collected. After Preprocessing of EEG, various EEG Parameters are estimated and compared. The proposed algorithm uses LP coefficients, neural network and pre-/post-processing techniques. The results showed good performance in human sensibility evaluation.

• Science of Emotion and Sensibility
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• v.5 no.1
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• pp.17-24
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• 2002

This research was the first step to develop Expert System for Evaluation of Human Sensibility, where human sensibility can be inferred from objective physiological signals. The study aim was to develop an algorithm in which human arousal level can be judged using measured physiological signals. Fuzzy theory was applied for mathematical handling of the ambiguity related to evaluation of human sensibility, and the degree of belonging to a certain sensibility dimension was quantified by membership function through which the sensibility evaluation was able to be done. Determining membership function was achieved using results from a physiological signal database of arousal/relaxation that was generated from imagination. To induce one final result (arousal level) based on measuring the results of more than 2 physiological signals and the membership function of each physiological signal, Dempster-Shafer's Rule of Combination in Evidence was applied, through which the final arousal level was inferred.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.52
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• pp.241-246
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• 1999

In this study, to specify an evaluation of human sensibility, the types of color, intensity of illuminations and lights consisting work environmental condition are decided, and image data from examining the change of human sensibility followed by changes of the above three conditions are obtained. Using the factor analysis and quantification theory in multi-variate analysis type of Sensibility Ergonomics, determinating the structure of factors, specifying the relations of environmental conditions and factors can be done so that the structure of image on human sensibility space with the change of environmental conditions is analyzed.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2690-2692
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• 2002

This paper describes a technique for human sensibility evaluation using 10-channel EEG(electroencephalogram). The proposed method uses the linear predictor coefficients as EEG feature parameters and a neural network as sensibility pattern classifier. For subject independent system, multiple templates are stored and the most similar template can be selected. EEG signals corresponding to 4 emotions such as, relaxation, joy, sadness and anger are collected from 5 armature performers. The states of relaxation and joy are considered as positive sensibility and those of sadness and anger as negative. The classification performance using the proposed method is about 72.6%. This will be promising performance in the human sensibility evaluation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.411-415
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• 1996

User's sensibility has an important effect upon appreciating household electronic appliances and user's feeling of satisfaction with products has a good effect on the choice of product on purchasing those items. In this point of view, the human-oriented approach of product development system can be adopted as Human Sensibility Engineering. The target of changed development system is to define user's sensibility factors and to apply them to design and development. In this study, the human sensibility ergonomics approach and usability test have been applied to the development and evaluation of an electronic product model.

• IE interfaces
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• v.18 no.2
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• pp.158-166
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• 2005

Human-error and mental stress caused by psychophysiological dissonance between people and artificial environments have become a social problem. And it is a common knowledge that comfort environment reduces human-error and mental stress. Comfort sensibility is related to complex interactions between fabric, climatic, physiological and psychological variables. Currently, comfort sensibility has been evaluated by many sensory tests. However, it is difficult to evaluate comfort sensibility because a concrete concept of comfort sensibility is hard to define. In this paper, we propose a model to evaluate the comfort sensibility using Fuzzy-weighted score on an individual's subjective state for the stimulus. To represent the degree of comfort sensibility level for the stimulus, we represent comfort sensibility using 2 dimensional sensibility vector model. And we use the fuzzy-weighted score that is a fuzzy version of the weighted checklist technique computerized for evaluating the subjects. As an example, this model is applied to 1/f fluctuation sound evaluation. The results show that this model can be effectively used to the quantitative evaluation of comfort sensibility for the stimulus.