• Science of Emotion and Sensibility
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• v.4 no.1
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• pp.43-51
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• 2001

When consumer evaluates a product, every aspec of the product affects the evaluation. Human uses at least five sensory organs for the evaluation. Multi-sensory or multi-modal design tries to add auditory and olfactory factors to the traditional visual-centered design. For the multi-modal design, it is essential to understand relationships between combined sensory stimuli and human sensibility. Information between simple sensory stimulus and human sensibility is pre-requisite to combine multi-modal stimuli. This study investigated human sensibility against 8 colors and 30 sounds, presented independently. The combined stimuli of color and sound were made based on the sensibility generated by each stimulus. Human sensibility generated by the combined stimuli of color and sound were made based on the sensibility generated by each stimulus. Human sensibility generated by the combined stimuli was investigated with 20 female subjects. For combined stimuli that generated the same kind of sensibility respectively, generated sensibility was same but strength was diminished. For combined stimuli that generated the different sensibilities respectively, subjects showed neutral sensibility or no special sensibilities. Sensibilities to the same stimuli also showed difference depending on personal background of the subjects.

• Journal of the Ergonomics Society of Korea
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• v.20 no.1
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• pp.1-13
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• 2001

Conventionally the subjective assessment for measuring the human sensibility is always performed after an experiment or a stimulus is terminated. This aftermath method can not. exactly, reflect the human sensibility which is produced at the moment of the presentation of the stimulus. In the present study, a new real-time subjective assessment system is developed. The system is composed of two parts: the sensibility input part and the sensibility evaluation part. The sensibility input part gets the values, which are recorded on the input board using pen-mouse, from the evaluation of each subject on his/her own subjective sensibility for the stimulus. The sensibility evaluation part displays the level of the pleasantness and arousal on one and two dimension in real time. An experiment on the design of the input board that any subject can easily and exactly evaluates one's own sensibility is also included in this study. The system can be used for evaluating the human subjective sensibility in real time, and, also, can be applied to other subjective assessment tests that require real time evaluation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.6
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• pp.1087-1094
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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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.12
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• pp.702-707
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• 2003

This study describes a new technique for human sensibility evaluation using electroencephalogram(EEG). Production of EEG is assumed to be linear. The linear predictor coefficients and the linear cepstral coefficients of EEG are used as the feature parameters of sensibility and pattern classification performances of them are compared. Using the better parameter, a human sensibility evaluation algorithm is designed. The obtained results are as follows. The linear predictor coefficients showed the better performance in pattern classification than the linear cepstral coefficients. Then, using the linear predictor coefficients as the feature parameter, a human sensibility evaluation algorithm is developed at the base of a multi-layer neural network. This algorithm showed 90% of accuracy in comfortableness evaluation in spite of fluctuations in statistics of EEG signal.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.277-281
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• 2000

This paper deals with the construction of database system for the human sensibility evaluation.Recently, although a great deal of research efforts have been made to find out the relationships between products and emotion, the main focus of studies have been on visual and auditory sense and less on human sensibility evaluation. Therefore, we think that continuous and systematic studies on odors and the construction of database system are strongly needed in order to enhance the competitive power of products related to them.In this paper, we developed a human sensibility evaluation database system fitted with the characteristics of our country. 쏜 design procedures of database system are presented. According to these procudures, a new database system is implemented on personal computer using MS Access and Visual and is validated.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.2
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• pp.127-134
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• 2005

Human sensibility is assessed by measuring and analyzing various physiological signals in an objective way, or by analyzing adjectives chosen by the subjects in a subjective way. The present study aims at developing an integrated human sensibility assessment system that measures changes in a person's objective and subjective sensibility in real-time and analyzes them in an integrative way. The present system is composed of a real-time subjective sensibility assessment system, an automatic subjective sensibility assessment system and a real-time physiological signal measurement and analysis system for sensibility assessment, which are separated from one another. It can be utilized individually, or can be combined as a synthetic sensibility assessment system for comprehensive sensibility assessment.

• Journal of the Ergonomics Society of Korea
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• v.23 no.1
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• pp.1-12
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• 2004

The purpose of this study was to develop an automatic expert system for the evaluation of human sensibility, where human sensibility can be inferred from objective physiological signals. The study aim was also to develop an algorithm in which human arousal and pleasant level can be judged by 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 and pleasant/unpleasant that was generated from imagination. To induce one final result (arousal and pleasant 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 and pleasant level was inferred.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.11
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• pp.528-534
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• 2002

This paper describes a technique for human sensibility evaluation using EEGs of 4 emotions. 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 suing the proposed method is about 72.6%. This may be promising performance in the human sensibility evaluation.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.463-464
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• 2007

This study describes a method of a human sensibility evaluation using photoplethysmogram(PPG) signal and a biofeedback algorithm to enhance the sensibility For this objective, the heart rate variability(HRV) is extracted from the PPG signal and using the HRV and its FFT the human sensibility is evaluated. The biofeedback algorithm is designed with motion image player interacting with the results of sensibility evaluation. The sensibility evaluation test showed feasibility of the designed method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1506-1511
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• 2018

This study presents a human sensibility evaluation method using neural network and multiple-template method on electroencephalogram(EEG). We used a multi-layer perceptron type neural network as the sensibility classifier using EEG signal. For our research objective, 10-channel EEG signals are collected from the healthy subjects. After the necessary preprocessing is performed on the acquired signals, the various EEG parameters are estimated and their discriminating performance is evaluated in terms of pattern classification capability. In our study, Linear Prediction(LP) coefficients are utilized as the feature parameters extracting the characteristics of EEG signal, and a multi-layer neural network is used for indicating the degree of human sensibility. Also, the estimation for human comfortableness is performed by varying temperature and humidity environment factors and our results showed that the proposed scheme achieved good performances for evaluation of human sensibility.