• 대한인간공학회지
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• 제23권1호
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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.

• 전기학회논문지
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• 제67권11호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 하계학술대회 논문집 D
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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.

• 감성과학
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• 제5권1호
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• pp.17-24
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• 2002

본 연구는 객관적인 생리신호로부터 인간의 감성을 추론할 수 있는 감성평가 전문가 시스템을 개발하기 위한 첫 번째 단계로 측정된 생리신호를 이용하여 인간의 긴장도를 판단하는 알고리즘의 개발을 목표로 한다. 감성평가와 관련된 애매함을 수리적으로 취급하기 위해 퍼지이론을 적용하여 임의의 감성영역에 속하는 정도를 소속함수로 정량화함으로써 감성평가를 가능하게 하고자 하였다. 소속함수의 결정은 상상을 통해 유발된 긴장/이완의 생리신호 데이터베이스 결과를 사용하였다. 그리고 두 가지 이상의 생리신호 측정결과와 각 생리신호의 소속함수로부터 하나의 최종결과(긴장도)를 유추하기 위해서 Dempster-Shafer증거합 법칙을 적용하였고, 이를 통해 최종적인 긴장도를 도출할 수 있도록 하였다.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2011년도 추계학술대회
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• pp.9-10
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• 2011

• 대한산업공학회지
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• 제31권2호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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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.

• 전기학회논문지
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• 제57권6호
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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.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권11호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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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.