• 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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• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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• pp.1190-1195
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• 2011

This paper presents a waist pressure evaluation method in human sensibility using a electroencephalogram(EEG) signal. For this objective, a size-controllable waist-belt is used. First of all, EEG signals for relaxed state are acquired. Then, the waist-belt of the subject is tightened about 90% of normal state. After a few minutes, the belt of the subject is released. Some necessary preprocessing is performed on the acquired signals, 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 state of body pressure. The results of the method showed 77.2% of coincidence with body pressure states. This may be compromising results for ssubject-independent sensibility evaluation using EEG signal.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.12
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• pp.834-838
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• 2004

This paper proposes an algorithm for EEG pattern classification using the Multi-template method, which is a kind of speaker adaptation method for speech signal processing. 10-channel EEG signals are collected in various environments. The linear prediction coefficients of the EEGs are extracted as the feature parameter of human sensibility. The human sensibility classification algorithm is developed using neural networks. Using EEGs of comfortable or uncomfortable seats, the proposed algorithm showed about 75% of classification performance in subject-independent test. In the tests using EEG signals according to room temperature and humidity variations, the proposed algorithm showed good performance in tracking of pleasantness changes and the subject-independent tests produced similar performances with subject-dependent ones.

• Proceedings of the ESK Conference
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• 1997.10a
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• pp.477-481
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• 1997

We are exposed to the various external stimuli input from the environment, which cause emotional changes based on the characteristics of the stimuli. Unfortunately, there are noquantitative results on relationship between human sensibility and the characteristics of physiological signals. The objective of this study was to quantify EEG signals evoked by visual stimulation based on the assumption that the analysis of the variability on the characteristics of the EEG waveform may provide the significant information regarding changes in psychological states of the subject. Seven university students were participated in this study. The experiment was devised with eleven experimental conditions, which are control and ten different types of visual stimulation based on IAPS(International Affective Picture Systems). Seven subjects were used to obtain EEGs while introducing visual stimulation. Wavelet transformation was employed to analyze the EEG signals. Most Positive and negative emotional response were pairely compared. The results showed that the reconstructed signals at the decomposition level revealed the different energy value on the EEG signals. Also, general patterns of EEG signals in rest state compare with negative and positive stimulus were found. This study could be extended to estabish an algorithm which distinguishes psychophysiological states of the subjects exposed to the visual stimulation.

• Proceedings of the ESK Conference
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• 1996.04a
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• pp.259-263
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• 1996

Psychological action is physiological response of outernal stimulus. Physiological response is accompanied b physiological signals which are EEG, EMG, GSR, ECG, BP, and tec. Physiological signals are recently studied for determination of human phychological state. Psychological activity causes electric potential of brain. Physiological signal is considered as measurement of human psychological state. Aditory sensibility which is one of the sense of human may determine differences between positive and negative feeling. EEG and GSR variation with auditory quality of stimulus can be define human negative and positive mental state. This study is to characterize parameters which can determine negative and positive psycholigical state of human.

• Science of Emotion and Sensibility
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• v.4 no.1
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• pp.23-31
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• 2001

Psychological and physiological effects from simulator sickness could be an important bias factor for sensibility evaluation. The present experiment investigated the effects of simulator sickness on sensibility evaluation in the controlled condition of driving a car for 60 minutes on a constant speed (60km/h) in graphic simulator. The simulator sickness was measured and analysed for every five minutes using their subjective evaluation and physiological signals. Results of the subjective evaluation showed that there was significant difference between rest and driving condition at 10 minutes from the start of driving, and the level of difference was increased linearly with time. The analysis on central and autonomic nervous systems showed the significant difference between rest and driving conditions after 5 minutes from the start of the driving on the parameters $\alpha$/total and $\beta$/total, and increased level of sympathetic nervous system. But there was no significant difference between different time conditions. The results indicates that physiological changes from simulator sickness can be a bias factor in objective evaluation of human sensibility which also, uses physiological signals. That is, the changes on the parameter $\alpha$/total and $\beta$/total, and on activation level of sympathetic nervous system from simulator sickness can be a bias factor for evaluation of the level of pleasantness and tension. Therefore the effort on improving the analysis by minimizing or eliminating the bias factors should be done for better and accurate sensibility evaluation in simulator environments.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.5
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• pp.374-379
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• 2004

This paper proposes an algorithm for human sensibility evaluation using 4-channel EEG signals of the prefrontal and the parietal lobes. The algorithm uses an artificial neural network and the multiple templates. The linear prediction coefficients are used as the feature parameters of human sensibility. Comfortableness for chairs and temperature/humidity are evaluated. Many conventional researches have emphasized that a wave of left prefrontal lobe is activated in case of positive sensibility and that of right prefrontal lobe is activated in case of negative sensibility. So the power ratio of a wave is obtained from FFT computation and the results are compared. The results of the comfortableness evaluation for temperature and humidity showed that the outputs of the proposed algorithm coincided with corresponding sensibilities depending on the task of the temperature and the humidity. The . conventional method using a wave is hardly related with comfortableness. And it is also observed that the uncomfortable state due to the high temperature and humidity can be easily changed to the comfortable state by small drop of the temperature and the humidity. It seems to be good results to get 66.7％ of evaluation performance in spite of using EEG and the subject independent approach.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.6
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• pp.811-817
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• 2013

In this study we present a system for pulse-rate period detection and human sensibility evaluation based on the wireless medical telemetry service (WMTS) used for transmission of data from medical telemetry devices to various medical facilities and services. We develop a medical-purpose specific WMTS communication module to transmit biometric signals. From the pulse rate variability(PRV) signal, we attempt to classify positive and negative emotional states based on analysis of the ratio of LF/HF in the frequency domain. We measure the data reception rate according to distance in order to test the performance of the WMTS module and analyze the effects on human sensibility evaluation.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.11a
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• pp.182-186
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• 2002

The process of human information transmission system is one of the foundation characters of energy transmission system on human. If energy transmission has not happened on human that human cannot react anything about everything. Therefore, to know about the system of human information transmission is a study to get basic information to explain a lot of things for human. This study deals with human reaction speed according to display signals of each color, and the result will be analyzed to apply to the design switches for various machines.