• Journal of Digital Contents Society
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• v.7 no.1
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• pp.47-52
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• 2006

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 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 n wave is obtained from for 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.

• Tribology and Lubricants
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• v.29 no.3
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• pp.167-170
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• 2013

The friction behavior of human skin is determined by the complex interplay of the material and surface properties of the skin, as well as the contacting material, and strongly depends on the contact parameters (e.g., pressure and sliding velocity) and the presence of substances such as water, sweat, or skin surface lipids at the interface. Including a study on the effect of a surface's physical roughness for skin sliding over the surface, various studies have been conducted to understand human tactile sensibility. However, to investigate products in relation to human tactile sensibility, more objective research is needed. This study performed sliding experiments between the skin and the surfaces of phone cases to understand how the texture, friction, and stick-slip characteristics are related. Eight phone case surfaces with different topologies and chemical (or mechanical) compatibilities with skin were prepared and tested multiple times.

• Science of Emotion and Sensibility
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• v.20 no.2
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• pp.171-178
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• 2017

'Smart Sensibility Mat (SSM)' was developed and manufactured for positive sensibility of newborn with fiber, digital, and sensibility technology to reflect features and advantages of kangaroo care. For tactile stimuli, the tube of the silicon material to provide a constant temperature of $32^{\circ}C$ was inserted into the mat and connected to the water-thermostat. To provide a uniform temperature throughout the mat, the fabric by the inserting conductive yarn was attached to the mat surface. After wrapping the mat with cotton pad, the polyurethane foam used as medicine in order to similar to the human skin was bonded to the surface of the mat. To provide the auditory stimuli of a level of 30dB with mother's heartbeat sounds and voice recorded in advance, the Bluetooth speaker was inserted into the mat. To investigate the effects of SSM, 10 newborns who born within two weeks were involved in this experiment. While the baby was lying on each of the general mat (GM) and SSM, the baby's physiological signals-heart rate, breathing rate, temperature- were measured and then, those were conducted t-test to examine the difference between the signals of SSM and GM. The results were as follows: heart rate (t=8.131, p<.001) and respiratory rate (t=7.227, p<.001) among the physiological signals of SSM decreased significantly than GM within the normal range. Temperature (t=1.062, p=0.292) at SSM showed a tendency to decrease than GM within the normal range. This means the tactile stimuli and the auditory stimuli providing from SSM give stable physiological responses. Thus, SSM leads to have psychological comfort and stability of newborns.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.935-939
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• 2003

The emotion recognition is one of the most significant interface technologies which make the high level of human-machine communication possible. The central nervous system stimulated by emotional stimuli affects the autonomous nervous system like a heart, blood vessel, endocrine organs, and so on. Therefore bio-signals like HRV, ECG and EEG can reflect one' emotional state. This study investigates the correlation between emotional states and bio-signals to realize the emotion recognition. This study also covers classification of human emotional states, selection of the effective bio-signal and signal processing. The experimental results presented in this paper show possibility of the emotion recognition.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.422-425
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• 1997

The purpose of this study is to estimate human sensibility quantitatively under color stimulation. We measured biological signals such as EEG, ECG, skin conductance and the number of respiration and eye blinking that were compared with color sensibilities mutually. Our result showed that red, yellow and violet color provoked active and exciting senses dominatively and blue, cyan, pink, and black color were involved in tranquil and resting emotions deeply. Our quantitative estimations of color sensibilites are useful in the design of manufactured goods and color therapy.

• Science of Emotion and Sensibility
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• v.6 no.2
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• pp.21-28
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• 2003

Tn the present study, 9 photographs from the International Affective Picture System (IAPS) judged to express best 2-dimensional sensibility were selected and used to stimulate the subjects. The goal of the study lay in verifying whether or not the consequent affective changes in the subjects can be discriminated psychologically and physiologically in terms of arousal and relaxation. In order to determine affective changes, the physiological signals of the subjects' autonomic nervous system were measured through electrocardiogram (ECG) , galvanic skin response (GSR), skin temperature, and respiration. After stimulation and measurement, subjective evaluation was conducted. Subjective evaluation revealed that affective arousal level could be classified into 4 consecutive stages: arousal 〉 unpleasant arousal, pleasant arousal 〉 comfort 〉 relaxation. Analysis revealed that the responses of the autonomic nervous system, too, could be classified into 3 consecutive stages: arousal, unpleasant arousal, pleasant arousal 〉 comfort 〉 relaxation. By selecting and using 9 photographs from the IAPS deemed best to express Koreans'2-dimensional sensibility, the present study confirmed that it is possible to discriminate changes in the subjects' affective arousal level in terms of arousal and relaxation through psychological and physiological evaluation.

• Science of Emotion and Sensibility
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• v.20 no.2
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• pp.161-170
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• 2017

Emotion affects many parts of human life such as learning ability, behavior and judgment. It is important to understand human nature. Emotion can only be inferred from facial expressions or gestures, what it actually is. In particular, emotion is difficult to classify not only because individuals feel differently about emotion but also because visually induced emotion does not sustain during whole testing period. To solve the problem, we acquired bio-signals and extracted features from those signals, which offer objective information about emotion stimulus. The emotion pattern classifier was composed of unsupervised learning algorithm with hidden nodes and feature vectors. Restricted Boltzmann machine (RBM) based on probability estimation was used in the unsupervised learning and maps emotion features to transformed dimensions. The emotion was characterized by non-linear classifiers with hidden nodes of a multi layer neural network, named deep belief network (DBN). The accuracy of DBN (about 94 %) was better than that of back-propagation neural network (about 40 %). The DBN showed good performance as the emotion pattern classifier.

• Journal of Navigation and Port Research
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• v.37 no.4
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• pp.401-407
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• 2013

In parallel with the development of ship equipment, bridge systems have been improved, but marine accidents due to human error have not been reduced. Recently, research in nautical bridge equipment has focused on suitable ergonomic designs in order to reduce these errors due to human factors. In a bridge of a ship, there are numerous auditory signals that deliver important information clearly to the sailors. However, only a few studies have been conducted related to the human recognition of these auditory signals. There are three types of auditory signals: voice alarms, abstract sounds, and auditory icons. This study was conducted in order to design more appropriate auditory icons using a sensibility evaluation method. The auditory icons were rated to have five warning situations (engine failure, fire, steering failure, low power, and collision) using the Semantic Differential Method. It is expected that the results of this study will be used as basic data for auditory displays inside bridges and for integrated bridge alarm systems.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.455-458
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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 no quantitative 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). Wavelet transformation was employed to analyze the EEG signals. Most positive and negative emotional response were compared in pairs. 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 positive and negative stimulus were found. This study could be extended to establish an algorithm which distinguishes psychophysiological states of the subjects exposed to the visual stimulation.

• Science of Emotion and Sensibility
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• v.20 no.4
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• pp.89-100
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• 2017

Since smart devices are able to efficiently provide information without barriers of time and location, they are widely utilized with advent of the hyper-connected society. Especially, the smart devices have been developed in the form of wearable devices for mutual interaction between human and objects. Smart clothing, which embeds smart devices within clothes, measures and obtains a variety of bio-signals as it is in close contact with the human bodies. Conventional smart clothing generated wearers' discomfort because they were developed by simple attachment of electronic devices to clothes. Therefore, it is highly recommended to develop novel smart clothing based on smart textiles which integrate electronic devices as parts of textiles. As smart watches are currently the most available wearable devices in the market, smart watch users were selected in this study, for the purpose of investigating core needs of wearable smart device users based on the user experience and user's sensibility. Qualitative research was performed through semi-structured interview in order to obtain detailed answers about user sensibility based on smart watch user experience. After the in-depth interview, the user's sensibility was categorized into four aspects; functional, aesthetic, social, and empirical. Sensibility adjectives and key words were assigned to each aspect and their frequency was analyzed. It was the functional aspect of sensibility that the wearable device users require the most. The results of this study will be utilized as a fundamental data to develop the smart textiles required for the next generation of smart clothing which is attracting as a future wearable device.