• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.1
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• pp.22-29
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• 2003

The study was to evaluate psychological and physiological changes of simulator sickness in the controlled condition of driving a car (1 hr. at speed of 60 km/h) in a graphic simulator. Simulator sickness was measured and analyzed every 5 min using both subjective responses(i.e., Simulator Sickness Questionnaire) and Physiological signals(EEG, HRV, Skin Temperature, GSR). The results showed that there was significant differences in subjective response 10 min after the main experiment. From 10 min after the driving, the level of subjective simulator sickness increased significantly, relative one of the rest condition. There also was significant differences in physiological responses between the rest and the 5 min after from the start of driving : for EEG, $\delta$ and $\theta$ at Fz area increased, while $\alpha$ decreased; the averaged R-R interval and skin temperature decreased; LF/HF and GSR increased. The results indicated that simulator sickness was induced by activation of the autonomic nerves and inactivation of the central nerves.

• Electronics and Telecommunications Trends
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• v.38 no.5
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• pp.61-70
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• 2023

We investigated technological trends in an electrocardiogram (ECG)-based biometric cryptosystem that uses physiological features of ECG signals to provide personally identifiable cryptographic key generation and authentication services. The following technical details of the cryptosystem were investigated and analyzed: preprocessing of ECG signals, extraction of personally identifiable features, generation of quantified encryption keys from ECG signals, reproduction of ECG encryption keys under time-varying noise, and new security applications based on ECG signals. The cryptosystem can be used as a security technology to protect users from hacking, information leakage, and malfunctioning attacks in wearable/implantable medical devices, wireless body area networks, and mobile healthcare services.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.181-185
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• 2002

The purpose of this study was to find out the relationship between sleep physiological signals data and subjective feeling of sleep quality. Sixteen subjective were investigated and they slept on both comfortable mattress and uncomfortable mattress. Information of sleep stage is one of the most important clues for sleep quality. Polysomnography is basically the recording of sleep. The several channels of brain waves (EEG), eyes (EOG), chin movements (EMG) and heart (ECG) were monitored. Sixteen subjects spent 6 days and nights in the laboratory and the data of sleeping 7h for each of 3 nights was analyzed. Percentage of deep sleep (III and IV, sleep efficiency, WASO, stage 1 and subjective feeling of sleep quality were significantly affected with mattress types (comfortable and uncomfortable mattress). When subjects slept on comfortable beds, percentage of deep sleep and sleep efficiency were higher than those of uncomfortable bed. The percentages of wake after sleep onset and stage 1 were lower when subject slept in a comfortable bed. The subjective feeling of sleep quality agreed with the recorded sleep data also.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1998.04a
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• pp.171-175
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• 1998

This work presents an estimation for stress status using biosignal and fuzzy theory. Stress is estimated by 'coin-build' experiment with two type, relax and stress status. The estimator uses five biosignals, fuzzy logic to combine these signals and physiological knowledge. The system was tested in 10 records of healthy indivisuals and acheived a template of a stress progress. This work presents an estimation for stress status using biosignal and fuzzy theory. Stress is estimated by 'coin-build' experiment with two type, relax and stress status. The estimator uses five biosignals, fuzzy logic to combine these signals and physiological knowledge. The system was tested in 10 records of healthy indivisuals and acheived a template of a stress progress.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.3
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• pp.262-267
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• 2013

The recognition of human emotional state is one of the most important components for efficient human-human and human- computer interaction. In this paper, four emotions such as fear, disgust, joy, and neutral was a main problem of classifying emotion recognition and an approach of visual-stimuli for eliciting emotion based on physiological signals of skin conductance (SC), skin temperature (SKT), and blood volume pulse (BVP) was used to design the experiment. In order to reach the goal of solving this problem, half-against-half (HAH) multi-class support vector machine (SVM) with Gaussian radial basis function (RBF) kernel was proposed showing the effective techniques to improve the accuracy rate of emotion classification. The experimental results proved that the proposed was an efficient method for solving the emotion recognition problems with the accuracy rate of 90% of neutral, 86.67% of joy, 85% of disgust, and 80% of fear.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.985-987
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• 2010

In this paper, we propose a maximum entropy-based emotion recognition model using individual average difference. In order to accurately recognize an user' s emotion, the proposed model utilizes the difference between the average of the given input physiological signals and the average of each emotion state' signals rather than only the input signal. For the purpose of alleviating data sparse -ness, the proposed model substitutes two simple symbols such as +(positive number)/-(negative number) for every average difference value, and calculates the average of physiological signals based on a second rather than the longer total emotion response time. With the aim of easily constructing the model, it utilizes a simple average difference calculation technique and a maximum entropy model, one of well-known machine learning techniques.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.2
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• pp.14-25
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• 2001

• Journal of Korea Game Society
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• v.15 no.2
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• pp.105-114
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• 2015

We propose a real time user interface that utilizes emotion recognition by physiological signals. To improve the problem that was low accuracy of emotion recognition through the traditional EEG(ElectroEncephaloGram), We developed a physiological signals-based emotion recognition system mixing relative power spectrum values of theta/alpha/beta/gamma EEG waves and autonomic nerve signal ratio of ECG (ElectroCardioGram). We propose both a data map and weight value modification algorithm to recognize six emotions of happy, fear, sad, joy, anger, and hatred. The datamap that stores the user-specific probability value is created and the algorithm updates the weighting to improve the accuracy of emotion recognition corresponding to each EEG channel. Also, as we compared the results of the EEG/ECG bio-singal complex data and single data consisting of EEG, the accuracy went up 23.77%. The proposed interface system with high accuracy will be utillized as a useful interface for controlling the game spaces and smart spaces.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.177-180
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• 2002

The type of physiological stress involved in driving is probably complex, and a comprehensive study involving recording of physiological signals such as electrocardiogram(ECG), electromyogram(EMG). Changes in relevant Physiological parameters, such as ECG, EMG, reflected changes in driver status. In order to derive the mental and physical load of driving a motor vehicle from driving behaviour alone it is necessary to establish the relationship between changes in a driver's physiological parameters and behavioral parameters. In this study, we choose two different condition and investigated driver's status using HRV analysis method. Many previous studies have shown that increasing driving time causes a variation of HRV signal.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.8
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• pp.172-180
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• 1994

Implantable biotelemetry systems are indispensable tools not only in animal research but also in clinical medicine as such systems enable the acquisition of otherwise unavailable physiological data. We present the manufacture of CMOS IC and its system for implantable multichannel biotelemeter system. The internal circuits of this system are designed not only to achieve as multiple functions and low power dissipation as possible but also to enable continuous measurement of physiological data. Its main functions are to enable continuous measurement of physiological data and to accomplish on-off power swiching of an implantable battery by receiving appropriate commanc signals from an external circuit. The implantable circuits of this system are designed and fabricated on a single silicon chip using $1.5\mu$m n-well CMOS process technology. The total power dissipation of implantable circuits for a continuous operation was 6.7mW and for a stand-by operation was 15.2$\mu$ W. This system used together with approriate sensors is expected to contribute to clinical medicine telemetry system of measuring and wireless transmitting such significant physiological parameters as pressure pH and temperature.