• The Journal of the Korea Contents Association
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• v.11 no.6
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• pp.26-32
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• 2011

Recently, in the U-health area, there are research related on monitoring brainwaves in real-time for coping with emergent situations like the fatigue driving, cerebral infarction or the heart attack of not only the patients but also the normal elderly folks by transmitting of the EEG(Electroencephalograph). This system could be applied to hospitals or sanatoriums. In this paper, it is applied for the vehicular ad-hoc network to prevent the car accident in advance by monitoring the brainwaves of a driver in real-time. In order to do this, I used mobile ad-hoc nodes supported in the Opnet simulator for the efficient EEG brainwave transmission in the VANET environment. The vehicular ad-hoc networks transmitting the brainwaves to the nearest road-side unit are designed and simulated to draw an efficient and proper vehicular ad-hoc network environment.

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.162-165
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• 2009

본 논문에서는 뇌-컴퓨터 인터페이스(Brain-Computer Interface) 기술을 중 움직임과 관련된 EEG(Electroencephalograph)신호를 이용하여 한국어를 생성하기 위한 시스템 설계 방법을 제안한다. 뇌-컴퓨터 인터페이스의 정보변환율(Information Transfer Rate)향상을 위하여 바이오피드백 방법과 기계학습 방법을 동시에 적용시킬 수 있는 방법과 움직임 관련 SMR(Sensorimotor Rhythm)과 한국어 음절, 어절 예측을 기술을 사용하여 ALS환자 혹은 운동능력이 없는 사람들을 위한 한국어 생성을 위한 설계 방법에 대해서 연구하였다.

• Biomedical Science Letters
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• v.5 no.2
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• pp.167-179
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• 1999

There are considerable interests in bat biology for investigating hibernation mechanism, in special regard to a hypothesis that the entry into hibernation is closely related with epileptic fit (petit mal) accompanying falling of body temperature, which is characterized by 3 spikes and wave/sec formation in electroencephalograph (EEG). This study was designed in order to examine physiological parameters (body temperature, heart rate, electroencephalograph and brain mapping) during normal patterns of the entry into hibernation and the hibernation period, and to observe effects of epileptogenic agents such as THC, Metrazol, and ILS on the physiological parameters. Based on the experimental results the entry into some hibernation seems to be related with epileptic fit, and therefore it is deduced that north temperate bats and the hamsters might be induced into hibernation by epileptogenic factors (pentylenetetrazol, THC and ILS etc) accompanying falling of body temperature and unique EEG and brain mapping.

• Physical Therapy Korea
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• v.15 no.4
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• pp.70-79
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• 2008

The purpose of this study was to find out the effects of electroencephalograph (EEG) power and coherence on cognitive function in normal elderly, non-demented elderly with mild cognitive impairment, and demented elderly during working cognition tasks. Forty elderly women (19 demented elderly, 10 non-demented elderly with mild cognitive impairment, 11 norma1 elderly) participated in this study, All subjects performed working cognition tasks with Raven's CPM while EEG signal was recorded, EEGs were measured continuously at rest and during the working cognition task. EEG power and coherence was computed over 21 channels: right and left frontal, central, parietal, temporal and occipital region. We found that there were more correct answers among normal elderly women than in other groups Owing the working cognition task, ${\Theta}$ wave at Fp1, Fp2 and F8, a wave at Fp2, ${\beta}$ wave at Fp1, Fp2. F4 and F8 of the frontal region was increased significantly in the demented elderly group. On the other hand. ${\Theta}$ wave at Fp1, Fp2 and F7, ${\beta}$ wave at Fp1, Fp2, F3 and F7 of the frontal region was increased significantly in the group of non-demented elderly with mild cognitive impairment. In contrast. in the normal elderly group, all of the ${\Theta}$ wave and ${\beta}$ wave at Fp1, Fp2, F3, F4, F7 and F8 of the frontal region (except ${\beta}$ wave at F3) was increased significantly, These results suggest that the nerves in prefrontal and right hemisphere regions were most active in the demented elderly group during problem solving, and the nerves in the prefrontal and left hemisphere lobe were most active in the group of non-demented elderly with mild cognitive impairment. In contrast, me majority of nerves in the frontal region were active in the normal elderly group.

• Journal of Biomedical Engineering Research
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• v.29 no.1
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• pp.17-24
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• 2008

The aim of this paper is to report our preliminary results of investigating the spatial focalization of Zen-meditation EEG (electroencephalograph) in alpha band (8-13 Hz). For comparison, the study involved two groups of subjects, practitioners (experimental group) and non-practitioners (control group). To extract EEG alpha rhythm, wavelet analysis was applied to multi-channel EEG signals. Normalized alpha-power vectors were then constructed from spatial distribution of alpha powers, that were classified by Fuzzy C-means based algorithm to explore various brain spatial characteristics during meditation (or, at rest). Optimal number of clusters was determined by correlation coefficients of the membership-value vectors of each cluster center. Our results show that, in the experimental group, the incidence of frontal alpha activity varied in accordance with the meditation stage. The results demonstrated three different spatiotemporal modules consisting with three distinctive meditation stages normally recognized by meditation practitioners. The frontal alpha activity in two groups decreased in different ways. Particularly, monotonic decline was observed in the control group, and the experimental group showed increasing results. The phenomenon might imply various mechanisms employed by meditation and relaxation in modulating parietal alpha.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.294-297
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• 1996

This paper proposes the method to recognize of time series data based on the chaotic feature extraction. Features extract from time series data using the chaotic time series data analysis and the pattern recognition process is using a neural network classifier. In experiment, EEG(electroencephalograph) signals are extracted features by correlation dimension and Lyapunov experiments, and these features are classified by multilayer perceptron neural networks. Proposed chaotic feature extraction enhances recognition results from chaotic time series data.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.7 no.4
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• pp.353-362
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• 1996

In this paper, SAR distribution is calculated according to the rabbit's head using approximation of its medium three layers model. Our experiment was classified 5 groups dependent on the power intensity of 2,450MHz microwave to measure EEG(Electroencephalograph) of rabbit, which was checked in left frontal lobe before and after irradiation of microwave. In results, mean total power of EEG was slightly decreased and mean composition percentages of $\theta$, $\delta$ and $\beta$ wave were increased after irradiation in observation. It means to decrease of elect- rophysiologic activity and trend of fast wave in brain after irradiation of its microwave. We analyzed the electrophysiological effect of the biobody quantitatively using measured EEG and estimated MPE (Maximum Permissible Exposure).

• Journal of KIISE:Software and Applications
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• v.27 no.1
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• pp.24-32
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• 2000

BCI(Brain-Computer Interface) is studied to control the machines with brain. In this study, an EEG(Electroencephalography) signal classification model is proposed. The model gets EEG pattern from each subject's brain and extracts characteristic features. The model discriminates the EEG patterns by using those extracted characteristic features of each subject. The proposed method classifies each pair of the given tasks and combines the results to give the final result. Four tasks such as rest, movement, mental-arithmetic calculation and point-fixing were used in the experiment. Over 90% of the trials, the model yielded successful results. The model exploits characteristic features of the subjects and the weight table that was produced after training. The analysis results of the model such as its high success rates and short processing time show that it can be used in a real-time brain-computer interface system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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• pp.104-112
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• 2001

Simply, Nonlinear dynamics theory means the complicated and noise-like phenomena originated form nonlinearity involved in deterministic dynamical system. An almost all the natural signals have nonlinear property. However, there exist few analysis software tool or package for a research and development of applications. We develop nonlinear time series analysis simulator is to provide a common and useful tool for this purpose and to promote research and development of nonlinear dynamics theory. This simulator is consists of the following four modules such as generation module, preprocessing module, analysis module and ICA module. In this paper, we applied to Electroencephalograph (EEG), as it turned out, our simulator is able to analyze nonlinear time series. Besides, we could get the useful results using the various parameters. These results are used to diagnostic the brain diseases.

• Korean Journal of Acupuncture
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• v.30 no.4
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• pp.305-318
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• 2013

Objectives : The aim of this study was to examine the effect of electroacupuncture(EA) at an acupoint, HT8(Sobu), on normal humans by using power spectral analysis. We examined the effect on the Heart Rate Variability(HRV), and the balance of the autonomic nervous system. Methods : Thirty-two healthy volunteers participated in this study. EEG(Electroencephalogram) power spectrum exhibits site-specific and state-related differences in specific frequency bands. A thirty-two channel EEG study was carried out on thirty-two subjects(14 males; mean age=23.5 years old, 18 females; mean age=21.5 years old). HRV and EEG were simultaneously recorded before and after acupuncture. Results : In the ${\alpha}$(alpha) band, during the HT8-acupoint treatment, the power values in the ${\alpha}$(alpha) band significantly decreased(p<0.05) at 28 channels. In the ${\beta}$(beta) band significantly decreased(p<0.05) at 26 channels. In ${\delta}$(delta) band significantly decreased(p<0.05) at 18 channels. In ${\theta}$(theta) band significantly decreased(p<0.05) at 20 channels. ${\alpha}/{\beta}$ values were increased at 6 channels and decreased at 10 channels.${\beta}/{\theta}$ values were increased at 10 channels and decreased at 19 channels. Mean-RR(RR-interval), Complexity, RMSSD(Root mean square of successive differences), SDSD(Standard deviations differences between adjacent normal R-R intervals), norm HF showed a significantly increased and mean-HRV, norm LF, LHR(LF/HF Ratio) showed a significantly decreased after HT8-acupoint treatment(p<0.05). Conclusions : These results suggest that EA at the HT8 mostly causes significant changes on alpha(28 channels), beta(26 channels), delta(18 channels), theta(20 channels) bands and mean-HRV, mean-RR, complexity, RMSSD, SDSD, norm LF, norm HF and LHR. If practicing EA at the HT8, it will regulate the function of the cerebral cortex, decrease activity of the sympathetic and increase parasympathetic nervous activity.