• Korean Journal of Biological Psychiatry
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• v.4 no.1
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• pp.67-73
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• 1997

The changes of electroencephalogram(EEG) in patients with dementia are most commonly studied by analyzing power or magnitude in certain traditionally defined frequency bands. However because of the absence of an identified metric which quantifies the complex amount of information, there are many limitations in using such a linear method. According to chaos theory, irregular signals of EEG can also result from low dimensional deterministic chaos. Chaotic nonlinear dynamics in the EEG can be studied by calculating the correlation dimension. The authors have analyzed EEG epochs from three patients with dementia of Alzheimer type and three matched control subjects. The multichannel correlation dimension is calculated from EEG epochs consisting of 15 channels with 16,384 data points per channel. The results showed that patients with dementia of Alzheimer type had significantly lower correlation dimension than non-demented controls on 12 channels. Topographic analysis showed that the correlation dimensions were significantly lower in patients with Alzheimer's disease on frontal, temporal, central, and occipital head regions. These results show that brains of patients with dementia of Alzheimer type have a decreased complexity of electrophysiological behavior. We conclude that the nonlinear analysis such as calculating correlation dimension can be a promising tool for detecting relative changes in the complexity of brain dynamics.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.103-108
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• 2016

In daily life, humans get stress very often. Stress is one of the important factors of healthy life and closely related to the quality of life. Too much stress is known to cause hormone imbalance of our body, and it is observed by the brain and bio signals. Based on this, the relationship between brain signal and stress is explored, and brain signal based stress index is proposed in our work. In this study, an EEG measurement device with 32 channels is adopted. However, only two channels (FP1, FP2) are used to this study considering the applicability of the proposed method in real enveironment, and to compare it with the commercial 2 channel EEG device. Frequency domain features are power of each frequency bands, subtraction, addition, or division by each frequency bands. Features in time domain are hurst exponent, correlation dimension, lyapunov exponent, etc. Total 6 subjects are participated in this experiment with English sentence reading task given. Among several candidate features, ${\frac{{\theta}\;power}{mid\;{\beta}\;power}}$ shows the best test performance (70.8%). For future work, we will confirm the results is consistent in low price EEG device.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.35-46
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• 2002

The EEG is a time series of electrical potentials representing the sum of a very large number of neuronal dendrite potentials in the brain. The collective dynamic behavior of neural mass of different brain structures can be assessed from EEG with depth electrodes measurements at regular time intervals. In recent years, the theory of nonlinear dynamics has developed methods for quantitative analysis of brain function. In this paper, we considered it is reasonable or not for ICA apply to EEG analysis. Then we applied ICA to EEG for big toe movement and separated the independent components for 15 samples. The strength of each independent component can be represented on the topological map. We represented ICA can be applied for time and spatial analysis of EEG.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2177-2178
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• 2006

학습 행동에서의 뇌파 측정은 실시간으로 두뇌 기능 상태를 연구하는데 유용한 연구 방법이며 대뇌의 부위 중 전두엽은 새로움에 대한 지향 반응과 사고 활동에 중요한 역할을 한다. 본 연구에서는 중학교 2학년 학생에게 새로운 시청각 학습 자료를 제시하고 5회의 반복학습이 이루어지는 과정에서의 전두부($Fp_2,Fp_2$)의 뇌파를 측정하고 Fourier, Wavelet 변환을 하여 정량적으로 분석하였다. 주의 집중, 정서 등 인지와 관련지어 특정파의 조절 능력 및 파의 특성을 이용한 여러 연구들을 종합해보면, 기억력, 주의지속과 연관되어 알파파, 베타파와 세타파가 발생되는 것을 볼 수 있다. 이 중 알파파는 기존의 뇌 상태를 동기화시키고 주의나 기억의 과정에 영향을 미칠 수 있는 것으로 증명되었다. 본 논문에서는 신호 처리에 높은 효율을 보이는 Wavelet 변환을 이용하여, 학습이 됨에 따라 변화하는 EEG 신호 가운데 알파파의 패턴과 활성도를 분석하고자 한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.536-547
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• 2020

This study analyzed the correlation between adolescents' smartphone addiction as well as depression, self-esteem, and self-regulation based on QEEG (Quantitative Electroencephalogram) analysis. The study period was from March 19 to July 12, 2019, and the subjects were 76 students at P Middle School in Gyeonggi-do (normal group 47, risk group 29) who filled out a questionnaire and were subjected to quantitative EEG. The data analysis was performed via frequency analysis, independent t-test, correlation analysis, and path analysis of the IBM SPSS Statics 21.0 program. First, smartphone addiction had a positive correlation with depression. Second, smartphone addiction showed a negative correlation with self-esteem and α wave. Third, depression showed a negative correlation with self-esteem, which did not show a significant correlation with self-regulation. Fourth, depression was higher in the risk group than the normal group. For self-esteem, the normal group scored higher than the risk group. Self-regulation showed higher significant differences with the normal group than the risk group. Fifth, for α wave and SMR, the normal group scored higher than the risk group. Sixth, α waves had a negative effect on smartphone addiction. This study is meaningful in that it applied a brain science approach using quantitative analysis for objective evaluation of smartphone addiction.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1997.11a
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• pp.199-204
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• 1997

뇌전위에서 개인차가 없는 일반적인 규칙을 지닌 두 개의 정보 변수, 즉 ILF와 LHF 를 발견하였다. 이러한 일반성을 지닌 정보 변수가 청각, 후각, 촉각 자극에 의해 유발된 쾌하거나 불쾌한 감성 상태를 구분할 수 있으며 전두엽에서 그 경향이 두드러짐을 확인하였다. 전두엽의 뇌전위에서 감성 자극이 주어지기전과 자극이 주어지는 동안의 ILF, IHF값을 정규화함으로써 새로운 변수, Relative Quantified Emotional State(RQES)을 구현하였다. RQES는 쾌, 중립, 불쾌한감성의 정도를 선형적으로 정량화하였다. 따라서 하나의 전극으로 측정한 전두엽부분의 뇌전위로부터RQES 값을 계산하면 인간의 쾌, 불쾌 감성을 신뢰도있게 정량화 할 수 있다.

• Science of Emotion and Sensibility
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• v.12 no.2
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• pp.205-214
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• 2009

This paper addresses analyzing affective color data for emotional interior design. Both the physical and psychological patterns for spatial colors were tested on thirty subjects, of which fifteen were male. All subjects participated in both the physiological and psychological experiments. The data on the reflecting subjects' affective moods is gathered through EEG physical experiments and SD (Semantic Differential Scale) method surveys. This research has suggested the relation of both experiments through affective color response. The methods of SPSS 10.0 and TeleScan Version 2 are used for analyzing response data to coordinate the colour palette with changeable moods. From the analysis of statistical data, all of the visual stimuli related emotional keywords and physiological responses. Finally, the initial goal of this research is to construct an affective colour database that is tested through human color perception by physical and psychological experiments.

• The Korean Journal of Pharmacology
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• v.32 no.3
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• pp.293-300
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• 1996

During the development of hepatic encephalopathy after thioacetamide (TAA) injection to rat, EEG was recorded at two different states: without or with tactile stimulation of tail at regular intervals. Calculations based on the spectral and band analysis were used. The changes in the power spectra and bands were examined in 3 different behavioral stages: normal, mild ataxia and severe ataxia. In normal rats, the stimulation produced the increase in the power of the theta $(3.5{\sim}8\;Hz)$ and the gamma $(30{\sim}50\;Hz)$ bands. These changes could not be produced in rats with the mild and severe ataxia. The changes in the power of the theta band occurred earlier than those of the beta3 and the gamma bands in the stimulated state. Gradual decreases in the spectral power of the beta3 $(21{\sim}30\;Hz)$ and the gamma bands were correlated with the progress of the stages from normal condition to mild to severe ataxia in both unstimulated and stimulated states. The results indicate that the spectral and band analysis used in this study can quantify the severity of the neurological malfunction during HE.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.585-594
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• 2021

This Quasi-experimental study was started under the assumption that the stress of students who participated in Buddhism and Mind Healing Lectures based on an understanding of the scriptures will be relieved through the lectures, thereby enhancing their psychological stability, thinking ability, and enhancing understanding. Stress can be confirmed through a self-report test, but in this study, quantitative EEG was measured to evaluate the stress level and secure objectivity. To this end, the difference between the 1st week as pre and 15th week as post quantitative EEG was verified for the experimental group taking the Buddhism and Mind Healing Lecture held from March to June 2019 at S University in G-gu, Seoul, and the control group who did not. The Mann Whitney U test and Wilcoxon code ranking test were used as analysis methods because the number of subjects was 14. As a result, there was a significant difference in the beta wave (F7, T3, 4, T5) and the high beta wave (F7, F8, T3, T4) in the experimental group. The coherence was also improved, while there was no significant difference in the control group. Buddhism and Mind Healing Lectures improved stress.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.11
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• pp.265-272
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• 2020

In the research of brain computer interface (BCI) technology, one of the big problems encountered is how to deal with some people as called the BCI-illiteracy group who could not control the BCI system. To approach this problem efficiently, we investigated a kind of spectral EEG characteristics in the prior resting state in association with BCI performance in the following BCI tasks. First, spectral powers of EEG signals in the resting state with both eyes-open and eyes-closed conditions were respectively extracted. Second, a convolution neural network (CNN) based binary classifier discriminated the binary motor imagery intention in the BCI task. Both the linear correlation and binary prediction methods confirmed that the spectral EEG characteristics in the prior resting state were highly related to the BCI performance in the following BCI task. Linear regression analysis demonstrated that the relative ratio of the 13 Hz below and above the spectral power in the resting state with only eyes-open, not eyes-closed condition, were significantly correlated with the quantified metrics of the BCI performance (r=0.544). A binary classifier based on the linear regression with L1 regularization method was able to discriminate the high-performance group and low-performance group in the following BCI task by using the spectral-based EEG features in the precedent resting state (AUC=0.817). These results strongly support that the spectral EEG characteristics in the frontal regions during the resting state with eyes-open condition should be used as a good predictor of the following BCI task performance.