• 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.

• Journal of IKEEE
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• v.18 no.3
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• pp.368-375
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• 2014

Brain computer interface(BCI) technology has been continuously developed due to the continuous development of interface technology and the promotion of brain wave research. In this paper, we propose a driving habit management system by adopting BCI to transportation. The proposed system consists of the electroencephalogram(EEG) measuring unit, the EEG analysis unit, the memory section for storing the state information of drivers, the speed controller unit and the alarming section for generating warnings. Our proposed system can reduce the drowsy driving, improve the driving habits of users and help to prevent traffic accidents.

• Journal of the Ergonomics Society of Korea
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• v.32 no.5
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• pp.421-427
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• 2013

Objective: This paper is to analyze the impact of musical training to the fast ${\alpha}$ wave activation of the EEG. Background: EEG is neurological research method that can observe the brain function in real time. EEG can be used to determine the nervousness and relaxedness of a person who receives stimuli in a structured environment. Therefore, it is possible to interpret the functional state of human brain by the analysis of EEG. Method: The brain activities of two groups of university students in the point of RFA(Relative Fast Alpha) caused by different music are analyzed in this paper. One is the group of music majors and the other is the group of non-majors. Results: Music major and non-major groups show meaningful differences in RFA during exposed to classic and metal music. Conclusion: Learning experience on music affects RFA increment of music majors. Application: The result of this study will be used as basic data to evaluate the learning effects of students who want to study music.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.3
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• pp.1066-1070
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• 2010

This study was to examine the effectiveness of Neurofeedback training by observing the pre and post brain wave measurement results of about S kindergarten kids 40 (experimental group 20 comparative group 20) subjects who have shown resistance stress, in between the months of Jan. 2008 and Dec. 2008. As the brain waves are adjusted by time series linear analysis, the result confirmed the differences of both resistance stress. The result of the study suggest Neurofeedback technique's possibility in positively affecting the subjects' mental state.

• 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.

• Annals of Clinical Neurophysiology
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• v.21 no.1
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• pp.16-29
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• 2019

Background: Sex influences is important to understand behavioral manifestations in a large number of neuropsychiatric disorders. We found electrophysiological differences specifically related to the influence of sex on psychopathic traits. Methods: The resting electroencephalography (EEG) activity and low-resolution brain electromagnetic tomography (LORETA) for the EEG spectral bands were evaluated in 38 teenagers with conduct disorder (CD). The 25 male and 13 female subjects had psychopathic traits as diagnosed using the Antisocial Process Screening Device. All of the included adolescents were assessed using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) criteria. The visually inspected EEG characteristics and the use of frequency-domain quantitative analysis techniques are described. Results: Quantitative EEG (QEEG) analysis showed that the slow-wave activities in the right frontal and left central regions were higher and the alpha-band powers in the left central and bitemporal regions were lower in the male than the female psychopathic traits group. The current source density showed increases in paralimbic areas at 2.73 Hz and decreases in the frontoparietal area at 9.37 Hz in male psychopathics relative to female psychopathics. Conclusions: These findings indicate that QEEG analysis and techniques of source localization can reveal sex differences in brain electrical activity between teenagers with CD and psychopathic traits that are not obvious in visual inspections.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06a
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• pp.95-96
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• 1999

The authors have considered the 1/f fluctuation of vial rhythm with $1/f\beta$ spectrum of $\alpha$ wave in relation to the invigoration for the learning memory by paid their attention to the hippocampus protocol in this paper. At the first clinical experiment, the data of the remembrance test at short period is able to make as the foundation of the repeat memory. It can replace this memory with long period memory through the hippocampus by the superposition of the same memory-nerve circuits.

• Journal of Korean Physical Therapy Science
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• v.26 no.3
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• pp.1-7
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• 2019

Purpose: The purpose of this study was to investigate the effects of the Otago exercise combined with action observation training on changes of the brain activity of the elderly. Design: Randomized controlled trial. Methods: Thirty elderly women in the experiment were included. Participants were randomly assigned to the Otago combined with action observation training group, the Otago exercise group, and the control group (10 in each group). The Otago combined with action observation training group and the Otago exercise group performed the strength and balance exercises of the Otago exercise program for 50 minutes three times a week for 12 weeks. The Otago combined with action observation training group underwent additional action observation training for the Otago movement for 20 minutes three times a week. No intervention was performed in the control group. PolyG-1 (LAXTHA Inc., Daejeon, Korea) was used to measure the changes in the brain activity following intervention. One-way analysis of variance was used to compare the effects among the groups and a post-hoc test was performed. Results: The relative mu rhythms in the F3, C3, and C4 regions were significantly increased in the Otago combined with action observation training group. Relative beta wave activity in the Fp1, F3, F3, and C3 regions was significantly increased in the Otago combined with action observation training group (p<0.05). Conclusion: The results indicated that the Otago exercise combined with action observation training was effective for promoting the brain activity of the elderly.

• Science of Emotion and Sensibility
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• v.16 no.4
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• pp.481-492
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• 2013

This study sorted scores of individual characteristics and multiple intelligence by sex, handle, blood type and age through previous questionnaire with 462 adult males and females. Then electrode was attached to prefrontal lobes Fp1 and Fp2 with EEG measuring system and changes of concentration between no stimulation state and pure pink noise stimulation and their relations to multiple intelligence were examined. As a result of analysis of covariance, the mean concentration of all subjects was significantly higher in the pink noise stimulation compared to no stimulation. According to individual characteristics, concentration was significantly higher in left-hander, type A blood, and group in their thirties except for gender. Concentration in pink noise state strengthened the relation to spatial intelligence and made negative correlations with musical intelligence compared to no stimulation state. These results suggested that individual characteristics should be reflected on using pink noise for improving concentration.

• Journal of IKEEE
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• v.22 no.4
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• pp.1109-1114
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• 2018

Electroencephalogram (EEG) is a tool used to study brain activity caused by external stimuli. In this process, artifacts are mixed and it is easy to distort the signal, so post-processing is necessary to remove it. Independent Component Analysis (ICA) is a widely used method for removing artifact. This method has a disadvantage in that it has excellent performance but some loss of brain wave information. In this paper, we propose a method to reduce EEG information loss by restricting the filter coverage using eye blink information obtained from Eyetracker. We then compared the results of the proposed method with the conventional method using quantization methods such as Signal to Noise Ratio (SNR) and Spectral Coherence (SC).