• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.387-393
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• 2016

The aim of this study is to analyze the effectiveness of QEEG-based neurofeedback clinical tests on patients diagnosed with anxiety disorder. Researchers tested six patients with anxiety disorder using 32-channel QEEG(Quantitative electroencephalograpy) and neurofeedback training equipment. The study measured anxiety levels of patients using QEEG and BAI physiological psychology tests. Test results found hyperactive beta waves present in all six patients' temporal lobe. The intensity of the wave of the right hemisphere temporal lobe T4(M=31.07) was the higher than that of the left hemisphere temporal lobe 3(M=29.11). Following Neurofeedback training, the beta wave of the right hemisphere lobe was reduced significantly in all patients. The average anxiety level decreased from 23.57 to 12.14 after the neurofeedback training. In addition, among the two patients who were taking medication, one patient reduced his dosage while the other patient discontinued taking medication. This result implies that the QEEG neurofeedback training technique can be effectively applied to patients with anxiety disorder.

• Journal of Biomedical Engineering Research
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• v.20 no.6
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• pp.555-560
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• 1999

간질은 신경세포의 일부가 짧은 시간동안 과도한 전기를 발생시킴으로써 일어나는 신경계의 발작적 증상으로 배경 활동파와는 구별되는 극파, 예파, 예파와 서파를 동반한 극서파 복합(sharp and slow complexes)의 뇌파 특징파를 갖는다. 장시간의 뇌파기록에서 시간의 절약과, 정량화를 위해 컴퓨터를 이용한 간질 파형의 자동 검출은 객관성을 높이고 정량적인 해석을 위해 필수적이다. 본 연구에서는 간질 뇌파를 검출하기 위해 웨이브렛 변환과 신경망을 사용하였다. 웨이브렛 변환은 잡음을 제거하고 간질 뇌파의 특징을 강조하며 신경망의 입력노드수를 줄였다. 전문가에 의해서 분류된 간질특성과 정상뇌파를 신경망에 입력시켜 최적의 신경망구조를 선택하였고, 검출 문턱치를 설정하였다. 신경망은 200ms(26개의 데이터포인트)신호의 웨이브렛 결과와 웨이브렛 변환후 데이터 상의 최대, 최소 기울기가 입력되어 전체 28개의 입력 노드로 구성하였다. 은닉층은 18노드, 문턱치값은 민감도와 선택도가 일치하는 0.65가 사용되었다. 결과로 임상 환자 데이터에 입력되어 78.54% 의 검출률을 보였다.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3227-3229
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• 2000

본 논문은 청각 자극이 제시되었을 때 변화되는 뇌파로부터 의미 있는 특징을 찾아내서 정량화 할 수 있는 변수 추출 및 분류 기법을 제시한다. 건강한 피실험자로부터 방향성 있는 청각 자극을 인가했을 때의 뇌파를 검출, 분류하였다. 뇌파의 변수 추출 방법으로는 짧은 시간영역에서의 신호의 갑작스런 변화량도 정량적으로 분석할 수 있는 Mallat's A1gorithm을 이용한 웨이블릿 변환(wavelet transform)을 적용하였고, 분류 방법으로는 그 결과로 나온 웨이블릿 계수를 변수로 하여 Neural Network을 학습하여 사용하였다. 향후 피실험자의 훈련을 통해서 청각 자극이 없이 순수한 생각만으로 방향을 검출할 수 있는 뇌파분석기를 만든다면 생각만으로도 물체의 방향을 제어할 수 있을 것이다.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.6
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• pp.729-738
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• 2019

Recently, we aim to improve the quality of virtual reality contents based on quantitative analysis results of emotions through combination of emotional recognition field and virtual reality field. Emotions are analyzed based on the participant's vital signs. Much research has been done in terms of signal analysis, but the methodology for quantifying emotions has not been fully discussed. In this paper, we propose a normalization function design and expression method to quantify the emotion between various bio - signals. Use the Brute force algorithm to find the optimal parameters of the normalization function and improve the confidence score of the parameters found using the true and false scores defined in this paper. As a result, it is possible to automate the parameter determination of the bio-signal normalization function depending on the experience, and the emotion can be analyzed quantitatively based on this.

• Journal of the Korean Data and Information Science Society
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• v.20 no.3
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• pp.541-550
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• 2009

This research attempted to find out any implications for strategies to design and develop the connections between the activities of the brain function and the fields of English learning (dictation, word level, speaking, word memory, listening). Thus, in developing the brain based learning model for the English education, attempts need to be made to help learners to keep the whole brain toward learning. On this point, this study indicated the significant results for the exclusive brain location and the brainwaves on the each English learning field by the quantitative EEG analysis. The results of this study presented the guidelines for the balanced development of the left brain and the right brain to train the specific site of the brain connected to the English learning fields. In addition, whole brain training model is developed by the quantitative EEG data not by the theoretical learning methods focused on the right brain training.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.05a
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• pp.26-31
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• 2001

긍/부정 선택 실험에서 나타나는 뇌파 변화를 연구하였다. 서로 다른 위치에서 측정된 뇌파의 시공간적 상호관계를 정량화하는 변수로, 시간영역에서 계산하기 용이한 동기율(synchronization rate), 편향성(synchronization rate), 편향성(polarity), 상호상관(cross-correlation) 등의 변수를 도입하여, 긍/부정 선택 순간의 뇌파 변화를 살펴보았다. 좌우 전전두엽(Fp1, Fp2)에서 특정된 뇌파를 사용하여 계산한 동기율, 편향성의 평균과 요동폭, 상호상관 등은, 선택 순간 근처에서, 평상시에 뇌파와 통계적으로 유의미한 차이를 보였다.

• Korean Journal of Psychosomatic Medicine
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• v.25 no.1
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• pp.63-72
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• 2017

Objectives : Attention-deficit hyperactivity disorder(ADHD) is characterized by significant impairments in executive functions, with a prevalence of approximately 3-5% of all children worldwide. The goal of this study was to examine the relationship between executive functions and electrophysiological activities in children and adolescents with ADHD. Methods : In 31 patients with ADHD, resting-state EEG was recorded, and Comprehensive Attention Test(CAT), Stroop Color-Word Inference Test(Stroop CWIT), Trail Making Test(TMT), and Wisconsin Card Sorting Test(CST) were administered. Korean version of the ADHD Rating Scale(K-ARS) was assessed. Results : Alpha and beta power positively correlated with the Attention Quotient(AQ), while delta power negatively correlated with AQ from CAT. In the Stroop CWIT, decreased delta power and increased beta power were related to higher performance. Power of the alpha band increased with higher TMT performance. Moreover, delta power negatively correlated with good performance on the CST, while alpha and high gamma band showed a positive correlation. Correlation with the parent-rating of ADHD symptoms showed a negative correlation between alpha power and higher scores on the K-ARS. Conclusions : These findings indicate that relative power in higher frequency bands of EEG is related to the higher executive function in children and adolescents with ADHD, while the association with the relative power in lower frequency bands of EEG seem to be vice versa. Furthermore, the findings suggest that QEEG may be a useful adjunctive tool in assessing patients with ADHD.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.81-85
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• 2000

EEG(electroencephalogram)는 주로 전문가의 판독에 따른 주관적 판단에 의존하여 임상에서 사용되어져 왔다. 그러나 비선형 동역학 분석을 이용한 해석학적인 정량화 연구가 진행 되어짐에 따라 특이 패턴을 이용한 환자의 질병진단 이외에도 정상인의 뇌 활동 및 인지기능 둥을 이해하기 위한 도구로써 그 활용범위가 넓어지고 있다. 본 논문에서는 정상인에게 다양한 자극을 준 후 측정한 EEG를 상관차원 분석법을 이용하여 다양한 자극에 대한 뇌파의 특징을 분석하였다. 그 결과 각 자극에 따른 뇌 활동도의 차이를 정량적으로 분석할 수 있었으며, 뇌 활동 부위와 자극과의 관계도 정량적으로 분석할 수 있었다.

• Korean Journal of Biological Psychiatry
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• v.3 no.2
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• pp.216-221
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• 1996

The quantitative EEGs of obsessive-compulsive disorder patients were analyzed using spectral analysis and compared to age and sex-matched controls. The subjects were 19 patients(men=15, women=4) suffering from obsessive-compulsive disorder(DSM-III-R). Absolute power, relative power and interhemispheric asymmetry of EEG were used to compare obsessive-compulsive disorder patients with controls. In order to fit the EEG data to a normal distribution, a log transformation of power values of every bandwidth in each deviation was calculated prior statistical analysis. The Wilcoxon rank test was performed to compare obsessive-compulsive group to the control group. In obsessive-compulsive disorder, abnormalities of quantitative EEGs are prominent in fronto-central. These results ore compatible with other brain imaging studies of obsessive-compulsive disorder and suggested that fronto-central area plays an important role in the pathophysiology of obsessive-compulsive disorder.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.644-652
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• 2017

The purpose of this study was to analyze the EEG according to the elderly's tendency to be addicted to smartphone games. We compared the effects of smartphone addiction on mental health such as brain waves, sleep problems and depression through comparative analysis of asymmetry and connectivity in quantitative EEG results. The study participants were two elderly people who were addicted to smartphone game and one elderly person who did not use smartphone (Ed- to confirm: only 3 participants?!). The participant's addiction tendency of smartphone was measured by using the smartphone addiction scale and EEG (QEEG) was used for EEG analysis. The results are as follows. First, the brain waves of elderly people and smartphone non-user elderly who showed symptoms of immersion and smartphone game showed a difference in asymmetry in both opening and closing anisles. Second, there were significant differences in the openness and the anxiety of the elderly who were immersed in the mobile phone and the elderly who did not use the smartphone. Through this, it is also meaningful to explore the relationship between senile cognitive impairment and smartphone use by exploring the effect of smartphone game use on brain cognitive function through comparison of EEG analysis.