• 대한물리치료과학회지
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• 제15권3호
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• pp.9-17
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• 2008

Background : The conventional electroencephalography(EEG) is commonly used as aid in the diagnosis of dementia. Recently developed quantitative electroencephalography(qEEG) provides data that are not achievable by conventional EEG. The aim of this study was to find out the usefulness of quantified-EEG in dementia. Method : Twenty elderly women(10 normal elderly, 10 demented elderly) were participated in this study. EEG power and coherence was computed over 21 channels; right and left frontal, central, parietal, temporal and occipital areas. Result : The activity of ${\alpha}$ wave was more higher than others significantly at frontal and parietal areas in normal elderly, but the activity of ${\theta}$ wave was higher in demented elderly. And the activity of ${\theta}$ wave in demented elderly women was more higher than normal elderly women significantly. Conclusion : In conclusion, we discovered that quantitative EEG was used to diagnose dementia.

• 대한임상검사과학회지
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• 제51권4호
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• pp.397-405
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• 2019

정량적 뇌파는 연구와 임상적 분야에서 활발하게 이용되어 다양한 임상적 증상과 인지기능의 자극 및 과제에 따른 대뇌의 생물학적인 바이오 마커를 규명하는 등 대뇌의 변화를 객관적으로 증명하는데 지속적으로 사용되고 있다. 뇌파에서 정량적 분석과 정성적 분석은 분석하는 방법이 다르기 때문에 측정 방법과 환경이 비슷하지만 한편으론 다르다. 정성적 분석은 뇌파를 판독하는 사람이 잡파를 제외시키고 볼 수 있지만 정량적 분석은 수학적 모델링을 기반으로 데이터의 모든 것을 포함하여 분석을 실시하고 있기 때문에 잡파가 결과에 영향을 준다. 병원에서 임상생리학적 검사인 뇌파를 담당하는 임상병리사들이 뇌파를 이용한 연구는 다른 분야에 비해서 아주 드물다. 이러한 현상은 임상검사과학 분야 중에 임상생리학적 검사에서 두드러지게 나타난다. 왜냐하면 현재 대학에서 임상생리학을 연구하는 실험실이 많지 않기 때문이다. 본 저자의 목적은 정량적 분석을 하고자 하는 임상병리사, 대학원생, 연구자들이 쉽게 접근하여 앞으로 뇌파의 많은 연구가 이루어 질 수 있는 기초자료로 활용되기를 기대하고, 앞으로 많은 대학에서 임상생리학 실험실이 생겨 많은 연구들이 이루어져 좋은 논문들이 많이 나오기를 기대해 본다.

• 한국임상수의학회지
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• 제23권1호
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• pp.31-35
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• 2006

본 연구는 건강한 12마리의 슈나우져견에서 정량적 뇌파검사를 이용하여 진정을 평가한 것이다. 뇌파검사는 뇌나 행동의 변화와 관련된 중추신경계의 변화를 객관적으로 측정하는 데 사용이 된다. 특히 정량적 뇌파검사 방법인 spectral edge frequency 95 (SEF 95)는 진정의 상태를 평가하는 효과적인 방법이다. 본 실험에서 뇌파 전극은 8곳의 각각 다른 부위의 피하에 장착 하였으며 뇌파의 원래 파형과 SEF 95로 변환된 수치를 획득하여 분석하였다. 기전이 다른 5종의 진정제를 투여 한 후 측정된 모든 실험군의 SEF 95 값이 진정제 투여 전 상태와 비교하였을 때, 유의적으로 감소한다는 것을 확인하였다. 이상의 결과로 SEF 95의 정량적인 뇌파검사는 개에서 진정 상태를 평가하는 효과적인 방법이라고 생각된다.

• Annals of Clinical Neurophysiology
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• 제22권2호
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• pp.82-91
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• 2020

Electroencephalography (EEG) produces time-series data of neural oscillations in the brain, and is one of the most commonly used methods for investigating both normal brain functions and brain disorders. Quantitative EEG analysis enables identification of frequencies and brain activity that are activated or impaired. With studies on the structural and functional networks of the brain, the concept of the brain as a complex network has been fundamental to understand normal brain functions and the pathophysiology of various neurological disorders. Functional connectivity is a measure of neural synchrony in the brain network that refers to the statistical interdependency between neural oscillations over time. In this review, we first discuss the basic methods of EEG analysis, including preprocessing, spectral analysis, and functional-connectivity and graph-theory measures. We then review previous EEG studies of brain network characterization in several neurological disorders, including epilepsy, Alzheimer's disease, dementia with Lewy bodies, and idiopathic rapid eye movement sleep behavior disorder. Identifying the EEG-based network characteristics might improve the understanding of disease processes and aid the development of novel therapeutic approaches for various neurological disorders.

• 한국직업건강간호학회지
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• 제30권3호
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• pp.101-109
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• 2021

Purpose: This study aimed to measure COVID-19 stress and the quantitative electroencephalography (QEEG) stress quotient and identify the coping styles of face-to-face service industry employees during the COVID-19 pandemic. Methods: This cross-sectional study administered structured questionnaires consisting of sections on general characteristics, COVID-19 stress, and coping style for stress to 21 face-to-face service industry employees between April 1 and April 18, 2021. The physical tension & stress quotient and psychological distraction & stress quotient were measured in the prefrontal lobe with QEEG. Results: Emotional easiness (r=.62, p=.002) and escape-avoidance (r=.55, p=.009) as a passive coping style were associated with COVID-19 stress, and seeking social support as an active coping style was associated with the left physical tension & stress quotient (r=.47, p=.031). Conclusion: These findings provide evidence regarding the objective status of the mental health of face-to-face service industry employees using both a self-reported scale and neuroscientific indicators, including brain quotients.

• 수면정신생리
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• 제2권1호
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• pp.31-43
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• 1995

Recently, the methods that measure and analyze brain electrical activity quantitatively have been available with the rapid development of computer technology. The quantitative electroencephalography(QEEG) is a method of computer-assisted analyzing brain electrical activity. The QEEG allows for a more sensitive, precise and reproducible examination of EEG data than that can be accomplished by conventional EEG. It is possible to compare various EEG parameters each other by using QEEG. Neurometrics, a kind of the quantitative EEG. is to compare EEG characteristics of the patient with normative data to determine in what way the patient's EEG deviates from normality and to discriminate among psychiatric disorders. Nowadays, QEEG is far superior to conventional EEG in its detection of abnormality and in its usefulness in psychiatric differential diagnosis. The abnormal findings of QEEG in various psychiatric disorders are also discussed.

• 한국임상수의학회:학술대회논문집
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• 한국임상수의학회 2006년도 춘계학술대회
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• pp.133-133
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• 2006

• 대한건축학회논문집:계획계
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• 제36권4호
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• pp.41-49
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• 2020

The purpose of this study was to investigate the use of the Deep Neural Networks(DNN) model to classify user's emotions, in particular Electroencephalography(EEG) toward Virtual-Reality(VR) based 3D design alternatives. Four different types of VR Space were constructed to measure a user's emotion and EEG was measured for each stimulus. In addition to the quantitative evaluation based on EEG data, a questionnaire was conducted to qualitatively check whether there is a difference between VR stimuli. As a result, there is a significant difference between plan types according to the normalized ranking method. Therefore, the value of the subjective questionnaire was used as labeling data and collected EEG data was used for a feature value in the DNN model. Google TensorFlow was used to build and train the model. The accuracy of the developed model was 98.9%, which is higher than in previous studies. This indicates that there is a possibility of VR and Fast Fourier Transform(FFT) processing would affect the accuracy of the model, which means that it is possible to classify a user's emotions toward VR based 3D design alternatives by measuring the EEG with this model.

• 대한수의학회지
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• 제45권1호
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• pp.131-137
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• 2005

To assess anesthetic depth using quantitative electroencephalography (q-EEG), we recorded processed EEG (raw EEG) till 100 minutes in beagle dogs anesthetized for 60 minutes with tiletamine/zolazepam (n=5, TZ group), xylazine/ketamine (n=5, XK group) and propofol (n=5, PI group) by intermittent bolus injection. Raw EEG was converted into 95% spectral edge frequency (SEF) and median frequency (MF) through fast fourier transformation (FFT) method. 95% SEF value of TZ group was significantly higher (p<0.05) than the XK group from 10 minutes to 100 minutes. 95% SEF value of PI group was significantly higher (p<0.05) than the XK group from 10 minutes to 40 minutes, and significantly low (p<0.05) than XK group at 90 and 100 minutes. MF was significantly higher (p<0.05) in TZ group from 60 minutes to 100 minutes. Based on these results, using dissociative agent with ${\alpha}_2$-adrenergic agent is more potent in CNS depressed than using dissociative agent alone, and low doses of propofol has a disinhibitory effect on CNS.

• Psychiatry investigation
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• 제15권11호
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• pp.1087-1093
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• 2018

Objective Posttraumatic stress disorder (PTSD) is distinct from anxiety disorders in its etiology and clinical symptomatology, and was reclassified into trauma- and stressor-related disorders in DSM-5. This study aimed to find neurophysiological correlates differentiating PTSD from anxiety disorders using resting-state quantitative electroencephalography (qEEG). Methods Thirty-six patients with either PTSD or acute stress disorder and 79 patients with anxiety disorder were included in the analysis. qEEG data of absolute and relative powers and patients' medication status on the day of qEEG examination were obtained. Electrodes were grouped into frontal, central, and posterior regions to analyze for regional differences. General linear models were utilized to test for group differences in absolute and relative powers while controlling for medications. Results PTSD patients differed from those with anxiety disorders in overall absolute powers [F(5,327)=2.601, p=0.025]. Specifically, overall absolute delta powers [F(1,331)=4.363, p=0.037], and overall relative gamma powers [F(1,331)=3.965, p=0.047] were increased in PTSD group compared to anxiety disorder group. Post hoc analysis regarding brain regions showed that the increase in absolute delta powers were localized to the posterior region [F(1,107)=4.001, p=0.048]. Additionally, frontal absolute gamma powers [F(1,107)=4.138, p=0.044] were increased in PTSD group compared to anxiety disorder group. Conclusion Our study suggests increased overall absolute delta powers and relative gamma powers as potential markers that could differentiate PTSD from anxiety disorders. Moreover, increased frontal absolute gamma and posterior delta powers might pose as novel markers of PTSD, which may reflect its distinct symptomatology.