• Title, Summary, Keyword: 정량뇌파분석

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Quantitative EEG research by the brain activities on the various fields of the English education (영어학습 유형별 뇌기능 활성화에 대한 정량뇌파연구)

  • Kwon, Hyung-Kyu
    • 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.

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Correlation Dimension Analysis of the EEG in Various Stimuli for Normal States (정상인의 다양한 자극에 대한 뇌파의 상관차원 분석)

  • 김응수;이유정;조덕연
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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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.

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Analysis of EEG Signal Evoked by Auditory Stimulation (청각 자극에 의해 유발되는 뇌파신호의 분석)

  • Lee, Dong-Han;Kim, Jae-Wook;Lee, Chong-Ho
    • Proceedings of the KIEE Conference
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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.

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EEG Recording Method for Quantitative Analysis (정량적 분석을 위한 뇌파 측정 방법)

  • Heo, Jaeseok;Chung, Kyungmi
    • Korean Journal of Clinical Laboratory Science
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    • v.51 no.4
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    • pp.397-405
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    • 2019
  • Quantitative electroencephalography (QEEG) has been widely used in research and clinical fields. QEEG has been widely used to objectively document cerebral changes for the purpose of identifying the electrophysiological biomarkers across various clinical symptoms and for the stimulation of specific cortical regions associated with cognitive function. In electroencephalography (EEG), the difference in quantitative and qualitative analyses is discriminated not by its measurement methods and relevant clinical or research environments, but by its analysis methods. When performing a qualitative analysis, it is possible for a medical technologist or experienced researchers to read the EEG waveforms to exclude artifacts. However, the quantitative analysis is still based on mathematical modeling, and all EEG data are included for the analysis, leading the results to be affected by unexpected artifacts. In the hospital setting, the case that the medical technologists in charge of the EEG test perform academic research has been little reported, compared to other clinical physiological measurement-based research. This is because there are few laboratories specialized in clinical physiological research. In this respect, this study is expected to be utilized as a basic reference material for medical technologists, students, and academic researchers, all of whom would like to conduct a quantitative analysis.

An Introduction to Quantitative Analyses of Sleep EEG Via a Wavelet Method (뇌Wavelet 방법론을 이용한 수면뇌파분석 고찰)

  • Kim, Jong-Won
    • Sleep Medicine and Psychophysiology
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    • v.19 no.1
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    • pp.11-17
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    • 2012
  • Objective: Among various methods developed to quantitatively explore electroencephalograms (EEG), we focused on a wavelet method that was known to yield robust results under nonstationary conditions. The aim of this study was thus to introduce the wavelet method and demonstrate its potential use in clinical sleep studies. Method: This study involved artificial EEG specifically designed to validate the wavelet method. The method was performed to obtain time-dependent spectral power and phase angles of the signal. Synchrony of multichannel EEG was analyzed by an order parameter of the instantaneous phase. The standard methods, such as Fourier transformation and coherence, were also performed and compared with the wavelet method. The method was further validated with clinical EEG and ERP samples available as pilot studies at academic sleep centers. Result: The time-frequency plot and phase synchrony level obtained by the wavelet method clearly showed dynamic changes in the EEG waveforms artificially fabricated. When applied to clinical samples, the method successfully detected changes in spectral power across the sleep onset period and identified differences between the target and background ERP. Conclusion: Our results suggest that the wavelet method could be an alternative and/or complementary tool to the conventional Fourier method in quantifying and identifying EEG and ERP biomarkers robustly, especially when the signals were nonstationary in a short time scale (1-100 seconds).

The Application of Quantitative Electroencephalography (Spectral Edge Frequency 95) to Evaluate Sedation in Dogs (개에서 진정 평가를 위한 정량적 뇌파검사의 적용)

  • Kim Min-Su;Nam Tchi-Chou
    • Journal of Veterinary Clinics
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    • v.23 no.1
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    • pp.31-35
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    • 2006
  • This study was performed to evaluate sedation with quantitative electroencephalography (EEG) analysis in dogs. EEG is used to evaluate objectively the effects of CNS acting with brain and behavioral changes. Especially, spectral edge frequency 95 (SEF 95) parameter is an effective method to determine the sedative status. The SEF 95 is the frequency below 95% of the total power. Twelve healthy intact male Miniature Schnauzer dogs, which did not show any neurological abnormalities and disease, were used for the study. EEG electrodes were inserted in subcutaneous tissue over the calvaria without entering adjacent muscles. The EEG data were acquired and analyzed by EEG raw wave and spectral edge frequency 95 analysis. After the administration of sedatives, the SEF 95 values were shown the significant changes compared with the normal state In all groups (p<0.05). It is suggested that SEF 95 analysis is useful method for assessing the state of sedation in dogs.

The effects of QEEG based on neurofeedback training for anxiety disorder (불안장애의 정량화 뇌파 기반 뉴로피드백 훈련 효과)

  • Cho, Sang hee;Cho, che hyung;Park, Pyong Woon
    • 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.

A Study on the generation of objective sound model for sonification using brain wave data set (소니피케이션(sonification) 구현을 위한 뇌파 데이타 기반 객관적 사운드 모델 연구)

  • Chun, Sung-Hwan;Joh, In-Jae;Suh, Jung-Keun
    • Proceedings of the Korea Information Processing Society Conference
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    • pp.795-798
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    • 2016
  • 소니피케이션은 다양한 데이터를 사운드로 변환시키는 과정으로 본 연구에서는 뇌파 신호를 사운드로 생성하는 객관적인 워크플로우를 제시하고자 하였다. 현재까지의 뇌파 소니피케이션은 사운드로의 변환이 인위적이고 임의적으로 진행되어 객관적인 논리를 제시하지 못하고 있는 실정이다. 이에 본 연구에서는 뇌파데이터의 정량적 분석을 통해 파라미터 추출, 사운드 맵핑, 사운드 모델 구축에 대한 논리적 근거를 제시하였으며 이를 통해 뇌파데이터의 객관적인 소니피케이션 과정을 구현하였다. 파라미터 추출을 위해 15Hz High pass filtering이 가장 적절한 방법으로 확인되었으며 뇌파 데이터의 최대값 빈도 분석과 음악코드의 비율 분석을 실제로 맵핑시켜 사운드 모델을 구축하여 사운드 생성을 구현하였다. 결론적으로, 본 연구에서는 뇌파데이터의 소니피케이션 과정에 대한 객관적이고 논리적인 워크플로우를 제시하였으며 이러한 워크플로우가 다양한 분야에서 적용될 수 있을 것으로 예상된다.

Comparison of QEEG between EEG asymmetry and Coherehnce with elderly people according to smart_phone game Addiction Tendency (노인의 스마트 폰 게임 중독 경향에 따른 뇌파 비대칭(asymmetry)와 연결성(Coherehnce)의 정량화뇌파(QEEG) 비교 분석)

  • Weon, Hee Wook
    • 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.