• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(5)
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• pp.127-130
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• 2000

Classification of Electroencephalogram(EEG) makes one of key roles in the field of clinical diagnosis, such as detection for epilepsy. Spectrum analysis using the fourier transform(FT) uses the same window to signals, so classification rate decreases for nonstationary signals such as EEG's. In this paper, wavelet power spectrum method using wavelet transform which is excellent in detection of transient components of time-varying signals is applied to the classification of three types of Event Related Potential(EP) and compared with the result by fourier transform. In the experiments, two types of photic stimulation, which are caused by eye opening/closing and artificial light, are used to collect the data to be classified. After choosing a specific range of scales, scale-averaged wavelet spectrums extracted from the wavelet power spectrum is used to find features by Back-Propagation(13P) algorithm. As a result, wavelet analysis shows superiority to fourier transform for nonstationary EEG signal classification.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2001년도 추계학술대회 논문집
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• pp.112-116
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• 2001

본 연구는 자동차 시뮬레이터에서 필연적으로 발생하는 Sickness와 생리신호 간의 관련성에 대해 알아보고자 하였다. 이를 위해 Driving Simulator에서 중추신경계의 EEG 생리신호를 측정하고 이의 정량적 분석을 통하여 Simulator Sickness가 생리신호에 미치는 영향을 검토하였다. 중추신경계의 뇌파반응은 주행시간의 경과에 따른 특정 경향은 나타나지 않았으나 안정에 비해 delta파, theta파의 증가와 alpha파의 감소경향이 나타났다. 단, theta파는 초기 5분에 증가한 수치가 시간이 지남에 따라 그 비율이 일정하게 감소하는 것으로 나타났다. 또한 Sick그룹과 Non-Sick그룹 및 남녀그룹의 비교결과에 대한 유의한 차이가 인정되었다.

• Korean Journal of Acupuncture
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• 제36권4호
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• pp.241-251
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• 2019

Objectives : The purpose of this study was to examine the effects of electroacupuncture at GB14, on brain activity assessed on an electroencephalogram(EEG). Methods : (1) Thirty-four healthy participants were randomly divided into two groups, receiving either real acupuncture or non-penetrating sham acupuncture at GB14. (2) EEG measurements were conducted simultaneously before and after a 5-minute electroacupuncture stimulation, and the differences in the resulting EEG parameters were compared between the test and control groups. Results : (1) Absolute power increased significantly in the theta-wave channel of the occipital region and in the entire alpha-wave channel. (2) Relative power decreased significantly in the theta-wave channels of the frontal and occipital regions. (3) Coherence decreased significantly in the theta- and beta-wave channels of the parietal and occipital regions, and increased significantly in the alpha-wave channels of most areas. Conclusions : This study shows that electroacupuncture stimulation at GB14 activates the alpha frequency band in particular.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 하계학술대회 논문집 D
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• pp.2690-2692
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• 2002

This paper describes a technique for human sensibility evaluation using 10-channel EEG(electroencephalogram). The proposed method uses the linear predictor coefficients as EEG feature parameters and a neural network as sensibility pattern classifier. For subject independent system, multiple templates are stored and the most similar template can be selected. EEG signals corresponding to 4 emotions such as, relaxation, joy, sadness and anger are collected from 5 armature performers. The states of relaxation and joy are considered as positive sensibility and those of sadness and anger as negative. The classification performance using the proposed method is about 72.6%. This will be promising performance in the human sensibility evaluation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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• pp.2804-2806
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• 2003

생체신호는 생리학이나 해부학에서 주로 다루어졌으나, 최근 컴퓨터 시스템의 발전으로 공학적인 접근이 활발히 진행되고 있다. 특히 뇌의 정보를 보여주는 EEG(Electroencephalogram) 신호의 각 주파수 대역 별 에너지 분석은 의학분야에서도 매우 큰 비중을 두고 있다. 특정 뇌신경 관련질환이 갖는 대역별 주파수 특징과 Spike등을 분석하는 것은 치료와 예방에 아주 좋은 방법의 하나가 될 수 있다. 본 논문에서는 신호처리에서 높은 효율을 보이는 Wavelet Transform을 이용하여 알츠하이머병의 EEG 신호를 분석하였다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2001년도 춘계학술발표논문집 (상)
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• pp.297-300
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• 2001

뇌파(Electroencephalogram, EEG)는 뇌의 자발적 전기활동을 두피에서 측정한 것이다. 그 동안 뇌질환과 관련된 임상에서 주로 사용되어져 왔으며, 비선형 동역학 연구를 통해 결정론적인 동역학 신호임이 밝혀짐에 따라 뇌 기능연구 분야에서 그 응용범위가 넓어지고 있다. 우리는 뇌파 신호에 대하여 독립성분분석(Independent Component Analysis, ICA)을 통하여 그 결과를 알아보았다. 즉, 뇌파의 독립성분 분석 적용 타당성을 알아본 다음 이를 적용하여 독립 소스들을 분리해 내었다. 또한 Topological Mapping을 이용하여 각각의 독립 소스들이 뇌의 어느 위치에서 발생하는지도 알아보았다. 이를 통하여 EEG에 독립성분분석을 적용함으로써 뇌 활동의 시간적, 공간적 분석이 가능하고 유용함을 나타내었다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2015년도 추계학술발표대회
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• pp.1396-1398
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• 2015

BCI (Brain Computer Interface)는 사람의 두뇌와 컴퓨터를 연결하는 '뇌-컴퓨터 인터페이스'를 나타내는 것이며 EEG(Electroencephalogram)을 주로 분석하여 인간의 행동이나 의도를 파악한다. 본 논문에서는 EEG를 이용한 행동인식의 하나로 졸음을 판단하는 방법을 제안한다. 제안방법에서는 MindWave를 이용하여 얻은 실험 데이터를 FFT를 이용하여 1초 단위로 스펙트럼을 분석하여 High-Alpha 영역의 시간에 따른 데이터 변화 패턴을 분석하여 졸음을 판단한다. 실험 결과, 100%의 최고 성능을 얻을 수 있었다.

• 대한인간공학회지
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• 제15권2호
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• pp.185-192
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• 1996

EEG(electroencephalogram) is characterized with auditory emotion in this study. Twenty university students participated in this study. The auditory stimulus was the natural sounds such as creek sound, clash, machining noise, and etc. They can cause the positive and negative emotion. EEG characteristics according to positive and negative auditory stimuli is tried to observe statistic difference. The significant difference is shown depending on the localized area. The auditory paraameters of EEG variation is examined for defining human emotion qualitatively. The results shows that the alpha and the beta at temproal area may be thd determinat of human auditory emotion.

• 대한간호학회지
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• 제45권6호
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• pp.928-938
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• 2015

Purpose: This study explored the effects of neurofeedback training on Electroencephalogram (EEG), Continuous Performance Task (CPT) and ADHD symptoms in ADHD prone college students. Methods: Two hundred forty seven college students completed Korean Version of Conners' Adult ADHD Rating Scales (CAARS-K) and Korean Version of Beck Depression Inventory (K-BDI). The 16 participants who ranked in the top 25% of CAARS-K score and had 16 less of K-BDI score participated in this study. Among them, 8 participants who are fit for the research schedule were assigned to neurofeedback training group and 8 not fit for the research schedule to the control group. All participants completed Adult Attention Deficiency Questionnaire, CPT and EEG measurement at pretest. The neurofeedback group received 15 neurofeedback training sessions (5 weeks, 3 sessions per week). The control group did not receive any treatment. Four weeks after completion of the program, all participants completed CAARS-K, Adult Attention Deficiency Questionnaire, CPT and EEG measurement for post-test. Results: The neurofeedback group showed more significant improvement in EEG, CPT performance and ADHD symptoms than the control group. The improvements were maintained at follow up. Conclusion: Neurofeedback training adjusted abnormal EEG and was effective in improving objective and subjective ADHD symptoms in ADHD prone college students.

• 제어로봇시스템학회논문지
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• 제17권8호
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• pp.747-752
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• 2011

HMMs (Hidden Markov Models) are widely used for biological signal, such as EEG (electroencephalogram) sequence, analysis because of their ability to incorporate sequential information in their structure. A recent trends of research are going after the biological interpretable HMMs, and we need to control the complexity of the HMM so that it has good generalization performance. So, an automatic means of optimizing the structure of HMMs would be highly desirable. In this paper, we described a procedure of classification of motor imagery EEG signals using HMM. The motor imagery related EEG signals recorded from subjects performing left, right hand and foots motor imagery. And the proposed a method that was focus on the validation of the HSA (Harmony Search Algorithm) based optimization for HMM. Harmony search algorithm is sufficiently adaptable to allow incorporation of other techniques. A HMM training strategy using HSA is proposed, and it is tested on finding optimized structure for the pattern recognition of EEG sequence. The proposed HSA-HMM can performs global searching without initial parameter setting, local optima, and solution divergence.