• 대한의용생체공학회:의공학회지
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• 제10권3호
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• pp.303-308
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• 1989

A new estimationn mothod of single-EP(evoked potential) using adaptive algorithm and paralnetrlc model is proposed. Since the EEG(eletroencephalogram) signal is stationary in short time interval the AR(autoregressive) parameters of the EEG are estimated by the Burg algorithm using the EEG of prestimulus interval. After stimulus, the single-EP is estimated by adaptive algorithm. The validity of this method is verified by the simulation for generated auditory single-EP based on parametric model.

• 전기학회논문지
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• 제67권11호
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• pp.1506-1511
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• 2018

This study presents a human sensibility evaluation method using neural network and multiple-template method on electroencephalogram(EEG). We used a multi-layer perceptron type neural network as the sensibility classifier using EEG signal. For our research objective, 10-channel EEG signals are collected from the healthy subjects. After the necessary preprocessing is performed on the acquired signals, the various EEG parameters are estimated and their discriminating performance is evaluated in terms of pattern classification capability. In our study, Linear Prediction(LP) coefficients are utilized as the feature parameters extracting the characteristics of EEG signal, and a multi-layer neural network is used for indicating the degree of human sensibility. Also, the estimation for human comfortableness is performed by varying temperature and humidity environment factors and our results showed that the proposed scheme achieved good performances for evaluation of human sensibility.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2017년도 추계학술발표대회
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• pp.1079-1082
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• 2017

최근에 각종 생체전위를 활용한 연구가 활발히 이루어 지고 있다 학습효과를 위해서 집중력 향상에 대한 연구는 교육분야에서 중요한 과제이다. 따라서 뇌파(eletroencephalogram)를 활용한 집중력 향상에 필요한 소프트웨어적 연구는 가치가 있는 연구로서 판단할 수 있다. 따라서 금번 연구에서는 뇌파와 컴퓨터 간 신호처리에 중점을 두고 효율적으로 데이터 프로세스를 할 수 있는 게임이라는 매체를 활용한 학습효과 증진 프로그램을 개발하고자 한다. 금번 연구에서는 학습에 필요한 인터페이스 프로그램과 뇌파 수집에 필요한 뇌파수집기를 중점으로 개발하였다.

• 대한전기학회논문지:전력기술부문A
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• 제48권4호
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• pp.478-485
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• 1999

The purpose of this paper was the determination of the relationship between the chaotic charateristics and various levels of brain activities. Assuming that EEG(eletroencephalogram), which is generated by a nonlinear electiecal behavior of billions of neurons in the brain, has chaotic characteristics, it was confirmed by frequency spectrum analysis, log frequency spectrum analysis, correlation dimension analysis and Lyapunov exponents analysis. Chaotic characteristics are related to the degree of brain activity. The slope of log frequency spectrum increased and the correlation dimension decreased with respect to the brain activities, while the lagrest Lyapunov exponent has some rough correlation.

• 대한산업공학회지
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• 제42권1호
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• pp.73-79
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• 2016

The purpose of this study is to understand human sensory and emotional response according to car noise. This study investigated human stress levels from car noise based on the data of electro-encephalogram (EEG) and subjective evaluation analysis data. Since there are few previous works on the effect of car noise on human's reaction, more profound research about the effect of car noise on driver's emotion would be worth performing. Subjects were exposed to five different kinds of car noises. EEG data were collected while the subject was exposed to noise. In order to process EEG data, FFT analysis was used to separate the collected EEG data into ${\alpha}$-wave and ${\beta}$-wave. Also, survey was performed to carry out subjective evaluation. The results of the subjective evaluation were closely correlated to those found in the EEG signal analysis. The results from this study may provide useful information for mitigating car noise induced stress.