• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1190-1195
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• 1990

A new system for automatic interpretation of the awake electroencephalogram(EEG) was developed in this work. We first clarified all the necessary items for EEG interpretation in accordance with an analysis of visual inspection of the rhythms by a qualified electroencephalographer (EEGer), and then defined each item quantitatively. Concerning the automatic interpretation, we made an effort to find out specific EEG parameters which faithfully represent the procedure of visual interpretation by the qualified EEGer. Those specific EEG parameters were calculated from periodograms of the EEG time series. By using EEG data of 14 subjects, the automatic EEG interpretation system was constructed and compared with the visual interpretation done by the EEGer. The automatic EEG interpretation thus established was proved to be in agreement with the visual interpretation by the EEGer.

• Korean Journal of Biological Psychiatry
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• v.8 no.2
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• pp.233-238
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• 2001

The routine interictal electroencephalogram(EEG) continues to play an important role in the diagnosis and treatment of epilepsy. The clinical investigation of brain disease in the last decade has been marked by dramatic advances in functional imaging, magnetic resonance scanning and digitized EEG. Epilepsy is a disorder of electrical hyperirritability of cerebral cortex and the interictal EEG remains the most convenient means available to demonstrate cortical hyperirritability. The sensitivity and specificity of the EEG in the diagnosis of epilepsy have been disputed. In this review, the type of EEG findings in epilepsy are reviewed and the sensitivity and specificity of interictal epileptiform discharge are discussed. And also the role of EEG in various clinical situations are summarized.

• Journal of the Korean Applied Science and Technology
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• v.35 no.4
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• pp.1175-1184
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• 2018

The purpose of this study was to investigate effects of 12-weeks finswimming exercise on electroencephalogram(EEG), SBP, DBP, and RHR in male adolescents. Eighteen male adolescents participated in this study. They were separated into a Control group(CG; n=9) and Finswimming training group(FG; n=9). FG participated in Finswimming training for 12weeks, 60 minutes per day, 3 times a week. All data of electroencephalogram were analyzed by repeated measures two-way ANOVA and Data of SBP, DBP and RHR were analyzed by ANCOVA and Paired t-test. As a result, Alpha and SMR waves were significantly increased in FG; however, Alpha wave was significantly decreased in CG and Theta wave was significantly decreased in FG. There were significant interaction in Alpha, Theta, and SMR waves. SBP, DBP, and RHR were significantly decreased in FG and there were significant differences of RHR and SBP between groups; otherwise, there were no significant differences of DBP between groups. The results of this study showed that 12 weeks of Finswimming training positively effects on electroencephalogram(EEG), SBP, DBP, and RHR in male adolescents.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.52.5-52
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• 2002

In this paper, we develop analysis models for classification of temporal data from human subjects. The study focuses on the analysis of electroencephalogram (EEG) signals obtained during various emotional states. We demonstrate a generally applicable method of removing EOG and EMG artifacts from EEGs based on independent component analysis (ICA). All EEG channel maps were interpolated from 10 EEG subbands. ICA methods are based on the assumptions that the signals recorded on the scalp are mixtures of signals from independent cerebral and artifactual sources, that potentials arising from different parts of the brain, scalp and body are summed linearly at the electrodes and that prop...

• Journal of the Ergonomics Society of Korea
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• v.17 no.1
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• pp.1-9
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• 1998

The sensitivity of the emotion evoked visually by IAPS was attempted to be defined using EEG(electroencephalogram). Twenty university students were participated in this study. Their EEG was measured and analyzed in terms of frequency range such as delta, theta, alpha and beta wave. The results showed that alpha increased, but delta and beta decreased with positive emotional progress. Inter-variation between alpha and delta in F4 and beta variation in P3 were indicative of the evaluation sensitivity of human emotion.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.6 no.8
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• pp.27-34
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• 1983

Bioelectrical measurement has long been an important area in medical researches and practices, and contributed valueable data to the field of human engineering. In particular, the measurement of EEG has been widely used for the study of brain function as well as for the diagnosis of various brain disorders. The present study tried to improve conventional measurements of EEG in that FFT algorithm with microcomputer machine language was applied to facilitate the computation of various aspects of the EEG.

• 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.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.739-741
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• 2003

Electroencephalogram (EEG)-based brain computer interface (BCI) provides a new communication channel between human brain and computer. EEG is very noisy data and contains artifacts, thus the extraction of features that are robust to noise and artifacts is important. In this paper we present a method with employ both independent component analysis (ICA) and oriented principal component analysis (OPCA) for artifact-robust feature extraction.

• Journal of Korean Physical Therapy Science
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• v.15 no.3
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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.

• Journal of KIISE
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• v.41 no.12
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• pp.1050-1057
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• 2014

Electroencephalogram (EEG)-based brain-computer interfaces (BCI) can be used for a number of purposes in a variety of industries, such as to replace body parts like hands and feet or to improve user convenience. In this paper, we propose a method to decompose and extract motor imagery EEG signal using Empirical Mode Decomposition (EMD) and Fast Fourier Transforms (FFT). The EEG signal classification consists of the following three steps. First, during signal decomposition, the EMD is used to generate Intrinsic Mode Functions (IMFs) from the EEG signal. Then during feature extraction, the power spectral density (PSD) is used to identify the frequency band of the IMFs generated. The FFT is used to extract the features for motor imagery from an IMF that includes mu rhythm. Finally, during classification, the Support Vector Machine (SVM) is used to classify the features of the motor imagery EEG signal. 10-fold cross-validation was then used to estimate the generalization capability of the given classifier., and the results show that the proposed method has an accuracy of 84.50% which is higher than that of other methods.