• Journal of Acupuncture Research
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• v.27 no.1
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• pp.137-148
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• 2010

Objectives : To research the changes of electroencephalogram(EEG) signals for acupuncture stimulation and to establish the hereafter direction for the study on EEG. Methods : We reviewed the domestic papers searched by search engine of Korean Acupuncture & Moxibustion Society and Korea Institute of Oriental Medicine. Results : We have searched 31 articles in 10 journals. The 13 articles were concerned with acupuncture. 1. All articles were published after 2001. In 2007 there were 10 articles. 2. The studies dealing with the changes of EEG signals were 24, the studies dealing with correlation of EEG signals were 5, and the studies analyzing EEG with Korean medicine were 2. 3. In the studies dealing with the changes of EEG signals, the case-control studies were 9, the non case-control studies were 14, and the case study was 1. 10 studies used electro-acupuncture, 1 study used herbal acupuncture, and 2 studies used manual acupuncture. Conclusions : We need more various kinds of studies. 1. Excited condition by acupuncture stimulation may reduce $\alpha$ wave. 2. There may be the acupuncture point-specific variation of EEG signal patterns. 3. The number of responding channels for acupuncture stimulation may correlate with the quantity or variety of acupuncture effect.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1333-1342
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• 2018

Until now, Electroencephalography(: EEG) has been the most important and convenient method for the diagnosis and treatment of epilepsy. However, it is difficult to identify the wave characteristics of an epileptic EEG signals because it is very weak, non-stationary and has strong background noise. In this paper, we analyse the effect of dimensionality reduction methods on Epileptic EEG feature selection and classification. Three dimensionality reduction methods: Pincipal Component Analysis(: PCA), Kernel Principal Component Analysis(: KPCA) and Linear Discriminant Analysis(: LDA） were investigated. The performance of each method was evaluated by using Support Vector Machine SVM, Logistic Regression(: LR), K-Nearestneighbor(: K-NN), Decision Tree(: DR) and Random Forest(: RF). From the experimental result, PCA recorded 75% of highest accuracy in SVM, LR and K-NN. KPCA recorded 85% of best performance in SVM and K-KNN while LDA achieved 100% accuracy in K-NN. Thus, LDA dimensionality reduction is found to provide the best classification result for epileptic EEG signal.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.257-260
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• 1993

A new method of spindle waveform detection is presented for the automated analysis of sleep EEG. The method is based on the combined application of signal conditioning in the time-domain and local spectrum analyzing in the frequency-domain. The overall detection system is implemented and, tested in real-time with a total of 24 hour data obtained from four subjects. The result shows an average agreement of 86.7% with the visually inspected result.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2011.06a
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• pp.187-188
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• 2011

Independent component analysis (ICA) is a method separating the mixture of signals into statistically and mutually independent ones. It has been applied to not only the Cocktail-party problem but also EEG analysis using the EEG waveform, digital signal processing, image processing and cognitive technique field actively. This study aims to propose a procedure to estimate the modal responses and mode shapes of a floating structure by using the ICA method from measured responses of the floating structure.

• Proceedings of the ESK Conference
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• 1996.04a
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• pp.259-263
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• 1996

Psychological action is physiological response of outernal stimulus. Physiological response is accompanied b physiological signals which are EEG, EMG, GSR, ECG, BP, and tec. Physiological signals are recently studied for determination of human phychological state. Psychological activity causes electric potential of brain. Physiological signal is considered as measurement of human psychological state. Aditory sensibility which is one of the sense of human may determine differences between positive and negative feeling. EEG and GSR variation with auditory quality of stimulus can be define human negative and positive mental state. This study is to characterize parameters which can determine negative and positive psycholigical state of human.

• Science of Emotion and Sensibility
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• v.4 no.1
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• pp.61-67
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• 2001

This paper described the effect of subjective approach in case of the human sensibility experiments. The procedure is proceeded subjectively. Human faces are selected as the image presentation media. Pleasant and unpleasant images are selected directly by examiner, And also the image presentation system, which is executed with a computer and has the square-type black box monitor equipment, is manufactured. Images are presented with the step-variation time interval technique. questionnaire test and EEG signal detection data are analyzed. The analysis parameters are a “frequency band integral value” and a “band differential variation ratio”. he results show the high sensibility and fast response. The fact that image presenting repetition alleviates is verified.

• Journal of the Ergonomics Society of Korea
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• v.29 no.1
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• pp.55-59
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• 2010

Driver distraction is a major cause of traffic accidents in Korea. Various measures are being introduced to detect and warn driver distraction. The objective of this research is to investigate changes in driver's physiological signals due to distraction during driving. Driving simulator experiments have been carried out to investigate discrepancy in EEG signals among normal driving, DMB watching during driving, and cellular phone use during driving. Based on the discrepancy, combination of EEG signals have been identfied as candidate variables for detecting driver distraction. Statistical analysis has been carried out to verify their statistical significance.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.11
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• pp.34-36
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• 1991

본 논문에서는 저주파의 envelope와 고주파의 neural oscillation 신호의 곱으로 이루어진 EEG 신호의 envelope를 추출을 하기 위하여 multiplicative homomorphic 시스템을 사용하였다. 이 방법은 다른 방법에 비하여 처리 과정이 간단하여 계산량이 감소되어 실시간 envelope 추출의 가능성을 보였으며, 또 neural oscillation signal의 주파수가 변하여도 정확한 envelope 추출할 수 있는 우수한 적응력을 보였다.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.311-314
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• 1996

The display of biological signals in monitors often involves a multirate sampling operation which consists of decimation and intenolation. All electroencephalographic (EEG) samples of 10 to 30 seconds must be displayed in the computer screen to keep the aspect ratio of the paper polygraph output. Since the current affordable display technology plots at most 2,000 pixels per row, some samples need to be discarded. This paper studies methods to perform this operation characterizing them from the signal processing viewpoint and compares the display quality among several decimations. Experimental results show that a nonlinear operation such as the peak detection could be preferable than the canonical linear filtering to reduce aliasing.

• Journal of Biomedical Engineering Research
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• v.20 no.1
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• pp.81-90
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• 1999

This paper describes an EEG(electroencephalogram) software for two-channel cerebral function monitoring system to detect the cerebral ischemia. In the software, two-channel bipolar analog EEG signals are digitized and from the signals various EEG parameters are extracted and displayed on a monitor in real-time. Digitized EEG signal is transformed by FFT(Fast Fourier transform) and represented as CSA(compressed spectral array) and DSA(density spectral array). Additional 5 parameters, such as alpha ratio, percent delta, spectral edge frequency, total power, and difference in total power, are estimated using the FFT spectra. All of these are effectively merged in a monitor and displayed in real-time. Through animal experiments and clinical trials on men, the software is modified and enhanced. Since the software provides raw EEG, CSA, DSA, simultaneously with additional 5 parameters in a monitor, it is possible to observe patients multilaterally. For easy comparison of patient's status, reference patterns of CSA, DSA can be captured and displayed on top of the monitor. And user can mark events of surgical operation and patient's conditions on the software, this allow him jump to the points of events directly, when reviewing the recorded EEG file afterwards. Other functions, such as forward/backward jump, gain control, file management are equipped and these are operated by simple mouse click. Clinical tests in a university hospital show that the software responds accurately according to the conditions of patients and medical doctors can use the software easily.