• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.19-23
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• 1996

A full automatic interpretation of awake electroencephalogram (EEG) had been developed by the authors and presented at the past KACCs in series. The automatic EEG interpretation consists of four main parts: quantitative EEG interpretation, EEG report making, preprocessing of EEG data and adaptable EEG interpretation. The automatic EEG interpretation reveals essentially the same findings as the electroencephalographer's (EEG's), and then would be applicable in clinical use as an assistant tool for EEGer. The method had been developed through collaboration works between the engineering field (Saga University) and the medical field (Kyoto University). This work can be understood as an artificial realization of human expert skill. The procedure for the artificial realization was summarized in a methodology for artificial realization of human skill which will be applicable in other fields of systems control.

• Clinical and Experimental Pediatrics
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• v.51 no.8
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• pp.861-867
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• 2008

Purpose : We carried out this study to determine if there is any difference in the occurrence rate of the epileptiform discharge between awake EEG and sleep EEG and if there are any factors influencing on the occurrence rate of EEG. Methods : This study included 178 epileptic children who had visited neurology clinic of the department of pediatrics, Pusan National University Hospital from July 2005 to July 2006. The medical and EEG records of these children who had had both awake EEG and sleep EEG were reviewed. We analysed the occurrence rate of the epileptiform discharge between awake EEG and sleep EEG. We investigated the related clinical factors which included sex, seizure types, underlying causes, age at first seizure, antiepileptic drug (AED) medication, age at recording, and background activity. Results : Among 178 epileptic children, 91 patients (51.1%) showed epileptiform discharge in awake or sleep states, 10 patients (11.0%) abnormal only in awake, 40 patients (44.0%) abnormal only in sleep, 41 patients (45.0%) abnormal in both awake EEG and sleep EEG. The occurrence rate of sleep EEG was 81 of 178 patients (45.5%) which was more than that of the awake EEG (28.7%) (P<0.001). The occurrence rate of sleep EEG is more than that of the awake EEG regardless of sex and underlying causes. But there is no significant difference from awake EEG and sleep EEG in finding the epileptiform discharge in the patient with generalized seizure, younger than 5 years old at first seizure, younger than 10 years old at recording, no antiepileptic medication, and abnormal background activity. Conclusion : The sleep EEG is thought to be more helpful in the diagnosis of childhood epilepsy.

• Biomolecules & Therapeutics
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• v.7 no.3
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• pp.242-248
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• 1999

Diazepam, a benzodiazepine (BDZ) agonist, produces sedation and flumazenil, a BDZ antagonist, blocks these actions. The aim of this study was to examine the effects of BDZs on cortical electroencephalogram (EEG) in rats. The recording electrodes were implanted over the frontal and parietal cortices bilaterally, and the reference and ground electrodes over cerebellum under ketamine anesthesia. To assess the effects of diazepam and flumazenil, rats were injected with diazepam (1 mgHg, i.p.) and/or flumazenil ( 1 mg/kg, i.p.), and the EEG was recorded before and after drugs. Normal awake had theta peak in the spectrum and low amplitude waves, while normal sleep showed large amplitude of slow waves. The powers of delta, theta and alpha bands were increased during sleep compared with during awake. Diazepam reduced the mobility of the rat and induced sleep with intermittent fast spindles and large amplitude of slow activity, and it produced broad peak over betaL band and increased the power of gamma band, which were different from EEG patterns in normal sleep. Saline injection awakened rats and abolished fast spindles for a short period about 2-5 min from EEG pattern during diazepam-induced sleep. Flumazenil blocked both diazepam-induced sleep and decreased the slow activities of delta, theta, alpha and betaL, but not of gamma activity for about 10 min or more. This study may indicate that decrease in power of betaL and betaH bands can be used as the measure of central action of benzodiazepines, and that the EEG parameters of benzodiazepines have to be measured without control over the behavioral state by experimenter.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.503-508
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• 1992

A new method for making automatic electroencephalogram(EEG) report based on the automatic quantitative interpretation of awake EEG was developed. We first analysed a. relationship between EEG reports and quantitative EEG interpretation done by a qualified electroencephalographer(EEGer) for 22 subjects. Based on the analysed relationship and usual process of report making by the EEGer, we defined all terminology necessary for EEG report and established rules for EEG report making. By the combined use of the proposed EEG report making and the method for automatic quantitative EEG interpretation presented at '90 KACC, we were able to make the automatic EEG reports which were equivalent to the EEG reports written by the EEGer. As all the procedures were programmed in a personal computer equipped with an AD (analogue-to-digital) converter, the automatic EEG reports were obtained in almost real time in usual actual EEG recording situation with only a few seconds time lag for the analysis in the computer. The proposed report making method and the quantitative EEG interpretation method will be effectively applicable to the clinical use as an assistant tool for physicians.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.106.5-106
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• 2001

A method for automatically selecting the electroencephalogram(EEG) segments was developed by grading each segment based on organization of EEG, vigilance level, open versus closed eyes condition and the artifact contamination.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.493-493
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• 2000

Multi-valued decision making for transitional stochastic events was newly derived based on conditional probability of database. The two values (on-off) decision making method without transition had been proposed by one of the author in a previous work for a purpose of realizing human on-off decision making. The current method is an extension of the previous on-off decision making. By combining the conditional probability and the transitional probability, the closed form of the algorithm for the multi-valued transitional decision making was derived. The proposed multi-valued decision making was successfully applied to the determination of the five levels of the vigilance of a subject during the EEG recording; awake stage, drowsy stage and sleeping stages (stage 1, stage 2/3, REM (rapid eye movement)). The method for determining the vigilance level can be directly usable for the two purposes; selection of awake EEG segments for automatic EEG interpretation, and determination of sleep stages through sleep EEG. The proposed multi-valued decision making with a mathematical background of the probability can be applicable widely, in industries and in medical fields for purposes of the multi-valued decision making.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.505-508
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• 1995

The automatic interpretation of awake background electroencephalogram (EEG), consisting of quantitative EEG interpretation and EEG report making, has been developed by the authors based on EEG data visually inspected by an electroencephalographer (EEGer). The present study was focused on the adaptability of the automatic EEG interpretation which was accomplished by the constructive neural network with forgetting factor. The artificial neural network (ANN) was constructed so as to give the integrative decision of the EEG by using the input signals of the intermediate judgment of 13 items of the EEG. The feature of the ANN was that it adapted to any EEGer who gave visual inspection for the training data. The developed method was evaluated based on the EEG data of 57 patients. The re-trained ANN adapted to another EEGer appropriately.

• Journal of Biomedical Engineering Research
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• v.28 no.6
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• pp.750-755
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• 2007

The linear SEF (Spectral Edge Frequency) parameter and spectrum analysis method can not reflect the non-linear of EEG. This method can not contribute to acquire real time analysis and obtain a high confidence in the clinic due to low discrimination. To solve the problems, the development of a new index is carried out using the bispectrum analyzing the EEG including the non-linear characteristic. At the bispectrum analysis of the 2 dimension, the most significant's power spectrum density peaks appeared much at the specific area in awake and anesthesia state. Because many peaks are showed at the specific area in the frequency coordinate, these points are used to create the new index. Range of the index is 0-100. At the anesthesia, the index is 20-50 and at the awake, the index is 90-60. New index can discriminate the awake and anesthesia state.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.1
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• pp.35-41
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• 2006

Although reachers have studied for a long time, they don't make criteria for anesthesia depth. anesthetists can't make a prediction about patient's reaction. Therefor, patients have potential risk such as poisonous side effect late-awake, early-awake and strain reaction. EEG are received from twenty-five patients who agreed to investigate themselves during operation with Enflurane-anesthesis in progress of anesthesia. EEG are divided pre-anesthesia, before incision of skin, operation 1, operation 2, awaking, post-anesthesia by anesthesia progress step. EEG is applied pre-processing, base line correct, linear detrend to get more reliable data. EEG data are handled by electronic processing and the EEG data are calculated by bicoherence. During pre-anesthesia and post anesthesia, appearance rate of bicoherence value is observed strong appearance rate in high frequency range($15\~30Hz$). During the anesthesia of patient, a strong appearance rate is revealed the low frequency area(0~10Hz). After bicoherence is calculated by percentage of a appearance rate, that is, Bicpara$\#$1, Bicpara$\#$2, Bicpara$\#$3 and Bicpara$\#$4 parameter are extracted. In result of bicoherence analysis, Bicpara$\#$2 and Bicpara#4 are considered that the best parameter showed progress of anesthesia effectively. And each separated bicoherence are calculated by average bicoherence's numerical value, divide by 2 area, appear by each BicHz$\#$1, BicHz$\#$2, and observed BicHz$\#$1/BicHz$\#$2's change. In result of bicoherence analysis, BicHz$\#$1, BicHz$\#$2 and BicHz$\#$1/BicHz$\#$2 are considered that the best parameter showed progress of anesthesia effectively. In conclusion, I confirmed the anesthesia progress phase, concluded to usefulness of parameter on bispectrum and bicoherence analysis and evaluated the depth of anesthesia. In the future, it is going to use for doctor's diagnosis and apply to protect an medical accident owing to anesthesia.