• Proceedings of the KOSOMBE Conference
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• v.1990 no.11
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• pp.114-117
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• 1990

EEG signal is analyzed by two methods, analysis by visual inspection of EEG recording sheets and analysis by quantative method. Generally visual inspection method is used in the clinical field. But this method has its limitation because EEG signal is random signal. Therefore it is necessary to analyze EEG signals quantatively to obtain more precise and objective information of neural and brain. In this paper, power spectrum of EEG signal was estimated by AR(AutoRegressive) model in the frequency domain. This process is useful as a preprocessing stage for tomographic brain mapping (TBM) at each frequency, band. As a method for estimating power spectral density of EEG signals, periodogram method, autocorrelation method. covariance method, modified covariance method, and Burg method are tested in this paper.

• 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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• 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.

• Journal of Biomedical Engineering Research
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• v.32 no.3
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• pp.207-217
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• 2011

Electrode impedances are measured to quantitatively characterize the electrode-electrolyte or cell-electrode interfaces. In the case of high-density microelectrode arrays(MEAs) that have been developed for brainmachine interface applications, the characterization process becomes a repeating and time-consuming task; a system that can perform the measurement and analysis in an automated fashion with accuracy and speed is required. However, due to the large number of channels, parasitic capacitance and off-capacitance components of the switching system become the major factors that decreased the accuracy for the measurement of high impedance microelectrodes. Here we investigated the implementation of automatic impedance measurement system with analyzing the causes of possible measurement-related problems in multichannel switching configuration. Based on our multi-channel measurement circuit model, we suggest solutions to the problems and introduce a novel impedance measurement scheme using electro-mechanical relays. The implemented measurement system could measure |Z| < 700 $k{\Omega}$ of impedance in - 10% errors, which can be widely applicable to high density neural recording MEAs.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.1060-1071
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• 2014

Signals of the Electroencephalogram (EEG) can reflect the electrical background activity of the brain generated by the cerebral cortex nerve cells. This has been the mostly utilized signal, which helps in effective analysis of brain functions by supervised learning methods. In this paper, an approach for improving the accuracy of EEG signal classification is presented to detect epileptic seizures. Moreover, Independent Component Analysis (ICA) is incorporated as a preprocessing step and Short Time Fourier Transform (STFT) is used for denoising the signal adequately. Feature extraction of EEG signals is accomplished on the basis of three parameters namely, Standard Deviation, Correlation Dimension and Lyapunov Exponents. The Artificial Neural Network (ANN) is trained by incorporating Levenberg-Marquardt(LM) training algorithm into the backpropagation algorithm that results in high classification accuracy. Experimental results reveal that the methodology will improve the clinical service of the EEG recording and also provide better decision making in epileptic seizure detection than the existing techniques. The proposed EEG signal classification using feed forward Backpropagation Neural Network performs better than to the EEG signal classification using Adaptive Neuro Fuzzy Inference System (ANFIS) classifier in terms of accuracy, sensitivity, and specificity.

• Journal of Integrative Natural Science
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• v.11 no.4
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• pp.167-183
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• 2018

Electroencephalogram (EEG) recording provides a new way to support human-machine communication. It gives us an opportunity to analyze the neuro-dynamics of human cognition. Machine learning is a powerful for the EEG classification. In addition, machine learning can compensate for high variability of EEG when analyzing data in real time. However, the optimal EEG electrode location must be prioritized in order to extract the most relevant features from brain wave data. In this paper, we propose an intelligent system model for the extraction of EEG data by training the optimal electrode location of EEG in a specific problem. The proposed system is basically a fuzzy system and uses a neural network structurally. The fuzzy clustering method is used to determine the optimal number of fuzzy rules using the features extracted from the EEG data. The parameters and weight values found in the process of determining the number of rules determined here must be tuned for optimization in the learning process. Genetic algorithms are used to obtain optimized parameters. We present useful results by using optimal rule numbers and non - symmetric membership function using EEG data for four movements with the right arm through various experiments.

• Dementia and Neurocognitive Disorders
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• v.22 no.3
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• pp.87-99
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• 2023

Background and Purpose: According to the amyloid cascade hypothesis, fibrillary amyloid-beta load in the brain causes Alzheimer's disease (AD) with toxic effects. Recently, perivascular spaces (PVSs), fluid-filled cavities around small penetrating arterioles and venules in the brain, and the glymphatic system relationship with type 2 diabetes mellitus (DM2) and AD has been an important research topic from a physiopathological point of view. There are two types of PVSs that are associated with sporadic atherosclerosis and cerebral amyloid angiopathy. In this study, we evaluated the relationship between the number and localization of enlarged PVSs in AD. Methods: A total of 254 patients with AD and 125 healthy controls were included in this study All the patients were evaluated with neurological and cognitive examinations and magnetic resonance imaging (MRI). PVSs on MRI were graded by recording their number and location. The study was a retrospective study. Results: In our study, the number of white matter convexity-central semiovale localized PVSs was higher in patients than in the control group. In addition, the number of PVSs in this localization score was higher in patients with DM2. Cerebral PVS counts were higher in patients with AD than in the control group. Conclusions: These results suggest the important role of cerebral amyloid angiopathy, one of the vascular risk factors, and the glymphatic system in the pathogenesis of AD. In addition, the results of our study suggest that the evaluation of PVSs levels, especially at the (centrum semiovale), using imaging studies in AD is a potential diagnostic option.

• Journal of Korean Neurosurgical Society
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• v.48 no.2
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• pp.134-138
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• 2010

Objective : Meige syndrome is the combination of blepharospasm and oromandibular dystonia. We assessed the surgical results of bilateral globus pallidus internus (GPi) deep brain stimulation (DBS) in patients with medically refractory Meige syndrome. Methods : Eleven patients were retrospectively analyzed with follow-ups of more than 12 months. The mean follow-up period was $23.1{\pm}6.4$ months. The mean age at time of surgery was $58.0{\pm}7.8$ years. The mean duration of symptoms was $8.7 {\pm}7.6$ years. DBS electrodes were placed under local anesthesia using microelectrode recording and stimulation. After $2.4{\pm}1.3$ days of trial tests, the stimulation device was implanted under general anesthesia. Patients were evaluated using the Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS). Results : BFMDRS total movement scores improved by 59.8%, 63.5%, 74.1%, 74.5%, and 85.5% during the immediate postoperative period of test stimulation, 3, 6, 12, and 24 months (n = 5) after surgery, respectively. The BFMDRS total movement scores were reduced gradually and the results reached statistical significance in the postoperative period (test period, p < 0.001; 3 months, p < 0.001; 6 months, p = 0.003; 12 months, p < 0.001; 24 months, p = 0.042). There was no statistical difference between 12 months and 24 months. BFM subscores improved by 63.3% for the eyes, 80.9% for the mouth, 68.4% for speech/swallowing, and 87.9% for the neck at 12 months after surgery. The adverse effects were insignificant. Conclusion : The bilateral GPi-DBS can be effective for the treatment of intractable Meige syndrome without significant side effects.

• Journal of Korean Neurosurgical Society
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• v.46 no.4
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• pp.346-350
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• 2009

Objective : The purpose of this study was to analyze in detail the relationship between outcome and time course of effect in medically refractory primary cervical dystonia (CD) with phasic type that was treated by bilateral globus pallidus internus (Gpi) deep brain stimulation (DBS). Methods : Six patients underwent bilateral implantation of DBS into the Gpi under the guide of microelectrode recording and were followed for $18.7{\pm}11.1$ months. The mean duration of the CD was $5.8{\pm}3.4$ years. The mean age at time of surgery was $54.2{\pm}10.2$ years. Patients were evaluated with the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS) and relief scale using patient self-reporting. Results : The TWSTRS total scores improved by 64.5%, 65.5%, 75.8%, and 76.0% at 3, 6, 12 months, and at the last available follow-up after surgery, respectively. Statistically significant improvements in the TWSTRS scores were observed 3 months after surgery (p=0.028) with gradual improvement up to 12 months after surgery, thereafter, the improvement was sustained. However, there was no statistically significant difference between the scores at 3 and 12 months. Subjective improvement reported averaged $81.7{\pm}6.8%$ at last follow-up. Mild dysarthria, the most frequent adverse event, occurred in 3 patients. Conclusions : Our results show that the bilateral Gpi-DBS can offer a significant therapeutic effect from 3 months postoperatively in patients with primary CD with phasic type, without significant side effects.

• Annals of Clinical Neurophysiology
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• v.2 no.1
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• pp.13-20
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• 2000

Background and Objective : Visual evoked potentials(VEPs) is considered to be a reliable diagnostic procedure for examining patients with anterior visual pathways. Some abnormalities in the recordings on monocular stimulation have been said to indicate retrochiasmal lesion, but less consistent results have been reported. This study is to evaluate the positive predictability of VEP for the detection of retrochiasmal lesion. Methods : We reviewed VEPs that could be interpreted as indicative of a retrochiasmal lesions, based on amplitude or latency asymmetry recorded on the left(O1) and right(O2) occipital regions. Bilateral absent VEPs on both recording(O1 and O2) without evidence of prechiasmal lesion were included. During 5 years, we identified 31 patients who met the above criteria and who had undergone magnetic resonance imaging(MRI) of brain(one patient underwent computerized tomography). Twenty three patients underwent pattern reversal VEPs and others underwent flash goggle VEPs. Results : Brain imagings were abnormal in 29 and were normal in 2. Of the 29 abnormal scans, lesions in posterior visual pathway were detected in 21 scans(predictive value=68%). The predictive value was not significantly different between flash goggle VEP(75%) and pattern reversal VEP(68%). The predictive value was higher in patient with visual field defect(100%) than those without visual field defect(25%). The pathologic nature of lesion also showed close relations to the predictive value. VEPs is usually paradoxically lateralized(78%), but not in all patients. Conclusion : VEPs abnormalities suggesting retrochiasmal lesion were usually corresponded with brain MRI findings. Diagnostic reliability could be increased when considering the visual field defect and nature of lesion. Therefore, the authors suggest that VEPs studies could be useful in evaluating the patients with the retrochismal lesion.