• Proceedings of the KOSOMBE Conference
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• v.1994 no.12
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• pp.81-84
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• 1994

A clinically oriented EEG and EP mapping system was developed with user-friendly interface and easy interactive operations. The system was based on the graphical user interface developed with C/C++ and Software Development Kit (SDK) operated under Microsoft Windows 3.1. Continuous acquisition for the EEG signal and burst mode acquisition for EEG signal syncronized to the external stimuli arc implemented with real time display. A neural network based automatic artifact discrimation is developed and implemented with which examination time can be reduced by a factor of 3 or more. Several bands of spectral maps and spectrums arc displayed for EEG diagnosis. Amplitude maps of EP signal at specified times by operator are displayed together with cine mode of EP maps for dynamic study. Source localization and other statistical signal processing are also included.

• Journal of Biomedical Engineering Research
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• v.32 no.4
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• pp.295-304
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• 2011

In this study, we evaluated the EEG based BCI algorithm using common spatial pattern to find realistic applicability using neurofeedback EEG based BCI algorithm - EEG mode, feature vector calculation, the number of selected channels, 3 types of classifier, window size is evaluated for 10 subjects. The experimental results have been evaluated depending on conditioned experiment whether neurofeedback is used or not In case of using neurofeedback, a few subjects presented exceptional but general tendency presented the performance improvement Through this study, we found a motivation of development for the specific classifier based BCI system and the assessment evaluation system. We proposed a need for an optimized algorithm applicable to the robust motor imagery evaluation system with more useful functionalities.

• 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.

• Journal of Biomedical Engineering Research
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• v.20 no.2
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• pp.205-212
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• 1999

When we want to observe and record a patient's EEG in an operating room, the operation of electrosurgical unit(ESU) causes undesirable artifacts with high frequency and high voltage. These artifacts make the amplifiers of the conventional EEG system saturated and prevent the system from measuring the EEG signal. This paper describes a high-performance bipolar EEG amplifier for a CSA (compressed spectral array ) system with reduced ESU artifacts. The designed EEG amplifier uses a balanced filter to reduce the ESU artifacts, and isolates the power supply and the signal source of the preamplifier from the ground to cut off the current from the ESU to the amplifier ground. To cancel the common mode noise in high frequency, a high CMRR(common mode rejection ratio) diffferential amplifier is used. Since the developed bipolar EEG amplifier shows high gain, low noise, high CMRR, high input impedance, and low thermal drift, it is possible to observe and record more clean EEG signals in spite of ESU operation. Therefore the amplifier may be applicable to a high-fidelity CSA system.

• 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.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.364-372
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• 2010

The aim of this study was to evaluate effects of EEG patterns induced by three types ((1) resting mode(control group), (2) light massage mode, (3) strong massage mode in the electrical chair-massager for 15 minutes) in a sample of 16 healthy adults. Changes in anxiety and stress were assessed, and electroencephalogram was recorded. Anxiety scores(STAI: State Anxiety Inventory, VAS: Visual Analog Scale) decreased in all groups. For anxiety scores, the strong massage group showed the greatest decrease in stress. All groups also showed an increase in delta and theta activity, but only strong massage group showed a signigicant difference. All groups showed a decrease in alpha activity. Also, EEG changes in two groups except a control group showed a decrease in beta activity.

• Progress in Medical Physics
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• v.13 no.3
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• pp.156-162
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• 2002

In this study, we attempted in preparing high precision EEG measuring equipment. To measure EEG in high efficiency, pre-amplifier should get high performance common mode rejection ratio. Also, separation amplifier is essential to eliminate common line noise. So, our study were pointed at elevating the efficiency of eliminating noise, user safety and low noise characteristics. Prepared high precision pre-amplifier for EEG was A/D converted to automatically classify $\alpha$ wave, $\beta$ wave and $\theta$ wave. And converted data were Fast Fourier Transformed with real time DSP (Digital Signal Processing). Clinical demonstrations were carried out with healthy students, aged between 20 to 26 who has no histories of illness. To recognize the efficiency of the EEG, prepared EEG were used with MS equipment in low stimulated state and high stimulated state. Then, we studied at the effect of sensitivity on brain wave. From this study, it is known that our EEG equipment is efficient in sensitivity evaluation and suitable stimulations for each psychological state are required.

• Journal of Korean Academy of Nursing
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• v.52 no.1
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• pp.36-51
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• 2022

Purpose: The purpose of this study was to examine the effects of electroencephalogram (EEG) biofeedback training for emotion regulation and brain homeostasis on anxiety about COVID-19 infection, impulsivity, anger rumination, meta-mood, and self-regulation ability of late adolescents in the prolonged COVID-19 pandemic situation. Methods: A non-equivalent control group pretest-posttest design was used. The participants included 55 late adolescents in the experimental and control groups. The variables were evaluated using quantitative EEG at pre-post time points in the experimental group. The experimental groups received 10 sessions using the three-band protocol for five weeks. The collected data were analyzed using the Shapiro-Wilk test, Wilcoxon rank sum test, Wilcoxon signed-rank test, t-test and paired t-test using the SAS 9.3 program. The collected EEG data used a frequency series power spectrum analysis method through fast Fourier transform. Results: Significant differences in emotion regulation between the two groups were observed in the anxiety about COVID-19 infection (W = 585.50, p = .002), mood repair of meta-mood (W = 889.50, p = .024), self-regulation ability (t = - 5.02, p < .001), self-regulation mode (t = - 4.74, p < .001), and volitional inhibition mode (t = - 2.61, p = .012). Neurofeedback training for brain homeostasis was effected on enhanced sensory-motor rhythm (S = 177.00, p < .001) and inhibited theta (S = - 166.00, p < .001). Conclusion: The results demonstrate the potential of EEG biofeedback training as an independent nursing intervention that can markedly improve anxiety, mood-repair, and self-regulation ability for emotional distress during the COVID-19 pandemic.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1812-1824
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• 2016

The neural dynamics underlying the causal network during motor planning or imagery in the human brain are not well understood. The lack of signal processing tools suitable for the analysis of nonlinear and nonstationary electroencephalographic (EEG) hinders such analyses. In this study, noise-assisted multivariate empirical mode decomposition (NA-MEMD) is used to estimate the causal inference in the frequency domain, i.e., partial directed coherence (PDC). Natural and intrinsic oscillations corresponding to the motor imagery tasks can be extracted due to the data-driven approach of NA-MEMD, which does not employ predefined basis functions. Simulations based on synthetic data with a time delay between two signals demonstrated that NA-MEMD was the optimal method for estimating the delay between two signals. Furthermore, classification analysis of the motor imagery responses of 29 subjects revealed that NA-MEMD is a prerequisite process for estimating the causal network across multichannel EEG data during mental tasks.

• Journal of Acupuncture Research
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• v.19 no.4
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• pp.132-139
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• 2002

This study was carried to identify whether acupuncture at several meridian points can affect the human anesthesia or not using the EEG mapping. We observe the change in the brain wave patterns obtained by electroencephalogram after acupuncture. 1. It is concluded that the pattern of resting computerized EEG map in intact human is normal and acupunctuation at determined meridian points induced lesser narrow field of alpha activity, more extensive field of ${\delta}$, ${\theta}$ activity, father resulted in marked shift to cerebrofrontal dominance in field of ${\delta}$, ${\theta}$ activity by t-SPM. 2. It seems likely that acupunctuation at experimental meridian points acts on slight anesthesia or hypnosis.