• Journal of Biomedical Engineering Research
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• v.16 no.3
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• pp.301-308
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• 1995

A high-precision pre-amplifier is designed for general use in EEG measurement system. It consists of signal generator, signal amplifier with a impedance converter, shield driver, body driver, differential amplifier, and isolation amplifier. The combination of minimum use of inaccurate passive components and the appropriate matching of each monolithic amplifiers results in good noise behavior, low leakage current, high CMRR, high input impedance, and high IMRR. The performance of EEG pre-amplifier has been verified by showing the typical EEG pattevn of a nomad person through the clinical experiments.

• Journal of the Korean Society of Radiology
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• v.17 no.7
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• pp.1179-1187
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• 2023

Recent advancements in modern transportation have led to the active development of various biomedical signal and medical imaging technologies. Particularly, in the field of cognitive/neuroscience, the importance of electroencephalography (EEG) measurement and the development of accurate EEG measurement technology in moving vehicles represent a challenging area. This study aims to extensively investigate and analyze the trends in technology research utilizing EEG during driving. For this purpose, the Scopus database was used to explore EEG-related research conducted since the year 2000, resulting in the selection of about 40 papers. This paper sheds light on the current trends and future directions in signal processing technology, EEG measurement device development, and in-vehicle driver state monitoring technology. Additionally, a ultra compact 32-channel EEG measurement module was designed. By implementing it simply and measuring and analyzing EEG signals, in-vehicle EEG module's functionality was checked. This research anticipates that the technology for measuring and analyzing biometric signals during driving will contribute to driver care and health monitoring in the era of autonomous vehicles.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.11a
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• pp.409-412
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• 2000

A high performance EEG signal measurement system is fabricated. It consists of high precision pre-amplifier and auto identification bandwidth unit. High precision pre-amplifier is composed of signal generator, signal amplifier with a impedance converter, body driver and isolation amplifier. The pre-amplifier is designed for low noise characteristics, high CMRR, high input impedance, high IMRR and safety, Auto identification bandwidth unit is composed of AD-converter and PIC micro-controller for real time processing EEG signal. The performance of EEG signal measurement system has been shown the classified bandwidth through the clinical demonstrations.

• 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.

• Journal of Oriental Neuropsychiatry
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• v.32 no.4
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• pp.345-378
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• 2021

Objectives: The purpose of this study was to investigate the recent trends of clinical research on acupuncture using electroencephalogram (EEG) as the outcome measurement. Methods: Nine domestic and foreign databases were searched to collect related studies published up to November 3, 2021. The participants, intervention, outcomes, results of the included studies were extracted and analyzed. Results: A total of 18 studies were selected. Neurological diseases and mental disorders were included in most studies, and vascular dementia were most frequently investigated. Electroacupuncture and body acupuncture intervention were most frequently conducted in seven studies. The most commonly used outcomes using EEG was EEG abnormality. However, in most studies there was accurate description of the EEG measurement. Most studies showed significant difference in EEG outcomes after intervention. The quality of included studies was poor. Conclusions: EEG as diagnostic markers and outcome measurements is increasingly studied. Standardized EEG measurement and the consistent EEG finding for specific diseases are needed to perform the future rigorous studies on EEG as diagnostic and outcome tools.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.1
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• pp.45-52
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• 2017

EEG signals that are the same as those that have the same disabled people. So, the EEG signals are becoming the next generation. In this paper, we propose an internet of things system that controls the indoor environment using EEG signal. The proposed system consists EEG measurement device, EEG simulation software and indoor environment control device. We use data as EEG signal data on emotional imagination condition in a comfortable state and logical imagination condition in concentrated state. The noise of measured signal is removed by the ICA algorithm and beta waves are extracted from it. then, it goes through learning and test process using SVM. The subjects were trained to improve the EEG signal accuracy through the EEG simulation software and the average accuracy were 87.69%. The EEG signal from the EEG measurement device is transmitted to the EEG simulation software through the serial communication. then the control command is generated by classifying emotional imagination condition and logical imagination condition. The generated control command is transmitted to the indoor environment control device through the Zigbee communication. In case of the emotional imagination condition, the soft lighting and classical music are outputted. In the logical imagination condition, the learning white noise and bright lighting are outputted. The proposed system can be applied to software and device control based BCI.

• Journal of Korean Academy of Nursing
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• v.45 no.6
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• pp.928-938
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• 2015

Purpose: This study explored the effects of neurofeedback training on Electroencephalogram (EEG), Continuous Performance Task (CPT) and ADHD symptoms in ADHD prone college students. Methods: Two hundred forty seven college students completed Korean Version of Conners' Adult ADHD Rating Scales (CAARS-K) and Korean Version of Beck Depression Inventory (K-BDI). The 16 participants who ranked in the top 25% of CAARS-K score and had 16 less of K-BDI score participated in this study. Among them, 8 participants who are fit for the research schedule were assigned to neurofeedback training group and 8 not fit for the research schedule to the control group. All participants completed Adult Attention Deficiency Questionnaire, CPT and EEG measurement at pretest. The neurofeedback group received 15 neurofeedback training sessions (5 weeks, 3 sessions per week). The control group did not receive any treatment. Four weeks after completion of the program, all participants completed CAARS-K, Adult Attention Deficiency Questionnaire, CPT and EEG measurement for post-test. Results: The neurofeedback group showed more significant improvement in EEG, CPT performance and ADHD symptoms than the control group. The improvements were maintained at follow up. Conclusion: Neurofeedback training adjusted abnormal EEG and was effective in improving objective and subjective ADHD symptoms in ADHD prone college students.

• Journal of the Korean Society of Clothing and Textiles
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• v.29 no.9_10 s.146
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• pp.1230-1240
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• 2005

The purpose of this study was to apply a scientific and systematic method for assessing fashion goods' TV ads effects by EEG and questionnaires as determined by the type of ads appeal. Ads stimulants used in the survey were limited to underwear and sportswear that were advertised during $2000{\sim}2002$ on TV: 4 information-transferring and 4 emotion-evoking ads were used. Subjects were thirty healthy male and female college students. EEG was extracted from six lobes and the recorded EEG was analyzed by the range of frequency of ${\theta},\;{\alpha}\;and\;{\beta}$ waves. Data were analyzed by SPSS 11.0 with reliability test, $x^2$-analysis, t-test and frequency analysis. The emotion-evoking ads showed higher scores in memory, recall and attitude towards the ads. The responses of ${\theta}\;and\;{\alpha}$ wave were active throughout the ads but the response of ${\beta}$ wave was not. The results by the survey and the EEG test showed high similarities, indicating the EEG tests could be used as the supplementary tool for measuring ads effects.

• Journal of Sensor Science and Technology
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• v.25 no.4
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• pp.257-263
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• 2016

Among several technologies related to human brain, Brain Computer Interface (BCI) system is one of the most notable technologies recently. Conventional BCI for direct communication between human brain and machine are discomfort because normally electroencephalograghy(EEG) signal is measured by using multichannel EEG sensor. In this study, we propose 2-channel EEG sensor-based application control system which is more convenience and low complexity to wear to get EEG signal. EEG sensor module and system algorithm used in this study are developed and designed and one of the BCI methods, Motor Imagery (MI) is implemented in the system. Experiments are consisted of accuracy measurement of MI classification and driving control test. The results show that our simple wearable system has comparable performance with studies using multi-channel EEG sensor-based system, even better performance than other studies.

• Science of Emotion and Sensibility
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• v.6 no.4
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• pp.15-23
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• 2003

Recently, there have been many attempts to develop BCI (brain computer interface) based on EEG (electroencephalogram). Measurement and analysis of EEG evoked by particular stimulation is important for the design of brain wave pattern and interface of BCI. The purpose of this study is to develop a general-purpose system that measures subject's reaction time after audio-visual stimulation which can work together with any other biosignal measurement systems. The entire system is divided into four modules, which are stimulation signal generation, reaction time measurement, evoked potential measurement and synchronization. Stimulation signal generation module was implemented by means of Flash. Measurement of the reaction time (the period between the answer request and the subject reaction) was achieved by self-made microcontroller system. EEG measurement was performed using the ready-made hardware and software without any modification. Synchronization of all modules was achieved by, first, the black-and-white signals on the stimulation screen synchronized with the problem presentation and the answer request, second, the photodetectors sensing the signals. The proposed method offers easy design of purpose-specific system only by adding simple modules (reaction time measurement, synchronization) to the ready-made stimulation and EEG system, and therefore, it is expected to accelerate the researches requiring the measurement of evoked response and reaction time.