• Annals of Clinical Neurophysiology
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• v.2 no.1
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• pp.8-12
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• 2000

Purpose : The rapid development and wide popularity of Digital EEG(DEEG) is due to its convenience, accuracy and applicability for quantitative analysis. These advantages of DEEG make one hesitate to use analog EEG(AEEG). To assess the advantage of DEEG system utilizing AEEG(DAEEG) over conventional AEEG and the clinical applicability, a DAEEG system was developed and applied to animal model Methods : Sprague-Dawley rat as status epilepticus model were used for collecting the EEG data. After four epidural electrodes were inserted and connected to 8-channel analog EEG(Nihon-Kohden, Japan), continous. EEG monitoring via computer screen was done from two rats simultaneously. EEG signals through analog amplifier and filters were digitized at digital signal processor and stored in Windows-based pentium personal computer. Digital data were sampled at a rate of 200 Hz and 12 bit of resolution. Acquisition software was able to carry out 'real-time view, sensitivity control and event marking' during continuous EEG monitoring. Digital data were stored on hard disk and hacked-up on CD-ROM for off-line review. Review system consisted of off-line review, saving and printing out interesting segment and annotation function. Results: This DAEEG system could utilize most major functions of DEEG sufficiently while making a use of an AEEG. It was easy to monitor continuously compared to Conventional AEEG and to control sensitivity during ictal period. Marking the event such as a clinical seizure or drug injection was less favorable than AEEG due to slowed processing speed of digital processor and central processing unit. Reviewing EEG data was convenient, but paging speed was slow. Storage and management of data was handy and economical. Conclusion : Relatively simple digital EEG system utilizing AEEG can be set-up at n laboratory level. It may be possible to make an application for clinical purposes.

• Journal of Biomedical Engineering Research
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• v.26 no.1
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• pp.49-54
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• 2005

This paper presents a design of 1-channel active dry electrode module for EEG from one's forehead. The IA(instrumentation amplifier) circuit inside the module is based on the configuration sown on the paper MettingVanRijn et al. We analyze the IA circuit to find out the related equation, and then compare its simulated characteristic with the result obtained from the real active dry electrode circuit. With the active dry electrode and the wet(Ag/AgCI) electrode connected to the separated analog processing module on one's forehead at the same time, their real time and FFT outputs of EEG are examined for comparison. The active dry electrode module has advantages over the wet electrode and its analog processing module: 1) The size of the analog processing circuit of the active dry electrode module is smaller than that of existing EEG analog processing module; 2) the total cost required to make the proposed analog processing circuit is much lower than that of the existing circuit, since the designed circuit needs smaller parts; 3) the electrical characteristic is comparable to the general EEG analog processing module even if the designed module has simpler circuit configuration.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.145-147
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• 2009

This research measures EEG signals which are generating on head skin and extracts brain concentration level related with brain activity. We have developed concentration wireless transmission system by displaying this EEG signal on PDA mobile device. The front head was used for measuring EEG signal and INA128 with TL084 and analog elements was used for measuring EEG signal, amplifying and filtering the signal. Measured analog EEG signals changed into digital signals by using ADC of PIC24FJ192 with 10bit resolution and 500Ks/s sampling rate. So The changed digital signals have transmitted to the PDA by using bluetooth. LabView 8.5 was also used for FFT transformation, frequency and spectrum analysis of the transferred EEG signal. As a result, $\alpha$ wave, $\beta$ wave, $\theta$ wave and $\delta$ wave were classified. we extracted the concentration index by adapting concentration extraction algorithm. This concentration index was transferred into PDA by wireless module and displaying.

• Journal of Korea Society of Industrial Information Systems
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• v.18 no.5
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• pp.15-18
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• 2013

This paper presents an analog front-end for electroencephalogram(EEG) signal processing. Since EEG signals are typically weak and located at very low frequencies, it is imperative to implement an amplifier with high gain, high common-mode rejection ratio(CMRR) and good noise immunity at very low frequencies. The analog front-end of this paper consists of a programmable-gain instrumentation amplifier and a band-pass filter. A frequency chopping technique is employed to remove the low-frequency noise. The circuits were fabricated in 0.18um CMOS technology and measurements showed that the analog front-end has the maximum gain of 60dB and >100dB CMRR over the programmable gain range.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.7
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• pp.623-629
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• 2013

This paper presents the implementation result of the EEG(electroencephalogram) signal transmission protocol and its test platform. EEG measured by a dry-type electrode is directly converted into digital signal by ADC(analog-to-digital converter). Thereafter it is transferred DSP(digital signal processor) platform by $I^2C$(inter-integrated circuit) protocol. DSP conducts the pre-processing of EEG and extracts feature vectors of EEG. In this work, we implement the $I^2C$ protocol with 16 channels by using 10 or 12-bit ADC. In the implementation results, the overhead ratio for the 4 bytes data burst transmission measures 2.16 and the total data rates are 345.6 kbps and 414.72 kbps with 10-bit and 12-bit 1 ksps ADC, respectively. Therefore, in order to support a high speed mode of $I^2C$ for 400 kbps, it is required to use 16:1 and $(8:1){\times}2$ ratios for slave:master in 10-bit ADC and 12-bit ADC, respectively.

• 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.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.38-46
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• 2024

In general, EEG signal analysis has been the subject of several studies due to its ability to provide an objective mode of recording brain stimulation, which is widely used in brain-computer interface research with applications in medical diagnosis and rehabilitation engineering. In this study, we developed EEG reception hardware to measure electroencephalograms and implemented a processing system, classifying it into server and data processing. It was conducted as an intermediate-stage research on the implementation of a brain-computer interface using electroencephalograms, and was implemented in the form of predicting the user's arm movements according to measured electroencephalogram data. Electroencephalogram measurements were performed using input from four electrodes through an analog-to-digital converter. After sending this to the server through a communication process, we designed and implemented a system flow in which the server classifies the electroencephalogram input using a convolutional neural network model and displays the results on the user terminal.

• 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.

• Journal of Biomedical Engineering Research
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• v.22 no.1
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• pp.81-90
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• 2001

본 연구에서는 디지털 영상 뇌파계(digital video electroencephalogram, Digital VEEG)에서 비디오 영상과 뇌전도 파형의 동기화된 편집 시스템을 구성한다. 이 시스템은 기존 아날로그 영상 뇌파계(analog video electroencephalogram)의 동기화 문제와 디지털 영상 시스템에서의 영상편집 문제를 해결하기 위하여 MPEG-I(이하 MPEG) 고압축 기술을 이용한 MPEG 인코딩 보드(encoding board)와 MPEG 편집 엔진(editing engine)을 각각 사용하였다. 시스템은 디지털 영상뇌파계모듈과 디지털 편집 모듈로 구성되며, 뇌전도모듈에서는 환자에게 연결된 전극을 통해 들어온 뇌파를 생체신호증폭기를 이용하여 증폭한 후 AD 보드(analog to digital board)를 이용 디지털화한다. 디지털 카메라로 촬영된 환자영상의 아날로그 영상신호(NTSC 신호)는 MPEG 인코딩 보드를 이용하여 고압축 디지털화한다. 이후 디지털화된 뇌전도신호와 MPEG 형식의 영상을 시간 동기화하여 두 개의 모니터에 각각보여준다. 편집 모듈에서는 영상신호와 뇌파신호를 어느 부분이든 간단한 조작으로 오려 붙이기(cut and paste) 기능을 이용할 수 있다. 본 시스템은 사용된 데이터 모두 디지털 기술을 이용하여 영상과 뇌파신호의 정확한 동기화 및 각각의 데이터의 오려 붙이기 기능을 가능케 하였으며, 이는 환자의 데이터를 관리 및 보관하는데 있어, 임상의에게 의미 있는 자료만을 모아서 효율적으로 관리할 수 있게 해준다. 이와 같은 장점을 갖는 디지 영상뇌파계 편집시스템을 구현하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.12
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• pp.452-458
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• 2017

In this study, a device was developed for diagnosing depression using EEG signals from July 2016 to June 2017. For normal people, the left alpha rhythm is more activated than the right alpha rhythm, but for the depressed patients, the right alpha rhythm is more activated than the left one. An analog circuit and digital low pass filter were used for noise removal and amplification of EEG, and the Hamming window function was applied to eliminate the signal leakage generated by the fast Fourier transform. To verify the validity of the developed diagnosis system, the EEG of 20 university students in the 3rd and 4th grade with an average age of 24 years was measured. Calculations of the relative value of the left and right alpha rhythm for the depression diagnosis revealed a minimum, maximum, and mean value of 66.7, 113.3, and 92.2, respectively. In addition, 7 out of 20 subjects were between 90 and 95, and those with a higher mean deviation of approximately 20 tended to have mild depression. These results can provide meaningful data for the development of depression treatment equipment by solving the left and right brain asymmetry problem, and it may be applied usefully to diagnose depression after clinical trials on a large number of depressed patients.