• Journal of IKEEE
• /
• v.14 no.2
• /
• pp.16-23
• /
• 2010

Since the interest of a brain science research is increased recently, various devices using brain waves have been developed in the field of brain training game, education application and brain computer interface. In this paper, we have developed a portable EEG measurement and a bluetooth based wireless transmission device measuring brain waves from the frontal lob simply and conveniently. The low brain signals about 10~100${\mu}V$ was amplified into several volts and low pass, high pass and notch filter were designed for eliminating unwanted noise and 60Hz power noise. Also, PIC24F192 microcontroller has been used to convert analog brain signal into digital signal and transmit the signal into personal computer wirelessly. The sampling rate of 1KHz and bluetooth based wireless transmission with 38,400bps were used. The LabVIEW programing was used to receive and monitor the brain signals. The power spectrum of commercial biopac MP100 and that of a developed EEG system was compared for performance verification after the simulation signals of sine waves of $1{\mu}V$, 0~200Hz was inputed and processed by FFT transformation. As a result of comparison, the developed system showed good performance because frequency response of a developed system was similar to that of a commercial biopac MP100 inside the range of 30Hz specially.

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

• Journal of the Ergonomics Society of Korea
• /
• v.25 no.4
• /
• pp.129-135
• /
• 2006

he purpose of this study is to measure bio-signal to investigate the driver's physiological response change under real situation using train simulator. The train simulator used in this study is KTX model and according to changes of driving situation, The bio-signal controlled by autonomic nervous system, such as GSR(Galvanic Skin Response), SpO2(Saturation percent O2), HR(Heart Rate), ECG(Electrocardiograph), EEG(Electroencephagram) and movement and response of eye were measured. Statistically significant difference in bio-signal data and eye movement activity pattern were investigated under several different driving speeds using analysis of variance (p<0.05). The GSR and HR value measured in average and mission speed operation is higher than in high-speed operation. β wave of EEG in average speed operation become more activated than in high speed operation. In accordance with a characteristic of rail vehicle, movement and response of eye in high-speed operation requiring relatively simple maneuver become less activated than in either average or mission speed operations. Conclusively, due to more careful driving controls in average and mission speed operation are required than in high-speed operation, level of mental and physical stresses of train driver was increased and observed through changes of bio-signal and eye movement measured in this study.

• Journal of Institute of Control, Robotics and Systems
• /
• v.19 no.3
• /
• pp.227-232
• /
• 2013

BCI (Brain Computer Interface) is technology to control external devices by measuring the brain activity, such as electroencephalogram (EEG), so that handicapped people communicate with environment physically using the technology. Among them, EEG is widely used in various fields, especially robot agent control by using several signal response characteristics, such as P300, SSVEP (Steady-State Visually Evoked Potential) and motor imagery. However, in order to control the robot agent without any constraint and precisely, it should take advantage of not only a signal response characteristic, but also combination. In this paper, we try to use the fusion of motor imagery and P300 from EEG for practical use of robot control in BCI environment. The results of experiments are confirmed that the recognition rate decreases compared with the case of using one kind of features, whereas it is able to classify each both characteristics and the practical use technology based on mobile robot and wireless BCI measurement system is implemented.

• Journal of Korea Society of Industrial Information Systems
• /
• v.18 no.5
• /
• pp.15-18
• /
• 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 the Korea institute of electronic communication sciences
• /
• v.13 no.2
• /
• pp.481-486
• /
• 2018

In this paper, we aimed to analysis EEG signals related to the relativity between musical stimuli and human brain activity for the arithmetical calculation and present the experimental results. We use two kinds of musical stimuli, one is a sedative tendency music and the other is a stimulative tendency music. The SMR wave and Mid-beta wave are analyzed because of the concentration. In our results, the sedative tendency music is not more interfere with human brain activity for the arithmetical calculations than the stimulative tendency music.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.6
• /
• pp.793-798
• /
• 2012

In this paper, we explored the new method for extracting feature from the electroencephalography (EEG) signal based on linear regression technique with the orthonormal polynomial bases. At first, EEG signals from electrodes around motor cortex were selected and were filtered in both spatial and temporal filter using band pass filter for alpha and beta rhymic band which considered related to the synchronization and desynchonization of firing neurons population during motor imagery task. Signal from epoch length 1s were fitted into linear regression with Legendre polynomials bases and extract the linear regression weight as final features. We compared our feature to the state of art feature, power band feature in binary classification using support vector machine (SVM) with 5-fold cross validations for comparing the classification accuracy. The result showed that our proposed method improved the classification accuracy 5.44% in average of all subject over power band features in individual subject study and 84.5% of classification accuracy with forward feature selection improvement.

• Journal of the Ergonomics Society of Korea
• /
• v.22 no.2
• /
• pp.15-28
• /
• 2003

The one of the most important factors is the platoon design on developing AH3(Advanced Highway System), as it is related to traffic efficiency and drivers' safety. This study was evaluated that how much speed is comfortable for drivers and how long distance is appropriate for vehicular gap of platoon by measuring drivers' physiology signal and sensibility. A fixed-based AHS simulator was developed by using a real vehicle cockpit and the restructured part of Korean highway for human factors evaluation. The EEG(electroencephalogram), ECG (electrocardiogram) and GSR(Galvanic Skin Response) were measured for obtaining drivers' physiology signal according to the change of speed and gap. The brain wave(${\alpha},\;{\beta},\;{\delta},\;{\theta}$) by EEG, the response of the autonomic nervous system. the sympathetic and parasympathetic nervous system, by ECG, and relax-arousal situation by GSR were analyzed. The SD(Semantic Differential) method was also applied to evaluate drivers' sensibility by 5-grade evaluation scale with 96 adjectives. SSQ(Simulator Sickness Questionnaire) was used to measure the simulator sickness of pre and post driving, two times. As the results, drivers were comfortable with 120km/h speed of platoon and lam to 15m vehicular distance. The results of this study may differ from the adaption of the reality because of many parameters. However, the purpose of this study is show to significant results of the drivers' safety and the acceptability of human factors evaluation.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.5 no.5
• /
• pp.848-852
• /
• 2001

The biomedical signals such as ECG, EMG, EEG, and etc are very Important information to diagnose patients The signal is hard to filter the noise because that is mixed with a lot of noise and biomedical signal has the properties of nonlinear and time-variance. So, we will filter under the measure environment for system or patient. But the general adaptive fillet has brought on the distortion of signal because the adaptive filter adjust the filter coefficient with the fixed order of filter, that filter has the unsuitable order in each other environment. So we propose the dynamic structure adaptive filter that is used for improving that disadvantage. In experiment, we obtain the optimal order of adaptive filter and have food results.

• Journal of Korean Institute of Industrial Engineers
• /
• v.42 no.1
• /
• pp.73-79
• /
• 2016

The purpose of this study is to understand human sensory and emotional response according to car noise. This study investigated human stress levels from car noise based on the data of electro-encephalogram (EEG) and subjective evaluation analysis data. Since there are few previous works on the effect of car noise on human's reaction, more profound research about the effect of car noise on driver's emotion would be worth performing. Subjects were exposed to five different kinds of car noises. EEG data were collected while the subject was exposed to noise. In order to process EEG data, FFT analysis was used to separate the collected EEG data into ${\alpha}$-wave and ${\beta}$-wave. Also, survey was performed to carry out subjective evaluation. The results of the subjective evaluation were closely correlated to those found in the EEG signal analysis. The results from this study may provide useful information for mitigating car noise induced stress.