• Journal of Sensor Science and Technology
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• v.21 no.2
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• pp.156-166
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• 2012

Over the past 15 years productive BCI research programs have arisen. Current mainstream EEG electrode setups permit efficient recordings but most of electrodes has the disadventages of need for skin preparation and gel application to correctly record signals. The new gel-free probe was adapted for EEG recording and it can be fixed to the scalp with the micro needle without neuro-gel. It use standard EEG cap for wearing electrodes on scalp so it is compatible with standard EEG electrodes. A comparison between electrode characteristics is achieved by performing simultaneous recordings with the gel electrodes and gel-free probe placed in parallel scalp positions on the same anatomical regions. The quality of EEG recordings for all two types of experimental conditions is similar for gel-electrodes and gel-free probe. Subjects also reported not having special tactile sensations associated with wearing of gel-free probes. According to our results, it is expected that gel-free probe can be adapted to BCI, BMI(Brain Machine Interface), HMI(Human Machine Interface) because of its simple application and comfortable wearing process.

• 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 Biomedical Engineering Research
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• v.28 no.2
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• pp.258-264
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• 2007

Spatiotemporal changes of brain rhythmic activity at a certain frequency have been usually monitored in real time using scalp potential maps of multi-channel electroencephalography(EEG) or magnetic field maps of magnetoencephalography(MEG). In the present study, we investigate if it is possible to implement a real-time brain activity monitoring system which can monitor spatiotemporal changes of cortical rhythmic activity on a subject's cortical surface, neither on a sensor plane nor on a standard brain model, with a high temporal resolution. In the suggested system, a frequency domain inverse operator is preliminarily constructed, considering the individual subject's anatomical information, noise level, and sensor configurations. Spectral current power at each cortical vertex is then calculated for the Fourier transforms of successive sections of continuous data, when a single frequency or particular frequency band is given. An offline study which perfectly simulated the suggested system demonstrates that cortical rhythmic source changes can be monitored at the cortical level with a maximal delay time of about 200 ms, when 18 channel EEG data are analyzed under Pentium4 3.4GHz environment. Two sets of artifact-free, eye closed, resting EEG data acquired from a dementia patient and a normal male subject were used to show the feasibility of the suggested system. Factors influencing the computational delay are investigated and possible applications of the system are discussed as well.

• Journal of Sensor Science and Technology
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• v.12 no.3
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• pp.121-127
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• 2003

In this study, we carried out a study for implementation of the pre-amplifier and the digital signal processing part for the potable EEG biofeedback system. As we consider characteristics of the EEG signal, we designed the pre-amplifier to obtain the EEG signal to be reduced noise signal. Because the EEG signal include EOG, EMG, ECG signals etc, it is difficult to analyze of the EEG signal. Therefore, we developed DSP board and operation program which was embed the LMS adaptive filter algorithm and operate with the pre-amplifier in the real time. The simulation signal and pure EEG signal is used in the experiment. As the result, we confirmed good efficiency of developed system and possibility of application to the portable EEG biofeedback system.

• Journal of Sensor Science and Technology
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• v.24 no.6
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• pp.392-397
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• 2015

Recently computer games have been widely spread. For the purpose of studying brain activities, EEG was measured during the computer game and analyzed in terms of channels and frequency bands. EEG data were obtained during the resting state and game immersion. Then the power spectra of alpha, beta and theta bands were computed. During game immersion, the ratio between theta / alpha could effectively differentiate between rest and game immersion. Changes in brain activity (26~53%) were observed in the parietal and occipital lobes. Interestingly, immersion shows different features compared to concentration. The state of game immersion could be detected. Therefore, it is possible to utilize the state of immersion as one of the game parameters or to generate a control signal that may be used to provide a warning message or abort the game when the situation of the excessive indulgence in the game reaches. EEG can be applied as smart interface for computer game.

• Journal of IKEEE
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• v.22 no.4
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• pp.1109-1114
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• 2018

Electroencephalogram (EEG) is a tool used to study brain activity caused by external stimuli. In this process, artifacts are mixed and it is easy to distort the signal, so post-processing is necessary to remove it. Independent Component Analysis (ICA) is a widely used method for removing artifact. This method has a disadvantage in that it has excellent performance but some loss of brain wave information. In this paper, we propose a method to reduce EEG information loss by restricting the filter coverage using eye blink information obtained from Eyetracker. We then compared the results of the proposed method with the conventional method using quantization methods such as Signal to Noise Ratio (SNR) and Spectral Coherence (SC).

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.140-147
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• 2021

EEG(electroencephalogram) are measured to accurately determine the level of sleep in various sleep examinations. In general, measurements are more accurate as the number of sensor channels increases. EEG can interfere with sleep by attaching electrodes to the skin when measuring. It is necessary for self sleep care to select the minimum number of EEG channels that take into account both the user's discomfort and the accuracy of the measurement data. In this paper, we proposed a sleep stage analysis model based on machine learning and conducted experiments for using from one channel to four channels. We obtained estimation accuracy for sleep stage as following 82.28% for one channel, 85.77% for two channels, 80.33% for three channels and 68.87% for four channels. Although the measurement location is limited, the results of this study compare the accuracy according to the number of channels and provide information on the selection of channel numbers in the EEG sleep analysis.

• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.1-9
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• 2018

A keyboard system for hands-free virtual reality head mounted display using electrooculogram (EOG) signal which occurs during the eye-blinking is proposed. This system consists of display device, gyroscope sensor, gravity sensor and electro-encephalogram (EEG) sensor, and it is implemented with Unity3D engine for system control and graphic processing. If the input language of proposed keyboard system is Korean, i.e. Hangul, the Chonjiin keyboard method is utilized; but for the English spelling, numbers or special characters, $3{\times}4$ keyboard method is used in order to solve the spatial problem. By the implemented method, it can be verified that the user can handle the keyboard input of virtual reality head mounted display with only neck movement and EOG, instead of using hands.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.169-178
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• 2020

This paper presents a study investigating the relationship between stress level and reworks for construction professionals. As employees' work-life balance (WLB) becomes more important nowadays, controlling the level of stress in the workplace becomes more important as occupational stress has negative impacts on WLB. Reworks can be one severe occupational stressor as people suffer from stress when they need to redo their works. This study hypothesizes that there is a positive correlation between reworks and level of stress, meaning that people tend to show high level of stress when they need to redo their works. The hypothesis will be tested by checking the stress level when engineers redo their works because of changes or errors. An electroencephalography (EEG) sensor will be used to measure the stress level of engineers when they redo their works. For more accurate measure of stress, the stress level will also be measured by the galvanic skin response (GSR). This experiment is expected to prove that rework process is a severe stressor for construction professionals, which will contribute to lower productivity and poorer WLB. The finding will emphasize the importance of managing reworks in the construction industry, which will eventually help construction managers to control the level of employees' stress successfully.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.136-144
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• 2015

The EEG system can be classified as a wired or wireless device. Each device used for the medical or entertainment purposes. The collected EEG signals from sensor are analyzed using feature extractions. A wireless EEG system provides good portability and convenience, however, it requires a mobile system that has heavy computing power. In this paper a single board system is proposed to handle EEG signal processing for BCI applications. Unfortunately, the computing power of a single board system is limited unlike general desktop systems. Thus, parallel approach using multiple single board systems is investigated. The parallel EEG signal processing system that we built demonstrates superlinear speedup for an EEG signal processing algorithm.