• Weed & Turfgrass Science
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• v.7 no.2
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• pp.130-139
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• 2018

The colors of packaging of herbicides and non-selective herbicides on the market in Korea are defined as brown and red, respectively, according to the notification of RDA. The present study aimed to understand consumer's electroencephalographic (EEG) response when looking at brown and red colors of herbicide and non-selective herbicide packaging papers. The EEG cap was placed on the scalp of each participant (men and women, 10 to 20 years old) and white (control) - brown - white - red colors were sequentially displayed for 5 seconds using the computer monitor. The EEG was measured and statistical analysis was performed using SPSS. For the brown color of the herbicide, men showed a decrease in concentration and a distracting response due to a decrease in the ratio of mid beta to theta (RMT) and the spectral edge of frequency (SEF90). In women, an increase in the ratio of SMR to theta (RSMT) and the spectral edge frequency 50% of the alpha (ASEF) was observed in different brain regions and these EEG changes may enhance the relaxation, stabilization and awakening states of the brain. For the red color of the non-selective herbicide, ASEF increased psychological stability in men. In women, a decrease in absolute high beta (AHB) may associate with a decrease in attention state of the brain. Overall data of the present study clearly revealed that the colors of two herbicides showed significantly different EEG response and gender difference.

• Korean Journal of Acupuncture
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• v.21 no.1
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• pp.29-40
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• 2004

Objectives : The aim of this study was to examine the effects of electroacupuncture(EA) at the $H_7$ (Shinmun) on normal humans using power spectral analysis. Methods : EEG power spectrum exhibit site-specific and state-related differences in specific frequency bands. In this study, power spectrum was used as a measure of complexity. 32 channel EEG study was carried out in 9 subjects (9 males; age=25,8 years). Results : In alpha band, the power values at Fp2 channels(p<0.05) during the $H_7-acupoint$ treatment significantly were decreased. In beta band, the power values at Fp1, Fp2 channels(p<0.05) during the $H_7-acupoint$ treatment significantly were decreased. In delta and theta band, the power values at the $H_7-acupoint$ treatment significantly was increased than the before-acupuncture treatment. Conclusions : This results suggest that electroacupuncture at the $H_7$ is significantly in beta band of EEG.

• Korean Journal of Acupuncture
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• v.20 no.3
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• pp.9-27
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• 2003

Objectives : The aim of this study was to examine the effects of electro-acupuncture(EA) at the SP6(Sameumgyo)-GB39(Hyeonjong) on normal human EEG using power spectral analysis. Methods : EEG power spectrum exhibit site-specific and state-related differences in specific frequency bands. In this study, power spectrum was used as a measure of complexity(LAXTHA Co., KOREA). 30 channel EEG study was carried out in 20 subjects $(20\;males;\;age=21.4{\pm}0.5\;years)$. Results : In $\alpha$(alpha) band, the power values at F4 channels(p<0.05) during the SP6-GB39 acupoints treatment was significantly increased. But, the power values at Fz channel during the non-acupoint treatment was significantly decreased . In $\beta$(beta) band, the power values at Fz, FTC1, T3 channels(p<0.05) was significantly increased during the SP6-GB39 acupoints treatment. In $\delta$(delta) band, the power values at F4, C3, Cz, CP1, Pz channels(p<0.05) during SP6-GB39 acupoints treatment were significantly decreased.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.65
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• pp.65-73
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• 2001

In this study, psychophysiological stress was quantitatively evaluated at various car interior noise levels by using Electroencephalogram(EEG). An experiment was performed to investigate the most comfortable range of noise level during simulated driving condition. Twelve healthy volunteers participated in the experiment. They were asked to operate the driving simulator while six levels of interior noise were given, such as 45dB(A), 50dB(A), 55dB(A), 60dB(A), 70dB(A), 80dB(A), and maximal subjective noise level. EEG signals were recorded for 60 seconds in each noise level. The power spectral analysis was performed to analyze EEG signal. At the same time, psychological stress was also measured subjectively by using a magnitude estimation method. The results showed that subjective stress and EEG spectrum indicated a statistically significant difference between noise levels. In particular, high level noise produced an increase in beta power at temporal(T3, T4) areas. It was also found that beta activity was highly correlated with subjective perception of discomfort, and subjects responded to car interior noise as arousing or negative stimuli. Moreover, beta power remained stable above 70dB(A), whereas subjective discomfort continued to increase even above 70dB(A) We concluded that brain waves could provide psychophysiological information of drivers emotional reaction to car interior noise. Thus, EEG parameters could be a new measure to determine optimal noise level in ergonomic workplace design after further verification in various experimental conditions.

• Annals of Clinical Neurophysiology
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• v.3 no.1
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• pp.31-36
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• 2001

Background & Objectives : Fractal Dimension(FD) could be an index of correlation between variable parameters in non-linear chaotic signals. We tried to demonstrate that EEG wave is compatible with chaotic waves by measuring the Lyapunov exponent index and compared the difference of FD between variable age groups(teens, 30's, 50's) Methods : We estimated the Lyapunov exponent index and the FD from digital EEG data among five persons in each normal age groups by using the software which is programmed in our laboratory. Statistical analysis was done with SPSS win 8.0. The statistical differences of Lyapunov exponent index and FD between each electrodes and each age groups were done with ANOVA and paired sample t-test. Result : The Lyapunov exponent indexes were larger than 1 in each electrode and age group. There is no statistical difference in FD between each electrodes and each age groups. Except in 30th age group. In this group the FD of right hemisphere is larger than that of left hemisphere. Conclusion : The result of Lyapunov exponent index means EEG wave is a non-linear chaotic signal. And the results of FD suggest that chaotic parameters of right hemisphere is larger than those of left hemisphere at rest at least in younger people. We think that chaotic parameters can be a useful tool in investigating the variable diseases or brain states.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.7
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• pp.71-78
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• 2017

There are several algorithms to classify emotion, such as Support-vector-machine (SVM), Bayesian decision rule, etc. However, many researchers have insisted that these methods have minor problems. Therefore, in this paper, we propose a novel method for emotion recognition based on Electroencephalogram (EEG) signal using the Gradient method which was proposed by Han. We also utilize a database for emotion analysis using physiological signals (DEAP) to obtain objective data. And we acquire four channel brainwaves, including Fz (${\alpha}$), Fp2 (${\beta}$), F3 (${\alpha}$), F4 (${\alpha}$) which are selected in previous study. We use 4 features which are power spectral density (PSD) of the above channels. According to performance evaluation (4-fold cross validation), we could get 85% accuracy in valence axis and 87.5% in arousal. It is 5-7% higher than existing method's.

• Annals of Clinical Neurophysiology
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• v.21 no.1
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• pp.16-29
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• 2019

Background: Sex influences is important to understand behavioral manifestations in a large number of neuropsychiatric disorders. We found electrophysiological differences specifically related to the influence of sex on psychopathic traits. Methods: The resting electroencephalography (EEG) activity and low-resolution brain electromagnetic tomography (LORETA) for the EEG spectral bands were evaluated in 38 teenagers with conduct disorder (CD). The 25 male and 13 female subjects had psychopathic traits as diagnosed using the Antisocial Process Screening Device. All of the included adolescents were assessed using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) criteria. The visually inspected EEG characteristics and the use of frequency-domain quantitative analysis techniques are described. Results: Quantitative EEG (QEEG) analysis showed that the slow-wave activities in the right frontal and left central regions were higher and the alpha-band powers in the left central and bitemporal regions were lower in the male than the female psychopathic traits group. The current source density showed increases in paralimbic areas at 2.73 Hz and decreases in the frontoparietal area at 9.37 Hz in male psychopathics relative to female psychopathics. Conclusions: These findings indicate that QEEG analysis and techniques of source localization can reveal sex differences in brain electrical activity between teenagers with CD and psychopathic traits that are not obvious in visual inspections.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.295-301
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• 2021

Individual mental fatigue not only reduces cognitive ability and work performance, but also becomes a major factor in large and small accidents occurring in daily life. In this paper, a CNN model for EEG-based mental fatigue discrimination was proposed. To this end, EEG in the resting state and task state were collected and applied to the proposed CNN model, and then the model performance was analyzed. All subjects who participated in the experiment were right-handed male students attending university, with and average age of 25.5 years. Spectral analysis was performed on the measured EEG in each state, and the performance of the CNN model was compared and analyzed using the raw EEG, absolute power, and relative power as input data of the CNN model. As a result, the relative power of the occipital lobe position in the alpha band showed the best performance. The model accuracy is 85.6% for training data, 78.5% for validation, and 95.7% for test data. The proposed model can be applied to the development of an automated system for mental fatigue detection.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.254-259
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• 2015

In this paper, The wireless robot control system was proposed using Brain-computer interface(BCI) systems based on the steady-state visual evoked potential(SSVEP). Cross Power Spectral Density(CPSD) was used for analysis of electroencephalogram(EEG) and extraction of feature data. And Linear Discriminant Analysis(LDA) and Support Vector Machine(SVM) was used for patterns classification. We obtained the average classification rates of about 70% of each subject. Robot control was implemented using the results of classification of EEG and commanded using bluetooth communication for robot moving.

• Sleep Medicine and Psychophysiology
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• v.15 no.2
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• pp.71-76
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• 2008

Introduction: In this study, we compared sleep structure, EEG characteristic of pediatric obstructive sleep apnea (OSA) and normal controls which were matched in sex and age. Methods: Fifteen children (male：female=4：11) who complained snoring and were suspected to have sleep apnea and their age and sex matched normal controls (male：female=5：10) have been done nocturnal polysomnography (NPSG). Sleep parameters, sleep apnea variables and relative spectral components of EEG from NPSG have been compared between both groups. Results: Pediatric OSA group were distinguished from normal controls in terms of apnea index, respiratory disturbance index and nadir of oxyhemoglobulin desaturation. Pediatric OSA group showed increased percent of sleep stage 1, decreased rapid eye movement sleep percent and increased delta power in O1 EEG channel. However other sleep parameters and spectral powers were not different between two groups. Conclusion: In pediatric OSA group, sleep structure parameter disruption may be not prominent as the previous studies for adult OSA group because of including mild OSA data in diagnostic criteria. In addition, EEG changes might not be distinct due to low arousal index compared to adult OSA patients. We can observe general characteristics and particularity of pediatric OSA through this study.