• The Korean Journal of Pharmacology
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• v.32 no.3
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• pp.293-300
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• 1996

During the development of hepatic encephalopathy after thioacetamide (TAA) injection to rat, EEG was recorded at two different states: without or with tactile stimulation of tail at regular intervals. Calculations based on the spectral and band analysis were used. The changes in the power spectra and bands were examined in 3 different behavioral stages: normal, mild ataxia and severe ataxia. In normal rats, the stimulation produced the increase in the power of the theta $(3.5{\sim}8\;Hz)$ and the gamma $(30{\sim}50\;Hz)$ bands. These changes could not be produced in rats with the mild and severe ataxia. The changes in the power of the theta band occurred earlier than those of the beta3 and the gamma bands in the stimulated state. Gradual decreases in the spectral power of the beta3 $(21{\sim}30\;Hz)$ and the gamma bands were correlated with the progress of the stages from normal condition to mild to severe ataxia in both unstimulated and stimulated states. The results indicate that the spectral and band analysis used in this study can quantify the severity of the neurological malfunction during HE.

• Journal of IKEEE
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• v.23 no.3
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• pp.805-810
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• 2019

We present a time-frequency analysis algorithm based on the multitaper method and the state-space frameworks. In general, time-frequency representations have a trade-off between the time duration and the spectral bandwidth by the uncertainty principle. To optimize the trade-off problems, the short-time Fourier transform and wavelet based algorithms have been developed. Alternatively, the authors proposed the state-space frameworks based on the multitaper method in the previous work. In this paper, we develop a real-time algorithm to estimate variances and spectrum using the state-space framework. We test our algorithm in spectral analysis of simulated data.

• Korean Journal of Clinical Laboratory Science
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• v.48 no.2
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• pp.144-152
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• 2016

Carotid-artery stenosis may reduce cerebral perfusion, and affect cerebral neuronal activities. We examined the question of whether the recovery of cerebral-perfusion reserve after carotid-artery stenting (CAS) can affect the EEG power-spectrum. Nineteen candidates for CAS were initially recruited. Subtraction imaging of single photon emissary computerized tomography (SPECT) and an electroencephalogram (EEG) were taken twice, before and 1 month after CAS. At each time point, the EEGs were recorded before and after injection of acetazolamide (pre-ACZ EEG and post-ACZ EEG). Finally, 7 patients were enrolled after exclusion of incomplete studies. We obtained the spectral ratio (SR) of each hemisphere. SR was defined as the divided value of the power-spectrum sum of fast activities by that of slow activities. The power-spectrum values between hemispheres were compared using the inter-hemispheric index of spectral ratio (IHISR), and we examined the correlation between the power-spectrum and the cerebral-perfusion reserve. Cerebral-perfusion reserve improved after CAS on the stent side in 6 of 7 patients. In 3 patients with unilateral carotid-artery stenosis, CAS increased SR on the pre-ACZ EEGs, and IHISR on the post-ACZ EEGs. The increases of SR and IHISR were concordant with the increment of cerebral-perfusion reserve. In contrast, the results in the other patients with bilateral stenosis showed complex patterns. The SR of pre-ACZ EEGs and IHISR of post-ACZ EEGs may be useful electrophysiological markers for the blood-flow reserve after CAS in patients with unilateral carotid-artery stenosis, but not in those with bilateral stenosis.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.89-94
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• 2021

In this paper, we presented the results of analysis with data obtained through EEG measurements to confirm the effect of musical stimulus when performing mathematical tasks. While the subject was solving a mathematical task, favorite and unfavorite music classified according to the subject's preference were presented as musical stimulus and the tasks were divided into memorization task and procedure task. The data measured in the EEG experiments was divided into theta waves, SMR waves and mid-beta waves which are the frequency bands related to concentration to compare the relative power spectrum values. In our results, in the case of comparing no music with favorite music and no music with unfavorite music, a significant difference was observed in the several channels, and the average difference was shown in the channels F3 and F4 of the frontal lobe. In that channels, the power was found to be greater when the music was presented than the case where there was no music. Depending on the subject's preference, it was confirmed that favorite music showed greater brain activity than unfavorite music.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.3
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• pp.178-184
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• 2007

The EEG signal in general can be categorized as the Alpha wave, the Beta wave, the Theta wave, and the Delta wave. The alpha wave, showed in stable state, is the dominant wave for a human EEG and the beta wave displays the excited state. The subject of this paper was to recognize the stable state of EEG quantitatively using wavelet transform and power spectrum analysis. We decomposed EEG signal into the alpha wave and the beta wave in the process of wavelet transform, and calculated each power spectrum of EEG signal, using Fast Fourier Transform. And then we calculated the stable state quantitatively by stable state ratio, defined as the power spectrum of the alpha wave over that of the beta wave. The study showed that it took more than 10 minutes to reach the stable state from the normal activity in 69 % of the subjects, 5 -10 minutes in 9%, and less than 5 minutes in 16 %.

• Journal of IKEEE
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• v.14 no.2
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• pp.16-23
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• 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
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• v.23 no.2
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• pp.3-12
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• 2020

The purpose of this work is to suggest the optimal color temperature, which induces a sense of comfort for autonomous vehicle users through the analysis of biosignal using electroencephalography (EEG) and photoplethysmography (PPG). To achieve this purpose, we applied lighting with a color temperature of 3000 K, 4000 K, 5000 K, and 6000 K to the autonomous driving environment. We experimented in a laboratory equipped with a graphic driving simulator. The experimental procedure is as follows: 1) stabilization (5 min). 2) Uchida-Kraepelin test (3 min). 3) Automatic driving + lighting (3 min). This procedure was repeated four times under different color temperatures. We performed frequency analysis on a collected time-series data and calculated the power value for each frequency band through power spectrum analysis. In the case of EEG, we analyzed α- and β-waves, which are indicators of stability and arousal, respectively. In the case of PPG, we analyzed the sympathetic nervous system activity. To reduce deviations between the subjects, we normalized the data before analysis. The result of the first analysis revealed that α-wave increased only at 5000 K, while the β-wave increased at almost all color temperatures. In addition, in the case of PPG, sympathetic nervous system activity (SNSA) increased under driving conditions. The result of the second analysis revealed that the difference between β-wave and SNSA is insignificant. In conclusion, the increase in α-waves showed that EEG was most stable at 5000 K. The results of this study can be applied to the upcoming autonomous driving era to induce high driver satisfaction. Furthermore, this approach could eventually lead to the acceptance of autonomous vehicles by suggesting a positive effect of autonomous driving.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.2
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• pp.112-124
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• 2010

Studies that can find resolutions to problems of subjective psychiatric analysis must be performed and indeed they are in the process. However there still lies many problems in researches of mentality examination, which should be the foundation of finding potential resolutions. One of the biggest problems in the conventional system is that there are many different opinions by psychiatrists depending on their educations and experiences. There is no objective standard on the subjects and there is no effective psychiatric analysis method. Also, the characteristic of such examinations is that it cannot be applied to disabilities, foreigners and infants alyce the examination is ch examinconversation. The objective of this atudy is to standardize TAT(Thematic Apperception Test)analysiBallken index method so that subjective data from the examination can be excluded and the examination thus maklysithe examination objectified. Furthermore, objective result and patients' brain wave pattern is read with BCI(Brain Computer Interface) ch exaTherenvironment to Alsare it to brain wave characteristics vectors to reate brain-wave characteristics vector DB. Therefore, such DB can be utilize durlysithe examination and diagnosis to reate objective examination method and standardized diagnosis system. Thus, mentality examination can be performed only with brain-wave scans with BCI based TAT system.

• Sleep Medicine and Psychophysiology
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• v.10 no.1
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• pp.52-60
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• 2003

Objectives: Stage 1 sleep provides important information regarding interpretation of nocturnal polysomnography, particularly sleep onset. It is a short transition period from wakeful consciousness to sleep. The lack of prominent sleep events characterizing stage 1 sleep is a major obstacle in automatic sleep stage scoring. In this study, utilization of simultaneous EEG and EOG processing and analyses to detect stage 1 sleep automatically were attempted. Methods: Relative powers of the alpha waves and the theta waves were calculated from spectral estimation. A relative power of alpha waves less than 50% or relative power of theta waves more than 23% was regarded as stage 1 sleep. SEM(slow eye movement) was defined as the duration of both-eye movement ranging from 1.5 to 4 seconds, and was also regarded as stage 1 sleep. If one of these three criteria was met, the epoch was regarded as stage 1 sleep. Results were compared to the manual rating results done by two polysomnography experts. Results: A total of 169 epochs were analyzed. The agreement rate for stage 1 sleep between automatic detection and manual scoring was 79.3% and Cohen’s Kappa was 0.586 (p<0.01). A significant portion (32%) of automatically detected stage 1 sleep included SEM. Conclusion: Generally, digitally-scored sleep staging shows accuracy up to 70%. Considering potential difficulty in stage 1 sleep scoring, accuracy of 79.3% in this study seems to be strong enough. Simultaneous analysis of EOG differentiates this study from previous ones which mainly depended on EEG analysis. The issue of close relationship between SEM and stage 1 sleep raised by Kinnari remains a valid one in this study.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.155-156
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• 2008

This research measures EEG signals which are generating on head skin and extracts brain concentration level related with brain activity. We develop concentration wireless transmission system for controlling hardware by using this signal. Two channels are used for measuring EEG signal on front head and Biopac system with MP-100 and EEG100C was used for measuring EEG signal, amplifying and filtering the signal. LabView 8.5 was also used for FFT transformation, frequency and spectrum analysis of the measure 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 lego automobile device by wireless module and applied for BCI application.