• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.4
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• pp.773-778
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• 2020

In this paper, we analyzed the effects of musical stimuli on humans in performing mathematical tasks through EEG measurements. The musical stimuli were divided into preferred music and non-preferred music, and mathematical tasks were divided into memorization task and procedure task. The data measured in the EEG experiments was divided into frequency bands of Theta, SMR, and Mid-beta because of the concentration. In our results, preferred music causes more positive emotional response than no music and non-preferred music regardless of the type of mathematical task.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.958-961
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• 2015

Emotional expression is universal and emotional state impacts important areas in our life. Until now, analyzing the acquired EEG signals under circumstances caused by invoked feelings and efforts to define their emotional state have been made mainly by psychologists based on the results. But, recently emotion-related information was released by research results that it is possible to identify mental activity through measuring and analyzing the brain EEG signals. So, this study has compared and analyzed emotional expressions of human by using brain waves. To get EEG difference for a particular emotion, we showed specific subject images to the people for changing emotions that peace, joy, sadness and stress, etc. After measured EEG signals were converged into frequence domain by FFT signal process, we have showed EEG changes in emotion as a result of the performance analyzing each respective power spectrum of delta, theta, alpha, beta and gamma waves.

• Sleep Medicine and Psychophysiology
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• v.15 no.1
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• pp.5-11
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• 2008

Sleep is an essential process maintaining the life cycle of the human. In parallel with physiological, cognitive, subjective, and behavioral changes that take place during the sleep, there are remarkable changes in the electroencephalogram (EEG) that reflect the underlying electro-physiological activity of the brain. However, analyzing EEG and relating the results to clinical observations is often very hard due to the complexity and a huge data amount. In this article, I introduce several linear and non-linear tools, developed to analyze a huge time series data in many scientific researches, and apply them to EEG to characterize various sleep states. In particular, the spectral analysis, detrended fluctuation analysis (DFA), and synchrony analysis are administered to EEG recorded during nocturnal polysomnography (NPSG) processes and daytime multiple sleep latency tests (MSLT). I report that 1) sleep stages could be differentiated by the spectral analysis and the DFA ; 2) the gradual transition from Wake to Sleep during the sleep onset could be illustrated by the spectral analysis and the DFA ; 3) electrophysiological properties of narcolepsy could be characterized by the DFA ; 4) hypnic jerks (sleep starts) could be quantified by the synchrony analysis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.397-400
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• 2015

Due to the anesthesia process is inappropriate on the operation, awakening state was appeared. Because of that patients suffered from severe mental and physical pain. To prevent the state, it is necessary to monitor the patients by measuring the depth of anesthesia. In this study, we investigate the possibility of the development of actual surgery available quantitative indicators. The DFA(detrended fluctuation analysis) which is included the correlation property of the EEG is used to analysis the depth of anesthesia and bispctrum index. In the results, at the pre-operation, the peak of bispectrum was widely distributed, DFA value was decreased. At the during operation, bispectrum was concentrically appeared in the low frequency area. At the post operation, bispectrum and DFA was both returned to the pre-operation state. As a result, we confirmed to be close correlation between the peaks of the bispectrum and DFA value.

• Sleep Medicine and Psychophysiology
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• v.15 no.1
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• pp.33-38
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• 2008

Introduction: It has been proposed that narcolepsy and REM sleep behavior disorder (RBD) have overlapped symptom profile and pathophysiology. This study was aimed at measuring and comparing changes in EEG frequency band of REM sleep in narcolepsy and RBD, applying EEG spectral analysis method. Methods: Nine patients diagnosed as narcolepsy and the same number of RBD patients were studied. Spectral analysis of the REM sleep EEG was performed in each patient on 9 epochs selected evenly from the first, second, and third REM periods. Then, we compared frequency band percentages of REM sleep EEG in narcolepsy and RBD. Results: Narcolepsy patients had significantly higher delta frequency ratio than RBD ones (p=0.00). In alpha and beta2 frequency bands, RBD patients showed higher percentage than narcolepsy ones. Slow wave sleep was more prevalent in narcolepsy patients. But, no difference of REM sleep percentage was found between the two groups (p=0.93). Conclusion: Higher delta frequency ratio in REM sleep of narcolepsy patients than RBD ones reflects that sleep-promoting mechanism is more dominant in narcolepsy than in RBD.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.367-372
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• 2023

In this paper, we analyzed through the EEG signals how musical stimulus affects learning activities. Musical stimuli were divided into sedative and stimulative tendency music, preferred and non-preferred music, and the learning activity tasks were divided into mathematics tasks and memorization tasks. The signals measured in the EEG experiments were analyzed with the power spectrum of SMR waves known to be related to human concentration. Those spectra used for quantitative comparison in this paper. As a result the power of the EEG signals was observed to be greater than the case where music was given as a stimulus. Regardless of the type of task, the power of the EEG signals was observed to be greater in the case of sedative tendency than in the case of stimulative tendency, and the power of the EEG signals was observed to be greater in the case of favorite music than in the case of unfavorite music. From these results, it is estimated that if the musical stimulus exists, in the case of sedative tendency music, and in the case of favorite music, concentration can be increased than in the relative case.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2755-2760
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• 2010

The moxibustion therapy of orient medical is well known. Moxibustion method is used to burning moxibustion. The variation factors of the moxibustion stimulation for body can be applied to the electronic moxibustion method. This study is to analyze and examine the electroencephalogram(EEG) variations for moxibustion stimulation. In experiment, we divided six healthy male subjects into two same sized groups : with and without stimuli. The given stimuli are the moxibustion for CV4(Kwan-Won), CV8(Shin-Guel), and CV12(Jung-wan) acupuncture points. We have analyzed the power spectrum for ${\alpha}$, ${\beta}$, ${\delta}$, ${\Theta}$ waves and the average EEG variation level and each channels variation level of EEG. The result was that the moxibustion stimulation decreased the EEG levels of parietal lobe(ch 2, 3, 6, 7) according to the somatosensory system. And the apparent different points are that mild-heat($42{\sim}44^{\circ}C$) stimulation generating ${\alpha}$-wave is increased and ${\beta}$-wave is decreased, also slight-hot($45{\sim}48^{\circ}C$) stimulation made ${\alpha}$-wave decrease and ${\beta}$-wave increase for occipital lobe(ch 4,8) on the simulation group.

• Sleep Medicine and Psychophysiology
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• v.17 no.2
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• pp.91-99
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• 2010

Objectives: Deficit schizophrenia (DS) constitutes a disease separate from non-deficit schizophrenia (NDS). The aim of the current study was to compare the quantitative EEG and low resolution electromagnetic tomography (LORETA) imaging between DS and NDS. Methods: This study was performed by 32 channels EEG for 42 schizophrenia patients who we categorized into DS and NDS using proxy instrument deficit syndrome (PDS). We performed the absolute power spectral analyses for delta, theta, alpha, low beta and high beta activities. We compared power spectrum between two groups using Independent t-test. Partial correlation test was performed with clinical parameters. Standardized LORETA (sLORETA) was used for comparison of cortical activity, and statistical nonparametric mapping (SnPM) was applied for the statistical analysis. Results: DS showed significantly increased delta and theta absolute power in fontal and parietal region compared with NDS (p<0.05). Power spectrum showed significant correlation with 'anergia' and 'hostility/suspiciousness' subscale of brief psychiatric rating scale (BPRS)(p<0.05). sLORETA found out the source region (anterior cingulate cortex/limbic part) that delta activity was significantly increased in DS (p=0.042). Conclusions: DS showed different cortical activity compared with NDS. Our results may suggest QEEG and LORETA could be the marker in differentiating between DS and NDS.

• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.42-50
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• 2011

Using EEG, human physiological signal, as part of research which investigates the state of student learning and provides appropriate feedback to maximize learning efficiency, the relationship of learning attitude and analysis of EEG for female college student is presented. We study the reaction of learner's EEG using the concentration level extracted from the EEG power spectrum when students learn at various learning attitude. The experiment was conducted for the concentrating on learning and, as a control group, erratic attitude and closed eyes state. The attitude of concentrated Learning shows high concentration index and low relaxation index, where as the erratic attitude, such as eye movement and clicking, shows high level of attention index and noisy wave ratio. Especially, the state of closed eyes shows the ratio of alpha and theta wave under 1. This is distinct with open eyes cases.

• Sleep Medicine and Psychophysiology
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• v.26 no.1
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• pp.44-48
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• 2019

Objectives: Insomnia is one of the most prevalent sleep disorders. Recent studies suggest that cognitive and physical arousal play an important role in the generation of primary insomnia. Studies have also shown that information processing disorders due to cortical hyperactivity might interfere with normal sleep onset and sleep continuity. Therefore, focusing on central nervous system arousal and normalizing the information process have become current topics of interest. It has been well known that neurofeedback can reduce the brain hyperarousal by modulating patients' brain waves during a sequence of behavior therapy. The purpose of this study was to investigate effects of neurofeedback therapy on electroencephalography (EEG) characteristics in patients with primary insomnia. Methods: Thirteen subjects who met the criteria for an insomnia diagnosis and 14 control subjects who were matched on sex and age were included. Neurofeedback and sham treatments were performed in a random order for 30 minutes, respectively. EEG spectral power analyses were performed to quantify effects of the neurofeedback therapy on brain wave forms. Results: In patients with primary insomnia, relative spectral theta and sigma power during a therapeutic neurofeedback session were significantly lower than during a sham session ($13.9{\pm}2.6$ vs. $12.2{\pm}3.8$ and $3.6{\pm}0.9$ vs. $3.2{\pm}1.0$ in %, respectively; p < 0.05). There were no statistically significant changes in other EEG spectral bands. Conclusion: For the first time in Korea, EEG spectral power in the theta band was found to increase when a neurofeedback session was applied to patients with insomnia. This outcome might provide some insight into new interventions for improving sleep onset. However, the treatment response of insomniacs was not precisely evaluated due to limitations of the current pilot study, which requires follow-up studies with larger samples in the future.