• Clinical and Experimental Pediatrics
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• v.59 no.11
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• pp.440-445
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• 2016

Purpose: This study aimed to identify prognostic factors of neurological outcomes, including developmental delay, cerebral palsy and epilepsy in late-preterm and term infants with perinatal asphyxia. Methods: All late-preterm and term infants with perinatal asphyxia or hypoxic-ischemic insults who admitted the neonatal intensive care unit of Inje University Sanggye Paik Hospital between 2006 and 2014 and were followed up for at least 2 years were included in this retrospective study. Abnormal neurological outcomes were defined as cerebral palsy, developmental delay and epilepsy. Results: Of the 114 infants with perinatal asphyxia, 31 were lost to follow-up. Of the remaining 83 infants, 10 died, 56 had normal outcomes, and 17 had abnormal outcomes: 14 epilepsy (82.4%), 13 cerebral palsy (76.5%), 16 developmental delay (94.1%). Abnormal outcomes were significantly more frequent in infants with later onset seizure, clinical seizure, poor electroencephalography (EEG) background activity, lower Apgar score at 1 and 5 minutes and abnormal brain imaging (P<0.05). Infants with and without epilepsy showed significant differences in EEG background activity, clinical and electrographic seizures on EEG, Apgar score at 5 minutes and brain imaging findings. Conclusion: We should apply with long-term video EEG or amplitude integrated EEG in order to detect and management subtle clinical or electrographic seizures in neonates with perinatal asphyxia. Also, long-term, prospective studies with large number of patients are needed to evaluate more exact prognostic factors in neonates with perinatal asphyxia.

• Korean Journal of Clinical Laboratory Science
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• v.37 no.2
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• pp.123-128
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• 2005

Magnetoencephalography (MEG) is the measurement of the magnetic fields produced by electrical activity in the brain, usually conducted externally, using extremely sensitive devices such as Superconducting Quantum Interference Device (SQUID). MEG needs complex and expensive measurement settings. Because the magnetic signals emitted by the brain are on the order of a few femtoteslas (1 fT = 10-15T), shielding from external magnetic signals, including the Earth's magnetic field, is necessary. An appropriate magnetically shielded room is very expensive, and constitutes the bulk of the expense of an MEG system. MEG is a relatively new technique that promises good spatial resolution and extremely high temporal resolution, thus complementing other brain activity measurement techniques such as electroencephalography (EEG), positron emission tomography (PET), single-photon emission computed tomography (SPECT) and functional magnetic resonance imaging (fMRI). MEG combines functional information from magnetic field recordings with structural information from MRI. The clinical uses of MEG are in detecting and localizing epileptic form spiking activity in patients with epilepsy, and in localizing eloquent cortex for surgical planning in patients with brain tumors. Magnetoencephalography may be used alone or together with electroencephalography, for the measurement of spontaneous or evoked activity, and for research or clinical purposes.

• Biomolecules & Therapeutics
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• v.25 no.4
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• pp.390-395
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• 2017

The present study investigated the sedative effects of Sophora flavescens (SF) and its bioactive compound, matrine through performing locomotor activity test and the electroencephalography (EEG) analysis in the rat. The underlying neural mechanism of their beneficial effects was determined by assessing c-Fos immunoreactivity and serotonin (5-HT) in the brain utilizing immunohistochemical method and enzyme-linked immunosorbent assay. The results showed that SF and matrine administration had an effect on normalization of caffeine-induced hyperactivity and promoting a shift toward non-rapid eye movement (NREM) sleep. c-Fos-immunoreactivity and 5-HT level in the ventrolateral preoptic nucleus (VLPO), a sleep promoting region, were increased in the both SF and matrine-injected groups. In conclusion, SF and its bioactive compound, matrine alleviated caffeine-induced hyperactivity and promoted NREM sleep by activating VLPO neurons and modulating serotonergic transmission. It is suggested that SF might be a useful natural alternatives for hypnotic medicine.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.1022-1028
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• 2013

It is well knowns that based on the CSP (Common Spatial Pattern) algorithm, the linear projection of an EEG (Electroencephalography) signal can be made to spaces that optimize the discriminant between two patterns. Sharing disadvantages from linear time invariant systems, CSP suffers from the non-stationary nature of EEGs causing the performance of the classification in a BCI (Brain-Computer Interface) system to drop significantly when comparing the training data and test data. The author has suggested a simple idea based on the parallel model of CSP filters to improve the performance of BCI systems. The model was tested with a simple CSP algorithm (without any elaborate regularizing methods) and a perceptron learning algorithm as a classifier to determine the improvement of the system. The simulation showed that the parallel model could improve classification performance by over 10% compared to conventional CSP methods.

• The Journal of Korean Physical Therapy
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• v.21 no.1
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• pp.65-71
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• 2009

Purpose: Numerous investigators demonstrated that adaptative changes were induced by motor skill acquisition in the central nervous system. We investigated the changes of neuroelectric potential following motor learning with serial reaction time task in young healthy subjects, using electroencephalography (EEG). Methods: Twelve right-handed normal volunteers were recruited, who have no history of neurological dysfunction and were given to written the informed consent. All subjects were assigned to flex to extend the wrist joint or flex the thumb for pressing the matched button as quickly and accurately as possible, when one of five colored lights was displayed on computer screen (red, yellow, green, blue, white). EEG was measured, whenfive types simulations ware presented randomly with equal probabilities of 20% in total 200 times at the pre and post test. And they were scheduled for 30 minutes practice session during two consecutive days in the laboratory. Results: The results showed that the reaction time at the post test was significantly reduced, compared to one of the pre test in serial reaction time task. In EEG map analysis, the broaden bilateral activation tended to be changed to the focused contralateral activation in the frontoparietal area. Conclusion: These findings showed that acquisition of motor skill led to product more fast motor execution, and that motor learning could change cortical activation pattern, from the broaden bilateral activation to the focused contralateral activation. Thus we concluded that the adaptative change was induced by motor learning in healthy subjects.

• Journal of Oriental Neuropsychiatry
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• v.23 no.2
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• pp.33-48
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• 2012

Objectives : This study aimed to assess the effects of incense smokes of 'Cheung-Woon' on the concentration and EEG in healthy individuals. Methods : A total of 48 healthy volunteers participated in this study. The volunteers were examined with K-MAS, CBT(Corsi block tapping task), and EEG before and after smelling the incense smokes of 'Cheung-Woon'. K-MAS measured the recalled words, and CBT measured the recalled positions and orders of the color boxes. EEG measured the relative power of ${\theta}$ wave, ${\alpha}$ wave, SMR wave, mid-${\beta}$ wave, high-${\beta}$ wave, ${\gamma}$ wave and T(concentraion index T = (SMR wave + mid-${\beta}$ wave) / ${\theta}$ wave). 'Cheung-Woon' consists of 7 herbal powder, known as a useful effect on the concentration and memory. Results : After smelling 'Cheung-Woon', K-MAS were increased significantly(p<0.05). In relative power of ${\theta}$ wave, F4, T3, and P4 were decreased significantly(p<0.05) and P3 was also decreased significantly(p<0.01). In the relative power of ${\alpha}$ wave, SMR wave, and mid-${\beta}$ wave, the values were not significant. In the relative power of high-${\beta}$ wave, Fp1, and P4 were increased significantly(p<0.05). In relative power of ${\gamma}$ wave, T3 were increased significantly (p<0.05). In T value, F4, T3, T4, and P4 were increased significantly(p<0.05) and P3 were also increased significantly(p<0.01). Conclusions : This results show that smelling incense smokes of 'Cheung-Woon' is an effective way of increasing concentration and memory.

• Journal of Sasang Constitutional Medicine
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• v.19 no.2
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• pp.113-126
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• 2007

1. Objectives The objective of this study was to measure the differences of EEG changes accoring to emotional stimulus in Sasangin. 2. Methods 44 healthy volunteers(Soyangin 10, Soeumin 14, Taeumin 20) were participated. Sasang Constitution was diagnosed by Sasang specialist. Volunteers watched horror movie as the emotional stimulus. We recorded EEG data during pre-stimulus rest(120sec), during-stimulus(197sec), rest-stimulus(120sec). Power spectral analysis was done and relitive power and ${\alpha}/{\beta}$ ratio were compared among each groups. 3. Results (1) The mean of relative ${\alpha}$ of Taeumin was significantly decreased according to stimulus compared with Soyagnin. (2) Relative ${\alpha}$ of Soeumin was significantly decreased in T3 area according to stimulus compared with Taeumin. (3) Relative ${\beta}$ of Taeumin group was significantly increased in Fp2 area according to stimulus compared with Soeumin. 4) Relative $high-{\beta}$ of Soyangin group was significantly decreased in F3 by the post-stimulus rest compared with Soeumin. (5) ${\alpha}/{\beta}$ ratio of Soeumin was significantly increased according to stimulus compared with other groups. 4. Conclusions Soyangin showed sensitive changes according to the emotional simulus compared with Soeumin and Taeumin. Above results suggest that the emotional characteristics of Sasangin can be measured by objective methods as by EEG.

• Journal of People, Plants, and Environment
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• v.24 no.6
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• pp.639-649
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• 2021

Background and objective: Various images from visual display terminals (VDTs) as well as living lighting are important parts of our daily life; thus, properly controlling the lighting environment - that is, illuminance, color temperature and good images from VDTs - can have a substantial effect on improving the mental health and work efficiency in everyday life. We examined electroencephalography (EEG) and heart rate variability (HRV) responses to various lighting conditions in 25 university students as they viewed images of a green landscape or traffic congestion. Methods: EEG was performed in darkness and when the room was illuminated with 10 different light-emitting diode (LED) color temperatures, while the EEG and HRV responses to green landscape or traffic congestion image stimuli were measured in darkness and during room illumination with three different LED color temperatures. Results: We found a significant difference between darkness and high LED illumination (400 lx) at 7 (CZ, F4, FZ, O1, O2, OZ, and T6) of 30 channels, while the alpha wave activity increased during darkness. In the second experiment, the green landscape image stimuli in the 30 lx-2600 K lighting condition elicited theta wave activity on the EEG, whereas the traffic congestion image stimuli under high LED illumination elicited high beta and gamma wave activities. Moreover, the subjects exhibited better stress coping ability and heart rate stability in response to green landscape image stimuli under illuminated conditions, according to their HRV. Conclusion: These results suggest that lower color temperatures and illumination levels alleviate tension, and that viewing green landscape image stimuli at low illumination, or in darkness, is effective for reducing stress. Conversely, high illumination levels and color temperatures are likely to increase tension and stress in response to traffic congestion image stimuli.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.1
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• pp.38-46
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• 2024

In general, EEG signal analysis has been the subject of several studies due to its ability to provide an objective mode of recording brain stimulation, which is widely used in brain-computer interface research with applications in medical diagnosis and rehabilitation engineering. In this study, we developed EEG reception hardware to measure electroencephalograms and implemented a processing system, classifying it into server and data processing. It was conducted as an intermediate-stage research on the implementation of a brain-computer interface using electroencephalograms, and was implemented in the form of predicting the user's arm movements according to measured electroencephalogram data. Electroencephalogram measurements were performed using input from four electrodes through an analog-to-digital converter. After sending this to the server through a communication process, we designed and implemented a system flow in which the server classifies the electroencephalogram input using a convolutional neural network model and displays the results on the user terminal.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.89-103
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• 2023

Obstructive sleep apnea (OSA) is one of the most prevalent sleep disorders that can lead to serious consequences, including hypertension and/or cardiovascular diseases, if not treated promptly. Continuous positive airway pressure (CPAP) is widely recognized as the most effective treatment for OSA, which needs the proper titration of airway pressure to achieve the most effective treatment results. However, the process of CPAP titration can be time-consuming and cumbersome. There is a growing importance in predicting personalized CPAP pressure before CPAP treatment. The primary objective of this study was to optimize the CPAP titration process for obstructive sleep apnea patients through EEG feature engineering with machine learning techniques. We aimed to identify and utilize the most critical EEG features to forecast key OSA predictive indicators, ultimately facilitating more precise and personalized CPAP treatment strategies. Here, we analyzed 126 OSA patients' PSG datasets before and after the CPAP treatment. We extracted 29 EEG features to predict the features that have high importance on the OSA prediction index which are AHI and SpO2 by applying the Shapley Additive exPlanation (SHAP) method. Through extracted EEG features, we confirmed the six EEG features that had high importance in predicting AHI and SpO2 using XGBoost, Support Vector Machine regression, and Random Forest Regression. By utilizing the predictive capabilities of EEG-derived features for AHI and SpO2, we can better understand and evaluate the condition of patients undergoing CPAP treatment. The ability to predict these key indicators accurately provides more immediate insight into the patient's sleep quality and potential disturbances. This not only ensures the efficiency of the diagnostic process but also provides more tailored and effective treatment approach. Consequently, the integration of EEG analysis into the sleep study protocol has the potential to revolutionize sleep diagnostics, offering a time-saving, and ultimately more effective evaluation for patients with sleep-related disorders.