• Journal of Life Science
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• v.22 no.8
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• pp.1077-1084
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• 2012

This study investigated the effects of Origanum majorana essential aroma therapy on electrical activity in the brain as evaluated by an electroencephalogram (EEG). The subjects were 29 healthy female young adults, and their sleep quality was assessed by using the Pittsburgh Sleep Quality Index. EEG electrodes were attached at the frontal, temporal, occipital, and parietal lobes according to the international 10-20 system. Subjects were exposed to organic Origanum majorana essential aroma (50 ${\mu}l$) for a period of 3 minutes each before, during, and after aromatherapy. Subjects with good sleep quality showed that Origanum majorana essential aroma increased the theta power at the frontal and temporal lobes of both cerebral hemispheres, the left parietal lobe, and the right occipital lobe. Furthermore, Origanum majorana essential aroma decreased the alpha power at the left occipital lobe and the beta power at the right temporal lobe. On the other hand, subjects with poor sleep quality showed an increase in the theta power at the temporal lobe of both cerebral hemispheres and a decrease in the alpha power at the left parietal lobe by Origanum majorana essential aroma therapy. It is concluded that Origanum majorana essential aroma therapy diminishes the state of wakefulness in the brain; alpha and beta powers were both decreased in the subjects with good sleep quality, but only alpha power was decreased in the subjects with poor sleep quality. Moreover, Origanum majorana essential aroma therapy has a sleep-inducing effect in both subjects with good sleep quality and poor sleep quality.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.1
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• pp.61-66
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• 2010

The purpose of this experiment is to analyze the basic status of brain. Which are consist of rest, attention and concentration, of the brain by measuring the temperature of color by changing RGB color after manufacturing LED-illumination stand. Basic status (rest, attention and concentration) of experimenter were measured temperature of colors having three difference temperature like as $2,300^{\circ}K$, $4,000^{\circ}K$ and $6,000^{\circ}K$. The results was shown that experimenter feels more comfortable and relaxation by decreasing the temperature of color. For example we can see the little increase of concentration index at $4,000^{\circ}K$ condition and we can estimate that right brain can be more activated at the $4,000^{\circ}K$ condition. But we can not find out any different at the $6,000^{\circ}K$ condition. Main cause of no difference from the color temperature was the similarity of color temperature under the general fluorescent lamp. And interface temperature of radiant heat design results LED and PCB was approximately 80 degrees to COMSOL Multiphysics, and changed until approximately 50 degrees until a floor plane of PCB, and verification as arranged chip LED to metal PCB, and it was possible, and a near radiant heat design was confirmed to an approximate value of, as a result, acid manufacture.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.103-108
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• 2016

In daily life, humans get stress very often. Stress is one of the important factors of healthy life and closely related to the quality of life. Too much stress is known to cause hormone imbalance of our body, and it is observed by the brain and bio signals. Based on this, the relationship between brain signal and stress is explored, and brain signal based stress index is proposed in our work. In this study, an EEG measurement device with 32 channels is adopted. However, only two channels (FP1, FP2) are used to this study considering the applicability of the proposed method in real enveironment, and to compare it with the commercial 2 channel EEG device. Frequency domain features are power of each frequency bands, subtraction, addition, or division by each frequency bands. Features in time domain are hurst exponent, correlation dimension, lyapunov exponent, etc. Total 6 subjects are participated in this experiment with English sentence reading task given. Among several candidate features, ${\frac{{\theta}\;power}{mid\;{\beta}\;power}}$ shows the best test performance (70.8%). For future work, we will confirm the results is consistent in low price EEG device.

• Clinical and Experimental Pediatrics
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• v.53 no.4
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• pp.560-564
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• 2010

Purpose : Electroencephalography (EEG) findings can play a critical role in a variety of decisions, including initiation and withdrawal of antiepileptic drugs (AEDs) therapy. Interictal epileptiform discharges (IEDs) are predictor of recurrent seizures. We investigated IEDs in EEG after AED therapy and related factors in epileptic children. Methods : The subjects were 257 children [151 males and 106 females; age, 6.79 (3.40) years; duration of therapy, 2.48 (1.85) years] diagnosed with epilepsy at the Department of Pediatrics, Pusan National University Hospital between January 2001 and December 2007, who received AEDs for more than 6 months. EEG was performed at the intervals of 6-12 months. We divided patients into 4 groups according to IED detection before and after AEDs treatment. Related clinical factors, including gender, age at the start of treatment, seizure type, cause of seizure, AED frequency, seizure control, duration of AED therapy, and background activity were investigated in the 4 groups. Results : Generalized epilepsy was relatively frequen in patients who did not show IEDs in last follow-up EEG. There were no clinically significant differences according to gender, age at the start of treatment, cause of seizure, AED frequency, seizure control, duration of AED medication, and background activity in the 4 groups ($P$>0.05). Conclusion : IEDs changed after AED treatment in one-third of the patients. Generalized epilepsy is positive factor for negative IEDs in last follow-up EEG.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2007.02a
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• pp.35-40
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• 2007

본 논문에서는 사운드디자이너가 주어진 영상조건 속에서 음원(sound source)을 어떻게 구성하고, 디자인하고, 믹싱하는가 에 따라 수용자의 그 감응도(감정적변화:sympathy response)와 인지도(이해와 기억도:acknowl-edgment)가 달라질 수 있는가를 분석하고자 한 것이다. 그 방법으로 영상음향의 구조에서 음악, 음향, 대사의 상호크기, 연결, 편집, 강조, 등을 달리한 영상 내에서 사운드디자인과 믹싱을 달리하여 실험하였으며 주관적평가방법과 뇌파변화측정방법 2가지로 하여 비교, 평가 분석하고자 했다. 사운드의 디자인구조가 수용자에게 미치는 영향도를 알아보는 이러한 연구는 영화, 방송 등 미디어사운드에서 사운드디자인 구조를 어떻게 만들어야 하는가? 에 대한 방법론적 정리에 기여할 것으로 기대된다.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1397-1398
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• 2015

본 연구에서는 뇌파를 이용하여 자동차에 HUD를 적용하였을 때, HUD의 위치와 이미지 컬러 변경 시 뇌 활성화 지수(Brain Activity Quotient)의 변화를 관찰하였다. 뇌파데이터는 Fp1, Fp2, O1, O2 총 4채널에서 얻었고, HUD위치는 좌측, 중앙, 우측으로 구성하였고 컬러는 초록, 주황, 빨강 총 3가지 색상을 사용하였다. HUD이미지의 크기는 $8{\times}4.5cm^2$로 구성하였다. 뇌 활성화 지수는 상대파워분석(Relative power analysis)를 사용하여 Slow beta wave(13~20 Hz)/alpha wave(4~7.99 Hz)로 계산하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.947-950
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• 2015

In the cause of car accidents in Korea, drowsy driving has shown that it is larger fctors than drunk driving. Therefore, in order to prevent drowsy driving accidents, drowsiness detection and warning system for drivers has recently become a very important issue. Furthermore, Many researches have been published that measuring alpha wave of EEG signals is the effective way in order to be aware of drowsiness of drivers. In this study, we have developed EEG measuring device that applies a signal processing algorithm using the LabView program for detecting drowsiness. According to results of drowsiness inducement experiments for small test subjects, it was able to detect the pattern of EEG, which means drowsy state based on the changing of power spectrum, counterpart of alpha wave. After all, Comparing to the results of drowsiness pattern between commercial equipments and developed device, we could confirm acquiring similar pattern to drowsiness pattern. With this results, the driver's drowsiness prevention system expect that it will be able to contribute to lowering the death rate caused by drowsy driving accidents.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.3
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• pp.136-141
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• 2012

One of the main reasons for serious road accidents is driving while drowsy. For this reason, drowsiness detection and warning system for drivers has recently become a very important issue. Monitoring physiological signals provides the possibility of detecting features of drowsiness and fatigue of drivers. One of the effective signals is to measure electroencephalogram (EEG) signals and electrooculogram (EOG) signals. The aim of this study is to extract drowsiness-related features from a set of EEG signals and to classify the features into three states: alertness, drowsiness, sleepiness. This paper proposes a neural-network-based drowsiness detection system using Linear Predictive Coding (LPC) coefficients as feature vectors and Multi-Layer Perceptron (MLP) as a classifier. Samples of EEG data from each predefined state were used to train the MLP program by using the proposed feature extraction algorithms. The trained MLP program was tested on unclassified EEG data and subsequently reviewed according to manual classification. The classification rate of the proposed system is over 96.5% for only very small number of samples (250ms, 64 samples). Therefore, it can be applied to real driving incident situation that can occur for a split second.

• Journal of Korea Game Society
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• v.15 no.4
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• pp.189-198
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• 2015

This paper is about a serious game controlled by EEG and motion capture. We developed our game for 2 users competitive and its method is as follows. One player uses a controlling interface using EEG signals based on the premise that the player's facial movements are a depiction of the player's emotion and intensity throughout the game play. The other player uses a controlling interface using kinect's motion capture technology which captures the player's vertical and lateral movements as well as state of running. The game shows the first player's EEG as a real-time graphic along the map on the game screen. The player will then be able to pace himself based on these visualization graphics of his brain activities. This results in higher concentration for the player throughout the game for a better score in the game. In addition, the second player will be able to improve his physical abilities since the game action is based on real movements from the player.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.813-815
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• 2016

This paper implements a device control system based on the brain wave data. Brain-Computer Interface (BCI) technology can pass directly to the system without going through the operation of the language or body. By controlling the device to detect brain waves in real time according to the change of status it helps to ease life for a variety of services, such as disabled people with limited mobility or students, people who need multi-tasking. In addition, it is possible to develop an application service such as the home device control system. A device control system implemented in the paper based on the data collected from the EEG Headset associated to control the power of the smart phone and audio. Control the power ON / OFF operation by the Attention, and support service functions to control the audio by the Meditation and Eye blink. It was confirmed that the device control using the brain wave data to be operated through a laboratory test successfully.