• Journal of Information Technology Applications and Management
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• v.9 no.4
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• pp.165-177
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• 2002

For measuring EEG with the international 10-20 electrode system on 16 channels, and to analyze the interrelationship between the original signals and the changed signals after the stimulation, we use the scent of lavender which stimulates the olfactory sense. Moreover, the effect of the scent stimulation to the brain is analyzed. The purpose of this analysis is to apply these results to the computerized mapping of the brain signals and to find possible ways of specifying the source of the brain signals through various medical applications.

• Korean Journal of Cognitive Science
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• v.20 no.2
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• pp.125-154
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• 2009

This paper describes the possibility of human physiological data, especially brain-wave activity, to detect cognitive overload, a phenomenon that may occur while learner uses an e-learning system. If it is found that cognitive overload to be detectable, providing appropriate feedback to learners may be possible. To illustrate the possibility, while engaging in cognitive activities, cognitive load levels were measured by EEG (electroencephalogram) to seek detection of cognitive overload. The task given to learner was a computerized listening and recall test designed to measure working memory capacity, and the test had four progressively increasing degrees of difficulty. Eight male, right-handed, university students were asked to answer 4 sets of tests and each test took from 61 seconds to 198 seconds. A correction ratio was then calculated and EEG results analyzed. The correction ratio of listening and recall tests were 84.5%, 90.6%, 62.5% and 56.3% respectively, and the degree of difficulty had statistical significance. The data highlighted learner cognitive overload on test level of 3 and 4, the higher level tests. Second, the SEF-95% value was greater on test3 and 4 than on tests 1 and 2 indicating that tests 3 and 4 imposed greater cognitive load on participants. Third, the relative power of EEG gamma wave rapidly increased on the 3rd and $4^{th}$ test, and signals from channel F3, F4, C4, F7, and F8 showed statistically significance. These five channels are surrounding the brain's Broca area, and from a brain mapping analysis it was found that F8, right-half of the brain area, was activated relative to the degree of difficulty. Lastly, cross relation analysis showed greater increasing in synchronization at test3 and $4^{th}$ at test1 and 2. From these findings, it is possible to measure brain cognitive load level and cognitive over load via brain activity, which may provide atimely feedback scheme for e-learning systems.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.204-215
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• 2020

People who have sleep disorders such as insomnia take a long time to get to sleep, namely sleep latency. In order to reduce it, effective stimulations and environments to induce sleep such as ASMR or pink noise are necessary. However these have different effects and preferences for each individual. Therefore customized service and control for the sleep induction will be provide to him/her. In this paper, we proposed SIS control system which provides selectively sound control among various kinds of ASMR and pink noise according to sleep state measured from brain wave data for an individual. In order to verify the effectiveness of the system, we had conducted totally 30 experiments for 5 people, and all EEG data measured from all the people during sleep. An average of 3.7 hours was spent per experiment. In comparison experiments with and without sound control for sleep induction, the latency time was reduced by an average of 8 minutes as well as delta waves and theta waves, which appear only in deep sleep, are increased by 21%.

• Journal of the Korean Society for information Management
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• v.36 no.3
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• pp.131-148
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• 2019

This study constructed a cognitive model of information processing to understand the topic of a sound material and its characteristics. It then proposed methods to generate sound summaries, by incorporating anterior-posterior N400/P600 components of event-related potential (ERP) response, into the language representation of the cognitive model of information processing. For this end, research hypotheses were established and verified them through ERP experiments, finding that P600 is crucial in screening topic-relevant shots from topic-irrelevant shots. The results of this study can be applied to the design of classification algorithm, which can then be used to generate the content-based metadata, such as generic or personalized sound summaries and video skims.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.170-174
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• 2007

Although research efforts for brain waves have prospered in medicine and engineering, acupuncture still has a long way to go regarding researches on brain waves analysis. Thus this study set out to analyze brain waves stimulated by indirect mugwort moxibustion, which was part of acupuncture techniques, and to investigate their correlations with the automatic nervous system. For the experiments, stimulation was given to Jungwan, Shingwol and Gwanwon, which were some of the spots on the body suitable for acupuncture, through indirect mugwort moxibustion. The subjects' brain waves were measured before the stimulation, during the stimulation, and one hour and two hours after the stimulation. The measurements were analyzed with Matlab 7.0 for FFT and frequency power spectrum. Then the ${\alpha}$, ${\beta}$, ${\delta}$, and ${\theta}$ waves were analyzed and examined for changes to the percentage of each frequency and to the amplitude of vibration according to the stages of stimulation. The EEG data of the entire brain were translated into FFT to analyze the percentage of the ${\alpha}$, ${\beta}$, ${\delta}$, and ${\theta}$ waves. As a result, the ${\alpha}$ waves recorded a double increase after the stimulation. The power spectrum analysis results of the entire brain decreased the ${\alpha}$ and ${\beta}$ waves dropping in the energy level, which suggested that the parasympathetic nerves were activated. When the results of the study were compared with those of the previous study, it's confirmed that indirect moxibustion stimulation could cause changes to the automatic nervous system and bring stability to those who were nervous or under stress due to the proportionate increase of the ${\alpha}$ waves.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.4
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• pp.238-244
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• 2019

In this study, we compared and analyzed the performance of each Convolution Neural Network (CNN) by implementing the CNN that reflected the characteristics of the cerebral structure, in order to analyze the CNN that was used for the prediction of cybersickness, and provided the performance varying depending on characteristics of the brain. Dizziness has many causes, but the most severe symptoms are considered attributable to vestibular dysfunction associated with the brain. Brain waves serve as indicators showing the state of brain activities, and tend to exhibit differences depending on external stimulation and cerebral activities. Changes in brain waves being caused by external stimuli and cerebral activities have been proved by many studies and experiments, including the thesis of Martijn E. Wokke, Tony Ro, published in 2019. Based on such correlation, we analyzed brain wave data collected from dizziness-inducing environments and implemented the dizziness predictive artificial neural network reflecting characteristics of the cerebral structure. The results of this study are expected to provide a basis for achieving optimal performance of the CNN used in the prediction of dizziness, and for predicting and preventing the occurrence of dizziness under various virtual reality (VR) environments.

• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.104-111
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• 2019

The purpose of this study is to know the change of brain wave with stress by SUKI pressure alternative therapy. The experiment group was 12 students(male 6/female 6) with complained upper trapezius pain. Calculated the brain wave before and after stimulate the upper trapezius trigger point by SUKI and the stimulate time was 3min each persons(FP2, F3, F4, FP1, T3, T4, P3, P4). the experimet periods was 5times in a weeks with EEG(QEEG-S). The Date collecting used by Telescan(LXE5209). All the data was analyzed with SPSS 22.0 for window program. To compare the differences before and after the point pressure method, a corresponding sample of t-test was performed, and the statistical significance level was p<.05. The results was followed. The points of Fp2, F3, F4(*p<0.049, *p<0.042, *p<0.019) of EEG was showed a significant differences but Fp1, T3, T4, P3, P4 points did not showed. The SUKI alternative medicine techniques had a reduced effects for the some kind of brain stress. It is need to continuous research in the future.

• 한국어정보학회:학술대회논문집
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• 2016.10a
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• pp.231-234
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• 2016

프로그래머들이 코딩을 할 때 발생하는 빈번한 실수는 많은 시간적 비용을 낭비할 수 있고 작은 실수가 전체 코드에 치명적인 에러를 유발하기도 한다. 이러한 문제점은 프로그래머들이 코드를 작성할 때 전체적인 알고리즘을 얼마나 잘 이해하는지와 이전 코드에 대한 이해력과 연관이 있다. 만약 코드에 대한 이해가 어렵다면 정교하고 간결한 코드를 작성하는데 무리가 있을 것이다. 기존 코드에 대한 난이도를 평가하는 방법은 자가평가 등을 통해 이루어져 왔다. 사람 내부 변화를 직접 측정하면 더 객관적인 평가가 가능할 것이다. 본 논문은 이런 문제들을 해결하고자 동공 추적이 가능한 아이트래커와 뇌파 측정이 가능한 EEG장비를 이용하여 습득한 생체 데이터를 통해 프로그래머들의 프로그램 난이도 예측 모델을 개발하였다.

• Science of Emotion and Sensibility
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• v.3 no.2
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• pp.41-55
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• 2000

경영활동에 있어서 직관력은 잘 알려진 인지능력이지만 효과적인 의사결정지원시스템의 개발 목적으로는 거의 고려되고 있지 않다. 본 연구는 의사결정자의 인지 유형에 따른 시계열 예측의 정확성과 뇌파의 차이를 통계적 검증, 인공신경망, 데이터 마이닝의 세 가지 접근방법으로 탐색하여 그 결과를 비교 분석함으로써 시계열 직관 예측에 영향을 주는 의사결정자의 인지적/생리적 특성을 도출함으로써 효과적인 의사결정환경을 조성하는데 공헌하고자 하였다. 실험결과 통계적 분석에서는 아무런 유의성을 찾을 수 없었으나, 인공신경망 분석에서는 인지유형과 감성유형이 모두 시계열 예측 정확도와 상관성이 있는 것으로 나타났으며, 데이터 마이닝 분석에서는 보다 의미 있는 상관관계를 찾아낼 수 있었다.

• Annual Conference on Human and Language Technology
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• 2016.10a
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• pp.231-234
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• 2016

프로그래머들이 코딩을 할 때 발생하는 빈번한 실수는 많은 시간적 비용을 낭비할 수 있고 작은 실수가 전체 코드에 치명적인 에러를 유발하기도 한다. 이러한 문제점은 프로그래머들이 코드를 작성할 때 전체적인 알고리즘을 얼마나 잘 이해하는지와 이전 코드에 대한 이해력과 연관이 있다. 만약 코드에 대한 이해가 어렵다면 정교하고 간결한 코드를 작성하는데 무리가 있을 것이다. 기존 코드에 대한 난이도를 평가하는 방법은 자가평가 등을 통해 이루어져 왔다. 사람 내부 변화를 직접 측정하면 더 객관적인 평가가 가능할 것이다. 본 논문은 이런 문제들을 해결하고자 동공 추적이 가능한 아이트래커와 뇌파 측정이 가능한 EEG장비를 이용하여 습득한 생체 데이터를 통해 프로그래머들의 프로그램 난이도 예측 모델을 개발하였다.