• Journal of Biomedical Engineering Research
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• v.9 no.1
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• pp.31-36
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• 1988

A personal computer-based brain map is described which will display a gray scale maps showing the distribution of signals derived from the electrical activity of the brain such as EEG or EP This topographic brain mapping system has a flexibility which describe the electrode number and placement mapping onto any shaped space and generate a brain maps by incoorporated the data acquisition and processing software with conventional EEG machine.

• Journal of Korea Multimedia Society
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• v.18 no.3
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• pp.330-338
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• 2015

Gradually increasing the value of the technology, the techniques of the various security systems to protect the core technology have been developed. The proposed security scheme, which uses both a Password and the various devices, is always open by malicious user. In order to solve that problem, the biometric authentication systems are introduced but they have a problem which is the secondary damage to the user. So, the authentication methods using EEG(Electroencephalography) signals were developed. However, the size of EEG signals is big and it cause a lot of problems for the real-time authentication. And the encryption method is necessary. In this paper, we proposed an efficient real-time authentication system applied encryption scheme with junk data using chaos map on the EEG signals.

• Information Systems Review
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• v.22 no.3
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• pp.1-14
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• 2020

This study aims to contribute to the existing literature in creativity from the viewpoint of neuro-physiological analysis. Further, we looked at emotional influences on creativity within a business problem-solving context that implemented the use of a cognitive map in exploring creativity. For this purpose, we measured brain cortical activity as people solved a business strategy problem to explore the neural mechanisms of "insight problems" that are influenced by distinct emotions. Through an Electroencephalography (EEG) analysis of 34 qualified participants, we investigated the relationship between emotions and business problem-solving creativity (BPSC). Insightful results were derived such that participants primed in a negative condition evoked higher temporal alpha band activity compared to those primed in the positive condition. Meanwhile, there were no significant differences between two priming conditions on the other band activities. Therefore, this study sheds a very positive light on the scholarly value of conducting rigorous studies about the relationship between emotional states and BPSC status.

• The KIPS Transactions:PartB
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• v.9B no.1
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• pp.35-46
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• 2002

The EEG is a time series of electrical potentials representing the sum of a very large number of neuronal dendrite potentials in the brain. The collective dynamic behavior of neural mass of different brain structures can be assessed from EEG with depth electrodes measurements at regular time intervals. In recent years, the theory of nonlinear dynamics has developed methods for quantitative analysis of brain function. In this paper, we considered it is reasonable or not for ICA apply to EEG analysis. Then we applied ICA to EEG for big toe movement and separated the independent components for 15 samples. The strength of each independent component can be represented on the topological map. We represented ICA can be applied for time and spatial analysis of EEG.

• Journal of Acupuncture Research
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• v.19 no.4
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• pp.132-139
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• 2002

This study was carried to identify whether acupuncture at several meridian points can affect the human anesthesia or not using the EEG mapping. We observe the change in the brain wave patterns obtained by electroencephalogram after acupuncture. 1. It is concluded that the pattern of resting computerized EEG map in intact human is normal and acupunctuation at determined meridian points induced lesser narrow field of alpha activity, more extensive field of ${\delta}$, ${\theta}$ activity, father resulted in marked shift to cerebrofrontal dominance in field of ${\delta}$, ${\theta}$ activity by t-SPM. 2. It seems likely that acupunctuation at experimental meridian points acts on slight anesthesia or hypnosis.

• Journal of Biomedical Engineering Research
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• v.33 no.1
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• pp.15-24
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• 2012

Classification of human thought is an emerging research field that may allow us to understand human brain functions and further develop advanced brain-computer interface (BCI) systems. In the present study, we introduce a new approach to classify various mental states from noninvasive electrophysiological recordings of human brain activity. We utilized the full spatial and spectral information contained in the electroencephalography (EEG) signals recorded while a subject is performing a specific mental task. For this, the EEG data were converted into a 2D spatiospectral pattern map, of which each element was filled with 1, 0, and -1 reflecting the degrees of event-related synchronization (ERS) and event-related desynchronization (ERD). We evaluated the similarity between a current (input) 2D pattern map and the template pattern maps (database), by taking the inner-product of pattern matrices. Then, the current 2D pattern map was assigned to a class that demonstrated the highest similarity value. For the verification of our approach, eight participants took part in the present study; their EEG data were recorded while they performed four different cognitive imagery tasks. Consistent ERS/ERD patterns were observed more frequently between trials in the same class than those in different classes, indicating that these spatiospectral pattern maps could be used to classify different mental states. The classification accuracy was evaluated for each participant from both the proposed approach and a conventional mental state classification method based on the inter-hemispheric spectral power asymmetry, using the leave-one-out cross-validation (LOOCV). An average accuracy of 68.13% (${\pm}9.64%$) was attained for the proposed method; whereas an average accuracy of 57% (${\pm}5.68%$) was attained for the conventional method (significance was assessed by the one-tail paired $t$-test, $p$ < 0.01), showing that the proposed simple classification approach might be one of the promising methods in discriminating various mental states.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1983-1984
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• 2008

뇌 활동의 전기적 신호인 뇌파(EEG)와 외부 자극에 대한 유발 전위(EP)를 측정하여 실시간으로 뇌지형도를 생성하는 real-time brain mapping system을 개발하였다. 측정 전극은 32채널을 사용하였고, EEG를 실시간 및 누적 주파수 분석을 통한 뇌파의 활성도 진단, EP를 측정하여 시각적/청각적 자극에 의한 유발 전위 분석을 할 수 있다. 본 시스템은 측정 대상군의 통계적 분석을 위한 Database를 구축하였고, 신뢰성 높은 뇌파 및 유발 전위 신호를 위하여 실시간 측정과정 및 측정 후 Data 검토과정에서 다양한 Artifact 제거 알고리즘이 도입되었다. 또한, 32 채널 Brain map을 구성하여 뇌파를 공간적으로 분석 가능하며, 시간 및 주파수의 증가에 따라 Brain map을 동영상화하여 시간적/주파수적 변화에 따른 분석이 가능하다.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.265-270
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• 2000

본 연구에서는 EEG 반응을 통하여 향이 인간에 미치는 영향을 평가하였다. 24-26세의 8명의 남성 피험자를 대상으로 국제 기준 전극법에 따라 19 부위에서 EEG를 기록하여 분석하였다. 실험에 사용한 향은 Rose oil bulgarian, Lemon oil misitano, Jasmin abs, Laverder iol france (KIMEX co. Ltd) 등 4가지의 천연오일을 사용하였다. 향에 대한 선입견을 배제하고 각 피실험자별로 주관적 평가를 통하여 가장 쾌하게 느낀 향이 제시되었을 때의 뇌파와 무향 상태 뇌파에서 $\alpha$/$\beta$ 대역의 power spectrum 비를 구하여 비교하였다. 무향 상태에 비해 각 피실험자별로 가장 쾌하게 느낀 향을 제시했을 때 F3, Fz, F4, T4 부분에서 $\alpha$/$\beta$ 대역의 power spectrum 비의 통계적으로 유의한 증가를 관찰할 수 있었으며 이는 $\alpha$/$\beta$ 대역의 power spectrum 비가 향의 쾌도를 측정하는 하나의 새로운 척도가 될 수 있음을 시사한다.

• Proceedings of the KOSOMBE Conference
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• v.1993 no.11
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• pp.156-159
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• 1993

In this paper, computerized BEAM (brain electrical activity map) was implemented for objective and quantitative multichannel EEG analysis. BEAM is calculated by 4 point Interpolation method and number of elements are 5140. Representation methods of BEAH are two. One is dot density method which classify brain electrical potential 9 levels by dot density and the other is color method which classify brain electrical 12 levers by different colors. In this BEAM, instantaneous change and average energy distribution over any arbitrary time interval of brain electrical activity could be observed and analyzed easily.

• Journal of Korea Game Society
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• v.15 no.2
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• pp.105-114
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• 2015

We propose a real time user interface that utilizes emotion recognition by physiological signals. To improve the problem that was low accuracy of emotion recognition through the traditional EEG(ElectroEncephaloGram), We developed a physiological signals-based emotion recognition system mixing relative power spectrum values of theta/alpha/beta/gamma EEG waves and autonomic nerve signal ratio of ECG (ElectroCardioGram). We propose both a data map and weight value modification algorithm to recognize six emotions of happy, fear, sad, joy, anger, and hatred. The datamap that stores the user-specific probability value is created and the algorithm updates the weighting to improve the accuracy of emotion recognition corresponding to each EEG channel. Also, as we compared the results of the EEG/ECG bio-singal complex data and single data consisting of EEG, the accuracy went up 23.77%. The proposed interface system with high accuracy will be utillized as a useful interface for controlling the game spaces and smart spaces.