• Child Studies in Asia-Pacific Contexts
• /
• v.5 no.2
• /
• pp.63-81
• /
• 2015

The present study examined electrical brain activations in participants playing three different video games. Forty-five adolescents between the ages of 13-17 (M=14.3 years, SD=1.5) were randomly assigned to play either a violent game, non-violent game, or brain training game. Electroencephalography (EEG) was recorded during video game play. Following game play, participants completed a questionnaire measuring prosocial personality. Results show an association between prosocial personality factors and differential patterns of brain activation in game groups. Adolescents with higher empathy playing the brain training game were positively correlated with frontal asymmetry scores, while empathy scores for those in non-violent and violent game groups were negatively linked to frontal asymmetric activation scores. Those with higher scores in helpfulness in the non-violent game group showed a positive association to left hemisphere activation. Implications behind these findings are discussed in the manuscript.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1628-1630
• /
• 1997

The purpose of this study is to see the method of the analysis of EEG(Electroencephalography) whcih is a nonlinear system, to quantize human emotion under color stimulation using the analysis of EEG. The result of this study would be used clinical study and development fo image instruments with color. In this study, the method of the analysis of EEG is power spectrum using FFT(Fast Fourier Transform) and the modelling of EEG under color stimulation base on back propagation Neural Networks ond of AI(Artfical Intellignece) skills. First, input layer make a match to relative power which get analyzing s in 4 channels, and output layer make a match to color stimulation which is measured human emotion. Finally, weights of each neurons determine by learing back porpagation Neural Networks.

• Journal of the Korean Society for Industrial and Applied Mathematics
• /
• v.12 no.3
• /
• pp.191-199
• /
• 2008

This paper proposes a new method for the inverse problem of the three-dimensional reconstruction of the electrical activity of the brain from electroencephalography (EEG). Compared to conventional direct methods using additional parameters, the proposed approach solves the EEG inverse problem iteratively without any parameter. We describe the Lagrangian corresponding to the minimization problem and suggest the numerical inverse algorithm. The restriction of influence space and the lead field matrix reduce the computational cost in this approach. The reconstructed divergence of primary current converges to a reasonable distribution for three dimensional sphere head model.

• Proceedings of the Korean Information Science Society Conference
• /
• 2010.11a
• /
• pp.21-22
• /
• 2010

Brain-Computer Interface (BCI) 는 뇌 신호를 이용하여 생각으로 기계 및 컴퓨터를 제어 할 수 있는 기술이다. 뇌전도(Electroencephalography, EEG) 를 이용한 본 연구는 왼쪽/오른쪽 손 상상 움직임 실험에 대해서 특징 추출 (feature extraction)에 관�� 연구로 총 9명의 피험자로부터 얻어진 뇌 전도 데이터를 이용하여 전통적인 방법 (Common Spatial Pattern, CSP 및 Fisher Linear Discriminant, FLDA)을 이용해 구한 분류 정확도와 본 논문에서 사용 된 Symbolic transfer entropy (STE)을 통해 얻어진 특징에 대한 결과를 보여 준다. 본 연구를 통하여 STE를 통한 특징 추출 방법이 의미가 있다고 생각한다.

• 한국HCI학회:학술대회논문집
• /
• 2009.02a
• /
• pp.330-334
• /
• 2009

본 연구는 뇌의 편측 영역 에서의 EEG(Electroencephalography) coherence 로 손동작 의도를 예측하고자 하는 연구이다. 손 동작 예측을 위한 실험에 신체에 이상이 없는 6 명의 피실험자가 참여 하였다. 실험은 데이터 트레이닝 6 분과 동작 의도 판단 6 분으로 진행되었으며 무작위 순서로 손 동작을 지시한 후 편측적 영역 5 개 지점의 EEG 와 동작 시점을 알기 위한 오른손 EMG(Electromyography)를 측정하였다. 측정된 EEG 데이터를 분석하기 위해 주파수 별 Alpha 와 Beta 를 분류하였고 EMG 신호를 기준으로 동작과 휴식으로 분류된 Alpha 와 Beta 데이터를 5 개의 측정 영역별 Coherence 분석을 하였다. 그 결과 동작과 휴식을 구분할 수 있는 통계적으로 유효한 EEG Coherence 영역을 통하여 동작 판단을 할 수 있음을 확인하였다.

• Journal of Computing Science and Engineering
• /
• v.7 no.2
• /
• pp.139-146
• /
• 2013

Recent advances in computer science enabled people with severe motor disabilities to use brain-computer interfaces (BCI) for communication, control, and even to restore their motor disabilities. This paper reviews the most recent works of BCI in stroke rehabilitation with a focus on methodology that reported on data collected from stroke patients and clinical studies that reported on the motor improvements of stroke patients. Both types of studies are important as the former advances the technology of BCI for stroke, and the latter demonstrates the clinical efficacy of BCI in stroke. Finally some challenges are discussed.

• Annals of Clinical Neurophysiology
• /
• v.10 no.1
• /
• pp.1-12
• /
• 2008

Intraoperative neuromonitoring (INM) is well known to be useful method to reduce intraoperative complications during the surgery of nervous system lesions. Evoked potentials are most commonly used among the electrophysiological tests. Brainstem auditory evoked potentials are for detecting the problems along the auditory pathways including the eighth cranial nerve and brainstem. Somatosensory evoked potentials are applied for preventing the spinal cord lesions. The INM is affected by many factors. In order to perform an optimal INM, the confounding factors including technical, anesthetical, and individual factors should be kept well under control. INM has frequent electrophysiologic changes during the surgery and it might be helpful to keep one's eyes on which monitoring modalities are reluctant to change during each operation. The skillful monitoring and timely interpretation of electrophysiologic changes can drive the patient to be undergone surgery, even in high surgical risk group.

• Annals of Clinical Neurophysiology
• /
• v.20 no.2
• /
• pp.97-100
• /
• 2018

Nonconvulsive status epilepticus (NCSE) is an unusual complication in patients treated with cefepime. An 82-year-old woman on maintenance hemodialysis was given cefepime for pneumonia. Her level of consciousness decreased since the administration of cefepime, and she was diagnosed with NCSE based on electroencephalography (EEG) findings. After discontinuation of cefepime, improvement was seen both in the level of consciousness and EEG findings. Clinicians should be aware of cefepime-induced NCSE, particularly in patients with renal failure.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.9
• /
• pp.1294-1299
• /
• 2014

The emotion is deeply affected by human behavior and cognitive process, so it is important to do research about the emotion. However, the emotion is ambiguous to clarify because of different ways of life pattern depending on each individual characteristics. To solve this problem, we use not only physiological signal for objective analysis but also hybrid unsupervised-supervised learning classifier for automatic emotion detection. The hybrid emotion classifier is composed of K-means, genetic algorithm and support vector machine. We acquire four different kinds of physiological signal including electroencephalography(EEG), electrocardiography(ECG), galvanic skin response(GSR) and skin temperature(SKT) as well as we use 15 features extracted to be used for hybrid emotion classifier. As a result, hybrid emotion classifier(80.6%) shows better performance than SVM(31.3%).

• Journal of Biomedical Engineering Research
• /
• v.31 no.1
• /
• pp.1-13
• /
• 2010

There are a great numbers of disabled individuals who cannot freely move or control specific parts of their body because of serious neurological diseases such as spinal cord injury, amyotrophic lateral sclerosis, brainstem stroke, and so on. Brain-computer interfaces (BCIs) can help them to drive and control external devices using only their brain activity, without the need for physical body movements. Over the past 30 years, several Bel research programs have arisen and tried to develop new communication and control technology for those who are completely paralyzed. Thanks to the rapid development of computer science and neuroimaging technology, new understandings of brain functions, and most importantly many researchers' efforts, Bel is now becoming 'practical' to some extent. The present review article summarizes the current state of electroencephalogram (EEG)-based Bel, which have been being studied most widely, with specific emphasis on its basic concepts, system developments, and prospects for the future.