• Proceedings of the Korean Information Science Society Conference
• /
• 2011.06c
• /
• pp.379-382
• /
• 2011

인터넷 뱅킹, 전자 상거래 등의 도래에 따라 생체 인식이 중요한 이슈가 되고 있다. 이에 따라 뇌전도(Electro Encephalo Graphy: EEG)로 측정되는 생체 신호를 통하여 기존 생체 인식의 단점을 보완하는 새로운 연구가 시도되고 있다. 본 논문에서는 인간 본인의 얼굴 사진에 특별한 반응을 보인다는 신경 생리학적 지식을 기반으로 한, 새로운 개인 인증 기술을 제안한다. 구체적으로는 뇌 신호 반응 유도를 위한 시각 자극 제시 패러다임의 설계 EEG신호의 특징을 추출을 위한 개인-의존적인 시간 영역 및 채널 선택 및 효율적인 분류기 설계 방법을 제안한다. 제안한 방법을 이용한 실험 결과는 EEG 기반의 개인 인증 및 인식의 가능성을 제시한다.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.11 no.9
• /
• pp.923-928
• /
• 2016

The various technologies related to the monitoring human health in real-time for the emergency situations are developing these days. Mostly the human pulse is used for measuring as the vital signs so far, but the EEG became a major research trend now. However, there are some problems measuring and sending EEG signals of all the people walking down the street to the dedicated server. Especially, there are some restrictions for collecting and sending EEG signals in 2-dimensional space in real-time. Therefore, I suggests an efficient network model using 3-dimensional space of drones to avoid the restrictions. The models are designed, simulated, and evaluated with the Opnet simulator.

• Proceedings of the Korea Contents Association Conference
• /
• 2018.05a
• /
• pp.155-156
• /
• 2018

뇌파 신호 등 생체 정보를 이용하여 상호작용적인 예술 콘텐츠를 설계 및 개발하는 방식에 대한 관심이 높아지고 있다. 이 논문은 EEG로 뇌파 신호를 수집하여 인공지능 기법으로 처리한 후에 사용자와 매체가 상호작용하는 콘텐츠 개발의 사례를 소개한다. 게임 등의 엔터테인먼트 콘텐츠와 미디어아트 등으로 연계되는 방식을 소개한다.

• Proceedings of the KIEE Conference
• /
• 2003.07d
• /
• pp.2804-2806
• /
• 2003

생체신호는 생리학이나 해부학에서 주로 다루어졌으나, 최근 컴퓨터 시스템의 발전으로 공학적인 접근이 활발히 진행되고 있다. 특히 뇌의 정보를 보여주는 EEG(Electroencephalogram) 신호의 각 주파수 대역 별 에너지 분석은 의학분야에서도 매우 큰 비중을 두고 있다. 특정 뇌신경 관련질환이 갖는 대역별 주파수 특징과 Spike등을 분석하는 것은 치료와 예방에 아주 좋은 방법의 하나가 될 수 있다. 본 논문에서는 신호처리에서 높은 효율을 보이는 Wavelet Transform을 이용하여 알츠하이머병의 EEG 신호를 분석하였다.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.8
• /
• pp.1637-1642
• /
• 2015

Next-generation applications using technology IT fused to biological signals from the emotional state to extract a lot of research has been, and the sensitivity of the human sensory functions influences the physiological condition known to be the fact that. In this paper, Propose an Emotional-lighting control algorithm using bio-signals. LED lighting for Emotion light is environmentally friendly and has a high efficiency and long life. In particular, LED lights are different colors represent the possible single light sphere advantages. And, Human sensitivity for determining a more accurate biological signals using EEG was collected using EEG equipment sensitivity was determined to analyze the EEG.

• Proceedings of the Korea Society of Information Technology Applications Conference
• /
• 2002.11a
• /
• pp.461-467
• /
• 2002

Signals reduced from the brain had been considered as a noise that is caused by the stochastic process until 1980. The recent non-linear dynamic theory researches, however, reported that these signals are meaningful and deterministic chaos signals in which they show how the brain deals with various information Since this report, a wide range of researches has been carried out and still in progress. Thus, by using the correlational dimension, one of the non-linear analytical methods, the characteristics of the brain signals can be analyzed. In this thesis, the scent of lavender, which stimulates the olfactory sense, is introduced to measure EEG with the International 10-20 electrode system on 16 channels, and to analyze the interrelationship between the original signals before the stimulation and the changed signals after the stimulation. Finally, the effect of the scent stimulation to the brain is analyzed. The purpose of this thesis is to apply these analyzed results to the computerized mapping of the brain signals and possible ways of specifying the source of the brain signals through various medical applications.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2002.11a
• /
• pp.461-467
• /
• 2002

Signals produced from the brain had been considered as a noise that is caused by the stochastic process until 1980. The recent non-linear dynamic theory researches, however, reported that these signals are meaningful and deterministic chaos signals in which they show how the brain deals with various information Since this report a wide range of researches has been carried out and still in progress. Thus, by using the correlational dimension, one of the non-linear analytical methods, the characteristics of the brain signals can be analyzed. In this thesis, the scent of lavender, which stimulates the olfactory sense, is introduced to measure EEG with the International 10-20 electrode system on 16 channels, and to analyze the interrelationship between the original signals before the stimulation and the changed signals after the stimulation. Finally, the effect of the scent stimulation to the brain is analyzed. The purpose of this thesis is to apply these analyzed results to the computerized mapping of the brain signals and possible ways of specifying the source of the brain signals through various medical applications.

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

• Journal of Biomedical Engineering Research
• /
• v.16 no.3
• /
• pp.301-308
• /
• 1995

A high-precision pre-amplifier is designed for general use in EEG measurement system. It consists of signal generator, signal amplifier with a impedance converter, shield driver, body driver, differential amplifier, and isolation amplifier. The combination of minimum use of inaccurate passive components and the appropriate matching of each monolithic amplifiers results in good noise behavior, low leakage current, high CMRR, high input impedance, and high IMRR. The performance of EEG pre-amplifier has been verified by showing the typical EEG pattevn of a nomad person through the clinical experiments.

• Journal of the Korea Convergence Society
• /
• v.11 no.2
• /
• pp.17-22
• /
• 2020

In this paper, we measured the user's EEG signal and classified the EEG signal using the Support Vector Machine algorithm and measured the accuracy of the signal. An experiment was conducted to measure the user's EEG signals by separating men and women, and a single channel EEG device was used for EEG signal measurements. The results of measuring users' EEG signals using EEG devices were analyzed using R. In addition, data in the study was predicted using a 80:20 ratio between training data and test data by applying a combination of specific vectors with the highest classifying performance of the SVM, and thus the predicted accuracy of 93.2% of the recognition rate. This paper suggested that the user's EEG signal could be recognized at about 93.2 percent, and that it can be performed only by simple linear classification of the SVM algorithm, which can be used variously for biometrics using EEG signals.