• 동의생리병리학회지
• /
• 제25권6호
• /
• pp.1113-1118
• /
• 2011

In this paper, when a physician make a diagnosis of the pattern identification (PI) in Korean stroke patients, the development methods of the PI classification function is considered by diagnostic questionnaire of the PI for stroke patients. Clinical data collected from 1,502 stroke patients who was identically diagnosed for the PI subtypes diagnosed by two physicians with more than 3 years experiences in 13 oriental medical hospitals. In order to develop the classification function into PI using Korean Stroke Syndrome Differentiation Standard was consist of the 44 items (Fire heat(19), Qi deficiency(11), Yin deficiency(7), Dampness-phlegm(7)). Using the 44 items, we took diagnostic and prediction accuracy rate through of discriminant model. The overall diagnostic and prediction accuracy rate of the PI subtypes for discriminant model was 74.37%, 70.88% respectively.

• 한국정보디스플레이학회:학술대회논문집
• /
• 한국정보디스플레이학회 2008년도 International Meeting on Information Display
• /
• pp.943-946
• /
• 2008

Many works have been done to enable computer, as brain of robot, to learn color categorization, most of them rely on modeling of human color perception and mathematical complexities. This paper aims at developing the innate ability of the computer to learn the human-like color categorization.

• 한국콘텐츠학회논문지
• /
• 제7권8호
• /
• pp.41-49
• /
• 2007

BCI시스템은 뇌 자체에서 발생하는 전기적인 신호를 측정하여 콘트롤 또는 통신 시스템에 접목시키는 것이다. 이 시스템은 뇌파의 움직임을 실시간으로 검출하고 이를 통해 발생된 신호를 사용하여 전자장비 또는 소프트웨어에 바탕을 둔 프로세서 등을 조정할 수 있다. 본 논문에서는 다양한 정신 상태에서 발생한 뇌전위 신호를 분석하고 인식하는 뇌-컴퓨터간 인터페이스 시스템을 개발할 때 뇌파 측정시 혼합되는 잡음제거 및 분리에 관한 것을 다루고자 한다. BCI시스템 구현을 위한 뇌파 분류과정에서 이분법의 수리적 모델을 사용하여 뇌파를 분류하고 잡음구간을 추출하는 방법을 제안하였다.

• Journal of Korean Neurosurgical Society
• /
• 제53권2호
• /
• pp.102-107
• /
• 2013

Objective : The Leksell Gamma Knife$^{(R)}$ (LGK) is based on a single-fraction high dose treatment strategy. Therefore, independent verification of the Leksell GammaPlan$^{(R)}$ (LGP) is important for ensuring patient safety and minimizing the risk of treatment errors. Although several verification techniques have been previously developed and reported, no method has ever been tested statistically on multiple LGK target treatments. The purpose of this study was to perform and to evaluate the accuracy of a verification method (modified variable ellipsoid modeling technique, MVEMT) for multiple target treatments. Methods : A total of 500 locations in 10 consecutive patients with multiple brain tumor targets were included in this study. We compared the data from an LGP planning system and MVEMT in terms of dose at random points, maximal dose points, and target volumes. All data was analyzed by t-test and the Bland-Altman plot, which are statistical methods used to compare two different measurement techniques. Results : No statistical difference in dose at the 500 random points was observed between LGP and MVEMT. Differences in maximal dose ranged from -2.4% to 6.1%. An average distance of 1.6 mm between the maximal dose points was observed when comparing the two methods. Conclusion : Statistical analyses demonstrated that MVEMT was in excellent agreement with LGP when planning for radiosurgery involving multiple target treatments. MVEMT is a useful, independent tool for planning multiple target treatment that provides statistically identical data to that produced by LGP. Findings from the present study indicate that MVEMT can be used as a reference dose verification system for multiple tumors.

• 대한전자공학회논문지SP
• /
• 제42권5호
• /
• pp.55-62
• /
• 2005

본 논문에서는 인간의 인지학적인 두뇌 원리인 대뇌피질과 해마 신경망을 공학적으로 모델링하여 얼굴 영상의 특징 벡터들을 고속 학습하고, 각 영상의 최적의 특징을 구성할 수 있는 해마 신경망 모델링 알고리즘인 HNMA(Hippocampal Neuron Modeling Algorithm)을 이용한 얼굴인식 시스템을 제안한다. 시스템은 크게 특징추출 부분과 학습 및 인식 부분으로 구성 되어 있으며, 특징추출 부분에서는 PCA(Principal Component Analysis)와 LDA (Linear Discriminants Analysis)를 순차적으로 적용하여 분별력이 좋은 특징들로 구성한다. 학습부분에서는 해마 신경망 구조의 순서에 따라 입력되는 영상 데이터의 특징들을 치아 이랑 영역에서 호감도 조정에 따라서 반응 패턴으로 이진화 하고, CA3 영역에서 자기 연상 메모리 단계를 거쳐 노이즈를 제거한다. CA3의 정보를 받는 CAI영역에서는 신경망에 의해 학습되어 장기기억이 만들어 진다. 제안한 시스템의 성능을 평가하기 위하여 실험은 표정과 포즈변화 그리고 저 화질 이미지를 각각 구분하여 인식률을 확인하였다. 실험 결과, 본 논문에서 제안하는 특징 추출 방법과 학습 방법을 다른 방법들과 비교하였을 때, 학습시간비용과 인식률에서 우수함을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
• /
• pp.70-73
• /
• 1992

This paper describes the modeling of human memory using a nerve field model which is proposed for modeling the mechanism of brain mathematically. In our model, two phases of memory, retention and recollection, are focused on. The former consists of two stages, short-term memory (STM) and long-term memory (LTM). The proposed model consists of three parts, the STM Layer, LTM Layer and the Intermediate Layer between them. Each of these is constructed by a nerve field. In the STM Layer, memorized information is retained dynamically in the form of the reverberating states of units within the layer, while in the LTM Layer, it is stored statically in the form of structures of the weight on the links between units. the Intermediate Layer is introduced to translate this dynamic representation in the STM Layer to the LTNI Layer, and also to extract the static information from the STM Layer. In addition to this, we consider the recollection of information stored in the LTM. Finally, the behavior of this model is demonstrated by computer simulation.

• 한국산학기술학회논문지
• /
• 제16권8호
• /
• pp.5096-5110
• /
• 2015

본 연구는 치료레크리에이션 프로그램 참가에 따른 치매노인의 뇌파 변화가 우울감 및 수면장애와 삶의 질에 미치는 효과를 실증적으로 규명하는데 목적이 있다. 이를 위해 대전광역시 소재 치매요양센터 및 시립노인전문병원에 입원 중인 65세 이상의 남 녀 노인 중 3개월간 규칙적인 치료레크리에이션 프로그램에 참가한 집단을 실험집단으로 그리고 특정한 치료레크리에이션 프로그램에 참가하지 않은 집단을 통제집단으로 선정하였으며, 참가 사전과 사후의 뇌파 변화와 우울감, 수면장애 및 삶의 질 수준을 측정하였다. 실험집단과 참가하지 않는 통제집단에 각각 20명씩 전체 40명을 연구대상으로 하였으나, 프로그램 참여 후 탈락되는 대상으로 인해 실험집단 14명, 통제집단 18명으로 최종 분석 대상이 되었다. 자료 분석의 주된 통계적 방법은 SPSS Version 17.0과 AMOS 7.0을 이용하여 공변량분석(ANCOVA)과 구조방정식모형분석(Analysis of Structural Equation Modeling)을 이용하여 인과관계를 분석하였다. 이러한 연구방법을 통하여 도출한 결과는 첫째, 치료레크리에이션 프로그램 참가는 노인의 뇌파, 우울감 및 수면장애와 삶의 질에 긍정적인 영향을 미쳤으며, 둘째, 치료레크리에이션 프로그램 참가에 따른 뇌파의 변화는 우울감 및 수면장애와 삶의 질 간에 인과관계가 있는 것으로 나타났다.

• 전자통신동향분석
• /
• 제33권6호
• /
• pp.58-68
• /
• 2018

A neuromorphic hardware that mimics biological perceptions and has a path toward human-level artificial intelligence (AI) was developed. In contrast with software-based AI using a conventional Von Neumann computer architecture, neuromorphic hardware-based AI has a power-efficient operation with simultaneous memorization and calculation, which is the operation method of the human brain. For an ideal neuromorphic device similar to the human brain, many technical huddles should be overcome; for example, new materials and structures for the synapses and neurons, an ultra-high density integration process, and neuromorphic modeling should be developed, and a better biological understanding of learning, memory, and cognition of the brain should be achieved. In this paper, studies attempting to overcome the limitations of next-generation neuromorphic hardware technologies are reviewed.

• 대한의용생체공학회:의공학회지
• /
• 제29권2호
• /
• pp.89-98
• /
• 2008

NIRS (Near-infrared Spectroscopy) and DOI (Diffuse Optical Imaging) are relatively new, non-invasive, and non-ionizing methods that measure or image optical properties (Scattering and Absorption Coefficient) and physiological properties (Water Fraction, concentration of Oxy-, Deoxy-Hemoglobin, Cytochrome Oxidase, etc) of biological tissues. In this paper, three different types of NIRS systems, mathematical modeling, and reconstruction algorithms are described. Also, recent applications such as functional brain imaging, optical mammography, NIRS based BMI (Brain-Machine Interface), and small animal study are reviewed.

• Investigative Magnetic Resonance Imaging
• /
• 제23권2호
• /
• pp.148-156
• /
• 2019

Hyperglycemia-induced hemichorea (HGHC) is a rare but characteristic hyperkinetic movement disorder involving limbs on one side of the body. In a 75-year-old woman with a left-sided HGHC, conventional brain MR imaging showed very subtle T1-hyperintensity and unique gadolinium enhancement in the basal ganglia contralateral to movements. Multi-parametric MRI was acquired using pulse sequence with quantification of relaxation times and proton density by multi-echo acquisition. Myelin map was reconstructed based on new tissue classification modeling. In this case report of multi-parametric MRI, quantitative measurement of myelin change related to HGHC in brain structures and its possible explanations are presented. This is the first study to demonstrate myelin loss related to hyperglycemic insult in multi-parametric quantitative MR imaging.