• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2021년도 제64차 하계학술대회논문집 29권2호
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• pp.305-307
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• 2021

Alzheimer's Disease (AD) is a cognitive disorder characterized by memory impairment that can be assessed at early stages based on administering clinical tests. However, the AD pathophysiological mechanism is still poorly understood due to the difficulty of distinguishing different levels of AD severity, even using a variety of brain modalities. Therefore, in this study, we present a hybrid EEG-fNIRS modalities to compensate for each other's weaknesses with the help of Machine Learning (ML) techniques for classifying four subject groups, including healthy controls (HC) and three distinguishable groups of AD levels. A concurrent EEF-fNIRS setup was used to record the data from 41 subjects during Oddball and 1-back tasks. We employed both a traditional neural network (NN) and a CNN-LSTM hybrid model for fNIRS and EEG, respectively. The final prediction was then obtained by using majority voting of those models. Classification results indicated that the hybrid EEG-fNIRS feature set achieved a higher accuracy (71.4%) by combining their complementary properties, compared to using EEG (67.9%) or fNIRS alone (68.9%). These findings demonstrate the potential of an EEG-fNIRS hybridization technique coupled with ML-based approaches for further AD studies.

• 대한의용생체공학회:의공학회지
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• 제44권6호
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• pp.392-403
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• 2023

This study presents a new hybrid fNIRS-EEG system to meet the demand for a lightweight and low-cost sleep pattern monitoring device. For multiple-channel configuration, a six-channel electroencephalogram (EEG) and a functional near-infrared spectroscopy (fNIRS) system with eight photodiodes (PD) and four dual-wavelength LEDs are designed. To enhance the convenience of signal measurement, the device is miniaturized into a patch-like form, enabling simultaneous measurement on the forehead. Due to its fully integrated functionality, the developed system is advantageous for performing sleep stage classification with high-temporal and spatial resolution data. This can be realized by utilizing a two-dimensional (2D) brain activation map based on the concentration changes in oxyhemoglobin and deoxyhemoglobin during sleep stage transitions. For the system verification, the phantom model with known optical properties was tested at first, and then the sleep experiment for a human subject was conducted. The experimental results show that the developed system qualifies as a portable hybrid fNIRS-EEG sleep pattern monitoring device.

• 한국광학회:학술대회논문집
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• 한국광학회 2008년도 하계학술발표회 논문집
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• pp.159-160
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• 2008

We measured hemodynamic responses of seizure in the mouse brain using frequencydomain near infrared spectroscopy (NIRS) and electroencephalogram (EEG). We adapted microfabricated optical holder for consistent contact of the optical fiber to the mouse brain. Our results show that the cerebral oxygenation and hemodynamics of mice can be stably monitored with EEG in the mouse brain.

• 한국HCI학회논문지
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• 제12권4호
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• pp.75-80
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• 2017

최근 인지과학의 활발한 연구와 기술의 발달로 인해 사회과학분야에서 정신생리학적 연구를 통한 뇌의 다양한 측정과 정교한 분석 기법이 개발 되었다. 그러나 뇌파를 이용한 뉴미디어활용에 관한 연구는 장비들을 장착하는 과정에서의 한계점으로 인해 진행되지 못하였다. 이러한 문제를 극복하고자, 가상현실장비를 착용한 상태에서도 전 영역의 뇌파측정이 가능한 캡을 디자인하고 활용방법을 제안한다.

• Journal of Computing Science and Engineering
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• 제7권2호
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• pp.132-138
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• 2013

Multi-modal techniques have received increasing interest in the neuroscientific and brain computer interface (BCI) communities in recent times. Two aspects of multi-modal imaging for BCI will be reviewed. First, the use of recordings of multiple subjects to help find subject-independent BCI classifiers is considered. Then, multi-modal neuroimaging methods involving combined electroencephalogram and near-infrared spectroscopy measurements are discussed, which can help achieve enhanced and robust BCI performance.

• 한국멀티미디어학회논문지
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• 제21권5호
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• pp.609-616
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• 2018

In this paper, we designed a multimodal bio-signal measurement system to observe changes in the brain nervous system and vascular system during sleep. Changes in the nervous system and the cerebral blood flow system in the brain during sleep induce a unique correlation between the changes in the nervous system and the blood flow system. Therefore, it is necessary to simultaneously observe changes in the brain nervous system and changes in the blood flow system to observe the sleep state. To measure the change of the nervous system, EEG, EOG and EMG signal used for the sleep stage analysis were designed. We designed a system for measuring cerebral blood flow changes using functional near-infrared spectroscopy. Among the various imaging methods to measure blood flow and metabolism, it is easy to measure simultaneously with EEG signal and it can be easily designed for miniaturization of equipment. The sleep stage was analyzed by the measured data, and the change of the cerebral blood flow was confirmed by the change of the sleep stage.

• 대한의용생체공학회:의공학회지
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• 제45권1호
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• pp.26-36
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• 2024

Functional brain imaging techniques have been used to diagnose psychiatric disorders such as dementia, depression, and autism. Recently, these techniques have also been actively used to study hearing loss. The present study reviewed the application of the functional brain imaging techniques in auditory research, especially those focusing on hearing loss, over the past decade. EEG, fMRI, fNIRS, MEG, and PET have been utilized in auditory research, and the number of research studies using these techniques has been increasing. In particular, fMRI and EEG were the most frequently used technique in auditory research. EEG studies mostly used event-related designs to analyze the direct relationship between stimulus and the related response, and in fMRI studies, resting-state functional connectivity and block designs were utilized to analyze alterations in brain functionality in hearing-related areas. In terms of age, while studies involving children mainly focused on congenital and pre- and post-lingual hearing loss to analyze developmental characteristics with and without hearing loss, those involving adults focused on age-related hearing loss to investigate changes in the characteristics of the brain based on the presence of hearing loss and the use of a hearing device. Overall, ranging from EEG to PET, various functional brain imaging techniques have been used in auditory research, but it is difficult to perform a comprehensive analysis due to the lack of consistency in experimental designs, analysis methods, and participant characteristics. Thus, it is necessary to develop standardized research protocols to obtain high-quality clinical and research evidence.

• 한국광학회:학술대회논문집
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• 한국광학회 2009년도 창립 20주년기념 특별학술발표회
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• pp.151-152
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• 2009

최근 신경과학 분야에서 대뇌피질 영역 간 연관성 분석은 신경학적 질병 (자폐증, 간질, 정신 분열증)의 분석 및 진단에 적용되고 있다. 기존 대뇌피질 영역 간 연관성 분석은 뇌전도 (EEG), 기능적 자기공명영상 (fMRI), 뇌자도 (MEG)등이 이용되었지만, 뇌전도의 낮은 공간분해능, 기능적 자기공명영상의 낮은 시분해능 등은 영역 간 연관성 분석에 단점으로 작용되고 있다. 반면, 근적외선 분광법(NIRS)은 대뇌피질에서의 혈류변화(oxy-, deoxy-hemoglobin)를 비침습적이며 빠른 시분해능으로 측정할 수 있는 방법으로 최근 신경과학 분야에 응용되고 있다 [1-2]. 본 논문에서는 근적외선 분광법을 이용한 대뇌피질영역 간 연관성 분석의 효용성을 입증하기 위해, 쥐의 수염자극 시 대응되는 지역 (일차-, 이차 체감각피질, 일차 운동피질 영역)에서의 혈류변화 신호의 영역 간 연관성 분석을 하였다. 본 연구결과에 의하면 수염자극 시 일차-, 이차 체감각피질 영역에서의 방향성은 확인할 수 없었고, 일차-, 이차 체감각피질 영역에서 일차 운동피질영역으로의 방향성은 확인할 수 있었다. 본 결과는 기존 수염자극 시 활성화되는 전기신호의 패턴과 일치하며, 향후 신경과학적 질병의 분석 및 진단에 근적외선을 이용한 대뇌피질 영역 간 연관성 분석이 유용할 수 있음을 보여준다.

• Journal of information and communication convergence engineering
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• 제8권2호
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• pp.205-211
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• 2010

In this study, a Magnetic stimulation Pulse Train control technique is introduced and applied to Flyback converter operating in discontinuous conduction mode. In contrast to the conventional pulse width modulation control scheme, the principal idea of a Magnetic stimulation Pulse Train is to achieve output voltage regulation using high and low power pulses. The proposed technique is applicable to any converter operating in discontinuous conduction. However, this work mainly focuses on Flyback topology. In this paper, the main mathematical concept of the new control algorithm is introduced and simulations as well as experimental results are presented.