• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2018년도 춘계 종합학술대회 논문집
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• pp.167-168
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• 2018

비즈니스 환경에서 창의성은 의사결정 문제해결을 위한 중요한 수단이 되고 있다. 본 연구는 실험 패러다임을 구축하고 기능적 근적외 분광법, 즉 fNIRS (functional Near-Infrared Spectroscopy)를 활용하여 창의성이 비즈니스 문제 해결에 미치는 영향을 뇌 인지 변화를 통해 측정하고자 한다. 본 연구에서는 비즈니스 문제해결 창의성이라는 새로운 차원의 창의성을 fNIRS로 측정하고 이를 경영성과 개선으로 연결하고자 하는 연구노력의 탐색적 수준의 결과를 제시하고자 한다.

• 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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• 제42권6호
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• pp.268-276
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• 2021

Functional near-infrared spectroscopy-based brain-computer interface (fNIRS-based BCI) has been receiving much attention. However, we are practically constrained to obtain a lot of fNIRS data by inherent hemodynamic delay. For this reason, when employing machine learning techniques, a problem due to the high-dimensional feature vector may be encountered, such as deteriorated classification accuracy. In this study, we employ an elastic net-based feature selection which is one of the embedded methods and demonstrate the utility of which by analyzing the results. Using the fNIRS dataset obtained from 18 participants for classifying brain activation induced by mental arithmetic and idle state, we calculated classification accuracies after performing feature selection while changing the parameter α (weight of lasso vs. ridge regularization). Grand averages of classification accuracy are 80.0 ± 9.4%, 79.3 ± 9.6%, 79.0 ± 9.2%, 79.7 ± 10.1%, 77.6 ± 10.3%, 79.2 ± 8.9%, and 80.0 ± 7.8% for the various values of α = 0.001, 0.005, 0.01, 0.05, 0.1, 0.2, and 0.5, respectively, and are not statistically different from the grand average of classification accuracy estimated with all features (80.1 ± 9.5%). As a result, no difference in classification accuracy is revealed for all considered parameter α values. Especially for α = 0.5, we are able to achieve the statistically same level of classification accuracy with even 16.4% features of the total features. Since elastic net-based feature selection can be easily applied to other cases without complicated initialization and parameter fine-tuning, we can be looking forward to seeing that the elastic-based feature selection can be actively applied to fNIRS data.

• 한국융합학회논문지
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• 제12권12호
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• pp.323-330
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• 2021

본 연구에서는 10명의 건강한 성인을 대상으로 기능적 근적외선 분광법(fNIRS)을 이용하여 우세손과 비우세손에 따른 뇌 활성화도의 차이를 알아보고자 하였다. 우세손, 비우세손 총 2가지 조건에서 상자와 나무토막검사(BBT)를 실시하였다. 실험을 진행하는 동안 fNIRS을 이용하여 뇌 활성도를 측정하였으며, 실험이 종료된 후 nirsLAB v2019.04 소프트웨어를 사용하여 신호를 분석하였다. 그 결과 우세손을 사용한 경우 10명 중 6명이 우세손과 관련 있는 대뇌반구의 활성화를 보였고, 비우세손을 사용한 경우는 10명 중 3명만이 비우세손과 관련 있는 대뇌반구의 활성화를 보였다. 즉, 우세손, 비우세손 모두 우세손과 관련 있는 대뇌반구가 좀 더 활성화되었음을 확인하였다. 따라서 우세손을 알기 어려운 감각처리장애를 가진 아동들에게 fNIRS을 적용할 수 있는 기초적 자료로 사용될 수 있으리라 사료된다.

• Molecules and Cells
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• 제40권8호
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• pp.523-532
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• 2017

Functional near-infrared spectroscopy (fNIRS) is a noninvasive optical imaging technique that indirectly assesses neuronal activity by measuring changes in oxygenated and deoxygenated hemoglobin in tissues using near-infrared light. fNIRS has been used not only to investigate cortical activity in healthy human subjects and animals but also to reveal abnormalities in brain function in patients suffering from neurological and psychiatric disorders and in animals that exhibit disease conditions. Because of its safety, quietness, resistance to motion artifacts, and portability, fNIRS has become a tool to complement conventional imaging techniques in measuring hemodynamic responses while a subject performs diverse cognitive and behavioral tasks in test settings that are more ecologically relevant and involve social interaction. In this review, we introduce the basic principles of fNIRS and discuss the application of this technique in human and animal studies.

• 한국컴퓨터정보학회논문지
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• 제27권8호
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• pp.1-7
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• 2022

인공지능 기술이 발달하면서 뉴로사이언스 마이닝(NSM: NeuroScience Mining)과 AI를 접목하려는 시도가 증가하고 있다. 나아가 NSM은 뉴로사이언스와 비즈니스 애널리틱스의 결합으로 인해 연구범위가 확장되고 있다. 본 연구에서는 fNIRS 실험을 통해 확보한 뉴로 데이터를 분석하여 비즈니스 문제 해결 창의성(BPSC: business problem-solving creativity)을 예측하고 이를 통해 NSM의 잠재력을 조사한다. BPSC는 비즈니스에서 차별성을 가지게 하는 중요한 요소이지만, 인지적 자원의 하나인 BPSC의 측정 및 예측에는 한계가 존재한다. 본 논문에서는 BPSC 예측 성능을 높이는 방안으로 CNN, BiLSTM 그리고 어텐션 네트워크를 결합한 새로운 NSM 기법을 제안한다. 제안된 NSM 기법을 15만 개 이상의 fNIRS 데이터를 활용하여 유효성을 입증하였다. 연구 결과, 본 논문에서 제안하는 NSM 방법이 벤치마킹한 알고리즘(CNN, BiLSTM)에 비하여 우수한 성능을 가지는 것으로 나타났다.

• 대한의용생체공학회:의공학회지
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• 제36권5호
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• pp.177-182
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• 2015

The activation of prefrontal cortex of brain during some mental tasks like mental arithmetic induce has been studied using hemodynamic imaging modalities. In this study, we focused on the differentiation of activated area in local prefrontal brain caused by the different mental activities as well as evaluating the classification accuracy of in-house fNIRS system. The study preliminarily validated the device including the signal quality and tightness of contact between detectors and prefrontal area. Experimental results of mental tasks on 5 subjects showed the subject dependent tendencies in correlated prefrontal activation and the area of highest accuracy.

• Physical Therapy Rehabilitation Science
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• 제12권3호
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• pp.334-339
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• 2023

Objective: The present study is designed to delve deeper into the realm of fibromyalgia (FM) symptom management by investigating the effects of diaphragmatic breathing on the prefrontal cortex (PFC) in women diagnosed with FM. Using functional near-infrared spectroscopy (fNIRS), the study aims to capture real-time PFC activation patterns during the practice of diaphragmatic breathing. The overarching objective is to identify and understand the underlying neural mechanisms that may contribute to the observed clinical benefits of this relaxation technique. Design: A case report Methods: To achieve this, a twofold approach was adopted: First, the patient's breathing patterns were meticulously examined to detect any aberrations. Following this, fNIRS was employed, focusing on the activation dynamics within the PFC. Results: Our examination unveiled a notable breathing pattern disorder inherent to the FM patient. More intriguingly, the fNIRS analysis offered compelling insights: the ventrolateral prefrontal cortex (VLPFC) displayed increased activation. In stark contrast, regions of the anterior prefrontal cortex (aPFC) and orbitofrontal cortex (OFC) manifested decreased activity, especially when benchmarked against typical activations seen in healthy adults. Conclusions: These findings, derived from a nuanced examination of FM, underscore the condition's multifaceted nature. They highlight the imperative to look beyond conventional symptomatology and appreciate the profound neurological and physiological intricacies that define FM.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2009년도 추계학술발표대회
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• pp.407-408
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• 2009

fNIRS(functional Near Infrared Spectroscopy)는 비침습형 뇌기능 분석 시스템으로 뇌활성화 시 옥시 헤모글로빈(oxy-hemoglobin)과 디옥시헤모글로빈(deoxy-hemoglobin) 변화량을 측정할 수 있는 장치이다. 본 논문에서는 뇌기능 분석 장치인 fNIRS를 이용하여 피험자가 컴퓨터 게임 중에 어떤 뇌활성화 패턴을 보이는지를 실험하였다. 컴퓨터 게임 주의 및 집중 시 뇌의 전두엽(Frontal Lobe) 영역이 활성화 및 변화되는 것을 실험결과로 확인하였다. 그리고 게임 중 다른 사람이 피험자에게 개입을 하였을 때 전두엽의 활성화 영역이 다른 패턴을 보이는 것을 실험결과로 확인하였다.

• 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.