• Title/Summary/Keyword: 정량뇌파

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A Study on Analysis of Depression, Cognition, Communication, and Quantitative Electroencephalogram in Hearing Impaired Elderly (난청 고령자의 우울정도, 인지기능, 의사소통능력 및 정량뇌파 분석 연구)

  • Kim, Hyoung Jae;Weon, Hee Wook
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.4
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    • pp.430-440
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    • 2021
  • The purpose of this study was to analyze the degree of depression, cognitive function, communication ability, and the quantitative electroencephalogram (EEG) in elderly individuals with hearing loss and to investigate their inter-relationship. Hearing-impaired elderly participants, aged 60 years or older (37 men and 26 women) who visited the S Hearing Rehabilitation Center in Y City from June 20, 2020, to September 3, 2020, participated voluntarily after a recruitment announcement.The participants' overall characteristics, depression, and cognitive functions were evaluated with a structured questionnaire. The Word Recognition Score (WRS) was evaluated with an audiometer using the Korean Standard Monosyllabic Word Lists for Adults (KS-MWL-A). The quantitative EEG was measured with dry electrodes using a 2-channel EEG on the frontal lobes Fp1 and Fp2. The results are summarized as follows: Communication ability showed a positive correlation with the left-right symmetry of the frontal lobes (**p<.01) and a negative correlation with right-brain mental distraction and stress (*p<.05). In the difference WRS test for each group, the left-right symmetry of the frontal lobes (**p<.01) showed the greatest correlation with communication ability. Our results suggest that the left-right symmetry of the frontal lobes can be a biomarker indicative of the communication ability of older people with hearing impairments.

EEG Analysis at the Moment of Yes/No Decision: Study of Spatio-Temporal Relations (긍/부정 선택 순간의 뇌파 변화 연구: 두 위치에서 측정된 뇌파의 상호관계 분석)

  • 김민준;신승철;송윤선;류창수;문성실;손진훈
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • 2001.05a
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    • pp.26-31
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    • 2001
  • 긍/부정 선택 실험에서 나타나는 뇌파 변화를 연구하였다. 서로 다른 위치에서 측정된 뇌파의 시공간적 상호관계를 정량화하는 변수로, 시간영역에서 계산하기 용이한 동기율(synchronization rate), 편향성(synchronization rate), 편향성(polarity), 상호상관(cross-correlation) 등의 변수를 도입하여, 긍/부정 선택 순간의 뇌파 변화를 살펴보았다. 좌우 전전두엽(Fp1, Fp2)에서 특정된 뇌파를 사용하여 계산한 동기율, 편향성의 평균과 요동폭, 상호상관 등은, 선택 순간 근처에서, 평상시에 뇌파와 통계적으로 유의미한 차이를 보였다.

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A Study on the generation of objective sound model for sonification using brain wave data set (소니피케이션(sonification) 구현을 위한 뇌파 데이타 기반 객관적 사운드 모델 연구)

  • Chun, Sung-Hwan;Joh, In-Jae;Suh, Jung-Keun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2016.04a
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    • pp.795-798
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    • 2016
  • 소니피케이션은 다양한 데이터를 사운드로 변환시키는 과정으로 본 연구에서는 뇌파 신호를 사운드로 생성하는 객관적인 워크플로우를 제시하고자 하였다. 현재까지의 뇌파 소니피케이션은 사운드로의 변환이 인위적이고 임의적으로 진행되어 객관적인 논리를 제시하지 못하고 있는 실정이다. 이에 본 연구에서는 뇌파데이터의 정량적 분석을 통해 파라미터 추출, 사운드 맵핑, 사운드 모델 구축에 대한 논리적 근거를 제시하였으며 이를 통해 뇌파데이터의 객관적인 소니피케이션 과정을 구현하였다. 파라미터 추출을 위해 15Hz High pass filtering이 가장 적절한 방법으로 확인되었으며 뇌파 데이터의 최대값 빈도 분석과 음악코드의 비율 분석을 실제로 맵핑시켜 사운드 모델을 구축하여 사운드 생성을 구현하였다. 결론적으로, 본 연구에서는 뇌파데이터의 소니피케이션 과정에 대한 객관적이고 논리적인 워크플로우를 제시하였으며 이러한 워크플로우가 다양한 분야에서 적용될 수 있을 것으로 예상된다.

Comparison of QEEG between EEG asymmetry and Coherehnce with elderly people according to smart_phone game Addiction Tendency (노인의 스마트 폰 게임 중독 경향에 따른 뇌파 비대칭(asymmetry)와 연결성(Coherehnce)의 정량화뇌파(QEEG) 비교 분석)

  • Weon, Hee Wook
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.11
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    • pp.644-652
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    • 2017
  • The purpose of this study was to analyze the EEG according to the elderly's tendency to be addicted to smartphone games. We compared the effects of smartphone addiction on mental health such as brain waves, sleep problems and depression through comparative analysis of asymmetry and connectivity in quantitative EEG results. The study participants were two elderly people who were addicted to smartphone game and one elderly person who did not use smartphone (Ed- to confirm: only 3 participants?!). The participant's addiction tendency of smartphone was measured by using the smartphone addiction scale and EEG (QEEG) was used for EEG analysis. The results are as follows. First, the brain waves of elderly people and smartphone non-user elderly who showed symptoms of immersion and smartphone game showed a difference in asymmetry in both opening and closing anisles. Second, there were significant differences in the openness and the anxiety of the elderly who were immersed in the mobile phone and the elderly who did not use the smartphone. Through this, it is also meaningful to explore the relationship between senile cognitive impairment and smartphone use by exploring the effect of smartphone game use on brain cognitive function through comparison of EEG analysis.

A Study on The Effects of The phonetics-Centered Chinese character Lecture on Quantitative EEG (성부 중심 한자강의가 정량화 뇌파에 미치는 영향에 관한 연구)

  • Lee, Byeong-Chan;Weon, Hee-Wook
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.12
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    • pp.482-492
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    • 2019
  • This study began with the assumption that the phonetics-centered interpretation of 100 Chinese characters would enhance thinking ability and comprehension. For this purpose, two experimental groups and a comparative group were recruited from the graduate students from June 3, 2017 to February 22, 2018. The experimental group participated in the phonetics-centered Chinese character lecture for 4 hours per week for 6 weeks for a total of 24 hours. QEEG were measured before and after the phonetics-centered Chinese character lecture. A total of 18 subjects ( nine subjects in the experimental group and nine comparative subjects) were included in the study, and the difference between before and after the QEEG of the experimental and comparative groups was analyzed, respectively. The conclusions drawn from this study are as follows. First, the Chinese character lecture changed brain waves. Second, the LORETA analysis before and after the lecture in the experimental group significantly decreased the delta wave in the brain region (Broadmann 40) associated with the meaning of language and phonology. This study result is meaningful because it shows the significant changes of EEG via the lecture.

COSA : Cursor Control System by EEG (COSA : 뇌파를 이용한 방향 제어 시스템)

  • Shin, Dong-Sun;Kim, Eung-Soo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2002.11a
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    • pp.801-804
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    • 2002
  • 뇌기능 연구 수단으로 널리 사용되고 있는 뇌파의 시각적 분석 및 정량적 분석시 오차를 증가시키는 원인이 되어 왔던 잡파(artifact)를 제거 대상이 아닌 제어 신호로써 활용한다. 본 연구에서는 다양한 잡파 중 뇌파 측정시 가장 잘 포함되고, 시각적으로 쉽게 구별이 가능한 안면근(facial muscle) 신호를 이용한다. 측정된 뇌파에 파워스펙트럼(power spectrum)을 적응하여 뇌파를 분석하고, Backpropagation 알고리즘을 이용하여 전 처리된 뇌파를 인식하는 2 채널 실시간 인식(recognition) 및 분류(classification) 시스템을 구현한다. 이와 같이 구현된 시스템을 이용하여 5 방향(상, 하, 좌, 우, 정지) 제어를 실시함으로써 뇌-컴퓨터간 통신을 통한 방향제어 시스템을 구현하였다.

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Quantitative EEG Analysis on Emotional characteristics of Children experiencing Domestic Violence (가정폭력을 경험한 피해자녀의 감정 특성에 관한 정량화 뇌파연구)

  • Byun, Youn-Eon;Weon, Hee-Wook
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.11
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    • pp.166-175
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    • 2017
  • This study examined children from two families exposed to domestic violence and had psychological counseling in July 2017 at KOVA, a support organization for crime victims. The subjects were exposed to family violence in excess of 10 years and was protected by the shelter with their mothers who had filed complaints with the local police. Victims of domestic violence often face difficulty in avoiding the source of aggression, and thus experience repetitive attacks. This research was conducted at the Buddhism Brain Research Facility, Seoul University, to identify and quantify the emotional characteristics of the affected children in which it is difficult to escape from their living conditions. Data was collected by BrainMaster, a 19-channel examination kit, and analyzed by NeuroGuide. As a result of analyzing the emotional characteristics of the affected children through Quantitative EEG and brain topographical map, we found an increase of slow wave and problems with abnormality of Alpha, High Beta in the left and right Frontal area asymmetry.

Implementation of Brain-machine Interface System using Cloud IoT (클라우드 IoT를 이용한 뇌-기계 인터페이스 시스템 구현)

  • Hoon-Hee Kim
    • Journal of Internet of Things and Convergence
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    • v.9 no.1
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    • pp.25-31
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    • 2023
  • The brain-machine interface(BMI) is a next-generation interface that controls the device by decoding brain waves(also called Electroencephalogram, EEG), EEG is a electrical signal of nerve cell generated when the BMI user thinks of a command. The brain-machine interface can be applied to various smart devices, but complex computational process is required to decode the brain wave signal. Therefore, it is difficult to implement a brain-machine interface in an embedded system implemented in the form of an edge device. In this study, we proposed a new type of brain-machine interface system using IoT technology that only measures EEG at the edge device and stores and analyzes EEG data in the cloud computing. This system successfully performed quantitative EEG analysis for the brain-machine interface, and the whole data transmission time also showed a capable level of real-time processing.

A study on the effect of emotion-evoking advertisement with EEG analysis (뇌파 분석을 이용한 감성자극형 광고 효과 연구)

  • 편흥국;김정룡
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2000.04a
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    • pp.413-416
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    • 2000
  • 현재 소비자의 광고 효과 측정에 대한 연구는 정보 처리 모형에 근거한 인지 반응 연구와 주관적인 감성 반응 연구가 주를 이루고 있다. 이에 본 연구에서는 TV 광고에 대한 광고 효과를 인지와 감성적 부분으로 분류하여 해석한 Shimp(1981)의 모델을 기초로하여 각각의 뇌파의 반응을 측정하였고, 동시에 광고에 대한 감성형용사, 선호도, 구매 욕구를 통한 주관적 평가를 실시하였다. 그 결과 정보전달형 광고와 감성자극형 광고에 있어 뇌파 활성도, 감성형용사, 선호도의 차이를 나타냈다. 본 결과는 광고에 대한 소비자의 반응을 정량적인 방법으로 측정하여, 광고 효과 파악을 위한 새로운 모델의 가능성을 제시하였다는데 의의가 있다.

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Study on Data Normalization and Representation for Quantitative Analysis of EEG Signals (뇌파 신호의 정량적 분석을 위한 데이터 정규화 및 표현기법 연구)

  • Hwang, Taehun;Kim, Jin Heon
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.9 no.6
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    • pp.729-738
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    • 2019
  • Recently, we aim to improve the quality of virtual reality contents based on quantitative analysis results of emotions through combination of emotional recognition field and virtual reality field. Emotions are analyzed based on the participant's vital signs. Much research has been done in terms of signal analysis, but the methodology for quantifying emotions has not been fully discussed. In this paper, we propose a normalization function design and expression method to quantify the emotion between various bio - signals. Use the Brute force algorithm to find the optimal parameters of the normalization function and improve the confidence score of the parameters found using the true and false scores defined in this paper. As a result, it is possible to automate the parameter determination of the bio-signal normalization function depending on the experience, and the emotion can be analyzed quantitatively based on this.