• Title/Summary/Keyword: 바이스펙트럼 분석

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Implementation of EEG Artifact Removal Process Based on Bispectrum Analysis (바이스펙트럼 분석 기반의 뇌파 Artifact 제거 프로세스 구현)

  • Park, Junmo
    • Journal of the Institute of Convergence Signal Processing
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    • v.20 no.2
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    • pp.63-69
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    • 2019
  • In this study, bispectrum analysis method introduced to reduce variability of SEF(spectral edge frequency) and MF(median frequency), which are the anesthetic depth indexes extracted by EEG spectral analysis. Bispectrum analysis is an analytical method that can confirm the nonlinearity of EEG. Signal measurement and analysis in the surgical environment should take into consideration various external artifact factors. Bispectrum analysis can confirm the presence of externally introduced artifacts, thereby effectively eliminating artifacts that affect the EEG signal. By applying bispectrum parameters, real-time variability of the anesthetic depth parameters SEF, MF could be reduced. Elimination of variability makes it possible to use SEF, MF as a real-time index during surgery.

Iterative Bispectrum Estimation and Signal Recovery Based On Weighted Regularization (가중 정규화에 기반한 반복적 바이스펙트럼 추정과 신호복원)

  • Lim, Won-Bae;Hur, Bong-Soo;Lee, Hak-Moo;Kang, Moon-Gi
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.37 no.3
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    • pp.98-109
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    • 2000
  • While the bispectrum has desirable properties in itself and therefore has a lot of potential to be applied to signal and Image restoration. few real-world application results have appeared in literature The major problem with this IS the difficulty In realizing the expectation operator of the true bispectrum, due to the lack of realizations. In this paper, the true bispectrum is defined as the expectation of the sample bispectrum, which IS the Fourier representation of the triple correlation given one realization The characteristics of the sample bispectrum are analyzed and a way to obtain an estimate of the true bispectrum without stochastic expectation, using the generalized theory of weighted regularization is shown. The bispectrum estimated by the proposed algorithm is experimentally demonstrated to be useful for signal recovery under blurred noisy condition.

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A Bispectrum Analysis of the EEG In Positive and Negative Emotional States Evoked by Auditory Stimuli (청각자극에 의한 쾌/불쾌 감성상태의 뇌파에 대한 바이스펙트럼 분석)

  • 김응수;조덕연;이유정;류창수
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • 1998.04a
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    • pp.176-182
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    • 1998
  • 청각자극에 의한 쾌/불쾌 감성상태의 특징을 구별하기 위하여 21채널의 측정된 뇌파신호를 이용하였다. 이를 위하여 비선형 분석방법인 바이스펙트럼 분석을 도입하였으며 청각신호에 잘 반응하는 T3, T4채널에 대하여 조사하였다. 쾌한 감성 상태에서는 비슷한 주파수 쌍의 상호작용이 큼을 알 수 있었다.

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Analysis stages of anesthesia with Bispectrum Coherence and DFA algorithm of the EEG (뇌파신호의 바이스펙트럼 Coherence와 DFA 알고리듬을 이용한 마취단계 분석)

  • Ye, Soo-young;Eum, Sang-hee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.6
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    • pp.1471-1476
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    • 2015
  • Due to the anesthesia process is inappropriate on the operation, awakening state was appeared. To prevent the state, it is necessary to monitor the patients by measuring the depth of anesthesia. In this study, we investigate the possibility of the development of actual surgery available quantitative indicators. The DFA which is included the correlation property of the EEG is used to analysis the depth of anesthesia and bispctrum index. In the results, at the pre-operation, the peak of bispectrum was widely distributed, DFA value was decreased. At the during operation, bispectrum was concentrically appeared in the low frequency area. At the post operation, bispectrum and DFA was both returned to the pre-operation state. We confirmed to be close correlation between the peaks of the bispectrum and DFA value.

Measuring depth of anesthesia with Bispectrum and DFA analysis of the EEG (뇌파의 바이스펙트럼과 DFA 분석을 이용한 마취심도 측정)

  • Ye, Soo-Young;Eum, Sang-hee
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2015.05a
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    • pp.397-400
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    • 2015
  • Due to the anesthesia process is inappropriate on the operation, awakening state was appeared. Because of that patients suffered from severe mental and physical pain. To prevent the state, it is necessary to monitor the patients by measuring the depth of anesthesia. In this study, we investigate the possibility of the development of actual surgery available quantitative indicators. The DFA(detrended fluctuation analysis) which is included the correlation property of the EEG is used to analysis the depth of anesthesia and bispctrum index. In the results, at the pre-operation, the peak of bispectrum was widely distributed, DFA value was decreased. At the during operation, bispectrum was concentrically appeared in the low frequency area. At the post operation, bispectrum and DFA was both returned to the pre-operation state. As a result, we confirmed to be close correlation between the peaks of the bispectrum and DFA value.

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Analyzing the Emotional State EEG by Mutual Information (상호정보에 의한 감성상태 뇌파분석)

  • 김응수
    • Journal of the Korean Institute of Intelligent Systems
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    • v.10 no.4
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    • pp.304-309
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    • 2000
  • For understanding the information processing in human brain, we analyze the EEG, a spontaneous electric activity on the scalp of the human. In this paper, we used the mutual information to analyze EEG. The mutual information is used to show the stochastic correlation between signals which are generated in the communication and information theory. The used EEG is evoked by each auditory stimulus in positive and negative emotional states. As a result, we found thet there is some difference at the mutual information in each emotional state.

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Mutual Information for Analyzing the EEG (뇌파 분석을 위한 상호정보)

  • 조덕연;이유정;김응수
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2000.05a
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    • pp.215-219
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    • 2000
  • 인간의 뇌 정보처리를 이해하기 위한 일환으로서, 많은 연구자들이 사람의 두피에서 자발적으로 발생하는 전기 활동인 뇌파(EEG)를 분석하였다. 측정된 뇌파는 잡음처럼 보이는 비선형적인 거동으로 인하여 단순한 관찰만으로는 그 특징을 분석하기가 매우 어렵다. 따라서 이러한 뇌파를 분석하고 이해하기 위한 방법으로 파워스펙트럼, 바이스펙트럼 등과 같은 스펙트럼 분석과 상관차원, 프랙탈 차원과 같은 비선형 카오스 분석 등과 같은 해석법들이 활발히 연구되어왔다. 본 논문에서는 이러한 기존의 방법 외에 두 신호사이의 통계적 의존성을 측정하는 양인 상호정보를 이용하여 뇌파의 특징을 분석하였다. 뇌파간의 상호정보 분석을 통해 두뇌에서의 정보의 흐름에 관한 특징을 알아보았고, 감성자극에 반응하는 두뇌의 활동영역을 알 수 있었다.

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EEG Artifact Detection Algorithm Base on Nonlinear Analysis Method (비선형 분석에 의한 뇌파 아티펙트 검출 알고리즘)

  • Kim, Chul-Ki;Park, Jun-Mo;Kim, Nam-Ho
    • Journal of the Institute of Convergence Signal Processing
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    • v.21 no.1
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    • pp.7-12
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    • 2020
  • Various parameters are used to measure anesthetic depth during surgery using brain waves, and in actual clinical use, the linear analysis SEF is widely used. However, with recent studies showing that biological signals including EEG, contain nonlinear properties interest in nonlinear analysis of brain signals is increasing and parameters based on these are being developed. In this study, we are going to develop a parameter that can measure EEG using the nonlinear analysis method and extract noise that can be mixed with external electronic equipment and EEG instrumentation by comparing it with the data from the bispectrum analysis of static waves.

A bicoherence analysis of EEG during Yes/No decision task (긍/부정 문답 과제 수행시 뇌파의 바이코히어런스 분석)

  • 남승훈;류창수;임태규;송윤선;유창용
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • 2003.05a
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    • pp.115-119
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    • 2003
  • 본 연구는 인간에 있어서 가장 간단한 의사라고 여겨지는 긍정과 부정 응답에 대해 나타나는 뇌파의 변화를 잘 반영하는 특징을 찾아내고자 하기 위한 것이다. 고차 통계적 방법(high order statical analysis)인 바이스펙트럼(bispectrum)은 뇌파의 다른 부위와 다른 주파수 사이의 비선형위상커플링(non-linear phase coupling)을 잘 반영하므로, 이를 이용하여 긍정이나 부정을 선택할 때 나타나는 뇌파를 분석하였다. 분석결과, 반응 전 1.25초∼0.5초 에 유의미한 차이를 보였다. 긍정과 부정 응답에 대한 뇌파의 주파수와 부위를 찾아 신경회로망의 입력으로 사용하여 긍정과 부정 응답에 대해 분별하였다. 2번의 뇌파실험에서 각각 실험 데이터에 대해서는 긍/부정 차이가 존재하지만 공통적인 특징이 나타나지는 않았다.

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