Journal of the Institute of Convergence Signal Processing (융합신호처리학회논문지)

The Korea Institute of Convergence Signal Processing (한국융합신호처리학회)
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EEG Artifact Detection Algorithm Base on Nonlinear Analysis Method

비선형 분석에 의한 뇌파 아티펙트 검출 알고리즘

  • Kim, Chul-Ki (Dept. of Control and Instrumentation Eng., Pukyoung National University) ;
  • Park, Jun-Mo (School of Electronic and Biomedical Engineering, Tongmyong University) ;
  • Kim, Nam-Ho (Dept. of Control and Instrumentation Eng., Pukyoung National University)
  • 김철기 (부경대학교 공과대학 제어계측공학과) ;
  • 박준모 (동명대학교 공과대학 전자및의용공학부) ;
  • 김남호 (부경대학교 공과대학 제어계측공학과)
  • Received : 2020.01.07
  • Accepted : 2020.03.21
  • Published : 2020.03.31
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Abstract

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.

수술 중 마취 깊이를 측정하는 방법으로 뇌파를 이용한 다양한 파라미터들이 사용되고 있으며, 실제 임상에서는 선형분석 기법 중 하나인 SEF가 널리 사용되고 있다. 그러나 최근 EEG를 포함한 생체학적 신호는 비선형 성질을 가지고 있다는 연구결과가 발표되면서, 이를 기반으로 한 파라미터 개발이 이뤄지고 있다. 본 연구에서는 보다 정확한 EEG 측정과 분석을 위해 비선형 분석 기법 기반의 파라미터를 개발과 이에 대한 정현파 분석을 통한 데이터와의 비교 분석을 통해 수술 중 전자장비와 EEG 계측 시 혼입될 수 있는 노이즈를 추출하고자 한다.

Keywords

References

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