Browse > Article
http://dx.doi.org/10.5391/JKIIS.2002.12.5.442

Nonlinear and Independent Component Analysis of EEG with Artifacts  

Kim, Eung-Soo (대전대학교 대학원 전자공학과)
Shin, Dong-Sun (대전대학교 대학원 전자공학과)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.12, no.5, 2002 , pp. 442-450 More about this Journal
Abstract
In measuring EEG, which is widely used for studying brain function, EEG is frequently mixed with noise and artifact. In this study, the signals relevant to the artifact were distracted by applying ICA to EEG signal. First, each independent component which was assumed to be the source was separated by applying ICA to EEG which involved artifact relevant to the eye movement of a normal person. Next, the signal which was assumed to be artifact was removed from the separated 18 independent components, and the nonlinear analysis method such as correlation dimension and the Iyapunov exponent was applied to each reconstructed EEG signal and the original signal including artifact in order to find meaningful difference between the two signals and infer the anatomical localization of its source and distribution. This study shows it is possible not only to analyze the brain function visually and spatially for visually complex EEG signal, but also to observe its meaningful change through the quantitative analysis of EEG by means of the nonlinear analysis.
Keywords
뇌파;잡파;독립성분분석;비선형분석;상관차원;리아프노프 지수;
Citations & Related Records
연도 인용수 순위
  • Reference
1 S. Makeig, et aI, "Independent Component Analysis of Electroencephalographic data", "Advances in Neural Information Processing Systems", Vol. 8, pp. 145-151, 1996.
2 L. Zhukov and D. Weinstein, "Independent Component Analysis for EEG source Localization", IEEE Engineering in Medicine and Biology, pp. 87-96, May/June, 2000.
3 윤중수, "뇌파학 개론" 고려의학, 1999.
4 Te-Won lee, Mark Girolami and Terrence J. Sejnowski, "Independent Component Analysis using an Extended Infomax Algorithm for Mixed Sub-Gaussian Sources", Neural Computation, Vol. 11, No. 2, pp. 409-433, 1999.
5 J. Jeong, J. Gore, "Independent Component Analysis to the Analysis of EEG and MEG Recordings", IEEE Trans. on Biomedical Eng., Vol. 47, No. 5, 2000.
6 김대식, 김영배, "뇌파 검사학", 고려의학, 2001.
7 Alan Wolf et at, Jack B. Swift, Harry L. Swinney and John A. Vastano, "Determining Lyapunov Exponents From a Time series", Physica D, Vol. 16, pp. 285-317, 1985.   DOI   ScienceOn
8 한선호, Satio Shoji , "임상뇌파", 일조각, 1987.
9 Th. Buzug & G. Pfister, "Comparison of algorithms calculating optimal embedding parameters for delay time coordinates", Physica D, Vol. 58, pp.127-137, 1992.   DOI   ScienceOn
10 Peter. Grassberger, ltamar. Procaccia, "Dimension and entropies of strange attractors from a fluctuating dynamic approach", Physica D, Vol. 13, pp. 34-54, 1984.   DOI   ScienceOn
11 A.J. Bell and T.J. Sejnowski, "An Information maximization approach to blind separation & blind deconvolution" , Neural Computation, Vol. 7, pp. 1129-1159, 1995.   DOI   ScienceOn
12 Peter. Grassberger, Itamar. Procaccia, "Measuring the strangeness of strange attractors", Physica D, Vol. 9, pp. 189-208, 1993.
13 K. Kobayashi, I. Merlet and J. Gotman, "Separation of spike from background by independent component analysis with dipole modeling and comparison to intracranial recording", Clinical Neurophysiology, Vol. 112, pp. 405-413, 2001   DOI   ScienceOn
14 H. Petsche, S. Kaplan, AV Stein, O.Filz, "The possible meaning of the upper and lower alpha frequency ranges for cognitive and creative tasks", Int. J. Psychophysiology, Vol. 26, pp. 77-97, 1997.   DOI   ScienceOn
15 N.H. Packard, J.P. Crutchfield, J.D. Farmer, and R.S. Shaw, "Geometry from a time series", Physical Review Letters, Vol. 45, No. 9, pp.712-716, 1980.   DOI
16 김응수, 이유정, "EEG 독립성분과 위치추정", 한국 정보처리학회 2001년 춘계학술대회 논문집, 제8권, pp. 297-300, 2001.   과학기술학회마을
17 최정미, "뇌전위의 물리적 모델링과 비선형분석에 의한 뇌기능연구", 한국과학기술원 석사학위 논문, 1997.
18 G. Wubbeler, et al, "Independent Component Analysis of Noninvasively Recorded Cortical Magnetic DC-Fields in humans", IEEE Trans. On Biomedical Eng., Vol. 47, No 5, pp. 594-599, 2000.   DOI   ScienceOn
19 W. Lutzenberger, et aI, "Fractal dimension of electroencephalographic time series and underlying brain processes", Biological Cybernetics, Vol. 73, pp. 477-482, 1995   DOI   ScienceOn
20 R. Vigario, et aI, "Independent Component Analysis to the Analysis of EEG and MEG Recordings", IEEE Trans. on Biomedical Eng., Vol. 47, No. 5, 2000.