전기학회논문지 (The Transactions of The Korean Institute of Electrical Engineers)

  • 제56권7호
  • /
  • Pages.1331-1338
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  • 2007
  • /
  • 1975-8359(pISSN)
  • /
  • 2287-4364(eISSN)
대한전기학회 (The Korean Institute of Electrical Engineers)
권호 표지

최소 제곱 가속 기반의 적응 디지털 필터를 이용한 두피 뇌전도에서의 심전도 잡음 추정 및 제거

A Method for Estimation and Elimination of EGG Artifacts from Scalp EEG Using the Least Squares Acceleration Based Adaptive Digital Filter

  • 조성필 (연세대학교 의공학과) ;
  • 송미혜 (연세대학교 의공학과) ;
  • 박호동 (연세대학교 의공학과) ;
  • 이경중 (연세대학교 의공학과, 연세의료공학연구원.이동형 응급의료정보시스템개발센터)
  • 발행 : 2007.07.01
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초록

A new method for detecting and eliminating the Electrocardiogram(ECG) artifact from the scalp Electroencephalogram(EEG) is proposed. Based on the single channel EEG, the proposed method consists of 4 procedures: emphasizing the R-wave of ECG artifact from EEG using the least squares acceleration(LSA) filter, detecting the R-wave from the LSA filtered EEG using the phase space method and R-R interval, generating the delayed impulse synchronized to the R-wave and elimination of the ECG artifacts based on the adaptive digital filter using the impulse and raw EEG. The performance of the proposed method was evaluated in the two separating parts of R-wave detection and, ECG estimation and elimination from EEG. In the R-wave detection, the proposed method showed the mean error rate of 6.285(%). In the ECG estimation and elimination using simulated and/or real EEG recordings, we found that the ECG artifacts were successfully estimated and eliminated in comparison with the conventional multi-channel techniques, in which independent component analysis and ensemble average method are used. From this we can conclude that the proposed method is useful for the detecting and eliminating the ECG artifact from single channel EEG and simple for ambulatory/portable EEG monitoring system.

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참고문헌

  1. E. Waterhouse, 'New Horizons in Ambulatory Electroencephalography,' IEEE Eng. Med. Biol. Mag, vol. 22, pp. 74-80, 2003 https://doi.org/10.1109/MEMB.2003.1213629
  2. J.-P. Lanquart, M. Dumontb, and P. Linkowski, 'QRS artifact elimination on full night sleep EEG,' Med. Eng. Phys., vol. 28, pp. 156-165, 2006 https://doi.org/10.1016/j.medengphy.2005.04.017
  3. G. Dirlich, L. Vogl, M. Plaschke, and F. Strian, 'Cardiac field effects on the EEG,' Electroencephalogr. Clin. Neurophys., vol. 102, pp. 307-315, 1997 https://doi.org/10.1016/S0013-4694(96)96506-2
  4. M. Nakamura and H. Shibasaki, 'Elimination of EKG artifacts from EEG records,' Electroencephalogr. Clin. Neurophys., vol. 66, pp. 89-92, 1987 https://doi.org/10.1016/0013-4694(87)90143-X
  5. Rajeev Agarwal, 'Automatic Detection of Micro- Arousals,' Proc. 27th Annu. Int. Conf. IEEE, Engineering in Medicine and Biology Society, Shanghai, China, Sep. 2005, pp. 1158-1161
  6. Wcidong Zhou, 'Removal of ECG Artifacts from EEG Using ICA,' Proc. 24th Annu. Int, Conf. IEEE, Engineering in Medicine and Biology Society, Houston, USA, Oct. 2002, pp. 206-207
  7. Fabienne Poree, Amar Kachenoura, Herve Gauvrit, Catherine Morvan, Guy Carrault, and Lotfi Senhadji, 'Blind Source Separation for Ambulatory Sleep Recording,' IEEE T. lnf. Technol. Biomed., vol. 10, No.2, 2006
  8. M. G. Frei, R. L. Davidchack, and L. Osorio, 'Least Squares Acceleration Filtering for the Estimation of Signal Derivatives and Sharpness at Extrema,' IEEE Trans. Biomed. Eng., vol. 6, pp. 971-977, 1999
  9. Willis J. Tomkins, 'Biomedical digital signal processing' Prentice-Hall, 1993
  10. P. Laguna, R. Jane, O. Meste, P. W. P. P. Caminal, H. Rix, and N. V. Thakor, Adaptive filter for event-related bioelectric signals using an impulse correlated reference input: comparison with signal averaging techniques,' IEEE Trans. Biomed. Eng., vol. 39, pp. 1032-1044, 1992 https://doi.org/10.1109/10.161335