• DocumentCode
    2584160
  • Title

    A study on the elimination of the ECG artifact in the polysomnographic EEG and EOG using AR model

  • Author

    Park, Hae-Jeong ; Han, Joo-Man ; Jeong, Do-Un ; Park, Kwang-Suk

  • Author_Institution
    Interdisciplinary Program of Med. & Biol. Eng. Major, Seoul Nat. Univ., South Korea
  • Volume
    3
  • fYear
    1998
  • fDate
    29 Oct-1 Nov 1998
  • Firstpage
    1632
  • Abstract
    We present the method of the elimination of ECG artifact from the polysomnographic EEG and EGG. The idea of this method is that the ECG-corrupted EEG segment can be detected from ECG R-wave and regarded as a missing segment. After this, we used two interpolations to recover the missing segment. One is the Lagrange polynomial interpolation and the other is the least square error AR interpolation. We also compared the AR-method with the LMS adaptive noise canceling method. Simulations show the AR-method performs better than other methods. To apply to the real EEG and EOG signals practically, we also developed the algorithm to detect whether the artifact level is high or not. If the artifact level is high, then the interpolations are applied
  • Keywords
    autoregressive processes; bioelectric potentials; electrocardiography; electroencephalography; eye; interpolation; least squares approximations; medical signal processing; polynomial approximation; sleep; ECG R-wave; ECG artifact elimination; ECG-corrupted EEG segment; Lagrange polynomial interpolation; autoregressive model; least square error AR interpolation; missing segment; polysomnographic EEG; polysomnographic EOG; Brain modeling; Electrocardiography; Electroencephalography; Electrooculography; Interpolation; Lagrangian functions; Least squares approximation; Least squares methods; Noise cancellation; Polynomials;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 1998. Proceedings of the 20th Annual International Conference of the IEEE
  • Conference_Location
    Hong Kong
  • ISSN
    1094-687X
  • Print_ISBN
    0-7803-5164-9
  • Type

    conf

  • DOI
    10.1109/IEMBS.1998.747219
  • Filename
    747219