• DocumentCode
    3118757
  • Title

    MP-Based Method on Detecting and Eliminating the Synchronous ECG Artifacts in the EEG Signals

  • Author

    Zhou, Yan-Bo ; Cai, Shi-Min ; Zhou, Tao ; Zhou, Pei-Ling

  • Author_Institution
    Dept. of Electron. Sci. & Technol., Univ. of Sci. & Technol. of China, Hefei, China
  • fYear
    2010
  • fDate
    18-20 June 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A method is proposed to detect and eliminate the synchronous ECG artifacts in the EEG Signals based on the matching pursuit algorithm, which doesn´t require the additional synchronous ECG channel or multichannel signals. By using the mixed over-complete dictionary, the EEG signals based on the matching pursuit algorithm are decomposed into atoms. The atoms that have the similar morphological characteristics of R-wave are selected to detect the synchronous ECG R-peak artifacts. Then, the adaptive threshold algorithm is introduced to filter the false detection induced by the morphological characteristics of both ECG artifacts and background EEG signals. At last, the elimination of detected ECG artifacts is realized by the ensemble average subtraction method. By analyzing EEG signals in MIT/BIH database, it presents the excellent result with mean error ratio 1.70%.
  • Keywords
    bioinformatics; electrocardiography; electroencephalography; iterative methods; medical signal processing; neurophysiology; signal denoising; signal detection; EEG signals; MIT-BIH database; MP-based method; matching pursuit algorithm; mean error ratio; multichannel signals; synchronous ECG artifacts; Cerebral cortex; Databases; Dictionaries; Electrocardiography; Electroencephalography; Matching pursuit algorithms; Neurons; Physics; Pursuit algorithms; Signal processing algorithms;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering (iCBBE), 2010 4th International Conference on
  • Conference_Location
    Chengdu
  • ISSN
    2151-7614
  • Print_ISBN
    978-1-4244-4712-1
  • Electronic_ISBN
    2151-7614
  • Type

    conf

  • DOI
    10.1109/ICBBE.2010.5516334
  • Filename
    5516334