• DocumentCode
    2402643
  • Title

    Power line interference cancellation in ECG signals using Alpha-Beta filter

  • Author

    Jamwal, Shilpa

  • Author_Institution
    Dept. of Electron. & Commun. Eng., Nat. Inst. of Tech. Teachers Training & Res. (NITTTR), Chandigarh, India
  • fYear
    2012
  • fDate
    15-17 March 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Electrocardiograph (ECG) signal provides a quick and easy interpretation of Heart-related diseases. But the presence of artifacts can pose a problem in its diagnosis and also leads to its degradation. Power Line Interference (PLI) is one of the artifacts which can deteriorate its quality. To deal with this noise and to nullify its effect, Alpha-Beta filter is proposed and addressed in this paper. The filter performs the estimation on the n-th observation and also smoothes it to reduce the noise level. The performance measures of the filter i.e. tracking accuracy and noise suppression hinge on its weighting factors i.e. α & β. The experiment is performed on different ECG records, taken from the benchmark MIT-BIH Arrhythmia Database. The results indicate the Alpha-Beta filter has estimated the ECG signals appropriately and also suppressed the noise to an acceptable level.
  • Keywords
    electrocardiography; filtering theory; medical signal processing; Alpha-Beta filter; ECG signals; Heart related disease; MIT-BIH arrhythmia database; PLI; electrocardiograph; n-th observation; noise suppression; power line interference cancellation; Adaptive filters; Electrocardiography; Equations; Filter banks; Filtering algorithms; Fourier transforms; Noise; Alpha-Beta filter; SNR; denoising; estimation; power line interference;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, Computing and Control (ISPCC), 2012 IEEE International Conference on
  • Conference_Location
    Waknaghat Solan
  • Print_ISBN
    978-1-4673-1317-9
  • Type

    conf

  • DOI
    10.1109/ISPCC.2012.6224372
  • Filename
    6224372