• DocumentCode
    2107497
  • Title

    Power line interference cancellation in in-vivo neural recording

  • Author

    Keshtkaran, Mohammad Reza ; Zhi Yang

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore, Singapore
  • fYear
    2012
  • fDate
    Aug. 28 2012-Sept. 1 2012
  • Firstpage
    5214
  • Lastpage
    5217
  • Abstract
    This paper presents an algorithm for removing power line interference in neural recording experiments. It does not require any interference reference signal and can reliably track interference changes in frequency, phase, and amplitude. The method includes three major steps. First, it employs a robust frequency estimator to obtain the fundamental frequency of the interference. Second, a series of discrete-time oscillators are used to generate interference harmonics, where harmonic phase and amplitude are obtained using the recursive least squares (RLS) algorithm. Third, the estimated interference harmonics are removed without distorting the neural signals at the interference frequencies. The simple structure and adequate numerical behavior of the algorithm renders it suitable for realtime implementation. Extensive experiments based on both in-vivo and synthesized data have been performed, where a reliable performance has been observed.
  • Keywords
    electrocardiography; frequency estimation; harmonic generation; interference (signal); least squares approximations; medical signal processing; neurophysiology; recursive estimation; ECG; discrete-time oscillators; harmonic amplitude; harmonic phase; in-vivo neural recording; interference frequency; interference harmonic estimation; interference harmonic generation; neural signals; power line interference algorithm; power line interference cancellation; real-time implementation; recursive least squares algorithm; robust frequency estimator; Frequency estimation; Harmonic analysis; Interference cancellation; Oscillators; Reliability; Time frequency analysis; Action Potentials; Algorithms; Artifacts; Diagnosis, Computer-Assisted; Electricity; Electroencephalography; Neurons; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE
  • Conference_Location
    San Diego, CA
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-4119-8
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/EMBC.2012.6347169
  • Filename
    6347169