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文章基本信息

  • 标题:Improved Power Spectrum Estimation for Rr-interval Time Series
  • 作者:B. S. Saini ; Dilbag Singh ; Moin Uddin
  • 期刊名称:International Journal of Computer Science
  • 出版年度:2009
  • 卷号:4
  • 期号:03
  • 出版社:World Enformatika Society
  • 摘要:

    The RR interval series is non-stationary and unevenly
    spaced in time. For estimating its power spectral density (PSD) using
    traditional techniques like FFT, require resampling at uniform
    intervals. The researchers have used different interpolation
    techniques as resampling methods. All these resampling methods
    introduce the low pass filtering effect in the power spectrum. The
    lomb transform is a means of obtaining PSD estimates directly from
    irregularly sampled RR interval series, thus avoiding resampling. In
    this work, the superiority of Lomb transform method has been
    established over FFT based approach, after applying linear and
    cubicspline interpolation as resampling methods, in terms of
    reproduction of exact frequency locations as well as the relative
    magnitudes of each spectral component

  • 关键词:HRV; Lomb Transform; Resampling; RR-intervals
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