• DocumentCode
    2722610
  • Title

    Application of the empirical mode decomposition to the analysis of esophageal manometric data in gastroesophageal reflux disease

  • Author

    Liang, Hualou ; Lin, Qiu-Hua ; Chen, J.D.Z.

  • Author_Institution
    Sch. of Health Inf. Sci., Texas Univ., Houston, TX, USA
  • Volume
    1
  • fYear
    2004
  • fDate
    1-5 Sept. 2004
  • Firstpage
    620
  • Lastpage
    623
  • Abstract
    The empirical mode decomposition (EMD) is a general signal processing method for analyzing nonlinear and non-stationary time series. The central idea of EMD is to decompose a time series into a finite and often small number of intrinsic mode functions (IMFs). An IMF is defined as any function having the number of extrema and the number of zero-crossings equal (or differing at most by one), and also having symmetric envelopes defined by the local minima, and maxima respectively. The decomposition procedure is adaptive, data-driven, therefore, highly efficient The EMD is first described, and its performance is validated by simulations. The EMD is then applied to the analysis of esophageal manometric time series in gastroesophageal reflux disease. The results show that the EMD may prove to be a vital technique for the analysis of esophageal manometric data.
  • Keywords
    biomedical measurement; diseases; manometers; medical signal processing; time series; empirical mode decomposition; esophageal manometric data analysis; gastroesophageal reflux disease; intrinsic mode functions; nonlinear time series; nonstationary time series; signal processing; Back; Cardiac disease; Cardiovascular diseases; Catheters; Esophagus; Muscles; Nose; Pollution measurement; Pressure measurement; Stomach; Empirical mode decomposition; esophageal manometry; gastroesophageal reflux disease; lower esophageal sphincter;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE
  • Conference_Location
    San Francisco, CA
  • Print_ISBN
    0-7803-8439-3
  • Type

    conf

  • DOI
    10.1109/IEMBS.2004.1403234
  • Filename
    1403234