Medical and Biological Engineering and Computing

, Volume 38, Issue 1, pp 35-41

First online:

Artifact reduction in electrogastrogram based on empirical mode decomposition method

  • H. LiangAffiliated withCenter for Complex Systems & Brain Sciences, Florida Atlantic University Email author 
  • , Z. LinAffiliated withDepartment of Medicine, University of Kansas Medical Center
  • , R. W. McCallumAffiliated withDepartment of Medicine, University of Kansas Medical Center

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Severe contamination of the gastric signal in electrogastrogram (EGG) analysus by respiratory, motion, cardiac artifacts, and possible myoelectrical activity from other organs, poses a major challenge to EGG interpretation and analysis. A generally applicable method for removing a variety of artifacts from EGG recordings is proposed based on the empirical mode decomposition (EMD) method. This decomposition technique is adaptive, and appears to be uniquely suitable for nonlinear, non-stationary data analysis. The results show that this method, combined with instantaneous frequency analysis, effectively separate, identify and remove contamination from a wide variety of artifactual sources in EGG recordings.


Electrogastrogram Empirical mode decomposition Artifact reduction Hilbert transform Nonstationary