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Artifact reduction in electrogastrogram based on empirical mode decomposition method

  • H. Liang (Corresponding Author)
  • , Z. Lin
  • , R. W. McCallum

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)35-41
Number of pages7
JournalMedical and Biological Engineering and Computing
Volume38
Issue number1
DOIs
Publication statusPublished - Jan 2000
Externally publishedYes

Keywords

  • Artifact reduction
  • Electrogastrogram
  • Empirical mode decomposition
  • Hilbert transform
  • Nonstationary

ASJC Scopus subject areas

  • Biomedical Engineering
  • Computer Science Applications

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