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 language | English |
|---|---|
| Pages (from-to) | 35-41 |
| Number of pages | 7 |
| Journal | Medical and Biological Engineering and Computing |
| Volume | 38 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 2000 |
| Externally published | Yes |
Keywords
- Artifact reduction
- Electrogastrogram
- Empirical mode decomposition
- Hilbert transform
- Nonstationary
ASJC Scopus subject areas
- Biomedical Engineering
- Computer Science Applications
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