Journal article
Artifact reduction in electrogastrogram based on empirical mode decomposition method
Medical & biological engineering & computing, v 38(1), pp 35-41
Jan 2000
PMID: 10829388
Abstract
Severe contamination of the gastric signal in electrogastrogram (EGG) analysis 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.
Metrics
Details
- Title
- Artifact reduction in electrogastrogram based on empirical mode decomposition method
- Creators
- H Liang - Center for Complex Systems & Brain Sciences, Florida Atlantic University, Boca Raton, USA. liang@walt.ccs.fau.eduZ LinR W McCallum
- Publication Details
- Medical & biological engineering & computing, v 38(1), pp 35-41
- Publisher
- Springer Nature; United States
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000086521600007
- Scopus ID
- 2-s2.0-0033983754
- Other Identifier
- 991014878441804721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Engineering, Biomedical
- Mathematical & Computational Biology
- Medical Informatics