title: Artifact reduction in electrogastrogram based on empirical mode decomposition method.
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.
authors.affiliation: Center for Complex Systems & Brain Sciences, Florida Atlantic University, Boca Raton, USA. liang@walt.ccs.fau.edu
authors.forename: H
authors.initials: H
authors.lastname: Liang
authors.forename: Z
authors.initials: Z
authors.lastname: Lin
authors.forename: R W
authors.initials: RW
authors.lastname: McCallum
mesh_terms: D016477:Artifacts; D004568:Electrodiagnosis / Q000379:methods*; D006801:Humans; D012815:Signal Processing, Computer-Assisted; D013270:Stomach / Q000503:physiopathology; D013272:Stomach Diseases / Q000175:diagnosis*