Artifact reduction in electrogastrogram based on empirical mode decomposition method

Severe contamination of the gastric signal in electrogastrogram (EGG) analy sus by respiratory, motion, cardiac artifacts, and possible myoelectrical a ctivity from other organs, poses a major challenge to EGG interpretation an d analysis. A generally applicable method for removing a variety of artifac ts from EGG recordings is proposed based on the empirical mode decompositio n (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, effe ctively separate, identify and remove contamination from a wide variety of artifactual sources in EGG recordings.