Electrogastrogram extraction using independent component analysis with references

Authors:
Cheng Peng;Xiang Qian;Datian Ye
Affiliations:
Tsinghua University, Department of Biomedical Engineering, Beijing, China and Tsinghua University, Research Center of Biomedical Engineering, Graduate School at Shenzhen, Shenzhen, China;Tsinghua University, Department of Biomedical Engineering, Beijing, China and Tsinghua University, Research Center of Biomedical Engineering, Graduate School at Shenzhen, Shenzhen, China;Tsinghua University, Department of Biomedical Engineering, Beijing, China and Tsinghua University, Research Center of Biomedical Engineering, Graduate School at Shenzhen, Shenzhen, China
Venue:
Neural Computing and Applications
Year:
2007

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PCA and ICA processing methods for removal of artifacts and noise in electrocardiograms: A survey and comparison

Applied Soft Computing

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Abstract

Electrogastrogram (EGG) is a noninvasive measurement of gastric myoelectrical activity cutaneously, which is usually covered by strong artifacts. In this paper, the independent component analysis (ICA) with references was applied to separate the gastric signal from noises. The nonlinear uncorrelatedness between the desired component and references was introduced as a constraint. The results show that the proposed method can extract the desired component corresponding to gastric slow waves directly, avoiding the ordering indeterminacy in ICA. Furthermore, the perturbations in EGG can be suppressed effectively. In summary, it can be a useful method for EGG analysis in research and clinical practice.