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Electrogastrogram extraction using independent component analysis with references

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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.

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Acknowledgements

The authors would like to thank Prof. Z. C. Wu and his colleagues in Acupuncture Institute of China Academy of Traditional Chinese Medicine for their assistance in acquiring the EGG data used in this paper.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Tsinghua University, Beijing, China

    Cheng Peng, Xiang Qian & Datian Ye

  2. Research Center of Biomedical Engineering, Graduate School at Shenzhen, Tsinghua University, Shenzhen, China

    Cheng Peng, Xiang Qian & Datian Ye

Authors
  1. Cheng Peng
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  2. Xiang Qian
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  3. Datian Ye
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Correspondence to Datian Ye.

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Peng, C., Qian, X. & Ye, D. Electrogastrogram extraction using independent component analysis with references. Neural Comput & Applic 16, 581–587 (2007). https://doi.org/10.1007/s00521-007-0100-3

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  • DOI: https://doi.org/10.1007/s00521-007-0100-3

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