Continuous Wavelet Transform as an Effective Tools for Detecting Motion Artifacts in Electrogastrographical Signals

  • Barbara T. Mika
  • Ewaryst J. Tkacz
  • Paweł S. Kostka
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 95)


The cutaneous recording of gastric myoelectrical activity of the stomach known as electrogastrography (EGG) seems to be the promising tool for the noninvasive assessment of gastric motility. Unfortunately the EGG recording is usually severely contaminated both by motion artefacts and endogenous biological noise source. In order to use EGG signals as reliable diagnostic tool it is necessity to look for the effective artefacts removal methods. In this paper Continuous Wavelet Transform (CWT) was applied for detection motion artefacts from the EGG data. The set of own mother wavelets extracted directly from EGG signal was created and applied for detecting motion artefacts from one channel EGG recording. The results was compared with the effects obtained by using standard mother wavelets. The proposed method based on CWT with own mother wavelet presents very good performance for detecting motion artefacts from the EGG data.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Alvarez, W.C.: The Electrogastrogram and What It Shows. Journal of the Americal Medical Association 78, 1116–1119 (1992)Google Scholar
  2. 2.
    Koch, K.L., Stern, R.M.: Handbook of Electrogastrography. Oxford University Press, Oxford (2004)Google Scholar
  3. 3.
    Liang, H., Lin, Z.: Stimulus Artifact Concellation in The Serosal Recordings of Gastric Myoelectrical Activity Using Wavelet Transform. IEEE Transactions on Biomedical Engineering 49(7) (July 2002)Google Scholar
  4. 4.
    Liang, H., Lin, Z.: Multiresolution Signal Decomposition and Its Applications to Electrogastric Signals. Recent Research Developments in Biomedical Engineering 1, 15–31 (2002)Google Scholar
  5. 5.
    Parkman, H.P., Hasler, W.L., Barnett, J.L., Eaker, E.Y.: Electrogastrography: a Document Prepared by The Gastric Section of The American Motility Society Clinical GI Motility Testing Task Force. Neurogastroenterol Motility 15, 89–102 (2003)CrossRefGoogle Scholar
  6. 6.
    Mallat, S.G.: A Theory for Multiresolution Signal Decomposition: The Wavelet Representation. IEEE Transactions on Pattern Analysis Machine Intelligence 11(7) (1989)Google Scholar
  7. 7.
    de Sobral Cintra, R.J., Tchervensky, I.V., Dimitrov, V.S., Mintchev, M.R.: Optimal Wavelets for Electrogastrography. In: 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEMBS 2004 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Barbara T. Mika
    • 1
  • Ewaryst J. Tkacz
    • 1
    • 2
  • Paweł S. Kostka
    • 1
  1. 1.Institute of Electronics, Division of Microelectronics and BiotechnologySilesian University of TechnologyGliwicePoland
  2. 2.IT Department Manager in DąbrowaAcademy of BusinessGórniczaPoland

Personalised recommendations