Continuous wavelet transform as effective tools for detecting motion artefacts in electrogastrographical signals

• Autorzy: Mika B. , Tkacz E. , Kostka P. S.
• Języki publikacji: EN

Abstrakty

EN

The cutaneous recording of gastric myoelectrical activity of the stomach known as electrogastrography (EGG) seems to be the promising tool for the non-invasive 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.

Słowa kluczowe

EN

electrogastrogram; EGG; stomach; wavelet; signal processing

PL

żołądek; falka; przetwarzanie sygnałów

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2011
• Tom: Vol. 18
• Strony: 59--68
• Opis fizyczny: Bibliogr. 7 poz., rys., tab.

Twórcy

autor

Mika B.

• Silesian University of Technology, Institute of Electronics, Division of Microelectronics and Biotechnology, Gliwice, Poland

autor

Tkacz E.

autor

Kostka P. S.

Bibliografia

• [1] ALVAREZ W.C., The Electrogastrogram and What It Shows, Journal of the Americal Medical Association, Vol. 78, 1992, pp. 1116-1119.
• [2] KOCH K.L., STERN R.M., Handbook of Electrogastrography, Oxford University Press, 2004.
• [3] LIANG H., LIN Z., Stimulus Artifact Concellation in The Serosal Recordings of Gastric Myoelectrical Activity Using Wavelet Transform, IEEE Transactions On Biomedical Engineering, Vol. 49, No.7, 2002.
• [4] LIANG H., LIN Z., Multiresolution Signal Decomposition and Its Applications to Electrogastric Signals, Recent research developments in biomedical engineering, Vol. 1, 2002, pp. 15-31.
• [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, Vol. 15, 2003, pp. 89-102.
• [6] MALLAT S.G., A Theory for Multiresolution Signal Decomposition: The Wavelet Representation, IEEE Transactions on Pattern Analysis Machine Intelligence, Vol. 11, No. 7, 1989.
• [7] DE SOBRAL CINTRA R.J., TCHERVENSKY I.V., DIMITROV V.S., MINTCHEV M.R., Optimal Wavelets for Electrogastrography, Engineering in Medicine and Biology Society, IEMBS '04, 26th Annual International Conference of the IEEE, 2004.