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Independent component analysis and adaptive filtering as successful tools for an improvement of normogastric rhythm extraction in electrogastrographic signals

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The aim of this study was to investigate the possibility of combining two methods: Independent Component Analysis (ICA) and Adaptive Signal Enhancement for the improvement of normogastric rhythm extraction from multichannel recording of electrogastrographic signals (EGG). Unfortunately the electrogastrogram, is a transcutaneous measurement of gastric electrical activity, does not contain pure signal but usually is a sort of mixture from both electrical activity of stomach as well as other organs surrounding it and random noise. In order to benefit the diagnostic power of multichannel recording of EGG, which can provide deeper understanding of gastric disorders, it is necessity to extract gastric slow wave in each channel. One of the parameters, which are analyzed and require proper registration is so called normogastric rhythm. According to the literature, the normogastric rhythm should cover around 70% of rhythmic behavior of signal for a healthy man. Proper extraction of basic 3-cpm normogastric rhythm in each channel is a subject of this paper. Independent Component Analysis is applied for extracting the reference signal for adaptive filtering what next result in obtaining less contaminated signal in each channel. Analysis has been perform for two postprandial phases with five minutes break between them. In both mention cases proposed procedure gives a promising results.
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27--34
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Bibliogr. 16 poz., rys., tab.
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Bibliografia
  • [1] ALVAREZ W.C., The Electrogastrogram and what it shows, Journal of the American Medical Association, 1992, 78 pp. 1116-1119.
  • [2] CHEN J., Spectral Analysis of Electrogastrogram and its Clinical Significance, China Natl J New Gastroenterol 1996 Mar 2, (Suppl 1), The WJGg Press.
  • [3] CHEN J.D.Z., ZOU X., LIN X., OUYANG S., LIANG J., Dectection of Gastric Slow Wave Propagation From The Cutaneous Electrogastrogrm, AJP - Gastrointestinal and Liver Physiology, Vol. 277, Issue 2, G424-G430, 1999.
  • [4] COMON P., Independent Component Analysis, A New Concept?, Elsevier, Vol.36, No 3, Special Issue on High-Order Statistics, April 1994.
  • [5] HYVARINEN A., New Approximations of Differential Entropy for Independent Component Analysis and Projection Pursuite, In Advances In Neural Information Processing Systems, Vol.10, Mit Press 1998, pp.273-379.
  • [6] HYVARINEN A., Survey on Independent Component Analysis. Neural Computing Surveys, 1999, pp. 94-128, http://www.cis.hut.fi/Aapo/.
  • [7] HYVARINEN A., Fast And Robust Fixed-Point Algorithms for Independent Component Analysis, IEEE Transactions on Neural Networks, 1999, 10(3), pp. 626-634.
  • [8] HYVARINEN A., OJA E., Independent Component Analysis: Algorithms and Applications, Neural Networks, 2000, 13(4-5), pp. 411-430.
  • [9] KOCH K.L., STERN R.M., Handbook of Electrogastrography, Oxford University Press, 2004.
  • [10] LIANG H., Extraction of Gastric Slow Waves From Electrogastrograms: Combining Independent Coponent Analysis and Adaptive Signal Enhancement, Medical & Biological Engineering & Computing, 2005, Vol.43, pp. 245-251.
  • [11] Medtronic Polygram Nettm Electrogastrography Application-User Guide. Medtronic Functional Diagnostics A/S 2001.
  • [12] 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, 2003, 15, pp. 89-102, Journal of Latex Class Files, Vol. 6, No. 1, January 2007.
  • [13] SANDERS K.M., WARD S.M., Physiology And Pathophysiology of Interstitial Cells Of Cajal: From Bench To Bedside, IV Genetic and Animals Models of GI Motility Disorders Caused By Loss of Interstitial Cells of Cajal. AJP Gastrointestinal And Liver Physiology, Vol. 282, May 2002, pp. 747-756.
  • [14] SHLENS J. A., Tutorial On Principal Component Analysis, December, 2005, Version 2.
  • [15] WANG Z.S., CHEUNG J.Y., CHEN J.D.Z., Blind Separation Of Multichannel Electrogastrograms Using Independent Component Analysis Based On A Neural Network, Medical & Biomedical Engineering & Computing, Vol. 37, 1999, pp. 80-86.
  • [16] WARD S.M., SANDERS K.M., Physiology And Pathophysiology of Interstitial Cell of Cajal: From Bench To Bedside, I Functional Development And Plasticity of Interstitial Cells of Cajal Networks, AJP Gastrointestinal And Liver Physiology, Vol. 281, September 2001, pp. 602-611.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-PWA4-0018-0003
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