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Part of the book series: IFMBE Proceedings ((IFMBE,volume 18))

Abstract

We propose in this paper a method for the elimination of noise in biosignals, based on Lyapunov’s algebraic equation of stability for linear systems. The biosignals used were extracted from the MIT-BIH cardiac Arrhythmia Database. We corrupted these electro-cardiographic signals by adding randomly generated gaussian noise signals of different amplitudes. The method herein presented cancels noise within reasonable effectiveness and represents an alternative to other source separation algorithms.

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Referencias

  1. P. Comon, “Independent component analysis, A new concept?,” Signal Processing, Vol. 36, pp. 287–314, 1994.

    Article  MATH  Google Scholar 

  2. Matlab, Toolbox User’s Guide. Natick: Massachusetts: The Math-Works Inc., 2006.

    Google Scholar 

  3. G. B. Moody and R. G. Mark, “The Impact of the MIT-BIH Arrhythmia Database,” IEEE Engineering in Medicine & Biology Magazine, Vol. 20, No. 3, pp.45–50, May/June 2001.

    Article  Google Scholar 

  4. G. B. Moody, R. G. Mark and A. L. Goldberger, “PhysioNet: A Web-Based Resource for the Study of Physiologic Signals,” IEEE Engineering in Medicine & Biology Magazine, Vol. 20, No. 3, pp.70–75, May/June 2001.

    Article  Google Scholar 

  5. A. Hyvärinen, J. Karhunen and E. Oja, Independent Component Analysis. New York, NY: John Wiley & Sons, 2001, pp. 1–12.

    Book  Google Scholar 

  6. E. Vincent, R. Gribonval and C. Févotte, “Performance Measurement in Blind Audio Source Separation,” IEEE Transactions on Audio, Speech and Language Processing, Vol. 14, No. 4, pp. 1462–1469, July 2006.

    Article  Google Scholar 

  7. C. Févotte, R. Gribonval and E. Vincent, “BSS_EVAL Toolbox User Guide — Revision 2.0,” French GdR-ISIS/CNRS, Paris, France, Internal Report 1706, pp. 1–19, 2005.

    Google Scholar 

  8. H. Gävert, J. Hurri, J. Särelä and A. Hyvärinen, FastICA for Matlab, version 2.5. Natick: Massachusetts: The MathWorks Inc., 2005.

    Google Scholar 

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© 2007 Springer-Verlag Berlin Heidelberg

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Pisarello, M.I., Picaza, C.Á., Monzón, J.E. (2007). Eliminación de ruido en bioseñales utilizando la ecuación algebraica de Lyapunov. In: Müller-Karger, C., Wong, S., La Cruz, A. (eds) IV Latin American Congress on Biomedical Engineering 2007, Bioengineering Solutions for Latin America Health. IFMBE Proceedings, vol 18. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74471-9_19

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  • DOI: https://doi.org/10.1007/978-3-540-74471-9_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74470-2

  • Online ISBN: 978-3-540-74471-9

  • eBook Packages: EngineeringEngineering (R0)

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