Applying Similarity Theory and Hilbert Huang Transform for Estimating the Differences of Pig-s Blood Pressure Signals between Situations of Intestinal Artery Blocking and Unblocking

Authors: Jia-Rong Yeh, Tzu-Yu Lin, Jiann-Shing Shieh, Yun Chen

Abstract:

A mammal-s body can be seen as a blood vessel with complex tunnels. When heart pumps blood periodically, blood runs through blood vessels and rebounds from walls of blood vessels. Blood pressure signals can be measured with complex but periodic patterns. When an artery is clamped during a surgical operation, the spectrum of blood pressure signals will be different from that of normal situation. In this investigation, intestinal artery clamping operations were conducted to a pig for simulating the situation of intestinal blocking during a surgical operation. Similarity theory is a convenient and easy tool to prove that patterns of blood pressure signals of intestinal artery blocking and unblocking are surely different. And, the algorithm of Hilbert Huang Transform can be applied to extract the character parameters of blood pressure pattern. In conclusion, the patterns of blood pressure signals of two different situations, intestinal artery blocking and unblocking, can be distinguished by these character parameters defined in this paper.

Keywords: Blood pressure, spectrum, intestinal artery, similarity theory and Hilbert Huang Transform.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1078154

References:

[1] C.M. Marris, "The Fourier analysis of biological transients", Journal of Neuroscience method, 83(1998), pp. 15-34.
[2] L. Keselbrener, S. Akselrod, "Time- frequency analysis of transient signals - application to cardiovascular control", Physica A 249(1998),pp. 482-490.
[3] G.O. Young, "Synthetic structure of industrial plastics (Book style with paper title and editor)," in Plastics, 2nd ed. Vol. 3, J. Peters, Ed. New York: McGraw-Hill, 1964, pp.15-64.
[4] W. K. Chen, "Linear Networks and Systems (Book style)," Belmont, CA: Wadsworth, 1993, ch. 4.
[5] N.E. Huang, Z. Shen, S.R. Long, M.C. Wu, H.H. Shih, Q. Zheng, N.C. Yen, C.C. Tung , H.H. Liu," The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis," Proc. R. Soc. Lond. A (1998) 454, pp. 903-995.
[6] Y.X. Hu, S.C. Liu, and W. Dong, "Earthquake engineering," London: Chapman & Hall, 1996.
[7] N.E. Huang, S.R. Long, " An experimental study of surface elevation probability distribution and statistics of wind generated waves", J. Fluid Mech. 101, pp. 179-200, 1980.
[8] W. Huang, Z. Shen, N.E. Huang, Y.C. Fung," Engineering analysis of biological variables: An example of blood pressure over 1 day," Proc. Natl. Acad. Sci. USA vol. 95 April 1998, pp. 4816-4821.
[9] A.C.C. Yang, S.S. Hseu, H.W. Yien, A. L. Goldberger, C.K. Peng, " Linguistic analysis of the human heartbeat using frequency and rank order statistics", Physical review letters vol.90 no. 10, 14 March 2003, 108103.
[10] B.Boashash, "Estimating and interpreting the instantaneous frequency of a signal," Fundamental. Proc. IEEE 80, pp.520-538, 1992.
[11] L. Cohen, "Time-frequency analysis", Eaglewood Cliffs, NJ: Prentice-Hall, 1995.
[12] E.C. Titchmarsh, "Introduction to the theory of Fourier integrals," Oxford University Press 1948.