Mathematical model to determine the Coagulation Time Human Blood from Experimental Data
Keywords:
Coagulation, Models, Signals, Dynamic SystemsAbstract
In this paper a linear mathematical model of first order with delay is presented to characterize the clotting time of blood from experimental data obtained by the technique of dynamic speckle. The experimental platform used has a CCD camera, a He-Ne laser and a computer for recording and processing information. Experimental results are presented, analysis and development of an automatic control system to validate the proposed medical treatment aimed at reducing the coagulation time of blood
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S. Krajewski, S. Krauss, J. Kurz, B. Neumann, C. Schlensak, and H. P. Wendel, “Real-time measu- rement of free thrombin: Evaluation of the usability of a new thrombin assay for coagulation monitoring during extracorporeal circulation,” Thrombosis Research, vol. 133, no. 3, pp. 455 – 463, 2014.
M. M. Patino Velasco, J. A. Vasquez Lopez, A. Erazo, C. Augusto, Arizaga, Ricardo, Rabal, H. Rabal, and T. Marcelo, “Determination of coagulation time of human blood by biospeckle technique,” pp. 80 118S–80 118S–5, 2011. [Online]. Available: http://dx.doi.org/10.1117/12.902185
S. Ravanshadi and M. Jahed, “Mathematical mode- ling of human blood clotting formation,” in Informa- tion Technology Applications in Biomedicine, 2007. ITAB 2007. 6th International Special Topic Conference on, Nov 2007, pp. 273–276.
A. Federico, G. Kaufmann, G. Galizzi, H. Rabal, M. Trivi, and R. Arizaga, “Simulation of dynamic speckle sequences and its application to the analysis of transient processes,” Optics Communications, vol. 260, no. 2, pp. 493 – 499, 2006.
A. V. Saúde, F. S. de Menezes, P. L. S. Freitas, G. F. Rabelo, and R. A. Braga, “Alternative measures for biospeckle image analysis,” J. Opt. Soc. Am. A, vol. 29, no. 8, pp. 1648–1658, Aug 2012.
M. F. Limia, A. M. N. nez, H. Rabal, and M. Trivi, “Wavelet transform analysis of dynamic speckle patterns texture,” Appl. Opt., vol. 41, no. 32, pp. 6745–6750, Nov 2002.
A. L. Dai Pra, L. I. Passoni, and H. Rabal, “Evaluation of laser dynamic speckle signals applying granular computing,” Signal Process., vol. 89, no. 3, pp. 266–274, Mar. 2009.
K. Åström and T. Hägglund, Advanced PID Control. ISA-The Instrumentation, Systems, and Automation Society, 2006.
L. Ljung, System Identification: Theory for the User, ser. Prentice-Hall information and system sciences series. Prentice Hall PTR, 1999.
B. Dahlbakc, “Blood coagulation and its regulation by anticoagulant pathways: genetic pathogenesis of bleeding and thrombotic diseases,” Journal of Internal Medicine, vol. 257, no. 3, pp. 209–223, 2005. [Online]. Available: http://dx.doi. org/10.1111/ j.1365-2796.2004.01444.x
W. H. Howell, “Theories of blood coagulation,” Phy- siological Reviews, vol. 15, no. 3, pp. 435–470, 1935.
M. M. P. Velasco, “Determinación del tiempo de coa- gulación en seres humanos a partir de speckle dinámico,” Master’s thesis, Universidad del Cauca, 2012.
J. G. Ziegler and N. B. Nichols, “ Optimum Settings for Automatic Controllers,” Transactions of ASME, vol. 64, pp. 759–768, 1942.
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