Arteriovenous Shunt Stenosis Evaluation Using a Fractional-Order Fuzzy Petri Net Based Screening System for Long-Term Hemodialysis Patients

DOI: 10.4236/jbise.2014.75029   PDF   HTML     2,522 Downloads   3,713 Views   Citations


This paper proposes the evaluation of arteriovenous shunt (AVS) stenosis using a fractional-order Fuzzy Petri net based screening system for long-term hemodialysis treatment of patients. The screening system uses the Burg method, the fractional-order chaos system, and the Fuzzy Petri net (FPN) for early detection of AVS dysfunction. The Burg method is an autoregressive (AR) model that is used to estimate the frequency spectra of a phonoangiographic signal and to identify the spectral peaks in the region from 25 Hz to 800 Hz. In AVS, the frequency spectrum varies between normal blood flow and turbulent flow. The power spectra demonstrate changes in frequency and amplitude as the degree of stenosis changes. A screening system combining fractional-order chaos system and FPN is used to track the differences in the frequency spectra between the normal and stenosis access. The dynamic errors are indexes that can be used to evaluate the degree of AVS stenosis using a FPN. For 42 long-term follow-up patients, testing results show that the proposed screening system is more efficient in the evaluation of AVS stenosis.

Share and Cite:

Chen, W. , Kan, C. and Lin, C. (2014) Arteriovenous Shunt Stenosis Evaluation Using a Fractional-Order Fuzzy Petri Net Based Screening System for Long-Term Hemodialysis Patients. Journal of Biomedical Science and Engineering, 7, 258-275. doi: 10.4236/jbise.2014.75029.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Tsai, J.-C., Chen, S.-C., Hwang, S.-J., Chang, J.-M., Lin, M.-Y. and Chen, H.-C. (2010) Prevalence and Risk Factors for CKD in Spouses and Relatives of Hemodialysis Patients. American Journal of Kidney Diseases, 55, 856-866.
[2] Bethesda, M.D. (2011) National Institute of Diabetes and Digestive and Kidney Diseases. National Institutes of Health, 2, 298.
[3] Fillinger, M.F., Reinitz, E.R., Schwartz, R.A., Resetarits, D.E., Paskanik, A.M., Bruch, D. and Bredenberg, C.E. (1989) Beneficial Effects of Banding on Venous Intimal-Medial Hyperplasia in Arteriovenous Loop Grafts. American Journal of Surgery, 11, 87-94.
[4] Allon, M. and Robbin, M.L. (2009) Hemodialysis Vascular Access Monitoring: Current Concepts. Hemodialysis International, 13, 153.
[5] Loth, F., Fischer, P.F. and Bassiouny, H.S. (2008) Blood Flow in End-to-Side Anastomoses. Annual Review of Fluid Mechanics, 40, 367-393.
[6] Beathard, G. (2004) A Practitioner’s Guide to Physical Examination of Dialysis Vascular Access. Fistula First Project.
[7] Cheng, S.-M., Ng, S.-P., Yang, F.-S. and Shih, S.-L. (2003) Interventional Treatment for Complete Occlusion of Arteriovenous Shunt: Our Experience in 39 Cases. Chinese Journal of Radiology, 28, 137-142.
[8] Mansy, H.A., Hoxie, S.J., Patel, N.H. and Sandler, R.H. (2005) Computerised Analysis of Auscultatory Sounds Associated with Vascular Patency of Haemodialysis Access. Medical and Biological Engineering and Computing, 43, 56-62.
[9] National Kidney Foundation (2006) Clinical Practice Guidelines and Clinical Practice Recommendations. Clinical Practice Guidelines for Vascular Access.
[10] A., Asif, Gadalean, F.N., Merrill, D., Cherla, G., Cipleu, C.D., Epstein, D.L. and Roth, D. (2005) Inflow Stenosis in Arteriovenous Fistulas and Grafts: A Multicenter, Prospective Study. Kidney International, 67, 1986-1992.
[11] Vasquez, O.P., Munguia, M.M. and Mandersson, B. (2009) Arteriovenous Fistula Stenosis Detection Using Wavelets and Support Vector Machines. 31st Annual International Conference of the IEEE EMBS, Mineapolis, 2-6 September, 1298-1301.
[12] Gram, M., Olesen, J.T., Riis, H.C., Selvaratnam, M., Meyer-Hofmann, H., Pedersen, B.B., Christensen, J.H., Struijk, J. and Schmidt, S.E. (2011) Stenosis Detection Algorithm for Screening of Arteriovenous Fistulae. IFMBE Proceedings of 15th Nordic Baltic Conference on Biomedical Engineering and Medical Physics, 34, 241-244.
[13] Akay, Y.M., Akay, M., Welkowitz, W., Lewkowicz, S. and Semmlow, J.L. (1993) Noninvasive Acoustical Detection of Coronary Artery Disease: A Comparative Study of Signal Processing Methods. IEEE Transactions on Biomedical Engineering, 40, 571-578.
[14] Kannathal, N., Rajendra, A.U., Paul, J. and Ng, E.Y.K. (2006) Analysis of EEG Signals with and without Reflexology Using FFT and Auto Regressive Modeling Techniques. Chinese Journal of Medicine, 1, 12-20.
[15] Roth, K., Kauppinen, I., Esquef, P.A.A. and Valimaki, V. (2003) Frequency Warped Burg’s Method for AR-Modeling. IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, October 19-22, 5-8.
[16] Collomb, C. (2009) Linear Prediction and Levinson-Durbin Algorithm.
[17] Hwang, C., Leu, J.F. and Tsay, S.Y. (2002) A Note on Time-Domain Simulation of Feedback Fractional-Order Systems. IEEE Transactions on Automatic Control, 47, 625-631.
[18] Ge, Z.M. and Hsu, M.Y. (2007) Chaos in a Generalized Van Der Pol System and in Its Fractional Order System. Chaos, Solitons & Fractals, 33, 1711-1745.
[19] Podlubny, I. (1999) Fractional Differential Equations, Mathematics in Science and Engineering. Academic Press, New York.
[20] Ahson, S.I. (1995) Petri Net Models of Fuzzy Neural Networks. IEEE Transactions on Systems, Man, and Cybernetics, 25, 926-932.
[21] Chen, S.M. (2000) Fuzzy Backward Reasoning Using Fuzzy Petri Nets. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, 30, 846-856.
[22] Chen, S.M. (2002) Weighted Fuzzy Reasoning Using Weighted Fuzzy Petri Nets. IEEE Transactions on Knowledge and Data Engineering, 14, 386-397.
[23] Cao, Y.Z. and Chen, G.Q. (2010) A Fuzzy Petri-Nets Model for Computing with Words. IEEE Transactions on Fuzzy Systems, 18, 486-499.
[24] Chen, H.K. (2005) Synchronization of Two Different Chaotic Systems: A New System and Each of the Lorenz Dynamical Systems. Chaos, Solitons & Fractals, 23, 1245-1251.
[25] Chen, J.H. (2008) Controlling Chaos and Chaotification in the Chen-Lee System by Multiple Time Delays. Chaos, Solitons & Fractals, 36, 843-852.
[26] Ma, C.B. and Hori, Y. (2007) Fractional-Order Control: Theory and Applications in Motion Control. IEEE Industrial Electronics Magazine, 1, 6-16.
[27] McKay, C.B. and Meiselman, H.J. (1988) Osmolality-Mediated Fahraeus and Fahraeus-Lindqvist Effects for Human RBC Suspensions. American Journal of Physiology-Heart and Circulatory Physiology, 254, H238-H249.
[28] Schmidt, S.E., Graebe, M., Toft, E. and Sruijk, J.J. (2011) No Evidence of Nolinear or Chaotic Behavior of Cardiovascular Murmurs. Biomedical Signal Processing and Control, 6, 157-163.
[29] Lin, C.H., Chen, J.L., Du, Y.C., Pan, S.M. and Wu, J.X. (2011) Diabetic Foot Peripheral Vascular Occlusive Disease Estimation Using Fractional-Order Chaos Synchronization Detector. International Conference on Fluid Power and Mechatronics, Beijing, 17-20 August 2011, 597-601.
[30] Chen, W.L., Chen, T.S., Lin, C.H., Chen, P.J. and Kan, C.D. (2013) Phonoangiography with a Fractional Order Chaotic System—A New and Easy Algorithm in Analyzing Residual Arteriovenous Access Stenosis. Medical & Biological Engineering & Computing, 51, 1011-1019.
[31] Looney, C.G. and Alfize, A.R. (1987) Logical Controls via Boolean Rule Matrix Transformations. IEEE Transactions on Systems, Man and Cybernetics, 17, 1077-1082.
[32] Prabir, R.C., Vikas, P.S. and Alfred, K.C. (2006) Hemodialysis Vascular Access Dysfunction: A Cellular and Molecular Viewpoint. Journal of the American Society of Nephrology, 17, 1112-1127.
[33] Van Der Linden, J., Smits, J.H.M., Assink, J.H., Wolterbeek, D.W., Zijlstra, J.J., De Jong, G.H., Van Den Dorpel, M.A. and Blankestijn, P.J. (2002) Short- and Long-Term Functional Effects of Percutaneous Transluminal Angioplasty in Hemodialysis Vascular Access. Journal of the American Society of Nephrology, 13, 715-720.
[34] Wu, J.X., Lin, C.H., Du, Y.C. and Chen, T.S. (2012) Sprott Chaos Synchronization Classifier for Diabetic Foot Peripheral Vascular Occlusive Disease Estimation. IET Science, Measurement & Technology, Manuscript Acceptance, 6, 533-540.
[35] De Jesus Rubio, J. (2009) SOFMLS: Online Self-Organizing Fuzzy Modified Last-Squares Network. IEEE Transactions on Fuzzy Systems, 17, 1296-1309.
[36] Ratnaweera, A., Halgamuge, S.K. and Watson, H.C. (2004) Self-Organizing Hierarchical Particle Swarm Optimizer with Time-Varying Acceleration Coefficients. IEEE Transactions on Evolutionary, Computation, 8, 240-255.

comments powered by Disqus

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.