Fuzzy Identification and Modeling of Common Caffeine-Containing Beverages Consumption on Blood Pressure
DOI:
https://doi.org/10.3923/pjn.2015.563.569Keywords:
Caffeine-containing beverages, caffeine consumption, diastolic blood pressure, fuzzy modeling, systolic blood pressureAbstract
The aim of the present study was to determine the effect of moderate caffeine consumption on blood pressure, also, to construct a prediction model for blood pressure using fuzzy modeling. The blood pressure was measured for each participant at several times after drinking the beverages. An adaptive neuro-fuzzy inference system (ANFIS) was used to model and identify the systolic and diastolic of the blood pressure. Experimental validation runs were conducted to compare the measured values and the predicted ones. The final fuzzy-based FIS model for the systolic blood pressure was formed from 62 total number of parameters, 398 number of training data pairs and 32 number of fuzzy rules. The results showed that the validation was 90% modeling or prediction accuracy of systolic blood pressure. The final fuzzy-based FIS model for the diastolic blood pressure was formed from 190 total number of parameters, 398 number of training data pairs and 162 number of fuzzy rules. The results showed that the average validation was 85% modeling or prediction accuracy of diastolic blood pressure. Based on the analysis results, it was found that the prediction of the systolic and diastolic of the blood pressure based on the caffeine consumption by ANIFS is probable. This method may be used to provide a simple means for determining the blood pressure after consuming a certain amount of caffeine-containing beverages.
References
Ghoush, M.A., M. Samhouri, M. Al-Holy and T. Herald, 2008. Formulation and fuzzy modeling of emulsion stability and viscosity of a gum-protein emulsifier in a model mayonnaise system. J. Food Eng., 84: 348-357.
AOAC, 1980. Official Methods of Analysis of the Association of Official Analytical Chemists. 13th Edn., Association of Official Analytical Chemists, Washington, DC, United State, ISBN-13: 9780935584141, Pages: 1018.
Bush, A., C.M. Busst, B. Clarke and P.J. Barnes, 1989. Effect of infused adenosine on cardiac output and systemic resistance in normal subjects. Br. J. Clin. Pharmacol., 27: 165-171.
Chvasta, T.E. and A.R. Cooke, 1971. Emptying and absorption of caffeine from the human stomach. Gastroenterology, 61: 838-843.
Carter, A.J., W.T. O'Connor, M.J. Carter and U. Ungerstedt, 1995. Caffeine enhances acetylcholine release in the hippocampus in vivo by a selective interaction with adenosine A1 receptors. J. Pharmacol. Exp. Therapeut., 273: 637-642.
Goldstein, I.B., D. Shapiro, K.K. Hui and J.L. Yu, 1990. Blood pressure response to the second cup of coffee. Psychosomatic Med., 52: 337-345.
Higdon, J.V. and B. Frei, 2006. Coffee and health: A review of recent human research. Crit. Rev. Food Sci. Nutr., 46: 101-123.
James, J.E., 2004. Critical review of dietary caffeine and blood pressure: A relationship that should be taken more seriously. Psychosomatic Med., 66: 63-71.
Jang, J.S.R., 1993. ANFIS: Adaptive-network-based fuzzy inference system. IEEE Trans. Syst. Man Cybern., 23: 665-685.
Lane, J.D. and R.B. Williams Jr., 1985. Caffeine affects cardiovascular responses to stress. Psychophysiology, 22: 648-655.
Noordzij, M., C.S. Uiterwaal, L.R. Arends, F.J. Kok, D.E. Grobbee and J.M. Geleijnse, 2005. Blood pressure response to chronic intake of coffee and caffeine: A meta-analysis of randomized controlled trials. J. Hypertens., 23: 921 -928.
Nurminen, M.L., L. Niittynen, R. Korpela and H. Vapaatalo, 1999. Coffee, caffeine and blood pressure: A critical review. Eur. J. Clin. Nutr., 53: 831-839.
Papaioannou, T.G., C. Vlachopoulos, N. Ioakeimidis, N. Alexopoulos and C. Stefanadis, 2006. Nonlinear dynamics of blood pressure variability after caffeine consumption. Clin. Med. Res., 4: 114-118.
Perrot, N., L. Me, G. Trystram, J. Trichard and M. Deloux, 2003. An hybrid approach based on fuzzy logic and genetic algorithms to control a crossflow microfiltration pilot plant. ENSIA-INRA, 91305, Department of Food Engineering, Massy, France.
Roberts, A.T., L. de Jonge-Levitan, C.C. Parker and F. Greenway, 2005. The effect of an herbal supplement containing black tea and caffeine on metabolic parameters in humans. Altern. Med. Rev., 10: 321-325.
Rall, T.W., 1990. Drugs Used in the Treatment of Asthma: The Methylxanthines, Cromolyn Sodium and other Agents. In: Goodman and Gilman's the Pharmacological Basis of Therapeutics, Gilman, A.G., T.W. Rall, A.S. Nies and P. Taylor (Eds.). Pergamon Press, New York, USA., pp: 618-637.
Smits, P., T. Thien and A. van't Laar, 1985. Circulatory effects of coffee in relation to the pharmacokinetics of caffeine. Am. J. Cardiol., 56: 958-963.
Samhouri, M., M. Abughoush and T. Herald, 2007. Fuzzy identification and modeling of a gum-protein emulsifier in a model mayonnaise color development system. Int. J. Food Eng., Vol. 3.
Tsourveloudis, N. and L. Kiralakis, 2002. Rotary drying of olive stones: Fuzzy modeling and control. Department of Production Engineering and Management, Technical University of Crete, BA3015.
Downloads
Published
Issue
Section
License
Copyright (c) 2015 Asian Network for Scientific Information
This work is licensed under a Creative Commons Attribution 4.0 International License.
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.
