Blood glucose regulation using labview

https://doi.org/10.31295/ijcms.v1n1.2

Authors

  • M Nalini Research Scholar/SCSVMV University, India, Department of Electronics and Instrumentation Engineering/Sri Sairam Engineering College, India
  • V Balaji Faculty of Electrical Engineering/Bahir Dar University, Ethiopia
  • R Gayathiri Department of Electronics and Instrumentation Engineering/Sri Sairam Engineering College, India.

Keywords:

Lab View, PID Controller, Artificial Pancreas, Glucose Regulation, Fuzzy logic Controller

Abstract

Diabetes mellitus (DM), commonly referred to as diabetes, is a group of metabolic diseases in which there are high blood sugar levels over a prolonged period. If not regulate the glucose level then it will cause the serious damage to heart, kidneys, eyes, and nerves. The pancreas produces insulin to absorb the glucose. In type I diabetes the pancreas does not secrete insulin to compensate this artificial pancreas will be used. The artificial pancreas will mimic the function of pancreas it consists of a sensor, controller and insulin pump. The sensor continuously monitors glucose, the amount of insulin required will be calculated using a controller then injected using insulin pump this is the function of the artificial pancreas. The food we take is converted into glucose. So, meal intake will greatly affect the glucose levels, in this paper a closed loop model is developed based on Bergman’s minimal model and meal intake is introduced as a disturbance then the control action is performed using Fuzzy and PID controller using LABVIEW software.  So, from this, if the glucose concentration exceeds/decreases, above/below a certain point necessary control action will be taken.

Downloads

Download data is not yet available.

References

Ackerman, E., Gatewood, L. C., Rosevear, J. W., & Molnar, G. D. (1965). Model studies of blood-glucose regulation. The bulletin of mathematical biophysics, 27(1), 21-37.

Bergman, R. N., Phillips, L. S., & Cobelli, C. (1981). Physiologic evaluation of factors controlling glucose tolerance in man: measurement of insulin sensitivity and beta-cell glucose sensitivity from the response to intravenous glucose. The Journal of clinical investigation, 68(6), 1456-1467.

Chee, F., Fernando, T. L., Savkin, A. V., & Van Heeden, V. (2003). Expert PID control system for blood glucose control in critically ill patients. IEEE Transactions on Information Technology in Biomedicine, 7(4), 419-425.

Cobelli, C., & Ruggeri, A. (1983). Evaluation of portal/peripheral route and of algorithms for insulin delivery in the closed-loop control of glucose in diabetes-A modeling study. IEEE Transactions on Biomedical Engineering, (2), 93-103.

Cobelli, C., Federspil, G., Pacini, G., Salvan, A., & Scandellari, C. (1982). An integrated mathematical model of the dynamics of blood glucose and its hormonal control. Mathematical Biosciences, 58(1), 27-60.

Dua, P., Doyle, F. J., & Pistikopoulos, E. N. (2006). Model-based blood glucose control for type 1 diabetes via parametric programming. IEEE Transactions on Biomedical Engineering, 53(8), 1478-1491.

Eiselein, L., Schwartz, H. J., & Rutledge, J. C. (2004). The challenge of type 1 diabetes mellitus. ILAR journal, 45(3), 231-236.

Fernandez, M., Acosta, D., Villasana, M., & Streja, D. (2004, September). Enhancing parameter precision and the minimal modeling approach in type I diabetes. In Engineering in Medicine and Biology Society, 2004. IEMBS'04. 26th Annual International Conference of the IEEE (Vol. 1, pp. 797-800). IEEE.

Ifeanyichukwu, C. D., & Peter, A. (2018). The Role of Sensory Marketing in Achieving Customer Patronage in Fast Food Restaurants in Awka. International Research Journal of Management, IT and Social Sciences (IRJMIS), 5(2), 155-163.

Jurgaitis, N. (2018). Economic crisis as a supernatural being in public discourse. International Journal of Linguistics, Literature and Culture (IJLLC), 4(2), 66-71.

Kanderian, S. S., Weinzimer, S., Voskanyan, G., & Steil, G. M. (2009). Identification of intraday metabolic profiles during closed-loop glucose control in individuals with type 1 diabetes.

Kienitz, K. H., & Yoneyama, T. (1993). A robust controller for insulin pumps based on H-infinity theory. IEEE Transactions on Biomedical Engineering, 40(11), 1133-1137.

Lam, Z. H., Hwang, K. S., Lee, J. Y., Chase, J. G., & Wake, G. C. (2002). Active insulin infusion using optimal and derivative-weighted control. Medical Engineering and Physics, 24(10), 663-672.

Li, C., & Hu, R. (2007, July). Simulation study on blood glucose control in diabetics. In Bioinformatics and Biomedical Engineering, 2007. ICBBE 2007. The 1st International Conference on (pp. 1103-1106). IEEE.

Meza, A. K. T., Freyre, J. R. A., Cevallos, M. G. O., & Pico, M. J. M. (2018). Autonomy, Good Humor and Support Networks, Potential of Community Resilience Intervention in People Victims of the Earthquake in the Calderón Parish. International Research Journal of Management, IT and Social Sciences (IRJMIS), 5(1), 1-8.

Nalini, M., Balaji, V., & Gayathiri, R. Closed loop model for blood glucose regulation system using labview.

Nuriyasa, I. M., Puspani, E., & Yupardhi, W. S. (2018). Growth and Blood Profile of Lepus Nigricollis Fed Diet Fermented Coffee Skin in Different Levels. International Journal of Life Sciences (IJLS), 2(1), 21-28.

Parker, R. S., & Doyle III, F. J. (2001). Control-relevant modeling in drug delivery. Advanced drug delivery reviews, 48(2-3), 211-228.

Puckett, W. R., & Lightfoot, E. N. (1995). A model for multiple subcutaneous insulin injections developed from individual diabetic patient data. American Journal of Physiology-Endocrinology and Metabolism, 269(6), E1115-E1124.

Santiago, J. V., Clemens, A. H., Clarke, W. L., & Kipnis, D. M. (1978). Closed-loop and open-loop devices for blood glucose control in normal and diabetic subjects. Diabetes, 28(1), 71-84.

Srinivas, P., & Rao, P. D. P. (2012). Closed loop model for glucose insulin regulation system using labview. International journal of instrumentation and control systems (IJICS), 2(4).

Suwitri, N. P. E., & Sidiartha, I. G. L. (2018). Omega-6 and Omega-3 Fatty Acid Content and Ratio of Commercial Complementary Foods. International Journal of Health Sciences (IJHS), 2(1), 21-28.

Published

2018-05-08

How to Cite

Nalini, M., Balaji, V., & Gayathiri, R. (2018). Blood glucose regulation using labview. International Journal of Chemical & Material Sciences, 1(1), 1-6. https://doi.org/10.31295/ijcms.v1n1.2