Achieving Open-loop Insulin Delivery using ITM Designed for T1DM Patients

Автор: Akash Rajak, Kanak Saxena

Журнал: International Journal of Computer Network and Information Security(IJCNIS) @ijcnis

Статья в выпуске: 1 vol.4, 2012 года.

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To simulate the glucose-insulin concentration of type 1 diabetic patient an Intelligent Temporal Mediator (ITM) has been designed. The ITM integrates the tasks of temporal reasoning and temporal maintenance. The paper discusses the design of ITM reasoning system which was based on open-loop insulin delivery technique. The result shows that ITM successfully models the blood glucose profile of the diabetic patient. The designed ITM is also compared with existing open-loop simulator for checking its performance.

Temporal mediator, temporal reasoning, temporal maintenance, T1DM

Короткий адрес: https://sciup.org/15011049

IDR: 15011049

Список литературы Achieving Open-loop Insulin Delivery using ITM Designed for T1DM Patients

  • A. Rajak, K. Saxena. Achieving Realistic and Interactive Clinical Simulation using Case based Therasim’s Therapy Engine Dynamically. In: Proceedings of the National Conference on Advanced Pattern Mining and Multimedia Computing, 2010, 624–628.
  • A. Rajak, K. Saxena. Modeling Temporal Databases-A Survey. International Journal of Computer and Electronics Engineering, 2009, 1(1), 77–82.
  • A. Rajak, K. Saxena. Managing Temporal Databases. In: Proceedings of the International Conference on Managing Next Generation Software Applications, 2008, 107–114.
  • Y. Shahar, C. Combi. Temporal Reasoning and Temporal Data Maintenance in Medicine: Issues and Challenges. Computers in Biology and Medicine, 1997, 27(5), 353–368.
  • A. Rajak, K. Saxena. Research Issues Related to Temporal Mediators based on Clinical Domain. International Journal of Recent Trends in Engineering, 2009, 1(1), 535–540.
  • A. Rajak, K. Saxena. Temporal Abstraction Database Mediators based on Clinical Guidelines. In: Proceedings of the IEEE International Advance Computing Conference, 2009, 2274–2279.
  • A. Rajak, K. Saxena. Temporal Reasoning with Time Oriented Medical Database using Models based on Insulin-Glucose Metabolism. International Journal of Computer Science and Information Technology & Security, 2011, 1(2), 66–70.
  • A. Rajak, K. Saxena. Design of ITM Reasoning System based on Open-loop Insulin Delivery Method for T1DM. Accepted for publication.
  • R. N. Bergman, G. M. Steil, A. Volund, S. E. Kahn. Reduced Sample Number for Calculation of Insulin Sensitivity and Glucose Effectiveness from the Minimal Model. Diabetes 42, 1993, 250–256.
  • R. N. Bergman, G. Pacini. MINMOD: A Computer Program to Calculate Insulin Sensitivity and Pancreatic Responsivity from the Frequently Sampled Intravenous Glucose Tolerance Test. Computer Methods and Programs in Biomedicine 23, 1986, 113–122.
  • R. N. Bergman, G. Toffolo, D. T. Finegood, C. R. Bowden, C. Cobelli. Quantitative Estimation of Beta Cell Sensitivity to Glucose in the Intact Organism-A Minimal Model of Insulin Kinetics in the Dog. Diabetes 29, 1980, 979–990.
  • R. N. Bergman, L. S. Phillips, C. Cobelli. Physiological Evaluation of Factors Controlling Glucose Tolerance in Man. Journal of Clinical Investigation 68, 1981, 1456–1467.
  • R. N. Bergman, M. F. Saad, R. L. Anderson, A. Laws, R. M. Watanabe, W. W. Kades, Y. D. I. Chen, R. E. Sands, D. Pei, P. J. Savage. A Comparison between the Minimal Model and the Glucose Clamp in the Assessment of Insulin Sensitivity across the Spectrum of Glucose Tolerance. Diabetes 43, 1994, 1114–21.
  • R. N. Bergman, Y. Z. Ider, C. R. Bowden, C. Cobelli. Quantitative Estimation of Insulin Sensitivity. American Journal of Physiology 236, 1979, E667–77.
  • R. N. Bergman. Minimal Models for Glucose and Insulin Kinetics. http://www.civilized.com/mlabexamples/glucose.htmld/
  • M. E. Fisher. A Semi-Closed Loop Algorithm for the Control of Blood Glucose Levels in Diabetes. IEEE Transactions on Biomedical Engineering 38, 1991, 57–61.
  • A. Roy. Dynamic Modeling of Free Fatty Acid, Glucose, and Insulin during Rest and Exercise in Insulin Dependent Diabetes Mellitus Patients. Doctoral Dissertation, University of Pittsburgh, PhD, 2008.
  • A. Rajak, K. Saxena. Modeling Clinical Database using Time Series based Temporal Mining. International Journal of Computer Theory and Engineering, 2010, 2(2), 185–188.
  • E. D. Lehmann, T. Deutsch. A Physiological Model of Glucose-Insulin Interaction in Type 1 Diabetes Mellitus. Journal of Biomedical Engineering, May 1992, 14(3), 235–242.
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