A novel insulin delivery algorithm in rats with type 1 diabetes: The fading memory proportional-derivative method

Artificial Organs

Volumn 29, Issue 8, 2005, Pages 599-607

  Gopakumaran, Bala ^a   Duman, Heather M ^a   Overholser, Douglas P ^a   Federiuk, Isaac F ^a   Quinn, Matthew J ^a   Wood, Michael D ^a   Ward, W Kenneth ^a  

^a LEGACY RESEARCH   (United States)

Author keywords

Artificial pancreas; Closed loop algorithm; Fading memory; Performance index; Type 1 diabetes

Indexed keywords

ARTIFICIAL ORGANS; BLOOD; ERRORS; GLUCOSE; INSULIN;

ARTIFICIAL PANCREAS; CLOSED-LOOP; CLOSED-LOOP ALGORITHM; DERIVATIVE METHOD; FADING MEMORY; INSULIN DELIVERY; LOOP ALGORITHMS; PERFORMANCE INDICES; PROPORTIONAL-DERIVATIVE; TYPE 1 DIABETES;

RATS;

INSULIN;

ALGORITHM; ANIMAL CELL; ANIMAL EXPERIMENT; ANIMAL MODEL; ARTICLE; ARTIFICIAL PANCREAS; CONTROLLED STUDY; GLUCOSE BLOOD LEVEL; INSULIN DEPENDENT DIABETES MELLITUS; INSULIN TREATMENT; MATHEMATICAL ANALYSIS; MEMORY; NONHUMAN; PANCREAS ISLET BETA CELL; PRIORITY JOURNAL; RAT;

ANIMALIA;

EID: 27744588950     PISSN: 0160564X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.1525-1594.2005.29096.x     Document Type: Article

References (26)

1. Kadish AH. Automation control of blood sugar. I. A servo-mechanism for glucose monitoring and control. Am J Med Electron 1964;39:82-6.
2. Albisser AM. Intelligent instrumentation in diabetic management. Crit Rev Biomed Eng 1989;17:l-24.
3. Marliss EB, Murray FT, Stokes EF, et al. Normalization of glycemia in diabetics during meals with insulin and glucagon delivery by the artificial pancreas. Diabetes 1977;26:663-72.
4. Rebrin K, Fischer U, von Woedtke T, Abel P, Brunstein E. Automated feedback control of subcutaneous glucose concentration in diabetic dogs. Diabetologia 1989;32:573-6.
5. Shimoda S, Nishida K, Sakakida M, et al. Closed-loop subcutaneous insulin infusion algorithm with a short-acting insulin analog for long-term clinical application of a wearable artificial endocrine pancreas. Front Med Biol Eng 1997;8:197-211.
6. Goriya Y, Kawamori R, Shichiri M, Abe H. The development of an artificial beta cell system and its validation in depancreatized dogs: the physiological restoration of blood glucose homeostasis. Med Prog Technol 1979;6:99-108.
7. Kerner W, Thum C, Tamas G, Beischer W, Clemens AH, Pfeiffer EF. Attempts at perfect normalization of glucose tolerance test of severe diabetics by artificial beta cell. Horm Metab Res 1976;8:256-61.
8. Steil G, Panteleon A, Rebrin K. Closed loop insulin delivery-the path to physiological insulin delivery. Adv Drug Deliv Rev 2004;56:125-44.
9. Parker RS, Doyle FJ 3rd, Peppas NA. A model-based algorithm for blood glucose control in type I diabetic patients. IEEE Trans Biomed Eng 1999;46:148-57.
10. Pacini G, Bergman RN. PACBERG. an adaptive program for controlling the blood sugar. Comput Prog Biomed 1983;16:13-20.
11. Kan S, Onodera H, Furutani E, et al. Novel control system for blood glucose using a model predictive method. ASAIO J 2000;46:657-62.
12. Hovorka R, Canonico V, Chassin LJ, et al. Nonlinear model predictive control of glucose concentration in subjects with type 1 diabetes. Physiol Meas 2004;25:905-20.
13. Hovorka R, Chassin LJ, Wilinska ME, et al. Closing the loop: the adicol experience. Diabetes Technol Ther 2004;6:307-18.
14. Gogou G, Maglaveras N, Ambrosiadou BV, Goulis D, Pappas C. A neural network approach in diabetes management by insulin administration. J Med Syst 2001;25:119-31.
15. Dazzi D, Taddei F, Gavarini A, Uggeri E, Negro R, Pezzarossa A. The control of blood glucose in the critical diabetic patient: a neuro-fuzzy method. J Diabetes Complications 2001; 15:80-7.
16. Trajanoski Z, Regittnig W, Wach P. Simulation studies on neural predictive control of glucose using the subcutaneous route. Comput Meth Prog Biomed 1998;56:133-9.
17. Trajanoski Z, Wach P. Neural predictive controller for insulin delivery using the subcutaneous route. IEEE Trans Biomed Eng 1998;45:1122-34.
18. Steil GM, Rebrin K, Janowski R, Darwin C, Saad MF. Modeling beta-cell insulin secretion-implications for closed-loop glucose homeostasis. Diabetes Technol Ther 2003;5:953-64.
19. Nomura M, Shichiri M, Kawamori R, Yamasaki Y, Iwama N, Abe H. A mathematical insulin-secretion model and its validation in isolated rat pancreatic islets perifusion. Comput Biomed Res 1984;17:570-9.
20. Ward WK, Bolgiano DC, McKnight B, Halter JB, Porte D Jr. Diminished B cell secretory capacity in patients with noninsulin-dependent diabetes mellitus. J Clin Invest 1984;74:1318-28.
21. Hosker JP, Rudenski AS, Burnett MA, Matthews DR, Turner RC. Similar reduction of first- and second-phase B-cell responses at three different glucose levels in type II diabetes and the effect of gliclazide therapy. Metabolism 1989;38:767-72.
22. Laury MC, Takao F, Bailbe D, et al. Differential effects of prolonged hyperglycemia on in vivo and in vitro insulin secretion in rats. Endocrinology 1991;128:2526-33.
23. Levenston ME, Beaupre GS, Jacobs CR, Carter DR. The role of loading memory in bone adaptation simulations. Bone 1994;15:177-86.
24. Institute of Laboratory Animal Resources Commission on Life Sciences. Guide for the Care and Use of Laboratory Animals. Washington, DC: National Academy Press, 1996.
25. Federiuk IF, Casey HM, Quinn MJ, Wood MD, Ward WK. Induction of type-1 diabetes mellitus in laboratory rats by use of alloxan. route of administration, pitfalls, and insulin treatment. Comp Med 2004;54:252-7.
26. Candas B, Radziuk J. An adaptive plasma glucose controller based on a nonlinear insulin/glucose model. IEEE Trans Biomed Eng 1994;41:116-24.