The remote control system of the insulin level

• Autorzy: Doniec R.
• Języki publikacji: EN

Abstrakty

EN

The following research characterises the system for remote data collection of blood glucose concentration. Based on the data an algorithm was introduced in order to determine the infusion of insulin. This paper presents a glucose measurement method using the test strips, instructions for collecting the source data, as well as the process of adjusting the insulin dosage.

Słowa kluczowe

EN

glucose concentration; telemedicine; artificial organs

PL

stężenie glukozy; telemedycyna; sztuczne organy

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2010
• Tom: Vol. 15
• Strony: 201--208
• Opis fizyczny: Bibliogr. 14 poz., rys., tab.

Twórcy

autor

Doniec R.

• Telekomunikacja Polska, Francuska 101, Katowice

Bibliografia

• [1] BROWN S.J., RAMARAJU H., LUNA A., KOCH C., Model of Glucose and Insulin Kinetics Implemented in SIMULINK, Antwerp KV, BMED, Gorgia Institute of Technology, 2003.
• [2] BELLAZZI R., SIVIERO C., STEFANELLI M., NICOLAO G., Adaptive Controllers For Intelligent Monitoring, Artificial Intelligence In Medicine 7, 1995, pp. 515A540.
• [3] COBELLI C., NUCCI G., Model Of Subcutaneous Insulin Kinetics. A critical review, Computer Methods and Programs in Biomedicine 62, 2000, pp. 249P257.
• [4] PARKER R., DOYLE F., Control–Relevant Modeling In Drug Delivery, Advanced Drug Delivery Reviews, Vol. 48, 2001, pp. 2114228.
• [5] YOUNG T.H., CHUANG W.Y., HSIEH M.Y., CHEN L.W., HSU J.P., Assessment And Modelling Of Poly(Winyl Alcohil) Bioartificial Pancreas In Vivo, Biomaterials 23, 2002, pp. 3495P3501.
• [6] YOUNG T.H., HSU J.P., NIEN T.W., Kinetic Modelling Of Blond Glucose Variation In A Bioartificial Pancreas, Biomateriale 24, 2003, pp. 2251B2256.
• [7] TOLIC I.M., MOSEKILDE E., STURIS J., Modeling the Insulin–Glucose Feedback System The Significance of Pulsatile Insulin Secretion, J. theor.Biol. 207, 2000, pp. 360375.
• [8] NAŁĘCZ M. chief editor, Biocybernetics and Biomedical Engineering 2000, Academic Publishing House EXIT, 200122005, (in Polish).
• [9] ŚWIERCZ M., Application of Neural Networks For Modeling of Selected Biomedical Systems. Regression and Classification of Data, IBIB PAN, Warszawa, 2001, (in Polish).
• [10] ŁADYŻYŃSKI P., Effective Methods And Systems To Monitor The Condition Of The Patient In The Treatment Of Some Chronic Diseases, IBIB PAN, Warszawa, Vol. 70, 2008, (in Polish).
• [11] TROJANOWSKI Z., REGITTNIG W., WACH P., Simulation Study On Neural Predictive Control Of Glucose Using The Subcutaneous Route, Computer Methods And Programs In Biomedicine, 56, 1998, pp. 133U139.
• [12] TROJANOWSKI Z., REGITTNIG W., WACH P., Neural Predictive Controller For Closed–Loop Control Of Glucose Using The Subcutaneous Route: A Simulation Study, Control Engineering Practice, Vol. 12, 1997, pp. 172711730.
• [13] TROJANOWSKI Z., WACH P., Neural Predictive Controller for Closed Loop Control of Glucose Rusing the Subcutaneous Router a Simulation Study, Control Eng. Practice 5, 1997, pp. 1727S1730.
• [14] PILINGER J., E–Health, The Experience Of The Test To Start The Service In Orange Austria, Innovation Day, Warszawa, 2009, (in Polish).