Literature DB >> 19885088

Dynamic modeling of exercise effects on plasma glucose and insulin levels.

Anirban Roy1, Robert S Parker.   

Abstract

BACKGROUND: Regulation of plasma glucose concentration for type 1 diabetic patients is challenging, and exercise is an added complication. From a metabolic prospective, the significant exercise-induced effects are increased glucose uptake rate by the working tissues, increased hepatic glucose release to maintain overall glucose homeostasis, and decreased plasma insulin concentration. During prolonged exercise, glucose levels drop significantly because of the decrease in hepatic glucose production. With the long-term goal of developing a closed-loop insulin delivery system operating under various physiological conditions, it is necessary to develop a model that is capable of predicting blood glucose concentration at rest and during physical activity.
METHODS: A minimal model developed previously was extended to include the major effects of exercise on plasma glucose and insulin levels. Differential equations were developed to capture the exercise-induced dynamics of plasma insulin clearance and the elevation of glucose uptake and hepatic glucose production rates. The decreasing liver glucose output resulting from prolonged exercise was modeled using an equation depending on exercise intensity and duration.
RESULTS: The exercise model successfully captured the glucose and insulin dynamics during short- and long-term exercise. Model predictions of glucose and insulin dynamics during the postexercise recovery period were also consistent with literature data.
CONCLUSION: The model successfully emulated the physiological effects of exercise on blood glucose and insulin levels. This extended model may provide a new disturbance test platform for the development of closed-loop glucose control algorithms.

Entities:  

Keywords:  diabetes; exercise; glucose; insulin; minimal model

Year:  2007        PMID: 19885088      PMCID: PMC2769581          DOI: 10.1177/193229680700100305

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  23 in total

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  22 in total

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4.  Evaluation of short-term predictors of glucose concentration in type 1 diabetes combining feature ranking with regression models.

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Journal:  Med Biol Eng Comput       Date:  2015-03-15       Impact factor: 2.602

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Authors:  Jing Fan Yang; Xun Gong; Naveed A Bakh; Kelley Carr; Nelson F B Phillips; Faramarz Ismail-Beigi; Michael A Weiss; Michael S Strano
Journal:  Diabetes       Date:  2020-03-09       Impact factor: 9.461

8.  Comparison of physical activity sensors and heart rate monitoring for real-time activity detection in type 1 diabetes and control subjects.

Authors:  Chinmay Manohar; Derek T O'Keeffe; Ling Hinshaw; Ravi Lingineni; Shelly K McCrady-Spitzer; James A Levine; Rickey E Carter; Ananda Basu; Yogish C Kudva
Journal:  Diabetes Technol Ther       Date:  2013-08-12       Impact factor: 6.118

9.  Clinical implications and economic impact of accuracy differences among commercially available blood glucose monitoring systems.

Authors:  Erwin S Budiman; Navendu Samant; Ansgar Resch
Journal:  J Diabetes Sci Technol       Date:  2013-03-01

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Authors:  B Wayne Bequette
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