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Method for calculating insulin action factor based on non-invasive blood glucose detection model of energy metabolism conservation method

A technology of acting factor and blood sugar detection, applied in the field of biomedical engineering, can solve problems such as insufficient accuracy, and achieve the effect of improving accuracy

Inactive Publication Date: 2019-01-04
GUILIN UNIV OF ELECTRONIC TECH
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Problems solved by technology

[0013] In order to solve the problem of insufficient accuracy of the existing non-invasive blood glucose meter in blood glucose detection of diabetic patients, the present invention provides a calculation method of insulin action factor based on the energy metabolism conservation method non-invasive blood glucose detection model, which can quantitatively analyze the regulation of insulin on blood glucose Improve the non-invasive blood sugar detection algorithm based on the energy metabolism conservation method to improve the accuracy of blood sugar detection

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  • Method for calculating insulin action factor based on non-invasive blood glucose detection model of energy metabolism conservation method
  • Method for calculating insulin action factor based on non-invasive blood glucose detection model of energy metabolism conservation method

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[0047]In the present invention, a method for calculating insulin action factors based on a non-invasive blood sugar detection model based on energy metabolism conservation method is to combine oral glucose test with insulin release test, use the data set obtained from the test, and establish a BP neural network structure based on MATLAB platform to evaluate four insulin evaluation indicators For prediction training, by adjusting the number of nodes in different hidden layers and selecting different transfer functions for hidden layers and output layers, the generalization ability of the training results is the strongest, and the prediction results are the most reliable. The verification method of the model adopts the 10-fold cross-validation method, and the root mean square error and correlation are selected as the performance indicators. The respective neural network prediction models obtained by training according to the input and output parameter settings, the correlation be...

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Abstract

The invention relates to a method for calculating insulin action factor based on non-invasive blood glucose detection model of energy metabolism conservation method. The method includes the step thatthrough oral glucose test combined with insulin release test, a BP neural network structure based on MATLAB platform is used to predict and train the four insulin evaluation indicators. By adjusting the number of nodes in different hidden layers, and selecting transfer functions with different hidden layers and output layers, the training results have the strongest generalization ability and the most reliable predicting results.

Description

technical field [0001] The invention belongs to the field of biomedical engineering, and specifically relates to a method for calculating an insulin action factor based on a non-invasive blood sugar detection model based on an energy metabolism conservation method. Background technique [0002] Sugar in the human body is an important component and main source of energy for the body, and glucose in the blood is the main source of energy for tissues and organs throughout the body. Abnormal blood sugar seriously affects the physiological function of the body, damages the body tissue, and maintains the dynamic and stable blood sugar phase has important clinical significance. Insulin is the only hypoglycemic hormone in the body, and its main function is to regulate the synthesis and metabolism of glucose, so that the glucose metabolism is in a state of balance. [0003] The main feature of type 2 diabetes is insulin resistance with relative insulin deficiency, or insufficient in...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/145
CPCA61B5/14532A61B5/72
Inventor 陈真诚钟婷婷朱健铭殷世民杜莹梁永波唐群峰
Owner GUILIN UNIV OF ELECTRONIC TECH
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