Blood glucose prediction method and system and application thereof

Abstract

The invention belongs to the technical field of medical health, and particularly relates to a blood glucose prediction method and system and application thereof. An existing blood glucose prediction algorithm has high accuracy in the stable blood glucose change stage, but the blood glucose prediction accuracy is obviously reduced in the large blood glucose fluctuation stage (such as postprandial). The invention provides a blood glucose prediction method. The method comprises the following steps: acquiring blood glucose data, carrying out preliminary prediction on a blood glucose value, fusing preliminary prediction results, and displaying a prediction result. The method can be better suitable for blood glucose prediction of different people, and the accuracy is higher.

Description

technical field [0001] The present application belongs to the field of medical and health technologies, and in particular relates to a blood sugar prediction method, system and application thereof. Background technique [0002] Diabetes is a metabolic disease that seriously endangers human health. Blood glucose prediction refers to estimating changes in blood glucose in the future based on current and historical blood glucose values, and is an integral part of diabetes management. By predicting blood sugar and taking certain measures according to the prediction results, diabetic patients can prevent the occurrence of adverse blood sugar events such as hypoglycemia and hyperglycemia in daily life, and improve the quality of life. [0003] Blood sugar prediction refers to estimating changes in blood sugar in the future based on current and historical blood sugar values, and is an important part of the diabetes management system. Accurate blood sugar prediction helps diabetic...

AI Technical Summary

Problems solved by technology

However, since changes in human blood sugar are affected by multiple factors such as diet, emotion, and exercise, blood sugar changes are time-varying, non-linear, and individualized, resulting in the current blood sugar prediction algorithm having high accuracy in some groups of people, but not in others. Accuracy is lower in crowd

In addition, for the same person, the current blood sugar prediction algorithm has high accuracy in the stage of relatively stable blood sugar changes, but its blood sugar prediction accuracy is significantly reduced in the stage of large blood sugar fluctuations (such as after meals)

Images