Online fault detection method of continuous blood sugar monitoring sensor based on multi-model fusion

A blood sugar monitoring and detection method technology, applied in the direction of biological testing, material inspection products, etc., can solve the problem of low accuracy of detection results and achieve the effect of reducing the impact

Active Publication Date: 2019-04-26
NORTHEASTERN UNIV
View PDF5 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In view of the existing technical problems, the present invention provides an online fault detection method for continuous blood glucose monitoring sensors based on multi-model fusion, which solves the problems of low accuracy of detection results in the prior art

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Online fault detection method of continuous blood sugar monitoring sensor based on multi-model fusion
  • Online fault detection method of continuous blood sugar monitoring sensor based on multi-model fusion
  • Online fault detection method of continuous blood sugar monitoring sensor based on multi-model fusion

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0074] In order to better explain the present invention and facilitate understanding, the present invention will be described in detail below through specific embodiments in conjunction with the accompanying drawings.

[0075] Such as figure 1 and Figure 4 As shown: this embodiment discloses a continuous blood glucose monitoring sensor online fault detection method based on multi-model fusion, including the following steps:

[0076] S1. Obtain online CGM monitoring signal data;

[0077] S2. Input the obtained online CGM monitoring signal data into the multi-model fusion algorithm model to obtain the online prediction error;

[0078] S3. Combining the obtained online prediction error and historical prediction error to calculate the entropy value at the online moment;

[0079] S4, the entropy value J obtained by calculating the online moment i1 、J i2 Respectively with the threshold T of the current moment kl1 , T kl2 Compare;

[0080] If the current entropy value J i1 ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to an online fault detection method of a continuous blood sugar monitoring sensor based on multi-model fusion, which comprises the following steps of: S1, acquiring online CGM monitoring signal data; S2, inputting the acquired on-line CGM monitoring signal data into a multi-model fusion algorithm model to acquire an on-line prediction error; S3, calculating the obtained on-line prediction error and the historical prediction error in combination to obtain the entropy value of the on-line time; S4, comparing the entropy values Ji1 and Ji2 of the online time obtained by calculation with the threshold values Tkl1 and Tkl2 of the current time respectively; if the entropy values Ji1 and Ji2 at the current moment are not all larger than the threshold values Tkl1 and Tkl2 atthe current moment, judging that the current blood sugar monitoring sensor works normally; if the entropy values Ji1 and Ji2 at the current moment are both larger than the threshold values Tkl1 and Tkl2 at the current moment, judging that the current blood sugar monitoring sensor works abnormally. The detection method has the advantage of high detection precision.

Description

technical field [0001] The invention belongs to the technical field of blood sugar monitoring, in particular to an online fault detection method for continuous blood sugar monitoring sensors based on multi-model fusion. Background technique [0002] The artificial pancreas (AP) system provides automatic regulation of blood glucose concentration (BGC) for type 1 diabetes (T1D) patients, and it mainly consists of three parts: continuous glucose monitoring (CGM) sensor, control of insulin infusion rate calculated based on CGM signal controller, and an insulin pump that delivers the amount of insulin calculated by the controller to the patient. Patients with T1D can have a more comprehensive understanding of blood sugar fluctuations through continuous monitoring of blood sugar, so as to better control blood sugar. However, in real life, the measurement results of the continuous blood glucose monitoring sensor are affected by many factors, resulting in inaccurate measurement res...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G01N33/66
CPCG01N33/66
Inventor 于霞崔悦刘建昌
Owner NORTHEASTERN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap