Noninvasive Method to Estimate Variation of Blood Glucose Levels Using Metabolic Measurements

• US 20100036221A1
• Filed: 01/10/2008
• Published: 02/11/2010
• Est. Priority Date: 01/19/2007
• Status: Abandoned Application

• Current Assignee: University of Hong Kong (Government of Hong Kong Special Administrative Region)
• Original Assignee: University of Hong Kong (Government of Hong Kong Special Administrative Region)
• Inventors: Li, Victor Onkwok, Lam, Karen Siuling, Lee, Chiyeung, Cheung, Yingsheung
• Application Number:
  US12/519,322
• Publication Number:
  US 20100036221A1
• Time in Patent Office: Days
• US Class Current: 600/365
• CPC Class Codes: A61B 5/0833 Measuring rate of oxygen consumption
• CPC Class Codes: A61B 5/091 Measuring volume of inspired or expired gases, e.g. to determine lung capacity
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/4866 Evaluating metabolism A61B5/083 takes precedence
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00

Abstract

A method to estimate the variation of blood glucose concentration in a patient without blood sampling. The method can be implemented by measuring metabolic parameters including heat dissipation by conduction, percentage oxygen content of expired air and volume per minute of expired air. These parameters are used to calculate estimated blood glucose variation.

Claims

1-8. -8. (canceled)

9. A method for estimating blood glucose variation in a patient based on metabolic parameters, comprising:

measuring raw metabolic parameters of the patient, wherein the raw metabolic parameters comprise conduction heat loss of an extremity of the patient, oxygen content of air expired by the patient, and a rate of expiration of air expired by the patient;

converting the raw metabolic parameters into metabolic features of the patient; and

calculating an estimated blood glucose variation for the patient based on the metabolic features.

10. The method of claim 9, wherein conduction heat loss is measured via a heat flow sensor.

11. The method of claim 10, wherein the heat flow sensor comprises a Data Harvest EasySense Advanced Datalogger™

.

12. The method of claim 9, wherein oxygen content is measured via an oxygen analyzer.

13. The method of claim 12, wherein the oxygen analyzer comprises a Teledyne AX300 Oxygen Analyzer with R-17 MED Oxygen Sensor™

.

14. The method of claim 9, wherein the rate of expiration of air is measured via a gas speed-measuring device.

15. The method of claim 14, wherein the gas speed-measuring device comprises a Vitalograph Micro Spirometer™

.

16. The method of claim 9, wherein the calculating step comprises use of a classification model, wherein the classification model takes the metabolic features as inputs and provides the estimated blood glucose variation as an output.

17. The method of claim 16, wherein the classification model classifies the estimated blood glucose variation into one of up to five classes.

18. The method of claim 9, wherein the calculating step comprises use of a multiple regression analysis, wherein the multiple regression analysis is used to calculate the estimated blood glucose variation from the metabolic features.

19. An apparatus comprising one or more memory units having computer-useable instructions encoded thereon for performing a method of classifying blood glucose variation of a patient based on metabolic parameters, the method comprising:

receiving raw metabolic parameters of the patient;

converting, in a first computer process, the raw metabolic parameters into metabolic features of the patient;

computing, in a second computer process, variations between the metabolic features of the patient and stored metabolic features of the patient; and

classifying, via a third computer process, the blood glucose variation of the patient based on the computed variations.

20. The apparatus of claim 19, wherein the raw metabolic parameters comprise conduction heat loss of an extremity of the patient, oxygen content of air expired by the patient, and a rate of expiration of air expired by the patient.

21. The apparatus of claim 20, wherein the metabolic features comprise heat dissipation and a resting metabolic rate.

22. The apparatus of claim 19, wherein the third computer process comprises a regression analysis.

23. The apparatus of claim 22, wherein the third computer process comprises a multiple linear regression analysis.

24. The apparatus of claim 23, wherein the multiple linear regression analysis is performed using a least-squares method.

25. The apparatus of claim 19, wherein the third computer process comprises a linear discriminant analysis.

26. An apparatus comprising a heat flow sensor and a heat flow analyzer, which respectively are capable of measuring and computing the conduction heat loss at an extremity'"'"'s tip.

27. The apparatus of claim 26, further comprising an oxygen analyzer, which is capable of measuring the percentage oxygen content of expired air from the mouth.

28. The apparatus of claim 26, further comprising a gas speed-measuring device, which is capable of measuring the expiratory flow rate at the mouth cavity.