IP Library Granted Patent US 12,295,730
Granted Patent B2
US 12,295,730 · App. 17/553,382 · Granted May 13, 2025

Method of determining a concentration of an analyte in a bodily fluid and mobile device configured for determining a concentration of an analyte in a bodily fluid

Inventors: Max Berg (Mannheim, DE); Fredrik Hailer (Limburgerhof, DE); Bernd Limburg (Soergenloch, DE); Daria Skuridina (Berlin, DE); Volker Tuerck (Berlin, DE); Momme Winkelnkemper (Berlin, DE)
Assignee: Roche Diabetes Care, Inc.
A61B5/14546A61B5/150358G01N21/78G01N21/8483G06T5/92G06T7/0012G06T7/80G01N2021/8488G01N2201/0221
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,295,730
App. No.
17/553,382
Granted
May 13, 2025
Kind
B2
Abstract

A method of determining concentration of an analyte in a body fluid using a mobile device having a camera is disclosed. In the inventive method, the camera is used to take a series of calibration images of a region of interest of an object. The calibration images differ in their brightness. A key calibration figure is derived from each calibration image, the key calibration images being characteristic for a tone mapping function of the mobile device. A probable tone mapping function of the mobile device is determined by taking into account the key calibration figures. An analysis image is taken of at least part of a test field of an optical test strip, the test field having a body fluid applied thereto. Analyte concentration is determined from the analysis image of the test field by taking into account the probable tone mapping function of the mobile device.

Claims (30)

1. A method of determining concentration of an analyte in a body fluid using a mobile device having a camera, the method comprising:

a) using the camera to take a series of calibration images of a region of interest of an object, wherein the calibration images differ in their brightness, and wherein the mobile device automatically applies to the calibration images a tone mapping function that renders the images taken by the camera less suitable for analytical measurements;

b) deriving from each calibration image a key calibration figure characteristic for the tone mapping function;

c) using the key calibration figures derived in step b) to approximate the tone mapping function;

d) taking an analysis image of at least part of a test field of an optical test strip, the test field having the body fluid applied thereto; and

e) determining the concentration of the analyte in the body fluid from the analysis image of the test field while taking into account the approximated tone mapping function, whereby the accuracy of the determined analyte concentration is improved by correcting for the effect of the tone mapping function.

2. The method according to claim 1 , wherein steps d) and e) are performed repeatedly.

3. The method according to claim 2 , wherein steps a)-c) are performed only once initially for a plurality of repetitions of steps d) and e), or each time before performing steps d) and e), or at a predetermined frequency.

4. The method according to claim 1 , wherein the object comprises the optical test strip, wherein the analysis image coincides with at least one of the calibration images, whereby that the analysis image is taken as part of the series of calibration images.

5. The method according to claim 1 , wherein the region of interest is selected from the group consisting of a white field, a black field, a grey field and a grey scale step wedge.

6. The method according to claim 1 , wherein each calibration image comprises at least two regions of interest, wherein a physical brightness ratio between the two regions of interest is known.

7. The method according to claim 1 , wherein for each calibration image the key calibration figure is derived from at least one brightness value of the region of interest of the calibration image.

8. The method according to claim 1 , wherein the brightness of the calibration images is varied in step a) by varying a parameter value of at least one of the following parameters: exposure time, light sensitivity of an image sensor of the camera, and light intensity of an illuminant.

9. The method according to claim 8 , wherein step c) comprises determining at least one sampling point for each calibration image, wherein the sampling point comprises the key calibration figure and the parameter value.

10. The method according to claim 9 , wherein step c) comprises determining the approximated tone mapping function by at least one of the following: (i) determining a fit curve for the sampling points of the series of calibration images, and (ii) choosing a function from a predetermined set of functions, wherein the chosen function fits the sampling points of the series of calibration images.

11. The method according to claim 1 , wherein step e) comprises deriving a key analysis figure from a brightness value of at least one part of the analysis image showing the at least one part of the test field.

12. The method according to claim 11 , wherein from each key analysis figure at least one probable analyte measurement figure is derived by applying an inverted probable tone mapping function to the key analysis figure.

13. The method according to claim 1 , wherein in step e) the analyte concentration is determined from a brightness ratio between the test field having the body fluid applied and the region of interest of the object.

14. A non-transitory computer readable medium having stored thereon computer executable instructions for performing the method according to claim 1 .

15. The method according to claim 1 , wherein the series of calibration images are taken with the built-in camera of the mobile device and are unaugmented by external devices.

16. A mobile device having a camera and a processor, the processor configured to:

prompt a user to take a series of calibration images of a region of interest of an object by using the camera, wherein the calibration images differ in their brightness, and wherein the mobile device automatically applies to the calibration images a tone mapping function that renders the images taken by the camera less suitable for analytical measurements;

derive from each calibration image a key calibration figure characteristic for the tone mapping function of the mobile device;

use the derived key calibration figures to approximate the tone mapping function;

prompt the user to take an analysis image of at least part of a test field of an optical test strip, the test field having a body fluid applied thereto; and

determining the concentration of the analyte in the body fluid from the analysis image of the test field by while taking into account the approximated tone mapping function, whereby the accuracy of the determined analyte concentration is improved by correcting for the effect of the tone mapping function.

17. A kit for determining concentration of an analyte in a body fluid, the kit comprising:

a mobile device according to claim 16 ; and

an optical test strip having at least one test field.

18. The method according to claim 16 , wherein the series of calibration images are taken with the built-in camera of the mobile device and are unaugmented by external devices.

Assignments (4)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 8, 2022
From: BERG, MAX; HAILER, FREDRIK; LIMBURG, BERND
To: ROCHE DIABETES CARE GMBH
Reel/Frame 058928/0415 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 8, 2022
From: SKURIDINA, DARIA; TUERCK, VOLKER; WINKELNKEMPER, MOMME
To: DR. TUERCK INGENIEURBUERO GMBH
Reel/Frame 058928/0629 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 8, 2022
From: DR. TUERCK INGENIEURBUERO GMBH
To: ROCHE DIABETES CARE GMBH
Reel/Frame 058928/0759 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 8, 2022
From: ROCHE DIABETES CARE GMBH
To: ROCHE DIABETES CARE, INC.
Reel/Frame 059012/0769 →
Priority Claims (1)
EP 19 182 555 · Jun 26, 2019 · regional
Continuity (2)
Continuation PCTEP2020067444 · Jun 23, 2020
Related Publication 20220104736A1 · Apr 7, 2022
References Cited (31)
US 9230509B2 · Van Der Vleuten · 2016 [cited by applicant]
US 9842381B2 · Douady-Pleven et al. · 2017 [cited by applicant]
US 20090231469A1 · Kato · 2009 [cited by applicant]
US 20110298819A1 · Evans et al. · 2011 [cited by applicant]
US 20130126712A1 · Petrich et al. · 2013 [cited by applicant]
US 20140072189A1 · Jena et al. · 2014 [cited by applicant]
US 20140078193A1 · Barnhoefer · 2014 [cited by examiner]
US 20150233898A1 · Chen · 2015 [cited by examiner]
US 20150359458A1 · Erickson · 2015 [cited by examiner]
US 20170139572A1 · Sunkavalli · 2017 [cited by examiner]
US 20170161881A1 · Najaf-Zadeh · 2017 [cited by examiner]
US 20170330529A1 · Van Mourik et al. · 2017 [cited by applicant]
US 20180024049A1 · Shyam et al. · 2018 [cited by applicant]
US 20190226985A1 · Roberts · 2019 [cited by examiner]
US 20190279549A1 · Shin · 2019 [cited by examiner]
US 20200078781A1 · Beckley · 2020 [cited by examiner]
US 20200316720A1 · Liu · 2020 [cited by examiner]
JP 2005202749A · 2005 [cited by applicant]
JP 2007188465A · 2007 [cited by applicant]
JP 2009245429A · 2009 [cited by applicant]
JP 2015533211A · 2015 [cited by applicant]
JP 2016163722A · 2016 [cited by applicant]
WO WO2007079843A2 · 2007 [cited by applicant]
WO WO2016132243A1 · 2016 [cited by applicant]
WO WO2019023376A1 · 2019 [cited by applicant]
WO WO2019081460A1 · 2019 [cited by applicant]
WO WO2019081541A1 · 2019 [cited by applicant]
International Search Report and Written Opinion of the International Searching Authority, PCT/EP2020/067444, Sep. 18, 2020, 10 pages. [cited by applicant]
Hönes et al., Diabetes Technology and Therapeutics, vol. 10, Supplement 1, 2008, pp. 10-26. [cited by applicant]
Burggraaff et al., Standardized Spectral and Radiometric Calibration of Consumer Cameras, arxiv.org, Cornell University Library, 201, Olin Library Cornell University, Ithaca, NY 14853, Jun. 7, 2019, 27 pages. [cited by applicant]
Budianto et al., Strip Test Analysis Using Image Processing for Diagnosing Diabetes and Kidney Stone Based on Smartphone, 2018 International Electronics Symposium on Knowledge Creation and Intelligent Computing (IES-KCI… [cited by applicant]