KETONE MEASUREMENT SYSTEM FOR MONITORING MEDICAL CONDITIONS

• US 20170332951A1
• Filed: 05/18/2017
• Published: 11/23/2017
• Est. Priority Date: 05/18/2016
• Status: Active Grant

• Current Assignee: Invoy Holdings, Inc.
• Original Assignee: Invoy Technologies, LLC
• Inventors: Ahmad, Lubna, Ahmad, Salman
• Granted Patent: US 10,736,548 B2
• Time in Patent Office: Days
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/082 Evaluation by breath analysis, e.g. determination of the chemical composition of exhaled breath A61B5/083, A61B5/091 take precedence
• CPC Class Codes: A61B 5/093 the gases being exhaled into, or inhaled from, an expansible chamber, e.g. bellows or expansible bag
• CPC Class Codes: A61B 5/0935 Recording apparatus specially adapted therefor
• CPC Class Codes: A61B 5/145 Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissuemeasuring of blood pressure or blood flow A61B5/02; non-radiation detecting or locating of foreign bodies in blood A61B5/06
• CPC Class Codes: A61B 5/14507 specially adapted for measuring characteristics of body fluids other than blood devices for taking samples of body liquids A61B10/0045
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/14539 for measuring pH
• CPC Class Codes: A61B 5/14551 for measuring blood gases
• CPC Class Codes: A61B 5/4836 Diagnosis combined with treatment in closed-loop systems or methods A61B5/0036 takes precedence
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: G01N 33/497 of gaseous biological material, e.g. breath
• CPC Class Codes: G16H 20/60 relating to nutrition control, e.g. diets
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

A portable system is provided for measuring a ketone, such as an acetone, in the breath or other bodily fluid of a user. The system includes a portable measurement device that analyzes fluid samples and generates corresponding ketone measurements. The portable measurement device communicates with an application which runs on a smartphone or other mobile device of the user. The application tracks, and generates graphs of, the ketone measurements, and may include various features for facilitating the analysis of the measurements.

Claims

1. A device-implemented process, comprising:

generating, by a portable ketone measurement device, a sequence of ketone measurements representing ketone levels of a human subject; and

by execution of program instructions by one or more processors;

detecting an abnormal pattern in the sequence of ketone measurements;

in response detecting the abnormal pattern, acquiring physiologic parameter data representing a non-ketone physiologic parameter of the human subject; and

determining, based at least partly on the acquired physiologic parameter data, whether a corrective action should be taken to address a condition of the human subject.

2. The device-implemented process of claim 1, wherein the physiologic parameter data is a measurement of at least one of glucose, hemoglobin A1c, and insulin.

3. The device-implemented process of claim 1, wherein acquiring the physiologic parameter data comprises activating a measurement device that measures the physiologic parameter.

4. The device-implemented process of claim 1, further comprising, in response to determining that a corrective action should be taken, automatically activating an insulin pump.

5. The device-implemented process of claim 1, further comprising, in response to determining that a corrective action should be taken, transmitting a notification to a user.

6. The device-implemented process of claim 1, wherein the abnormal pattern is detected based on results of a device-implemented learning process in which historical ketone measurements of the human subject are correlated with historical glucose measurements of the human subject t at least one ketone measurement pattern associated with a glucose level abnormality.

7. The device-implemented process of claim 1, wherein the one or more processors include a processor of a mobile phone that wirelessly communicates with the portable ketone measurement device.

8. The device-implemented process of claim 1, wherein the one or more processors include a processor of a remote server.

9. The device-implemented process of claim 1, wherein the one or more processors include a processor of the portable ketone measurement device.

10. The device-implemented process of claim 1, wherein the one or more processors include a processor of a measurement device that measures the physiologic parameter, the measurement device being separate from the portable ketone measurement device.

11. The device-implemented process of claim 1, wherein the portable ketone measurement device is a breath analysis device that measures ketone levels in breath samples.

12. The device-implemented process of claim 1, wherein generating the sequence of ketone measurements comprises detecting color changes occurring in cartridges through which breath samples are passed.

13. A system, comprising:

a portable ketone measurement device configured to analyze bodily fluid samples of a human subject, and to generate ketone measurements representing ketone levels in the bodily fluid samples; and

executable program code, stored in non-volatile memory, that directs one or more processors to perform a process that comprises (1) determining that a sequence of the ketone measurements generated by the portable ketone measurement device follows an abnormal pattern, (2) acquiring physiologic parameter data representing a non-ketone physiologic parameter of the human subject, and (3) determining whether the physiologic parameter data is consistent with the abnormal pattern in the sequence of ketone measurements, said computing system comprising one or more processing devices.

14. The system of claim 13, wherein determining whether the physiologic parameter data is consistent with the abnormal pattern comprises determining whether the physiologic parameter data follows an abnormal pattern corresponding to the abnormal pattern in the sequence of ketone measurements.

15. The system of claim 14, wherein the physiologic parameter data comprises glucose measurements.

16. The system of claim 14, wherein the process further comprises, in response to determining that the physiologic parameter data follows an abnormal pattern corresponding to the abnormal pattern in the sequence of ketone measurements, selecting a corrective action to perform.

17. The system of claim 16, wherein the corrective action comprises activation of an insulin pump.

18. The system of claim 16, wherein the corrective action comprises output of a notification.

19. The system of claim 13, wherein the acquiring of the physiologic parameter data is performed in response to determining that the sequence of ketone measurements follows the abnormal pattern.

20. The system of claim 13, wherein the portable ketone measurement device comprises a wireless transceiver and a processor, and is programmed to use the wireless transceiver to wirelessly transmit the ketone measurements to a mobile device, and the executable program code comprises code of an application that runs on the mobile device.

21. The system of claim 13, wherein at least a portion of the executable program code runs on the portable ketone measurement device.

22. The system of claim 13, wherein the physiologic parameter data comprises a measurement of at least one of the following:

glucose, hemoglobin A1c, and insulin.