Method and device for analyzing continuously monitored physiological measurement values of a user

• US 10,791,993 B2
• Filed: 05/27/2016
• Issued: 10/06/2020
• Est. Priority Date: 11/28/2013
• Status: Active Grant

• Current Assignee: Roche Diabetes Care Inc. (Roche Holding AG)
• Original Assignee: Roche Diabetes Care Inc. (Roche Holding AG)
• Inventors: Steiger, Bernd, Rasch-Menges, Jurgen
• Primary Examiner(s): Jang, Christian
• Assistant Examiner(s): Toth, Karen E
• Application Number:
  US15/166,413
• Publication Number:
  US 20160270737A1
• Time in Patent Office: 1,593 Days
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/4842 Monitoring progression or stage of a disease
• CPC Class Codes: A61B 5/6898 Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• CPC Class Codes: A61B 5/7246 using correlation, e.g. template matching or determination of similarity
• 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: A61B 5/743 Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
• CPC Class Codes: A61B 5/7475 User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

The application relates to a method for analyzing continuously monitored physiological measurement values of a user, the method being performed in a data processing system and comprising: providing, by a data interface, a set of present physiological measurement values, determining whether a common pattern of values is contained in both the set of present physiological measurement values and a set of historical physiological measurement values, if the common pattern of values is found, requesting the user to provide contextualization for at least the present physiological measurement values of the common pattern of values, receiving contextualization and storing contextualized data. Furthermore, the application relates to a device for analyzing continuously monitored physiological measurement values of a user.

Claims

1. A method for analyzing continuously monitored glucose measurement values of a user, the method being performed in a data processing system and comprising:

providing, by a data interface, a set of present glucose measurement values collected in a continuously performed present measurement;

determining whether a common pattern is contained in both the set of present glucose measurement values and a set of historical glucose measurement values collected in a continuously performed historical measurement; and

when the common pattern is found to be contained in both the set of present glucose measurement values and the set of historical glucose measurement values;

a) requesting the user to provide context data for at least the present glucose measurement values of the common pattern via a user input/output device (“

TO-device”

) of the data processing system;

b) receiving the context data for at least the present glucose measurement values of the common pattern via the IO-device;

c) storing the context data for at least the present glucose measurement values of the common pattern in a storing device of the data processing system;

d) comparing the context data for the present glucose measurement values to context data of the historical glucose measurement values;

e) when it is determined in step d) that the present context data resembles the historical context data, predicting a future glucose measurement value based on the historical glucose measurement values that follow the common patter;

f) using the comparison between the context data for the present glucose measurement values and the context data of the historical glucose measurement values to determine a confidence level for the predicted future glucose measurement value; and

g) administering insulin when the predicted future glucose measurement value exceeds a recommended level.

2. The method according to claim 1, wherein the determining of whether a common pattern is contained in both the set of present glucose measurement values and the set of historical glucose measurement values further comprises:

determining a present pattern of values in the set of present glucose measurement values;

providing electronic pattern information about a historical pattern of values determined from the set of historical glucose measurement values; and

determining the presence of the common pattern if the present pattern resembles the historical pattern.

3. The method according to claim 1, wherein the requesting in step a) further comprises outputting a pre-selection of proposed context data.

4. The method according to claim 3, wherein the outputting comprises outputting a pre-selection of proposed context data determined from context data of the historical glucose measurement values from the common pattern.

5. The method according to claim 3, wherein the outputting further comprises outputting the pre-selection of proposed context data with a data format determined from the context data of the historical glucose measurement values from the common pattern.

6. The method according to claim 3, wherein the outputting further comprises:

determining a type of pattern for the common pattern contained in both the set of present glucose measurement values and the set of historical glucose measurement values; and

outputting the pre-selection of proposed context data assigned to the type of pattern determined.

7. The method according to claim 1, wherein the context data comprises information selected from the following group:

time of measurement, intake of carbohydrates, type of exercise, type of event, illness, medication, stress, menstruation, and insulin bolus.

8. The method according to claim 1, wherein the confidence level for the predicted future glucose measurement value is displayed.

9. The method according to claim 1, wherein the data processing system is provided in a blood glucose control device configured to continuously monitor the blood glucose level of a user.

10. A non-transitory computer-readable medium having embodied thereon computer-executable instructions, which when executed by a data processing system, cause the system to perform the method according to claim 1.

11. The method according to claim 1, further comprising using a glucose sensor to continuously monitor blood glucose values of the user and to collect the set of present glucose measurement values.

12. The method according to claim 11, further comprising using the glucose sensor to continuously monitor blood glucose values of the user and to collect the set of historical glucose measurement values.

13. The method according to claim 1, wherein the requesting of the user to provide context data comprises displaying a request on a screen.

14. The method according to claim 1, wherein the receiving context data step comprises the user inputting into a keyboard.

15. The method of claim 1, wherein the confidence level for the predicted future glucose measurement value is a function of the degree of matching of the present context data and the historical context data.