SYSTEM AND METHOD FOR MODE SWITCHING

• US 20160198988A1
• Filed: 03/03/2016
• Published: 07/14/2016
• Est. Priority Date: 09/22/2014
• Status: Active Application

• Current Assignee: DexCom Incorporated
• Original Assignee: DexCom Incorporated
• Inventors: Hughes, Jonathan, Kamath, Apurv Ulas, Bhavaraju, Naresh C., Bloom, Michael A., Bowman, Leif N., Carlton, Alexandra Lynn, Koehler, Katherine Yerre, Hampapuram, Hari, Jepson, Lauren Hruby, Rack-Gomer, Anna Leigh, Simpson, Peter C., Vanslyke, Stephen J.
• Application Number:
  US15/060,401
• Publication Number:
  US 20160198988A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: A61B 2560/0223 of calibration, e.g. protocols for calibrating sensors
• CPC Class Codes: A61B 2560/0487 Special user inputs or interfaces
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/0004 characterised by the type of physiological signal transmitted
• CPC Class Codes: A61B 5/14503 invasive, e.g. introduced into the body by a catheter or needle or using implanted sensors A61B5/1459, A61B5/1464, A61B5/1473, A61B5/1482, A61B5/14865 take precedence
• CPC Class Codes: A61B 5/14532 for measuring glucose, e.g. by tissue impedance measurement
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/1455 using optical sensors, e.g. spectral photometrical oximeters
• CPC Class Codes: A61B 5/1486 using enzyme electrodes, e.g. with immobilised oxidase
• CPC Class Codes: A61B 5/1495 Calibrating or testing of in-vivo probes
• CPC Class Codes: A61B 5/6898 Portable consumer electronic devices, e.g. music players, telephones, tablet computers
• CPC Class Codes: A61B 5/72 Signal processing specially adapted for physiological signals or for diagnostic purposes character recognition, recognising digital ink, document-oriented image-based pattern recognition G06V30/00; recognition or understanding of postal images G06V30/424
• CPC Class Codes: A61B 5/7221 Determining signal validity, reliability or quality A61B5/7207 and A61B5/7217 take 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: A61B 5/7282 Event detection, e.g. detecting unique waveforms indicative of a medical condition A61B5/4094, A61B5/4818, A61B5/349, A61B5/0823 take precedence
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/7435 Displaying user selection data, e.g. icons in a graphical user interface
• CPC Class Codes: A61B 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B
• CPC Class Codes: A61B 5/7475 User input or interface means, e.g. keyboard, pointing device, joystick
• CPC Class Codes: A61M 2230/005 Parameter used as control input for the apparatus
• CPC Class Codes: A61M 2230/201 : Glucose concentration
• CPC Class Codes: A61M 5/1723 : using feedback of body parameters, e.g. blood-sugar, pressure measurement of body parameters A61B5/00
• CPC Class Codes: G16H 40/40 : for the management of medical equipment or devices, e.g. scheduling maintenance or upgrades
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: Y02A 90/10 : Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

Systems and methods described provide dynamic and intelligent ways to change the required level of user interaction during use of a monitoring device. The systems and methods generally relate to real time switching between a first or initial mode of user interaction and a second or new mode of user interaction. In some cases, the switching will be automatic and transparent to the user, and in other cases user notification may occur. The mode switching generally affects the user'"'"'s interaction with the device, and not just internal processing. The mode switching may relate to calibration modes, data transmission modes, control modes, or the like.

Claims

1. A method of operating a continuous glucose monitoring device, the continuous glucose monitoring device coupled to a glucose sensor and operating in an initial mode of operation, comprising:

a. measuring a signal indicative of glucose concentration data;

b. displaying the glucose concentration data on a user interface of the continuous glucose monitoring device, the user interface in the initial mode of operation having an initial mode of user interaction;

c. determining data indicative of a usability of the continuous glucose monitoring device;

d. comparing the determined data to one or more transition criteria;

e. if the comparing indicates the determined data has met or will meet the transition criteria, causing the continuous glucose monitoring device to transition to a new mode of operation; and

f. displaying the glucose concentration data on the user interface of the continuous glucose monitoring device, the user interface in the new mode of operation having a different mode of user interaction than the initial mode,

g. such that the continuous glucose monitoring device operates in a mode of user interaction according to the device usability.

2. The method of claim 1, wherein the displaying is based at least in part on the mode of operation.

3. The method of claim 1, wherein the determining data includes receiving data from the sensor.

4. The method of claim 1, wherein the sensor is configured for in vivo insertion into the patient.

5. The method of claim 1, wherein a first output of the monitoring device in the initial mode of operation represents the initial mode of user interaction and a second output of the monitoring device in the new mode of operation represents the new mode of user interaction, and wherein the first and second outputs are different.

6. The method of claim 5, wherein the initial and new modes of user interaction are configured such that the new mode of user interaction requires less user interaction than the initial mode of user interaction.

7. The method of claim 5, wherein the initial and new modes of user interaction are selected from the group consisting of:

user-dependent calibration and device self-calibration.

8. The method of claim 7, wherein the analyte is glucose and wherein the user-dependent calibration corresponds to entry of a calibration value from an external blood glucose meter.

9. The method of claim 5, wherein the analyte is glucose and wherein the initial and new modes of user interaction include different levels of control in an artificial pancreas system.

10. The method of claim 5, wherein the analyte is glucose and wherein the initial and new modes of user interaction are data transmission modes selected from the group consisting of:

scheduled data transmissions and unscheduled data transmissions.

11. The method of claim 1, wherein the determined data includes an analyte concentration value and/or a time rate of change thereof.

12. The method of claim 1, wherein the determined data indicative of the usability of the device and the transition criteria include one or more parameters indicative of the usability of a signal from the sensor.

13. The method of claim 12, wherein the one or more parameters related to the usability of the signal corresponds to one or more parameters selected from the group consisting of accuracy, reliability, stability, confidence, and/or glycemic urgency index.

14. The method of claim 12, wherein the one or more parameters related to the usability of the signal correspond to a level of noise or to one or more faults detected in the signal, and wherein the transition criteria is a threshold level of noise or a predetermined type or level of fault.

15. The method of claim 12, wherein the one or more parameters related to the usability of the signal correspond to one or more of the group consisting of:

a. signal value, a range of signal values, or a time rate of change thereof;

b. analyte concentration value or range of values;

c. calibration data;

d. a measured error at calibration;

e. data from self diagnostics or calibration diagnostics;

f. metadata about sensor identity;

g. environmental data corresponding to a sensor;

h. historical pattern data;

i. external data;

j. data about frequency of calibration;

k. biological data about sensor placement;

l. a time duration since sensor implantation;

m. an impedance associated with the signal;

n. a received user response to a prompt displayed on a user interface;

o. a decision support mode;

P. a data transmission mode;

q. data about a selected use of the monitoring device;

r. data about clinical or user goals;

or

s. combinations of the above.

16. The method of claim 15, wherein the calibration data is selected from the group consisting of:

calibration values, confidence in calibration values, uncertainty in calibration values, range of calibration values, rate of change of calibration values, current calibration values compared to historical calibration values, stability in calibration values, whether calibration values match expected or predicted values, confidence in a user'"'"'s ability to accurately enter calibration values from a meter, whether entered calibration data corresponds to a default or pre-entered value, or combinations of the above.

17. The method of claim 15, wherein the external data is from an activity monitor, a sleep monitor, a medicament pump, GPS device, a redundant analyte sensor, or a smart pen, or combinations of the above.

18. The method of claim 15, wherein the biological data about sensor placement corresponds to data about:

tissue type, wound response, diffusion distance, or combinations of the above.

19. The method of claim 18, wherein the diffusion distance is proportional to one or more selected from the group consisting of:

impedance, thickness of membrane over electrode array, oxygen depletion rate, or diffusion of specific species between electrodes, or combinations of the above.

20. The method of claim 15, wherein the decision support mode is selected from different levels of control of an artificial pancreas system.