Use of Electrochemical Impedance Spectroscopy (EIS) in gross failure analysis
Electrochemical Impedance Spectroscopy (EIS) is used in conjunction with continuous glucose monitors and continuous glucose monitoring (CGM) to enable in-vivo sensor calibration, gross (sensor) failure analysis, and intelligent sensor diagnostics and fault detection. An equivalent circuit model is defined, and circuit elements are used to characterize sensor behavior.
1. A method of performing diagnostics on a subcutaneous or implanted glucose sensor having at least one working electrode, comprising:
defining a vector containing values associated with one or more electrochemical impedance spectroscopy (EIS)-based parameters and values associated with one or more non-EIS-based parameters;
defining a combined threshold value for a combination of said EIS-based parameters and said non-EIS-based parameters;
performing, by a microprocessor, a first EIS procedure to generate a first set of data for said values associated with the one or more EIS-based parameters;
after a calculated time interval, performing, by said microprocessor, a second EIS procedure to generate a second set of data for said values associated with the one or more EIS-based parameters;
updating, by said microprocessor, the vector with said first and second sets of data; and
monitoring, by said microprocessor, vector values to determine whether the sensor has lost sensitivity based on a combined vector value of said combination of EIS-based and non-EIS-based parameters crossing said combined threshold value,
wherein sensor glucose values are blinded to a user of the sensor by the microprocessor based on the determination that the sensor has lost sensitivity.
2. The method of claim 1 , wherein said one or more EIS-based parameters include double layer capacitance (Cdl).
3. The method of claim 1 , wherein said one or more non-EIS-based parameters include a period of time during which Isig is low.
4. The method of claim 1 , further including periodically updating the vector values for each of said non-EIS-based parameters.
5. The method of claim 4 , wherein said determination of sensitivity loss is made based on comparison of one of the vector values to a corresponding threshold value.
6. The method of claim 4 , wherein the sensor is determined to have lost sensitivity when a plurality of the vector values have crossed their corresponding threshold values.
7. The method of claim 6 , wherein said plurality of vector values include values for at least one EIS-based parameter and at least one non-EIS-based parameter.
8. The method of claim 1 , wherein each of said threshold values is an absolute threshold value.
9. The method of claim 1 , wherein each of said threshold values is a relative threshold value.
10. The method of claim 1 , further including applying a weighting factor to each of the vector values to generate weighted vector values, and determining sensitivity loss based on said weighted vector values.
11. The method of claim 10 , wherein said weighting factor is different for each of the EIS-based parameters and for each of the non-EIS-based parameters.
12. The method of claim 11 , wherein, for each said EIS-based parameter and each said non-EIS-based parameter, a respective weighting factor is calculated based on each parameter's said respective threshold value.
13. The method of claim 1 , wherein said combined threshold value is an absolute threshold value.
14. The method of claim 1 , wherein said combined threshold value is a relative threshold value.
15. The method of claim 1 , wherein said one or more EIS-based parameters include membrane resistance (Rmem).
16. The method of claim 1 , wherein said one or more EIS-based parameters include membrane capacitance (Cmem).
17. The method of claim 1 , wherein said one or more non-EIS-based parameters include variability in sensor current (Isig).
18. The method of claim 1 , wherein said one or more non-EIS-based parameters include rate of change of Isig.
19. A method of performing diagnostics on a subcutaneous or implanted glucose sensor having at least one working electrode, comprising:
defining a vector containing values associated with one or more electrochemical impedance spectroscopy (EIS)-based parameters and values associated with one or more non-EIS-based parameters;
defining a combined threshold value for a combination of said EIS-based parameters and said non-EIS-based parameters;
performing, by a microprocessor, a first EIS procedure to generate a first set of data for said values associated with the one or more EIS-based parameters;
after a calculated time interval, performing, by said microprocessor, a second EIS procedure to generate a second set of data for said values associated with the one or more EIS-based parameters;
updating, by said microprocessor, the vector with said first and second sets of data;
monitoring, by said microprocessor, vector values to determine whether the sensor has lost sensitivity based on a combined vector value of said combination of EIS-based and non-EIS-based parameters crossing said combined threshold value; and
terminating said glucose sensor by the microprocessor based on the determination that the sensor has lost sensitivity.