US2016320338A1PendingUtilityA1

Application of electrochemical impedance spectroscopy in sensor systems, devices, and related methods

66
Assignee: MEDTRONIC MINIMED INCPriority: Jun 8, 2012Filed: Jul 11, 2016Published: Nov 3, 2016
Est. expiryJun 8, 2032(~5.9 yrs left)· nominal 20-yr term from priority
A61B 5/6852A61B 5/0537A61M 5/14244A61M 5/14276G01N 33/49G01N 27/028A61B 5/14532G01N 27/416G01N 33/96G01R 35/005A61B 5/746A61B 5/7221A61B 5/1495A61B 5/1473G01N 27/026A61M 2005/1726A61M 5/1723A61B 5/14865G01N 27/4163A61B 5/4839A61B 5/6849G01R 35/00A61B 5/6846A61B 5/1459A61B 5/7203A61B 5/7225A61B 5/14503A61M 5/1582A61B 2562/04G01N 33/66A61B 2562/0214A61B 5/7242A61B 5/0538G08B 21/182A61B 5/6886
66
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Claims

Abstract

A diagnostic Electrochemical Impedance Spectroscopy (EIS) procedure is applied to measure values of impedance-related parameters for one or more sensing electrodes. The parameters may include real impedance, imaginary impedance, impedance magnitude, and/or phase angle. The measured values of the impedance-related parameters are then used in performing sensor diagnostics, calculating a highly-reliable fused sensor glucose value based on signals from a plurality of redundant sensing electrodes, calibrating sensors, detecting interferents within close proximity of one or more sensing electrodes, and testing surface area characteristics of electroplated electrodes. Advantageously, impedance-related parameters can be defined that are substantially glucose-independent over specific ranges of frequencies. An Application Specific Integrated Circuit (ASIC) enables implementation of the EIS-based diagnostics, fusion algorithms, and other processes based on measurement of EIS-based parameters.

Claims

exact text as granted — not AI-modified
What is claimed is: 
     
         1 . A method of performing real-time sensor diagnostics on a subcutaneous or implanted sensor having at least one working electrode, comprising:
 (a) performing a first electrochemical impedance spectroscopy (EIS) procedure to generate a first set of impedance-related data for the at least one working electrode, said first set of impedance-related data including a first dataset for at least one impedance-related parameter that is substantially glucose independent;   (b) after a predetermined time interval, performing a second EIS procedure to generate a second set of impedance-related data for the at least one electrode, said second set of impedance-related data including a second dataset for said at least one impedance-related parameter that is substantially glucose-independent; and   (c) based only on said first and second datasets, determining whether the sensor is functioning normally.   
     
     
         2 . The method of  claim 1 , wherein each of the first and second EIS procedures is performed for a respective range of frequencies. 
     
     
         3 . The method of  claim 2 , wherein the range of frequencies for the first EIS procedure is different from the range of frequencies for the second EIS procedure. 
     
     
         4 . The method of  claim 1 , wherein each of the first and second sets of impedance-related data includes data for at least one of real impedance, imaginary impedance, impedance magnitude, and phase angle. 
     
     
         5 . The method of  claim 1 , wherein said at least one impedance-related parameter is real impedance. 
     
     
         6 . The method of  claim 5 , wherein the real impedance is measured at a frequency of at least about 1 kHz. 
     
     
         7 . The method of  claim 1 , wherein said at least one impedance-related parameter is imaginary impedance. 
     
     
         8 . The method of  claim 7 , wherein the imaginary impedance is measured at a frequency of at least 1 kHz. 
     
     
         9 . The method of  claim 1 , wherein, a predetermined time period after the second EIS procedure has been performed and subsequent to step (c), a third EIS procedure is performed to generate a third set of impedance-related data for the at least one electrode, said third set of impedance-related data including a third dataset for said at least one impedance-related parameter that is substantially glucose independent, and wherein a determination is made as to whether the sensor is functioning normally based on the second and third datasets. 
     
     
         10 . The method of  claim 9 , wherein the predetermined time period is different from said predetermined time interval. 
     
     
         11 . The method of  claim 9 , wherein the second and third EIS procedures are performed for the same range of frequencies. 
     
     
         12 . The method of  claim 9 , wherein the second EIS procedure is performed for a range of frequencies that is different than the range of frequencies for the third EIS procedure. 
     
     
         13 . The method of  claim 1 , wherein the sensor includes between two and five independent working electrodes. 
     
     
         14 . A method of performing real-time sensor diagnostics on a subcutaneous or implanted sensor having at least one working electrode, comprising:
 (a) performing a first electrochemical impedance spectroscopy (EIS) procedure to generate a first set of impedance-related data for the at least one working electrode;   (b) after a predetermined time interval, performing a second EIS procedure to generate a second set of impedance-related data for the at least one electrode, wherein each of the first and second sets of impedance-related data includes values for impedance-related parameters; and   (c) based on the first and second sets of impedance-related data, determining whether the sensor is functioning normally, wherein said determination comprises comparing the value of at least one impedance-related parameter from the first set of impedance-related data to the value of the same parameter from the second set of impedance-related data.   
     
     
         15 . The method of  claim 14 , wherein each of the first and second sets of impedance-related data includes a respective dataset for at least one impedance-related parameter that is substantially glucose-independent. 
     
     
         16 . The method of  claim 14 , wherein the at least one impedance-related parameter is real impedance. 
     
     
         17 . The method of  claim 14 , wherein the at least one impedance-related parameter is imaginary impedance. 
     
     
         18 . The method of  claim 14 , wherein the at least one impedance-related parameter is phase angle. 
     
     
         19 . The method of  claim 14 , wherein, a predetermined time period after the second EIS procedure has been performed and subsequent to step (c), a third EIS procedure is performed to generate a third set of impedance-related data for the at least one electrode, and wherein a determination is made as to whether the sensor is functioning normally based on the second and third sets of impedance-related data. 
     
     
         20 . The method of  claim 19 , wherein each of the second and third sets of impedance-related data includes values for impedance-related parameters, and wherein the determination as to whether the sensor is functioning normally is made by comparing the value of at least one impedance-related parameter from the second set of impedance-related data to the value of the same parameter from the third set of impedance-related data.

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