Methods and apparatus for information gathering, error detection and analyte concentration determination during continuous analyte sensing
A continuous glucose monitoring (CGM) device may include a wearable portion having a sensor configured to produce glucose signals from interstitial fluid, a processor, a memory and transmitter circuitry. The memory may include a pre-determined gain function based on a point-of-interest glucose signal and glucose signals measured prior to the point-of-interest glucose signal. The memory may also include computer program code stored therein that, when executed by the processor, causes the CGM device to (a) measure and store a plurality of glucose signals using the sensor and memory; (b) for a presently-measured glucose signal, employ the plurality of previously-measured glucose signals stored in the memory and the pre-determined gain function to compute a compensated glucose value; and (c) communicate the compensated glucose value to a user of the CGM device. Numerous other embodiments are provided.
1 . A method of determining concentrations of an analyte during continuous monitoring measurements comprising:
inserting a biosensor subcutaneously into a subject, the biosensor including a counter electrode, a reference electrode, a background electrode, and a working electrode having a catalyst configured to oxidize the analyte;
applying a constant voltage to the working electrode and to the background electrode;
sensing a working electrode current signal (Iw) from the working electrode and a background electrode current signal (Ib) from the background electrode at a regular interval and storing the working electrode current signal (Iw) and the background electrode current signal (Ib) into a memory;
determining a glucose signal (Iw−Ib) as a difference between the working electrode current signal (Iw) and the background electrode current signal (Ib) and storing the glucose signal in the memory for each regular interval;
gathering a point-of-interest working electrode current signal and a point-of-interest background electrode current signal:
calculating a plurality of sensor progression parameters as a plurality of ratios between a point-of-interest glucose signal and a plurality of previously-measured glucose signals stored in the memory,
wherein the point-of-interest glucose signal is the difference between the point-of-interest working electrode current signal and the point-of-interest background electrode current signal;
computing a compensated analyte concentration for the point-of-interest glucose signal by applying the plurality of sensor progression parameters to a predetermined gain function stored in the memory; and
communicating the compensated analyte concentration to a user.
2 . The method of claim 1 , wherein the regular interval is a three-minute interval and wherein each of the plurality of previously-measured glucose signals correspond to multiples of the three-minute interval.
3 . The method of claim 1 , wherein at least one sensor progression parameter includes a ratio of the point-of-interest working electrode current signal and a portion of previously-measured working electrode current signals stored in the memory.
4 . The method of claim 1 , further comprising:
calculating a gain function value from the plurality of sensor progression parameters for the predetermined gain function; and
modifying a system gain according to the gain function value.
5 . The method of claim 4 , wherein the gain function value includes a ratio of the point-of-interest working electrode current signal and a previously-measured working electrode current signal measured at least one hour before the point-of-interest working electrode current signal.
6 . The method of claim 4 , wherein the gain function value includes a ratio of the point-of-interest working electrode current signal and a previously-measured working electrode current measured between 6 and 12 hours before the point-of-interest working electrode current signal.
7 . The method of claim 1 , wherein the predetermined gain function is factory determined using multi-variate regression and stored in the memory.
8 . The method of claim 1 , wherein the predetermined gain function is determined by:
obtaining an error-free signal from a blood glucose meter (BGM) at a time increment and storing the error-free signal in the memory;
pairing one or more glucose signals (Iw−Ib) sensed at the regular interval with a most-recent error-free signal;
determining a relative analyte error by calculating a difference between the one or more glucose signals (Iw−Ib) and the error-free signal proportional to the error-free signal;
performing multivariate regression with the plurality of sensor progression parameters as input variables that target the relative analyte error to obtain the predetermined gain function,
wherein the predetermined gain function includes the plurality of sensor progression parameters and a plurality of corresponding weighted coefficients; and
storing the predetermined gain function in the memory.
9 . A wearable continuous analyte monitoring (CAM) device comprising:
a biosensor configured to be subcutaneously inserted into a subject, the biosensor including a counter electrode, a reference electrode, a background electrode, and a working electrode having a chemical composition configured to oxidize an analyte and to produce analyte signals from interstitial fluid;
a bias circuit;
a current measurement circuit;
a processor; and
a memory coupled to the processor storing a predetermined gain function and a plurality of instructions that configure the processor:
cause the bias circuit to apply a constant voltage to the working electrode and to the background electrode;
cause the current measurement circuit to sense a working electrode current signal (Iw) from the working electrode and a background electrode current signal (Ib) from the background electrode at a regular interval and store the working electrode current signal (Iw) and the background electrode current signal (Ib) into the memory;
determine a glucose signal (Iw−Ib) as a difference between the working electrode current signal (Iw) and the background electrode current signal (Ib) and store the glucose signal in the memory for each regular interval;
gathering a point-of-interest working electrode current signal and a point-of-interest background electrode current signal:
calculate a plurality of sensor progression parameters as a plurality of ratios between a point-of-interest glucose signal and a plurality of previously-measured glucose signals stored in the memory,
wherein the point-of-interest glucose signal is the difference between the point-of-interest working electrode current signal and the point-of-interest background electrode current signal;
determine a compensated analyte concentration for the point-of-interest glucose signal by applying the plurality of sensor progression parameters to the predetermined gain function stored in the memory; and
communicate the compensated analyte concentration to a user.
10 . The wearable CAM device of claim 9 , wherein the compensated analyte concentration is transmitted wirelessly to a portable user device.
11 . The wearable CAM device of claim 9 , wherein at least one sensor progression parameter includes a ratio of the point-of-interest working electrode current signal and a portion of previously-measured working electrode current signals stored in the memory.
12 . The wearable CAM device of claim 9 , wherein the processor is further configured to:
calculate a gain function value from the plurality of sensor progression parameters for the predetermined gain function; and
modify a system gain according to the gain function value.
13 . The wearable CAM device of claim 12 , wherein the gain function value includes a ratio of the point-of-interest working electrode current signal and a previously-measured working electrode current signal measured between 1 and 12 hours before the point-of-interest working electrode current signal.
14 . The wearable CAM device of claim 9 , wherein the predetermined gain function is factory determined using multi-variate regression and stored in the memory.
15 . A portable user device configured to interface with a wearable monitoring device, the portable user device comprising:
a display;
a processor; and
a memory coupled to the processor storing a predetermined gain function and a plurality of instructions that, when executed by the processor, causes the portable user device to:
receive a working electrode current signal and a background electrode current signal from the wearable monitoring device having a biosensor subcutaneously inserted into a subject, the biosensor including a counter electrode, a reference electrode, a background electrode, and a working electrode having a chemical composition configured to oxidize an analyte;
determine a glucose signal (Iw−Ib) as a difference between the working electrode current signal (Iw) from the working electrode and the background electrode current signal (Ib) from the background electrode and store the glucose signal in the memory for each regular interval;
gather a point-of-interest working electrode current signal and a point-of-interest background electrode current signal;
calculate a plurality of sensor progression parameters as a plurality of ratios between a point-of-interest glucose signal and a plurality of previously-measured glucose signals stored in the memory,
wherein the point-of-interest glucose signal is the difference between the point-of-interest working electrode current signal and the point-of-interest background electrode current signal;
determine a compensated analyte concentration for the point-of-interest glucose signal by applying the plurality of sensor progression parameters to the predetermined gain function stored in the memory; and
communicate the compensated analyte concentration to a user.
16 . The portable user device of claim 15 , wherein at least one sensor progression parameter includes a ratio of the point-of-interest working electrode current signal and a portion of previously-measured working electrode current signals stored in the memory.
17 . The portable user device of claim 15 , wherein the processor is further configured to:
calculate a gain function value from the plurality of sensor progression parameters for the predetermined gain function; and
modify a system gain according to the gain function value.
18 . The portable user device of claim 17 , wherein the gain function value includes a ratio of the point-of-interest working electrode current signal and a previously-measured working electrode current signal measured at least one hour before the point-of-interest working electrode current signal.
19 . The portable user device of claim 17 , wherein the gain function value includes a ratio of the point-of-interest working electrode current signal and a previously-measured working electrode current measured between 6 and 12 hours before the point-of-interest working electrode current signal.
20 . The portable user device of claim 15 , wherein the predetermined gain function is factory determined using multi-variate regression and stored in the memory.