Method to recalibrate continuous glucose monitoring data on-line
Abstract
In a method of recalibrating continuous glucose monitoring data from a user, operable on a digital processor, an indication from the user that the user has taken a meal is received ( 806 ). A self-monitored of blood glucose levels from the user ( 810 ) at two separate times during a day corresponding to when the user has taken a meal. A glucose signal is received from a continuous glucose monitoring sensor ( 818 ) at times corresponding to the two separate times that the user has taken a meal. Two reconstructed blood glucose values based on the glucose signal from the continuous monitoring sensor at times when the at least two self-monitored of blood glucose levels are received from the user. A linear regression is performed ( 822 ) using y=ax+b, wherein x corresponds to the two reconstructed blood glucose values and y corresponds to the two self-monitored of blood glucose levels thereby generating an estimation of a and b. A recalibration signal, including the estimation of a and b, is transmitted to the continuous glucose monitoring sensor ( 824 ) based on the linear regression.
Claims
exact text as granted — not AI-modifiedWhat is claimed is:
1 . A system for recalibrating continuous glucose monitoring data from a user, comprising:
a. a digital processor; b. a continuous glucose monitoring sensor, in communication with the digital processor, configured to generate a glucose signal; c. a recalibration module, configured to:
i. receive at least two self-monitored of blood glucose levels from the user;
ii. receive meal information from the user;
iii. receive the glucose signal from the continuous glucose monitoring sensor;
iv. generate two reconstructed blood glucose values based on the glucose signal from the continuous monitoring sensor at times when the at least two self-monitored of blood glucose levels are received from the user;
v. perform a linear regression using y=ax+b, wherein x corresponds to the two reconstructed blood glucose values and y corresponds to the two self-monitored of blood glucose levels thereby generating an estimation of a and b; and
vi. transmit a recalibration signal, including the estimation of a and b, to the continuous glucose monitoring sensor based on the linear regression.
2 . The system of claim 1 , wherein the calibration module is configured to generate two reconstructed blood glucose values by converting the glucose signal from the continuous glucose monitoring sensor into a potential plasma glucose concentration.
3 . The system of claim 1 , wherein the calibration module converts continuous glucose monitoring data in the glucose signal into reconstructed blood glucose data with a deconvolution procedure based on a dynamic model of a blood glucose to interstitial glucose system.
4 . The system of claim 1 , wherein the calibration module is configured to generate a request to the user for a self monitored blood glucose level at a first predetermined period after the user has had a meal.
5 . The system of claim 4 , wherein the first predetermined period comprises thirty minutes.
6 . The system of claim 5 , wherein the calibration module is configured to generate a request to the user for a self monitored blood glucose level at a second predetermined period after the user has had a meal.
7 . The system of claim 6 , wherein the first predetermined period comprises three hours.
8 . The system of claim 1 , wherein the processor and the continuous glucose monitoring sensor are in communication with each other via a global computer network.
9 . The system of claim 1 , wherein the recalibration module is further configured to execute each day after the user has taken two different meals.
10 . A method of recalibrating continuous glucose monitoring data from a user, operable on a digital processor, comprising the steps of:
a. receiving an indication from the user that the user has taken a meal; b. receiving a self-monitored of blood glucose levels from the user at two separate times during a day corresponding to when the user has taken a meal; c. receiving a glucose signal from a continuous glucose monitoring sensor at times corresponding to the two separate times that the user has taken a meal; d. generating two reconstructed blood glucose values based on the glucose signal from the continuous monitoring sensor at times when the at least two self-monitored of blood glucose levels are received from the user; e. performing a linear regression using y=ax+b, wherein x corresponds to the two reconstructed blood glucose values and y corresponds to the two self-monitored of blood glucose levels thereby generating an estimation of a and b; and f. transmitting a recalibration signal, including the estimation of a and b, to the continuous glucose monitoring sensor based on the linear regression.
11 . The method of claim 10 , wherein the step of generating two reconstructed blood glucose comprises converting the glucose signal from the continuous glucose monitoring sensor into a potential plasma glucose concentration.
12 . The method of claim 10 , further comprising the step of converting continuous glucose monitoring data in the glucose signal into reconstructed blood glucose data using a deconvolution procedure based on a dynamic model of a blood glucose to interstitial glucose system.
13 . The method of claim 10 , further comprising the step of generating a request to the user for a self monitored blood glucose level at a first predetermined period after the user has had a meal.
14 . The method of claim 13 , wherein the first predetermined period comprises thirty minutes.
15 . The method of claim 14 , further comprising the step of generating a request to the user for a self monitored blood glucose level at a second predetermined period after the user has had a meal.
16 . The method of claim 15 , wherein the first predetermined period comprises three hours.
17 . The method of claim 10 , further comprising the step of communicating data from the continuous glucose monitoring sensor to the processor and from the processor to the continuous glucose monitoring sensor via a global computer network.Join the waitlist — get patent alerts
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