Substance monitoring and control in human or animal bodies
First Claim
1. Apparatus for real time control of glucose in a human or an animal, the apparatus comprising:
- a sensor providing a time series of measurements of glucose level, said measurements being indicative of an inferred level of said glucose in a part of said human or animal,a processor which is adapted to perform the following steps;
calculate a first estimate of said inferred glucose level from said measured glucose level using a first glucoregulatory system model,calculate a second estimate of said inferred glucose level from said measured glucose level using a second glucoregulatory system model with said second system model being a variation of said first system model, andpredict a combined estimate of the inferred glucose level based on a combination of the first and second estimates,wherein the processor is a state estimator and is adapted to define a state vector for each model, the state vector comprising a set of variables each having an associated uncertainty, the set of variables including a variable representing an unexplained change in glucose level with each model having a different standard deviation in the unexplained change in glucose level;
wherein the first and second glucoregulatory models each comprise a sub-model of glucose kinetics in the blood of said human or animal, a sub-model of interstitial glucose kinetics, a sub-model of insulin absorption, a sub-model of insulin action and a sub-model of gut absorption; and
wherein the state vector includes the following states
xk=(q1ƒ
,k,q2ƒ
,kuS,k,Fk,q3ƒ
,k)T where q1ƒ
,k, q2ƒ
,k, and q3ƒ
,k represent glucose amounts in the accessible, non-accessible, and interstitial compartments excluding the contribution from meals, us,k is the unexplained glucose influx and Fk is glucose availability, and a dispenser that delivers a specified amount of medication to a user in response to a command from the processor based on the predicted combined estimate of the inferred glucose level.
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Accused Products
Abstract
Apparatus for monitoring a substance in human or animal in real time, the apparatus comprising a sensor providing a time series of measurements of substance level, said measurements being indicative of an inferred level of said substance in a part of said human or animal and a processor which applies an interacting multiple model strategy to a system model to provide a combined estimate of the inferred substance level from the substance level measurements. The substance may be glucose. The apparatus may also be adapted to control said substance using said interacting multiple model strategy to a system model to provide a combined estimate of a dose to be applied.
44 Citations
34 Claims
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1. Apparatus for real time control of glucose in a human or an animal, the apparatus comprising:
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a sensor providing a time series of measurements of glucose level, said measurements being indicative of an inferred level of said glucose in a part of said human or animal, a processor which is adapted to perform the following steps; calculate a first estimate of said inferred glucose level from said measured glucose level using a first glucoregulatory system model, calculate a second estimate of said inferred glucose level from said measured glucose level using a second glucoregulatory system model with said second system model being a variation of said first system model, and predict a combined estimate of the inferred glucose level based on a combination of the first and second estimates, wherein the processor is a state estimator and is adapted to define a state vector for each model, the state vector comprising a set of variables each having an associated uncertainty, the set of variables including a variable representing an unexplained change in glucose level with each model having a different standard deviation in the unexplained change in glucose level; wherein the first and second glucoregulatory models each comprise a sub-model of glucose kinetics in the blood of said human or animal, a sub-model of interstitial glucose kinetics, a sub-model of insulin absorption, a sub-model of insulin action and a sub-model of gut absorption; and wherein the state vector includes the following states
xk=(q1ƒ
,k,q2ƒ
,kuS,k,Fk,q3ƒ
,k)Twhere q1ƒ
,k, q2ƒ
,k, and q3ƒ
,k represent glucose amounts in the accessible, non-accessible, and interstitial compartments excluding the contribution from meals, us,k is the unexplained glucose influx and Fk is glucose availability, and a dispenser that delivers a specified amount of medication to a user in response to a command from the processor based on the predicted combined estimate of the inferred glucose level.- View Dependent Claims (2, 3, 4, 5, 6, 9, 12, 14, 27, 28, 29, 34)
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28. Apparatus according to claim 1, wherein the interstitial glucose kinetics sub-model is described as
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29. Apparatus according to claim 1, wherein the state vector comprises a subset of the parameters of each model.
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34. Apparatus according to claim 12, wherein the desired glucose value varies with time to define a trajectory of values.
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7. Apparatus for real time control of a substance in a human or an animal, the apparatus comprising:
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a sensor providing a time series of measurements of substance level, said measurements being indicative of an interred level of said substance in a part of said human or animal, a processor which applies an interacting multiple model strategy to a system model to predict a combined estimate of the inferred substance level from the substance level measurements, wherein the interacting multiple model strategy comprises first and second glucoregulatory models each of which comprise a sub-model of glucose kinetics in the blood of said human or animal, a sub-model of interstitial glucose kinetics, a sub-model of insulin absorption, a sub-model of insulin action and a sub-model of gut absorption; wherein said inferred substance level comprises a level of glucose in said blood and said substance level measurements comprise measurements of an interstitial glucose level; wherein the processor is a state estimator and is adapted to define a state vector for each model, the state vector comprising a set of variables each having an associated uncertainty, the set of variables including a variable representing an unexplained change in glucose level with each model having a different standard deviation in the unexplained change in glucose level; wherein the state vector includes the following states
xke=(i1,k,i2,k,rD,k,rE,k,a1,k,a2,k,q1,k,q3,k,uS,k)Twhere i1,k and i2,k is the amount of insulin in the two subcutaneous insulin depots at time k, rD,k and rE,k are the remote insulin actions affecting glucose disposal and endogenous glucose production, a1,k and a2,k are the amount of glucose in the two absorption compartments q1,k, q2,k, q3,k represent glucose amounts in the accessible, non-accessible, and interstitial compartments and us,k is the unexplained glucose influx; and wherein said processor is configured to apply the interacting multiple model strategy to calculate a first estimate for said inferred glucose level from said measured substance level using said first glucoregulatory system model, calculate a second estimate for said inferred glucose level from said measured substance level using said second glucoregulatory system model and predict said combined estimate of the inferred glucose level based on a combination of said first and second estimates, and a dispenser that delivers a specified amount of medication to a user in response to a command from the processor based on the predicted combined estimate of the inferred glucose level.
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8. Apparatus for real time control of glucose in a human or an animal, the apparatus comprising:
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a sensor providing a time series of measurements of glucose level, said measurements being indicative of an inferred level of said glucose in a part of said human or animal; a processor which is adapted to construct at least two state vectors each comprising a set of variables for a respective one of at least two glucose level models, said state vectors representing states of said at least two models, said state vectors also including a variable representing an uncertainty in a change in glucose level with time, each of said variables having an associated probability distribution; predict a value of a said glucose level using said probability distribution and said state vectors; update values of said state vectors responsive to a difference between a predicted glucose level measurement for each said model and a glucose level measurement from said sensor; update a mixing probability representing a respective probability of each said model correctly predicting said glucose level responsive to a difference between said predicted glucose level measurement of each respective said model and said glucose level measurement from said sensor; and determine a combined predicted glucose level measurement for said human or animal by combining outputs from said glucose level models according to said updated mixing probability, wherein said at least two models each comprise a sub-model of glucose kinetics in the blood of said human or animal, a sub-model of interstitial glucose kinetics, a sub-model of insulin absorption, a sub-model of insulin action and a sub-model of gut absorption; and wherein the state vector includes the following states
xk=(q1ƒ
,k,q2ƒ
,k,uS,k,Fk,q3ƒ
,k)Twhere q1ƒ
,k, q2ƒ
,k, and q3ƒ
,k represent glucose amounts in the accessible, non-accessible, and interstitial compartments excluding the contribution from meals, us,k is the unexplained glucose influx and Fk is glucose availability, and a dispenser that delivers a specified amount of medication to a user in response to a command from the processor based on the predicted combined estimate of the inferred glucose level.
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10. Apparatus for real time control of a substance in a human or an animal, the apparatus comprising
a sensor providing a time series of measurements of substance level, said measurements being indicative of an inferred level of said substance in a part of said human or animal, a processor which is adapted to calculate an estimate of said inferred level, and a dispenser that delivers a specified amount of medication to a user in response to a command from the processor based on the calculated estimate of said inferred level, wherein the processor is adapted to calculate the specified amount of medication as the amount of medication required to bring the estimate of said inferred level in line with a desired value by calculating a first estimate of said specified amount of medication using a first system model, calculating a second estimate of said specified amount of medication using a second system model with said second system model being a variation of said first system model, and calculating a combined estimate of said specified amount of medication based on a combination of the first and second estimates, wherein said first system model and said second system model each comprise a sub-model of glucose kinetics in the blood of said human or animal, a sub-model of interstitial glucose kinetics, a sub-model of insulin absorption, a sub-model of insulin action and a sub-model of gut absorption; -
wherein said inferred substance level comprises a level of said glucose in said blood and said substance level measurements comprises measurements of an interstitial glucose level; wherein the processor is a state estimator and is adapted to define a state vector for each model, the state vector comprising a set of variables each having an associated uncertainty, the set of variables including a variable representing an unexplained change in glucose level with each model having a different standard deviation in the unexplained change in glucose level; and wherein the state vector includes the following states
xk=(q1ƒ
,k,q2ƒ
,k,uS,k,Fk,q3ƒ
,k)Twhere q1ƒ
,k, q2ƒ
,k, and q3ƒ
,k represent glucose amounts in the accessible, non-accessible, and interstitial compartments excluding the contribution from meals, us,k is the unexplained glucose influx and Fk is glucose availability. - View Dependent Claims (11, 13)
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15. A computer-implemented method for real time control of glucose in a living human or an animal, the method comprising:
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inputting, to a processor, a time series of glucose level measurements from a sensor, said glucose level measurements being indicative of a inferred level of said glucose in a part of said human or animal, calculating, using said processor, a first estimate of said inferred glucose level from said measured substance level using a first glucoregulatory system model, calculating, using said processor, a second estimate of said inferred glucose level from said measured substance level using a second glucoregulatory system model with said second system model being a variation of said first system model, defining, using said processor, a state vector for each model, the state vector comprising a set of variables each having an associated uncertainty, the set of variables including a variable representing an unexplained change in substance level with each model having a different standard deviation in the unexplained change in substance level; wherein the first and second glucoregulatory models each comprise a sub-model of glucose kinetics in the blood of said human or animal, a sub-model of interstitial glucose kinetics, a sub-model of insulin absorption, a sub-model of insulin action and a sub-model of gut absorption; wherein said inferred substance level comprises a level of said glucose in said blood and said substance level measurements comprises measurements of an interstitial glucose level; wherein the state vector includes the following states
xk=(q1ƒ
,k,q2ƒ
,k,uS,k,Fk,q3ƒ
,k)Twhere q1ƒ
,k, q2ƒ
,k, and q3ƒ
,k represent glucose amounts in the accessible, non-accessible and interstitial events excluding the contribution from meals, us,k is the unexplained glucose influx and Fk is glucose availability,predicting, using said processor, a combined estimate of the inferred glucose level based on a combination of the first and second estimates, and delivering a specified amount of medication to a user in response to a command from the processor based on the predicted combined estimate of the inferred glucose level. - View Dependent Claims (16, 17, 18, 19, 20, 25, 26, 30, 31, 32, 33)
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21. A computer-implemented method for real time control of glucose in a living human or an animal, the method comprising
inputting a time series of glucose level measurements from a glucose sensor; -
constructing, using said processor, at least two state vectors each comprising a set of variables for a respective one of at least two glucose level models, said state vectors representing states of said at least two models, said state vectors also including a variable representing an uncertainty in a change in glucose level with time, each of said variables having an associated probability distribution; predicting, using said processor, a value of a said glucose level using said probability distribution and said state vectors; updating, using said processor, values of said state vectors responsive to a difference between a predicted glucose level measurement for each said model and a glucose level measurement from said sensor; updating, using said processor, a mixing probability representing a respective probability of each said model correctly predicting said glucose level responsive to a difference between said predicted glucose level measurement of each respective said model and said glucose level measurement from said sensor; and determining, using said processor, a combined predicted glucose level measurement for said human or animal by combining outputs from said glucose level models according to said updated mixing probability, wherein said at least two models each comprise a sub-model of glucose kinetics in the blood of said human or animal, a sub-model of interstitial glucose kinetics, a sub-model of insulin absorption, a sub-model of insulin action and a sub-model of gut absorption, and wherein the state vector includes the following states
xke=(i1,k,i2,k,rD,k,rE,k,a1,k,a2,k,q1,k,q2,k,q3,k,uS,k)Twhere i1,k and i2,k is the amount of insulin in the two subcutaneous insulin depots at time k, rD,k and rE,k are the remote insulin actions affecting glucose disposal and endogenous glucose production, a1,k and a2,k are the amount of glucose in the two absorption compartments, q1,k, q2,k, q3,k represent glucose amounts in the accessible, non-accessible, and interstitial compartments and us,k is the unexplained glucose influx, and delivering a specified amount of medication to a user in response to a command from the processor based on the predicted combined estimate of the inferred glucose level. - View Dependent Claims (22)
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23. A method for real time control of a substance in a human or animal, the method comprising
providing a time series of measurements of substance level to a processor, said measurements being indicative of an inferred level of said substance in a part of said human or animal, calculating, using said processor, an estimate of said inferred level, calculating, using said processor, a specified amount of medication to be the amount of medication required to bring the estimate of said inferred level in line with a desired value by calculating, using said processor, a first estimate of said specified amount of medication using a first system model, calculate, using said processor, a second estimate of said specified amount of medication using a second system model with said second system model being a variation of said first system model, calculating, using said processor, said specified amount of medication based on a combination of said estimates, and delivering said specified amount of medication to a user in response to a command from the processor based on the combination of said estimates, wherein the processor is a state estimator and is adapted to define a state vector for each model, the state vector comprising a set of variables each having an associated uncertainty, the set of variables including a variable representing an unexplained change in glucose level with each model having a different standard deviation in the unexplained change in glucose level; -
wherein the first and second models each comprise a sub-model of glucose kinetics in the blood of said human or animal, a sub-model of interstitial glucose kinetics, a sub-model of insulin absorption, a sub-model of insulin action and a sub-model of gut absorption; and wherein the state vector includes the following states
xk=(q1ƒ
,k,q2ƒ
,k,uS,k,Fk,q3ƒ
,k)Twhere q1,ƒ
,k, q2ƒ
,k, and q3ƒ
,k represent glucose amounts in the accessible, non-accessible and interstitial compartments excluding the contribution from meals, us,k is the unexplained glucose influx and Fk is glucose availability. - View Dependent Claims (24)
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Specification