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US 10,307,109 B2Granted
Glucose predictor based on regularization networks with adaptively chosen kernels and regularization parameters
AssigneeNovo Nordisk A/S
InventorsJette Randloev, Samuel McKennoch, Sergei Pereverzyev, Sivananthan Sampath
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Abstract
The invention relates to a method and a device for predicting a glycaemic profile of a subject. A multistage algorithm is employed comprising a prediction setting stage specifying a functional space for the prediction and a prediction execution stage specifying a predicted future glycaemic state of the subject in the functional space as a continuous function of time.
Claims41
A glucose prediction device comprising:
- an input device structured to receive information indicative of a physiologic condition of a subject;
- a processing device comprising an adaptive regularization network that is structured to predict a future glucose profile;
- an output device structured to convey the future glucose profile;
- and
- an alarm;
- wherein the future glucose profile is the glycaemic state of the subject as a continuous function of time;
- wherein the adaptive regularization network is adapted to perform a multistage prediction process and comprises a supervising learning machine and a supervised learning machine that allows the future glucose profile to be predicted with irregularly sampled data in the information received by the input device;
- wherein (a) the supervising learning machine is adapted to (i) compress the information received by the input device and (ii) run the compressed information through a pre-constructed machine to produce kernel parameters and a regularization parameter;
- and (b) the supervised learning machine is adapted to calculate the future glucose profile as a function of the information received by the input device and the kernel parameters and the regularization parameter produced by the supervising learning machine;
- and
- wherein the alarm is structured to alert the subject if the future glucose profile includes an impending hypo- or hyperglycaemic event.
8 more elements
A computer-implemented method for predicting a future glucose profile of a subject that is the glycaemic state of the subject as a continuous function of time, the method comprising:
- providing a glucose prediction device comprising a processing device;
- receiving, by the processing device, information indicative of a physiologic condition of the subject;
- specifying, by the processing device, a functional space for the predicted glucose profile by compressing the received information and running the compressed information through a pre-constructed machine to produce kernel parameters and a regularization parameter;
- calculating, by the processing device, predicted glucose values as a continuous function of time based on the received information, the kernel parameters, and the initial regularization parameter to thereby produce the predicted future glucose profile of the subject;
- and
- alerting the user, by the glucose prediction device, if the future glucose profile of the subject includes an impending hypo- or hyperglycaemic event.
3 more elements
A glucose prediction device comprising:
- an input device structured to receive information indicative of a physiologic condition of a subject, wherein the information comprises blood or tissue glucose measurements;
- a processing device comprising an adaptive regularization network that is structured to predict a future glucose profile;
- an output device structured to convey the future glucose profile;
- and
- an alarm;
- wherein the future glucose profile is the glycaemic state of the subject as a continuous function of time;
- wherein the adaptive regularization network is adapted to perform a multistage prediction process and comprises a supervising learning machine and a supervised learning machine that allows the future glucose profile to be predicted with irregularly sampled data in the blood or tissue glucose measurements received by the input device;
- wherein (a) the supervising learning machine is adapted to (i) compress the information received by the input device and (ii) run the compressed information through a pre-constructed machine to produce kernel parameters and a regularization parameter;
- and (b) the supervised learning machine is adapted to calculate the future glucose profile as a function of the information received by the input device and the kernel parameters and the regularization parameter produced by the supervising learning machine;
- and
- wherein the alarm is structured to alert the subject if the future glucose profile includes an impending hypo- or hyperglycaemic event.
8 more elements
A computer-implemented method for predicting a future glucose profile of a subject that is the glycaemic state of the subject as a continuous function of time, the method comprising:
- providing a glucose prediction device comprising a processing device;
- receiving, by the processing device, information indicative of a physiologic condition of the subject, wherein the information comprises blood or tissue glucose measurements;
- specifying, by the processing device, a functional space for the predicted glucose profile by compressing the received information and running the compressed information through a pre-constructed machine to produce kernel parameters and a regularization parameter, wherein the kernel parameters are produced by a regularized learning algorithm in a reproducing kernel Hilbert space defined by at least approximately minimizing an error function;
- calculating, by the processing device, predicted glucose values as a continuous function of time based on the received information, the kernel parameters, and the initial regularization parameter to thereby produce the predicted future glucose profile of the subject;
- and
- alerting the user, by the glucose prediction device, if the future glucose profile of the subject includes an impending hypo- or hyperglycaemic event.
3 more elements
Dependencies are inferred from the claim text.