Abstract: An insulin monitoring system includes one or more processors, one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors. The program instructions include: first program instructions to track, in real time, the amount of insulin active in a patient; second program instructions to calculate the amount of insulin need of the patient by tracking the patient's metabolic states; third program instructions to compare the insulin active in the patient with the insulin need of the patient; and fourth program instructions to determine an insulin fault level based on the comparison.

Abstract: An insulin delivery supervisor (IDS) with a safety analysis and supervision function that can reside between the insulin request and the insulin delivery and can intercept any excessive insulin requests before the insulin was delivered. The IDS can be implemented in any system based on insulin pump or pen and will work with either SMBG or CGM modes of blood glucose monitoring.

Abstract: An aspect of an embodiment or partial embodiment of the present invention (or combinations of various embodiments in whole or in part of the present invention) comprises, but not limited thereto, a method and system (and related computer program product) for continually assessing the risk of hypoglycemia for a patient and then determining what action to take based on that risk assessment. A further embodiment results in two outputs: (1) an attenuation factor to be applied to the insulin rate command sent to the pump (either via conventional therapy or via open or closed loop control) and/or (2) a red/yellow/green light hypoglycemia alarm providing to the patient an indication of the risk of hypoglycemia. The two outputs of the CPHS can be used in combination or individually.

Abstract: Embodiments relate to a system for processing glucose data by efficient glucose database management. The system includes a physical data store containing glucose measurement data and a representation for at least one cluster of the glucose measurement data, wherein the representation approximates a glycemic profile vector array for a cluster of multiple glucose profiles segmented by plural time ranges. The system includes a processor and computer memory configured with instructions stored thereon that when executed will cause the processor to: 1) receive glucose measurements; 2) convert the glucose measurements into vectorial form; 3) search the physical data store by comparing a newly received glucose measurement to a centroid of a cluster using a similarity metric; 3) classify the newly received glucose measurement with a cluster having a matched similarity metric based on the comparing; and 4) ascribe a treatment to the newly received glucose measurement.

Abstract: A structure, method, and computer program product for a diabetes control system provides, but is not limited thereto, the following: open-loop or closed-loop control of diabetes that adapts to individual physiologic characteristics and to the behavioral profile of each person. An exemplary aspect to this adaptation is biosystem (patient or subject) observation and modular control. Consequently, established is the fundamental architecture and the principal components for a modular system, which may include algorithmic observers of patients' behavior and metabolic state, as well as interacting control modules responsible for basal rate, insulin boluses, and hypoglycemia prevention.

Abstract: An aspect of an embodiment or partial embodiment of the present invention (or combinations of various embodiments in whole or in part of the present invention) comprises, but not limited thereto, a method and system (and related computer program product) for continually assessing the risk of hypoglycemia for a patient and then determining what action to take based on that risk assessment. A further embodiment results in two outputs: (1) an attenuation factor to be applied to the insulin rate command sent to the pump (either via conventional therapy or via open or closed loop control) and/or (2) a red/yellow/green light hypoglycemia alarm providing to the patient an indication of the risk of hypoglycemia. The two outputs of the CPHS can be used in combination or individually.

Abstract: Provided are a method, system and computer-readable storage medium for quantitative physiological assessment and prediction of clinical subtypes of glucose metabolism disorders, including but not limited to, Type 1 diabetes, obesity, pre-diabetes, gestational diabetes, or variants of Type 2 diabetes. The method allows a virtual population of in silico entities to be created, reproducing faithfully the clinical subtype distributions observed in vivo. Potential applications of this method may include, but are not limited to: (a) enabling in silico experiments assessing and/or predicting, for a real patient, treatment or intervention outcomes for a given population/clinical-subtype level; (b) pre-clinical testing of properties of new medications; (c) augmenting limited clinical trial data with in silico experiments to an extent that the domain of their validity and test corner cases may not be observed in vivo.

Abstract: Provided are a method, system and computer-readable storage medium for mapping a metabolic phenotype of a subject to a database entity for creating a digital twin of the subject, and enabling as to such subject, one or more of in silico titration of treatment as to such subject prior to initiating clinical intervention, in silico adjustment and optimization of medication dosing and timing, personalized training through in silico replay of particularized treatment scenario, and tracking over time of any divergence in one or more metabolic traits as between the subject and the digital twin to thereby detect deterioration or improvement in the subject's condition.

Abstract: A method, apparatus, and a kit are capable of improving accuracy of CGS devices using dynamic outputs of continuous glucose sensors.

Abstract: An insulin monitoring system includes one or more processors, one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors. The program instructions include: first program instructions to track, in real time, the amount of insulin active in a patient; second program instructions to calculate the amount of insulin need of the patient by tracking the patient's metabolic states; third program instructions to compare the insulin active in the patient with the insulin need of the patient; and fourth program instructions to determine an insulin fault level based on the comparison.

Abstract: An aspect of an embodiment or partial embodiment of the present invention (or combinations of various embodiments in whole or in part of the present invention) comprises, but not limited thereto, a method and system (and related computer program product) for continually assessing the risk of hypoglycemia for a patient and then determining what action to take based on that risk assessment. A further embodiment results in two outputs: (1) an attenuation factor to be applied to the insulin rate command sent to the pump (either via conventional therapy or via open or closed loop control) and/or (2) a red/yellow/green light hypoglycemia alarm providing to the patient an indication of the risk of hypoglycemia. The two outputs of the CPHS can be used in combination or individually.

Abstract: Embodiments can relate to systems and methods for automatically detecting sensor compression in continuous glucose monitoring in real time. A system may include at least one sensor and at least one processor in communication with the at least one sensor. The at least one processor is programmed or configured to cause the processor to retrieve first measurement data including at least one time series of blood glucose (BG) measurements, the at least one time series being measured by the at least one sensor while not subject to compression; receive, from the at least one sensor, second measurement data including at least one BG measurement; determine a clearance value between BG measurements based on the first measurement data and the second measurement data; and generate a signal output indicating that the at least one sensor is subject to compression based on the clearance value between BG measurements exceeding a predefined threshold.

Abstract: Embodiments can relate to a system for automatically detecting sensor compression in continuous glucose monitoring including at least one sensor and at least one processor in communication with the at least one sensor, the at least one processor executing at least two machine learning models, wherein the at least one processor is programmed or configured to cause the processor to receive, from the at least one sensor, measurement data including at least one time series of blood glucose (BG) measurements measured by the at least one sensor, determine that the at least one time series of BG measurements is a candidate series including a compression artifact using a first machine learning model, and generate, using a second machine learning model, a signal output indicating that the at least one time series of BG measurements was obtained while the at least one sensor was subject to compression.

Abstract: A structure, method, and computer program product for a diabetes control system provides, but is not limited thereto, the following: open-loop or closed-loop control of diabetes that adapts to individual physiologic characteristics and to the behavioral profile of each person. An exemplary aspect to this adaptation is biosystem (patient or subject) observation and modular control. Consequently, established is the fundamental architecture and the principal components for a modular system, which may include algorithmic observers of patients' behavior and metabolic state, as well as interacting control modules responsible for basal rate, insulin boluses, and hypoglycemia prevention.

Abstract: A method, apparatus, and a kit are capable of improving accuracy of CGS devices using dynamic outputs of continuous glucose sensors.

Abstract: An insulin monitoring system includes one or more processors, one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors. The program instructions include: first program instructions to track, in real time, the amount of insulin active in a patient; second program instructions to calculate the amount of insulin need of the patient by tracking the patient's metabolic states; third program instructions to compare the insulin active in the patient with the insulin need of the patient; and fourth program instructions to determine an insulin fault level based on the comparison.

Abstract: A system, method and non-transient computer readable medium for tracking hypoglycemia risk in patients with diabetes exercise. A system may include a digital processor configured to execute instructions to receive an input from each available data source of a plurality of intermittently available data sources; determine a plurality of probability signals for impending hypoglycemia, wherein each probability signal is based on one or more of the inputs from the available data sources or a lack of input from an unavailable data source; wherein a probability signal for each unavailable data source is assigned a value corresponding to a zone of uncertainty; and determine an aggregate risk of hypoglycemia based on the plurality of intermittently data sources by aggregating the plurality of probability signals.

Abstract: An aspect of an embodiment or partial embodiment of the present invention (or combinations of various embodiments in whole or in part of the present invention) comprises, but not limited thereto, a method and system (and related computer program product) for continually assessing the risk of hypoglycemia for a patient and then determining what action to take based on that risk assessment. A further embodiment results in two outputs: (1) an attenuation factor to be applied to the insulin rate command sent to the pump (either via conventional therapy or via open or closed loop control) and/or (2) a red/yellow/green light hypoglycemia alarm providing to the patient an indication of the risk of hypoglycemia. The two outputs of the CPHS can be used in combination or individually.

Abstract: Method, system and computer program product for providing real time detection of analyte sensor sensitivity decline is continuous glucose monitoring systems are provided.

Abstract: A method, system and computer readable medium for tracking changes in average glycemia in diabetes is based on a conceptually new approach to the retrieval of SMBG data. Using the understanding of HbA1c fluctuation as the measurable effect of the action of an underlying dynamical system, SMBG provides occasional glimpses at the state of this system and, using these measurements, the hidden underlying system trajectory can be reconstructed for individual diabetes patients. Using compartmental modeling a new two-step algorithm is provided that includes: (i) real-time estimate of HbA1c from fasting glucose readings, updated with any new incoming fasting SMBG data point(s), and (ii) initialization and calibration of the estimated HbA1c trace with daily SMBG profiles obtained periodically. The estimation of these profiles includes a factorial model capturing daily BG variability within two latent factors.