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 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 for generating a hypoglycemia risk signal associated with exercise-induced Hypoglycemia. The system can include a processor configured to obtain a blood glucose signal (BGstart), a ratio of absolute insulin on board over total daily insulin signal (IOBabs/TDI), and an initial glycemic slope signal (S0); generate a hypoglycemia risk signal based on a hypoglycemia prediction algorithm that determines the probability of a user being hypoglycemic during or after exercise based on the obtained BGstart, IOBabs/TDI and S0.

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: A method, system, and computer-readable medium are provided for a dual mode Closed-Loop Control (CLC) system integrating each of (i) an adaptive, personalized Model Predictive Control (MPC) control law that modulates the control strength of insulin infusion depending on recent past control actions, glucose measurements, and their derivative(s), (ii) an automatic Bolus Priming System (BPS) that commands additional insulin injections upon the detection of enabling metabolic conditions (e.g., an unannounced meal), and (iii) a hyperglycemia mitigation system (HMS) to avoid prevailing hyperglycemia.

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: 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: The invention relates to a methods and systems for determining an insulin dosing recommendation. The invention employs Linear Quadratic methodology to determine the insulin dosing recommendation based on a patient's present physiological state, which is estimated by an adaptive filter methodology employing a dynamic model, which utilizes real-time measurements of blood glucose concentration.

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.

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, system, and computer-readable medium are provided for modeling a time-varying representation of the glucose homeostasis of a patient with Type 1 diabetes (T1D) according to a computational model therefor. The model implements a reconstruction of data supporting a glucose time series for the patient, and based on the reconstruction, further implements model personalization and a variability control (VC) signal accounting for insulin sensitivity so as to enable the patient to learn an effect of adjustment to one or more portions of the data. Such knowledge is acquired upon a replay of the reconstruction implementing the adjustment.

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: 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: 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: 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 system for generating a hypoglycemia risk signal associated with exercise-induced Hypoglycemia. The system can include a processor configured to obtain a blood glucose signal (BGstart), a ratio of absolute insulin on board over total daily insulin signal (IOBabs/TDI), and an initial glycemic slope signal (S0); generate a hypoglycemia risk signal based on a hypoglycemia prediction algorithm that determines the probability of a user being hypoglycemic during or after exercise based on the obtained BGstart, IOBabs/TDI and S0.

Abstract: A system for generating a hypoglycemia risk signal associated with exercise-induced Hypoglycemia. The system can include a processor configured to obtain a blood glucose signal (BGstart), a ratio of absolute insulin on board over total daily insulin signal (IOBabs/TDI), and an initial glycemic slope signal (S0); generate a hypoglycemia risk signal based on a hypoglycemia prediction algorithm that determines the probability of a user being hypoglycemic during or after exercise based on the obtained BGstarts, IOBabs/TDI and S0.

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 systems and methods for informing, determining, or controlling insulin dosage. The method involves generating plural disturbance profiles, each disturbance profile being a data representation based on historical patient data pertaining to a deviation from a threshold blood glucose level. The method involves receiving current patient data. The method involves applying a predictive model so that current patient data is compared to a disturbance profile and a probability analysis is used to assess the likelihood of a disturbance profile being an anticipated disturbance profile, the anticipated disturbance profile being a disturbance profile that is determined to match with the current patient data based on the probability analysis. The method involves determining an insulin dose amount based on the anticipated disturbance profile.