Abstract: A flexible system capable of utilizing data from different monitoring techniques and capable of providing assistance to patients with diabetes at several scalable levels, ranging from advice about long-term trends and prognosis to real-time automated closed-loop control (artificial pancreas). These scalable monitoring and treatment strategies are delivered by a unified system called the Diabetes Assistant (DiAs) platform. The system provides a foundation for implementation of various monitoring, advisory, and automated diabetes treatment algorithms or methods. The DiAs recommendations are tailored to the specifics of an individual patient, and to the patient risk assessment at any given moment.

Abstract: An insulin device configured to control insulin dosage adapts a basal rate profile, using a sensor configured to produce a blood glucose level measurement data, and detect changes of the blood glucose level measurement data over time. A processor is configured to receive the blood glucose level measurement data and a basal rate profile. A basal rate set point corresponds to an insulin delivery reference for a nominal blood glucose. The insulin device includes an insulin dispensing valve controlled by the processor to administer insulin in accordance with the received basal rate profile. The processor is configured to update the basal rate set point over a time period based on both an assessment of at least one of a risk of hyperglycemia and a risk of hypoglycemia from historical blood glucose data, and patterns of actions taken by the insulin device to mitigate glycemic risk during the time period.

Abstract: Equivalent insulin pump retrospective virtual basal rates for daily injections are constructed from planned insulin injections according to a virtual basal rate profile developed for a patient, and a database of historical insulin injections, i.e. basal injections actually administered by the patient, providing a unified framework for analysis, design, optimization, and adaptation of MDI (multiple daily injections) and CSII (continuous subcutaneous insulin infusion (i.e. insulin pump)) treatment parameters for patients with diabetes.

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: Time-varying hyperglycemic stresses are derived from actual ICU patients and applied to non-critically ill virtual patients, using any model of normal glucose-insulin physiology that fulfills certain requirements, in order to model and simulate stress hyperglycemia. Other aspects provide: 1) a methodology to perform sensitivity analyses of the parameters of ICU insulin infusion therapy protocols and to improve the protocols; and 2) a training system for clinicians about the course and management of stress hyperglycemia in the ICU or other facility.

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 computer-implemented method for treating a patient suffering from T1D. The method can include quantifying physical activity (PA) of the patient; calculating an accumulated PA periodically based on the quantified PA, the accumulated PA indicating an aggregate of the PA; and generating an activity informed insulin bolus by adjusting a prevalent functional insulin therapy bolus with a previous activity component, wherein the previous activity component is based on the accumulated daily PA, an activity profile, and an activity factor of the patient. The method can include determining an additional glucose uptake within a time period, the additional glucose uptake being caused by a PA; translating the additional glucose uptake into a number of insulin units with a same BG lowering impact; and generating an activity informed insulin bolus by adjusting a prevalent functional insulin therapy bolus with the insulin units.

Abstract: A method, system, and apparatus for remote patient monitoring or tracking sepsis-related indicators or markers in ambulatory patients or outpatients. The method, system, and apparatus is devised or configured to provide remote patient monitoring of patient vitals signs for determining the risk for sepsis.

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 and system use mathematical models and available patient information to virtualize a continuous glucose monitoring trace for a period of time. Such a method and system can generate the virtualized trace when episodic patient data is incomplete. Such a method and system can also rely on self-monitored blood glucose measurement information to improve the virtualized continuous glucose monitoring trace.

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 gait pathology detection and monitoring system, and method using rotation, scale, and offset invariant dynamic time warping (RSOI-DTW).

Abstract: A system, method and non-transient computer readable medium for assessing the opportunity to address either hyperglycemic or hypoglycemic risk (or both) in patients with diabetes based on historical continuous glucose monitoring (CGM) data.

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 end 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: Architecture and associated methods are provided for power management of ambulatory medical devices. The medical devices is described by a suite of services, each assigned a level of priority (from discretionary to critical), and the power management architecture allows use interchangeable control modules of various levels. A Power Safety Controller supervises the system to ensure appropriate preservation of critical services and provide warnings for low battery level. A Fidelity Controller ensures optimal allocation of power between the different services. A device supervision module estimates device characteristics which can be used by the other levels. The overall architecture ensures a safe and optimal management of services, and allows for a bottom-up deployment of the device.

Abstract: Method and System for providing a signal from an insulin pump, artificial pancreas, or another insulin delivery device as a source of information for improving the accuracy of a continuous glucose sensor (CGS). The effect of using insulin information to enhance sensor accuracy is most prominent at low blood glucose levels, i.e. in the hypoglycemic range, which is critical for any treatment. A system for providing a filtering/state estimation methodology that may be used to determine a glucose state estimate at time t-?. The estimation may be extrapolated to some future time t and then the extrapolated value is used to extract the blood glucose component. The blood glucose component of the extrapolation and the output of the CGS are weighted and used to estimate the blood glucose level of a subject.

Abstract: Time-varying hyperglycemic stresses are derived from actual ICU patients and applied to non-critically ill virtual patients, using any model of normal glucose-insulin physiology that fulfills certain requirements, in order to model and simulate stress hyperglycemia. Other aspects provide: 1) a methodology to perform sensitivity analyses of the parameters of ICU insulin infusion therapy protocols and to improve the protocols; and 2) a training system for clinicians about the course and management of stress hyperglycemia in the ICU or other facility.

Abstract: An Adaptive Advisory Control (AA Control) interactive process involving algorithm-based assessment and communication of physiologic and behavioral parameters and patterns assists patients with diabetes with the optimization of their glycemic control. The method and system may uses all available sources of information about the patient; (i) EO Data (e.g. self-monitoring of blood glucose (SMBG) and CMG), (ii) Insulin Data (e.g. insulin pump log files or patient treatment records), and (iii) Patient Self Reporting Data (e.g. self treatment behaviors, meals, and exercise) to: retroactively assess the risk of hypoglycemia, retroactively assess risk-based reduction of insulin delivery, and then report to the patient how a risk-based insulin reduction system would have acted consistently to prevent hypoglycemia.