Glucose Monitor-Pump Integration for Automated Insulin Delivery

Compensating for varying accuracy of medical sensors over their lifetime to improve performance of devices like insulin pumps. The technique involves adjusting sensor readings based on estimated accuracy levels at different points in the sensor's lifespan. This accounts for the fact that sensors can have lower accuracy early on and higher accuracy later. By taking into account the sensor age, the adjustment aims to provide more accurate readings to devices like insulin pumps to improve dosing decisions.

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Automated insulin delivery (AID) system that can still calculate insulin delivery settings even when it doesn't receive real-time glucose readings from a wireless glucose monitor. If a glucose reading is missed, the AID device estimates the missing value using past readings and insulin action. This allows insulin delivery to continue without suspension. When the wireless connection is restored, the AID device backfills the missing reading from the monitor.

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A blood glucose meter that goes beyond just measuring glucose levels and provides personalized insulin dose recommendations. The meter has a single button for navigating through menus and displays. The user takes a blood sample, gets their glucose level, and then presses the button to see the recommended insulin dose based on the glucose level and current regimen. The meter connects glucose events to insulin regimens. This simplified, intuitive interface helps users learn and use the meter effectively. The meter can also override recommended doses.

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Automated medication delivery using wearable devices that allow fully autonomous insulin delivery from a wearable pump based on algorithms executed on separate devices like smartwatches. The wearable pump communicates with separate devices to receive insulin dosage instructions. This decoupling allows more powerful computing for the algorithm on separate devices, while the pump can be simpler. The separate devices monitor patient conditions, compute dosages, and send instructions wirelessly to the pump.

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System for optimizing insulin dosage for diabetes patients using a sensor, processors, and communication between devices. The system measures the patient's blood glucose level using a sensor. It calculates an initial insulin dose based on that level. It then optimizes the initial dose using correction factors received from other sources. Finally, it facilitates therapy by delivering the optimized dose to the patient's pump or injection device.

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System for managing insulin dosing for diabetes patients using a cloud-based subcutaneous outpatient process that calculates optimal insulin doses based on historical glucose readings. The process involves aggregating blood glucose measurements over intervals like breakfast and dinner to determine representative aggregate values. These are then used along with patient-specific subcutaneous information to calculate the next insulin doses. The doses are transmitted to the patient's device for administration. The aggregation helps account for variability in meal timings and absorption.

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Miniature, portable, skin-securable insulin patch pump that is less bulky, thinner, lighter, concealable, and has no operating buttons compared to traditional pumps. The patch pump has a reusable main part and a disposable part that adheres to the skin. A preloaded insertion system helps insert the cannula. The patch pump avoids air entry into the reservoir during filling by reversing the fluid flow and engaging the doser locker. The patch pump can be remotely controlled using devices like smartphones.

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Integrated peritoneal dialysis (PD) system that uses closed-loop insulin delivery to manage blood glucose levels during PD treatments. It involves a PD cycler, an insulin pump, a glucose sensor, and a controller. The controller monitors glucose levels during PD, detects high levels, and initiates insulin delivery to maintain glycemic control. This reduces glucose absorption during PD, prevents hypertonicity, and avoids insulin resistance. The closed-loop PD-insulin integration provides better glucose management compared to separate PD and insulin treatments.

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A clinical decision support system for insulin dosing in hospitalized patients with diabetes or fluctuating blood sugar levels. The system calculates personalized subcutaneous insulin regimens based on patient data and glucose measurements. It selects between options like standard programs, meal-by-meal without carb counting, and non-diabetic regimens. The system determines insulin doses using factors like meal timings, previous glucose trends, and adjustment factors. This aims to provide safer and more efficient subcutaneous insulin management compared to paper protocols.

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Integrated glucose monitoring and insulin delivery system for diabetes management. The system has a continuous glucose sensor, an insulin delivery device, and an electronics module with controllers to automate insulin therapy decisions based on glucose levels and other factors. The system can provide features like automated basal insulin delivery, automated bolus insulin delivery with constraints, and integrated glucose sensing and insulin delivery for closed loop control. The controllers iteratively determine insulin therapy instructions in response to evaluations of relationships between internal data and glucose boundaries/constraints.

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Insulin delivery system that uses flash glucose monitoring to personalize insulin delivery for people with diabetes. The system obtains frequent glucose readings from a flash monitor, generates custom insulin profiles based on those readings, and selects the one that best approximates the target glucose level. It then provides the selected profile to the insulin pump to deliver the personalized insulin. This allows for optimizing insulin delivery for each person's glucose variability.

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Redundant glucose sensor and insulin pump system for diabetes management that uses multiple glucose sensors and pumps to ensure continuous monitoring and dosing during warm-up, stabilization, and end-of-life periods of individual sensors. When a sensor is inaccurate, another sensor takes over. This provides backup glucose measurement capability to avoid insulin errors during sensor setup and end-of-life phases. The system can house multiple sensors and pumps together or separately. It can also have features like prefilled pumps, distractors, and applicators for patient comfort. The redundant sensor setup allows reliable diabetes management with less risk of errors due to sensor limitations.

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A blood sugar monitoring and control system that uses a continuous glucose monitor, a warning device, and a control device to automatically inject insulin when glucose levels get too high. The system collects real-time glucose values, determines control status based on target ranges, and responds with emergency measures like insulin injection if needed. It integrates glucose data and patient characteristics to calculate optimal insulin doses. This helps prevent hyperglycemia complications by proactively adjusting insulin when levels get too high.

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Improving accuracy of glucose control in closed-loop insulin delivery systems for diabetes patients by dynamically adjusting the maximum insulin dose based on patient sensitivity to insulin. The sensitivity is calculated using a physiological model of insulin absorption and glucose metabolism. By considering the patient's insulin response and adjusting the maximum insulin dose accordingly, it aims to reduce the risk of hyperglycemia and hypoglycemia.

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Integrated diabetes management system that connects glucose monitoring devices, insulin pens, and display devices to enable easy transfer of glucose and insulin dose data. The system allows visualization of metrics like average glucose, low glucose events, insulin doses, and carb intake. It also provides alerts and reports to optimize insulin dosing based on glucose trends. The aim is to provide a more holistic view of diabetes management by correlating glucose and insulin data.

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Diabetes digital health management system based on big data that uses sensors, data preprocessing, glucose control, and monitoring to provide personalized diabetes care. The system has a sensor module with a subcutaneous glucose sensor that continuously monitors interstitial glucose levels. The sensor data is preprocessed to clean and screen abnormal values. A blood glucose control module calculates insulin requirements using machine learning. An insulin pump delivers insulin based on the calculations. The continuous monitoring ensures real-time glucose levels. An alarm module alerts for insulin infusion and low insulin levels.

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Automated insulin delivery system that can opportunistically obtain missed blood glucose readings to improve accuracy and reduce insulin stacking. The system uses a drug delivery device that receives periodic blood glucose values from a sensor. If a current reading is missed, the device initiates actions to obtain it. This can include querying other devices, generating estimates, or using stored values. Based on the outcome, it calculates the insulin dose using the obtained glucose. This avoids using stale predictions and reduces errors from missing readings.

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Insulin pump control system that reduces the number of devices carried by diabetic patients for better user experience and convenience. The system uses a wearable or smartphone device that integrates continuous glucose monitoring and insulin pump control. It communicates with the implanted glucose sensor and external insulin pump. The device receives user input to control insulin delivery or generates control signals based on glucose levels. This eliminates the need for separate pump and glucose meter devices, reducing burden and improving user experience.

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Integrated system for managing diabetes that combines a continuous glucose sensor, medicament delivery device, and receiver to provide enhanced functionality, convenience, and safety compared to separate devices. The receiver processes sensor data, calculates therapy recommendations, validates them, and outputs therapy instructions. The system can adapt therapy based on individual metabolic patterns, estimate glucose levels, and prevent hypoglycemic conditions. Integration leverages device data for better diabetes management.

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Glucose control systems for managing blood sugar levels that include features like software update techniques to avoid interrupting therapy delivery, gesture-based control of therapy delivery, automatic resumption of therapy after pause, improved alarm management, display of autonomously calculated dosing recommendations, wide area network connectivity, and security features. The systems can have an infusion pump that delivers insulin and/or other glucose control agents. They allow modifying therapy settings like insulin doses and rate, meal doses, correction doses, and glucose targets. Eligibility for modifying settings can be determined based on factors like test results, history, or authorized access levels. The systems can also provide remote viewing of therapy data and reports.

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