Integrated Glucose Monitoring and Insulin Pump Devices

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 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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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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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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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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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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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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A portable device for diabetes management that helps patients optimize their insulin dosage regimen by analyzing their blood glucose levels and adjusting insulin doses. The device has a memory to store the patient's insulin regimen and blood glucose measurements. It also has a display, input interface, and processor to analyze trends and recommend adjustments. The device can communicate with other devices like glucose meters to collect data. It aims to provide personalized insulin dose recommendations based on patient-specific factors.

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Closed-loop insulin infusion systems using orthogonally redundant glucose sensors for improved accuracy and reliability. The system has two glucose sensors, one optical and one electrochemical, to provide orthogonal redundancy. An algorithm combines the sensor data to improve accuracy and reliability. If one sensor fails, the other can provide glucose values. The sensors have features like distributed electrodes and membrane barriers to reduce drift and fouling. The system uses on-demand calibration rather than frequent fingersticks.

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Determining insulin doses for diabetes management using continuous glucose monitoring (CGM) data instead of traditional methods like carbohydrate counting. The method involves calculating insulin bolus requirements based on glucose levels measured by a CGM, without needing to estimate carbohydrate intake. The calculation uses formulas with glucose level, carbohydrate-to-insulin ratio (CIR), and insulin sensitivity factor (ISF). The CIR and ISF values are determined from historical CGM data around meals. This allows automating insulin dose calculation using CGM data without relying on subjective carb estimation.

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Mitigating risk in automated insulin dosing using continuous glucose monitoring (CGM) to prevent over- or under-dosing due to CGM inaccuracy. The method involves disabling automated insulin dosing when CGM accuracy is poor. This is determined by factors like time since the last calibration, maximum glucose deviation, and CGM error prediction. By disabling automated dosing in uncertain conditions, manual user intervention is required to prevent incorrect insulin delivery based on potentially unreliable CGM readings.

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Integrated device for monitoring glucose levels and delivering insulin therapy to diabetes patients. The device has a continuous glucose sensor, an insulin delivery device, and an electronics module with controllers. The controllers iteratively determine insulin therapy instructions based on internally derived data and glucose boundaries/constraints. This allows automated insulin delivery without requiring user input. The controllers can adjust insulin delivery rates based on glucose trends and metabolic response. The integrated system provides convenience, accuracy, and safety compared to separate devices.

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Optimizing basal insulin rates for closed-loop diabetes therapy by using continuous glucose monitoring to adapt the pre-programmed basal rate profile over time. The method involves periodically updating the basal rate profile based on retrospective analysis of glucose data, and optionally adjusting it in real-time in response to sensor data indicating impending hyper or hypoglycemia. This iterative optimization adapts the basal rates to better match the patient's daily insulin needs, improving closed-loop control and reducing the risk of over- or under-insulinization.

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Wearable insulin injection device that automatically injects insulin based on real-time blood glucose levels. The device has a detachable module that attaches to the body and contains a glucose sensor and insulin injector. The sensor measures glucose using Raman spectroscopy and sends instructions to the injector. This allows continuous glucose monitoring and automated insulin delivery without user intervention.

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A clinical decision support system for managing insulin dosing in hospitalized patients. The system calculates personalized insulin doses for subcutaneous administration using a data processing device. It selects a subcutaneous insulin treatment program based on patient blood glucose measurements and information. The program determines recommended doses based on the timing of the glucose measurements. This provides safer and more accurate insulin dosing for tube-fed patients transitioning from IV to subcutaneous insulin. The system also provides features like adjustment factors, half-life calculations, and configurable constants to further refine the dosing.

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