Glucose Monitor-Pump Integration for Automated Insulin Delivery

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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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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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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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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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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Integrated, automated system for glucose monitoring and insulin delivery in diabetes management. The system uses a continuous glucose sensor, a controller, and an insulin pump. The controller receives glucose levels, calculates insulin dosages, and sends commands to the pump. It can automate insulin delivery during sleep, detect calibration errors, suspend basal rates during boluses, prevent hypoglycemia, adjust insulin delivery based on trends, and suggest carb consumption. The system aims to improve usability, control, and safety of closed-loop insulin delivery.

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A continuous glucose monitoring and regulating device that provides minimally invasive, visualized, and intelligent glucose monitoring and regulation for diabetic patients. The device consists of a partially implanted sensor component, a fixed external component, and a mobile terminal. The implanted component has a sensor, insulin channel, and implant device. The fixed component has a transmitter, pump, and adhesive. The mobile terminal connects to analyze, control insulin, and provide warnings. The implanted sensor has a hollow channel for insulin delivery. The fixed component adheres to the skin and connects to the implanted sensor. The mobile terminal communicates wirelessly. The implant device moves the sensor in and out of the skin for calibration.

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Integrated insulin pump control device that replaces separate insulin pump and glucose monitor devices. The device has a communication module to connect to the implanted glucose sensor and the insulin pump. It receives glucose signals from the sensor and user commands to generate pump control signals. This eliminates the need for separate pump and glucose devices, as the integrated device can monitor glucose and control pump infusion. It is wearable or smartphone-based to reduce burden compared to separate devices.

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Integrating user-defined insulin doses into a closed-loop glucose control system that automatically calculates and delivers insulin to regulate blood sugar levels. The system allows users to input specific insulin doses, like meal doses, which the system will attempt to deliver in addition to its autonomous dosing. The user-defined doses are passed to the control algorithm, which takes them into account in subsequent calculations. This allows users to have some control over certain insulin doses while still relying on the system for others.

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A closed-loop system for automated insulin delivery to manage blood sugar levels in people with diabetes. The system uses a subcutaneous glucose sensor to continuously monitor blood sugar levels. A DSP controller processes the sensor signals to extract the glucose value. Based on the glucose level, the controller sends instructions to an insulin pump to deliver the appropriate dose of insulin. This closed-loop feedback system allows automated insulin adjustment without manual input. The sensor, controller, and pump communicate wirelessly for remote monitoring and management.

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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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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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Diabetes management system that combines automatic basal insulin control with manual bolus insulin control to prevent contradictions and improve safety. The system has an insulin pump, a glucose sensor, and a controller. The controller automatically adjusts basal insulin based on MPC algorithm predictions. But it also takes into account manual bolus insulin initiated by the user. This prevents issues like overdosing from conflicting models. The controller receives glucose levels from the sensor and coordinates insulin delivery accordingly.

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Apparatus for regulating blood glucose levels in people with diabetes using two independent controllers to prevent overdosing. The apparatus has a glucose sensor and optionally other sensors to monitor factors like heart rate, temperature, pH, and ketones. It has two pumps with separate cannulas or a shared cannula with two passages. One pump raises glucose, the other lowers it. The controllers calculate insulin/substance amounts based on sensor data. If the calculations differ too much, the apparatus locks and alerts the user to prevent overdosing. The redundant controllers provide backup and error detection.

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Enhancing the accuracy of glucose sensors used in continuous glucose monitoring (CGM) systems for diabetes management by leveraging information from insulin pumps to improve sensor accuracy, particularly during hypoglycemia where CGM accuracy is lowest. The method involves using insulin delivery data along with glucose sensor readings and a filtering algorithm to estimate glucose levels. This estimated glucose is then weighted more heavily than the sensor reading during hypoglycemia to account for the sensor's accuracy issues in that range. The weighting scheme balances sensor and estimated glucose based on factors like insulin delivery and sensor error indices.

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A smart insulin pump system that automatically adjusts insulin delivery based on glucose levels measured by a continuous glucose monitor (CGM). The system includes a CGM sensor, a transceiver, an insulin pump, and a display device. The CGM sensor measures glucose levels and sends data to the transceiver. The transceiver calculates glucose levels and sends them to the display. The display calculates an adjusted insulin delivery rate based on the glucose levels. It sends the adjusted rate to the pump. The pump uses the adjusted rate instead of its current rate. The display also shows the CGM status, transceiver status, and pump status.

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Continuous glucose monitoring (CGM) system for managing a patient's glucose level using a closed-loop algorithm. The system has an analyte sensor, an insulin pump, and sensor electronics. The sensor electronics store predetermined sensor characteristics. A computing device receives sensor data, retrieves the characteristics, and uses them in the closed-loop algorithm to provide insulin delivery instructions to the pump. The characteristics normalize glucose data, prevent overexertion on difficult periods, detect intervention failures, and adjust insulin dosing based on lag and uncertainty.

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Closed loop insulin delivery system using redundant glucose sensors to improve reliability and safety. The system has two glucose sensors in different locations. It predicts the glucose value from one sensor using the other sensor as input. By comparing the predicted to the actual reading, it detects sensor failures. It also determines which sensor has lower error and uses that one for infusion control. This allows using two sensors with different characteristics to corroborate and validate each other's readings.

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Insulin administration system using continuous glucose monitoring to optimize insulin dosing based on individual patient response characteristics. The system involves continuously measuring blood glucose, calculating optimal insulin doses based on patient-specific response functions, and transmitting the doses in real-time to an insulin pump. The patient response functions are updated in real-time as glucose readings are received. This allows personalized, real-time insulin dosing that accounts for individual glucose response variability.

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Insulin delivery systems that personalize insulin delivery for people with diabetes based on glucose monitoring data. The systems use algorithms to adjust basal insulin rates and deliver microboluses to approximate target blood glucose levels. They also have constraints to prevent excessive insulin delivery. If the system calculates an insulin dose above a threshold, it triggers an alarm to the user. This helps avoid accidental overdosing from personalization algorithms.

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Closed loop control of an artificial pancreas that provides improved glucose regulation for diabetes patients using an insulin pump and continuous glucose monitor. The control algorithm uses a model predictive controller (MPC) to optimize insulin delivery based on glucose measurements. It avoids oscillations by using a zone control strategy where the goal is to keep glucose within a range instead of a single set point. The MPC also adds states for insulin and food memory to account for delayed effects. The aggressiveness of the controller response is adjusted based on a gain parameter. This provides more accurate and stable glucose control compared to traditional PID controllers.

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Diabetic patient management system with real-time glucose and beta-hydroxybutyrate monitoring, insulin injection control, and transmission to a hospital server. The system uses an implantable sensor to measure glucose and beta-hydroxybutyrate in the body. An implantable insulin pump with an electroosmotic pump provides precise insulin delivery. The sensor measures glucose and beta-hydroxybutyrate using redox reactions with electrodes surrounded by insulation. An external device connects to the implant for insulin adjustment and displays glucose/beta-hydroxybutyrate levels. The external device also transmits the levels to a hospital server for monitoring.

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Advanced medical system for managing health conditions like diabetes that uses sensors, actuators, logic circuits, and communication schemes to monitor and treat patients. The system includes devices like contact lenses, drones, and wearables with embedded sensors and actuators. It also has features like energy management, cryptography, social mechanisms, and personalized sensors. The system can involve devices like glucose sensors, insulin pumps, CGM, FGM, spectrometers, etc.

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Insulin administration system using continuous glucose monitoring that adapts insulin dosing in real time based on the patient's unique glucose response characteristics. The system continuously measures glucose levels and calculates the optimal insulin dose in real time using a patient-specific glucose response function. This function is updated over time as the patient's response is monitored. The calculated insulin dose is transmitted to the insulin injector for administration. By customizing insulin dosing based on each patient's unique glucose response, it aims to provide more effective and personalized insulin therapy.

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A diabetes management device that can automatically adjust insulin and glucose delivery based on real-time blood glucose levels. The device has an insulin and glucose generator that can deliver either insulin or glucose through a subcutaneous line based on the current blood glucose level. An external blood glucose sensor wirelessly sends the level to the generator's control unit. The unit then calculates the needed partial dose based on the setpoint and delivers it via the line. This provides automated glucose correction when needed to prevent hypoglycemia.

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A diabetes management system that provides improved glucose control by integrating an infusion pump, continuous glucose monitor, and intermittent glucose meter. The system uses a microcontroller to coordinate the devices and calculate insulin doses based on both continuous and intermittent glucose readings. It also monitors compliance with recommended bolus doses and adjusts future recommendations based on actual doses. The system aims to provide more accurate and personalized insulin delivery compared to just using continuous monitoring.

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A closed-loop insulin delivery system that aims to mimic the body's natural insulin response to glucose levels. The system uses a controller to adjust insulin infusion rates based on feedback from a glucose sensor. The controller gains are calculated from clinical data on insulin response curves. Fuzzy logic is used to select between multiple sets of gains. State variable feedback is incorporated to make insulin appear faster than it actually is. The system also adjusts controller aggressiveness based on sensor integrity to prevent overreliance on potentially faulty sensors.

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