Reducing Sensor Noise in Glucose Monitoring Systems

Calibrating a handheld diabetes managing device to accurately determine interstitial glucose levels from a continuous glucose monitor (CGM) without needing separate blood glucose measurements. The method involves subtracting the time-dependent zero-signal level of the CGM sensor from the continuous sensor signal to compensate for baseline drift. This allows the CGM to provide accurate glucose readings without needing separate calibration using blood glucose measurements.

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Adjusting blood glucose algorithms in a continuous glucose monitoring (CGM) system using motion sensors to provide more accurate glucose readings and alerts based on patient activity levels. The CGM system with motion sensors detects activity like sleeping or exercising. It then adjusts the glucose algorithms to account for the activity-related glucose fluctuations. For example, it recalculates low glucose alerts for sleeping patients to prevent false alarms.

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Improving the reliability of continuous glucose monitoring (CGM) devices, particularly for detecting the presence of acetaminophen medication and correcting the sensor glucose value. The method involves activating a glucose oxidase (GOx) electrode and a non-GOx electrode on the user. They are set to different voltages and signals are compared to detect acetaminophen ingestion. If acetaminophen is detected, the sensor glucose value is adjusted using a predetermined model. This allows for reducing finger sticks for calibration and improving CGM reliability by compensating for medication interference.

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Redundant glucose sensing and disease management system that provides continuous monitoring when one sensor is in warmup, stabilization, or end-of-life periods. Multiple glucose sensors and insulin pumps attach to a patient simultaneously and communicate with each other. If a sensor goes offline, another sensor takes over. This ensures continuous glucose monitoring for closed-loop insulin administration systems even if a sensor fails.

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Real-time detection of declining sensitivity in continuous glucose monitors (CGMs) to improve accuracy and prevent false alarms. The detection involves estimating the probability of sensitivity decline based on current sensor signals, and confirming if a threshold is exceeded using a single blood glucose measurement. This allows accurate detection of declining sensitivity without false positives.

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Blood glucose measuring device that adaptively adjusts calibration intervals to minimize pain and errors. The device compares glucose readings from the sensor versus blood to calculate sensor error. It then determines how long it takes for that error to reach a threshold, using the initial calibration interval. The device then sets the calibration interval based on that time, allowing more frequent calibration if sensor error is high. This allows personalized calibration intervals based on sensor performance.

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Communication protocol for data communication between a continuous glucose monitoring transmitter and receiver. It involves generating a radio frequency (RF) data stream based on the monitored glucose data using a low-power, low-noise logic circuit consisting of finite-state machines and digital circuits. This avoids a high-power ASIC and enables accurate glucose monitoring for diabetes treatment. The transmitter sends glucose data in a synchronized window over RF to the receiver, which identifies the transmitter and displays the glucose levels.

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Monitoring the reliability of a glucose sensor used in closed-loop insulin pumps to determine when to switch to manual or open-loop operation. The reliability is assessed based on trends in the sensor data. If the trends indicate reduced sensitivity, anomalies, drift, or noise, it indicates the sensor is less reliable. A metric representing the reliability is calculated based on these trends. If the metric falls below a threshold, it triggers a switch to manual or open-loop operation to prevent relying on potentially inaccurate sensor readings for closed-loop insulin delivery.

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Implantable glucose sensor that reduces calibration needs compared to traditional glucose sensors. The sensor has two electrodes, one inside the enzymatic part of the membrane and one outside. By measuring both signals, it detects changes in non-glucose electroactive compounds like urea that affect sensor performance. This allows adaptive calibration based on stability instead of frequent calibrations. It also helps prevent false readings by filtering when glucose transport stability falls. The sensor design enables bifunctionality with enzyme and non-enzyme electrodes.

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An improved blood glucose monitoring system for diabetics that combines noninvasive and invasive glucose detection methods to provide more accurate and continuous monitoring. The system has a blood sampler for traditional finger prick testing, a noninvasive glucose sensor, and a monitor that uses the sampler readings to calibrate the noninvasive sensor. This compensates for the noninvasive sensor's accuracy issues and provides continuous monitoring without the need for invasive devices. The monitor also alarms when glucose levels are outside safe ranges. The system can store glucose trends over time for analysis. The noninvasive sensor can be ultrasound or optical to measure tissue thickness or time of flight for glucose estimation.

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