Advanced Wearable Glucose Sensors

Improved method of monitoring blood sugar using a wearable device that switches blood sugar measurement cycles based on context, initializes blood sugar tracking after events, and calculates features to judge health. The method involves measuring blood sugar in a first cycle, storing the level at a timepoint, detecting events, switching to a different cycle, measuring after events, and calculating features using both levels. This allows more accurate monitoring based on user context.

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Glucose level deviation detection for continuous glucose monitoring devices to improve user understanding and management of their glucose levels. The technique analyzes glucose measurements over time to detect deviations from past levels. It generates aggregated metrics for a user's glucose levels during specific time periods, like a day or multiple days. Deviations from expected levels are identified by comparing the aggregated metrics to previous periods. Users are alerted to deviations to help them recognize unusual patterns and take action.

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Instantaneous dynamic blood glucose monitor with an alarm function to improve the timeliness of glucose level alerts. The monitor has a sensor with a detection module to collect blood glucose data and a communication module to send it to a terminal. The terminal has a storage module, processing module, and separate alarm module. This allows the sensor to continuously send real-time glucose readings to the terminal which can process and analyze them. If a critical glucose level is detected, the alarm module can immediately trigger an alert without relying on the user to check the monitor.

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Continuous glucose monitoring (CGM) system with embedded SIM (eSIM) for real-time glucose monitoring, automatic emergency notifications, global connectivity, and improved data security. The CGM device integrates an eSIM for automatic network provisioning and cellular connectivity, allowing direct transmission of real-time glucose data to healthcare providers, contacts, and emergency services. This provides faster, more reliable data transfer compared to relying on separate smartphones. The eSIM also enables features like GPS tracking of the CGM device and user location.

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A system and method for predicting blood glucose levels using variables measured by an activity bracelet, without needing a glucose meter. The system leverages techniques like wavelet transforms, deep learning, and fuzzy logic to estimate interstitial glucose levels from non-invasive variables like heart rate, physical activity, and ECG. It generates alerts for dangerous hypoglycemic or hyperglycemic events based on the predicted glucose values. The system aims to provide convenient, accurate, and continuous glucose monitoring using a wearable device instead of finger pricking.

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Extending the life of adhesive patches on wearable medical devices like continuous glucose monitors (CGMs) to prevent premature detachment due to skin perspiration, water exposure, and other factors. The method involves applying a thin film of a moisture-absorbing material over the original adhesive patch without covering the sensor itself. This additional layer absorbs moisture and prevents it from deteriorating the adhesive, extending the patch's life. The moisture-absorbing film is thin and transparent, so it doesn't affect the sensor's performance or appearance.

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A wearable medical device that can adjust the frequency of glucose measurements from a continuous glucose monitor (CGM) based on the user's glucose trend. The device processes the CGM data to determine the rate of change in glucose levels over time. If the rate indicates a rapid change, the device instructs the CGM to provide more frequent glucose readings. This allows faster detection of extreme glucose events to enable timely intervention. The device can also suspend insulin delivery based on the CGM data.

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In vivo medical sensors that can be implanted under the skin to continuously monitor analytes like glucose without requiring regular blood samples. The sensors are small, wireless devices that are positioned inside the body and communicate with external devices like smartphones using RFID. They can be left in place for weeks to months to provide real-time glucose data without the need for frequent fingerprick tests. The sensors are fully integrated with electronics and can store and log the monitored data. The sensors are also designed to be self-powered and can convert energy from the body fluids to operate. This eliminates the need for separate batteries. The sensors can be implanted using specialized devices that retain the sensor electronics until insertion. The implantable sensors can also be recharged using magnetic induction through the skin. The sensors can be customized to measure other analytes besides glucose.

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Continuous glucose monitoring (CGM) system that enables accurate, stable, and uninterrupted glucose monitoring without the need for frequent fingerstick calibrations. The system involves overlapping sensor placements during sensor swaps. After calibrating the first sensor, a second sensor is placed while the first is still in the body. The second sensor's calibration is based on data from the first sensor, eliminating the need for fingerstick calibrations. This allows continuous calibration and monitoring without gaps as sensors are replaced.

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Real-time blood glucose monitoring system that provides accurate, trended, and real-time blood glucose data to help users make better diabetes management decisions. The system uses a noninvasive sensor to continuously monitor blood glucose levels. It analyzes the data in real time to detect anomalies like rapid changes or trends outside normal ranges. This allows quick identification of potential issues before they become critical. The system provides alerts and indicators in real time to alert users when blood glucose levels are outside normal ranges or trends. This helps users catch potential issues early before they become critical.

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Method for transmitting and receiving biometric information between a continuous blood glucose monitoring sensor and a communication terminal. The method involves generating transmission packets with a sequential generation identifier when the sensor measures biometric data like glucose. The packets are transmitted to the terminal which checks the identifiers to find and request any missing packets. This allows reliable reception even if there are disconnections.

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Blood glucose monitoring device that adapts sampling intervals based on user events to more accurately determine blood glucose levels. The device detects glucose levels using a first interval. When events like exercise, food intake, sleep, or hormone changes occur, it reduces the sampling interval to better track glucose dynamics during those periods. This prevents false readings when glucose levels are rapidly changing.

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Monitoring glucose levels in a patient and displaying the data differently on a wearable device versus a patient device to provide more convenient and actionable notifications. The system determines the patient's glucose level and creates graphical representations for display on their primary device (like a smartphone) and a wearable (like a smartwatch). The representations are customized based on the target range, with different features to indicate when glucose is out of range. This allows the wearable to provide more attention-grabbing alerts compared to the patient device's display.

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Wearable blood glucose monitoring device that allows real-time tracking and viewing of blood sugar levels. The device has a main board with components like a processor, memory, display, and battery. The processor connects to a wearable sensor via I2C to measure blood sugar. This allows users to check their blood sugar without needing a separate meter. The device can be worn like a watch and provides instant feedback on blood sugar levels.

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Predicting timing of postprandial hyperglycemic spikes in diabetic patients using a wearable device that monitors blood glucose equivalents. The device predicts spike timings based on past variations and meal times, then notifies optimal times for blood sampling to monitor actual glucose levels during spikes. This allows targeted blood testing to catch the spikes and help manage diabetes.

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Continuous, minimally invasive glucose monitoring system for diabetics that avoids needing to prick the skin to take blood samples. The system uses a body-attachable sensor module that can be inserted into the skin using an applicator. When attached to the body, the user presses a button on the applicator to initiate the sensor's operation. This allows precise insertion depth and timing. The sensor has a PCB, sensor probe, and pressure module.

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Continuous glucose monitoring system with improved usability that allows users to easily attach the sensor to their skin. The system has an applicator that protrudes the sensor needle into the body when pressed. This eliminates the need for users to manually insert the sensor. After insertion, the applicator also extracts the needle.

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Flexible, adhesive patch for long-term monitoring of bodily fluids like glucose. The patch has a thin, flexible circuit board with sensors and electronics, protected by layers. It adheres to the skin using a stronger adhesive than the removable applicator. The patch can be applied using an insertion tool. This allows inserting sensors into tissue. The tool then removes the patch on the skin. The tool can also press contacts onto the circuit. The patch can transmit data wirelessly. The thin, flexible design allows comfortable long-term wear. The patch can be manufactured using roll-to-roll printing techniques.

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A body attachable unit for continuous glucose monitoring that can be inserted and attached to the skin using an applicator. The attachable unit contains the glucose sensor, electronics, and communication components. The user inserts the sensor into their skin through the applicator. After attachment, the user manually makes contact between the sensor and PCB to initiate operation. This allows precise sensor insertion timing, avoids contamination, and improves accuracy compared to pre-assembled sensors.

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Monitoring and treating health conditions using wearable devices and interoperable data standards. The system involves using wearable sensors to continuously monitor biomarkers like glucose, heart rate, etc. The sensors communicate over wireless networks to a central database. The database normalizes and stores the data using common formats. This allows interoperability between devices from different manufacturers. It also enables sharing of normalized data with other systems like emergency vehicles or hospitals. The normalized data can be analyzed to detect medical issues like stroke or glucose extremes. This allows proactive treatment before symptoms appear.

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A wearable patch for monitoring blood glucose levels of diabetes patients using machine learning. The patch has sensors like PPG and NIR to detect blood circulation and glucose levels. The sensor data is analyzed by a microcontroller and then sent to a cloud server for further analysis using machine learning. If the glucose level gets abnormal, an alarm on the patch notifies the patient to take action. The patch aims to provide non-invasive, remote, and continuous glucose monitoring without finger pricks.

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A portable non-invasive device for estimating blood glucose levels without needing blood samples. The device uses near-infrared (NIR) spectroscopy to measure glucose concentration through the skin. It emits light at specific wavelengths, including one that maximally absorbs glucose. The device captures the transmitted light and sends it wirelessly to a monitoring unit that estimates glucose based on the NIR spectrum. The device provides customized glucose estimation models tailored to the user and measurement context. The device also compensates for detector saturation and normalizes against reference wavelengths and pulsating components to improve accuracy.

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Discreetly displaying blood glucose information on a smartwatch with limited screen size. The smartwatch receives alerts about a host patient's blood glucose level from a glucose sensor. When the user requests a glance view, the smartwatch presents a compact display with just the glucose state. This allows quick, discreet checking of glucose levels without cluttering the small screen. It also anonymizes the patient identity.

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Monitoring blood glucose levels without direct measurement using physiological sensors in wearables or implanted medical devices. The sensors detect indicators correlated to glucose levels but different from actual glucose readings. An algorithm analyzes the sensor data to determine a glucose index indicating abnormal glucose levels. This provides early warning of hypo/hyperglycemia without frequent finger prick tests. The glucose index triggers additional testing or therapy adjustment.

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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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An implantable glucose monitoring device for diabetics that eliminates the need for frequent finger pricking and external glucose meters. The device is implanted under the skin and continuously measures glucose levels using a biosensor. The implant contains biocompatible materials like titanium or zirconia to avoid rejection. The biosensor uses carbon nanotubes to provide high sensitivity and speed in contact with glucose oxidase cells. The implant communicates the glucose levels wirelessly to external devices for monitoring and management. The goal is to provide a more convenient and less invasive alternative to traditional finger pricking and external glucose meters for diabetics.

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Flexible body-mountable devices with sensors that can be worn on the skin to continuously monitor analytes like glucose in interstitial fluid. The devices have flexible substrates that adhere to the skin and extend probes beneath it to access the fluid. The probes contain sensors to measure analyte concentrations. The devices also have electronics, batteries, and antennas all on a flexible substrate. This allows long-term wearability and wireless communication. The flexible form factor reduces discomfort and enables unobtrusive monitoring.

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Monitoring glycemic levels using continuous glucose monitoring (CGM) devices while also tracking characteristics related to events. The method involves forming sets of event-specific characteristics for CGM monitoring associated with different events. The sets differ for each event. This allows tailoring CGM parameters based on the event to improve monitoring accuracy. The sets can be used in real-time or retrospectively to optimize CGM settings for future similar events.

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In vivo glucose monitoring system that provides warnings of impending hypoglycemic conditions in real time. The system has a wearable sensor with a glucose sensor and electronics implanted under the skin. The sensor continuously monitors glucose levels and stores them. It checks for hypoglycemic trends by analyzing subsets of stored data. If hypoglycemia is confirmed, it wirelessly transmits a warning to a remote device using a separate communication module. This allows autonomous detection and alerts without user requests. The main communication uses RFID tags for periodic glucose readouts.

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A non-invasive system for monitoring blood glucose levels without requiring finger pricks. The system uses sensors to detect changes in heart rate pulse, muscle response, skin conductance, and sweat volume. These signals are converted to digital format and wirelessly transmitted to a processing module. The module analyzes the signals to provide real-time and trending blood glucose estimates. The system also has an alarm and display to alert users of potential high or low glucose levels.

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Reducing errors in continuous glucose monitoring (CGM) devices by using a second sensor to measure blood flow and heart rate, and leveraging that data to better predict blood glucose levels. The device measures glucose in interstitial fluid using a dedicated glucose sensor. It also uses a second sensor on the device that contacts the skin to measure blood flow and heart rate. By analyzing signals from this sensor, the device can determine the time delay for glucose diffusion between blood and interstitial fluid based on factors like blood flow. This allows more accurate blood glucose prediction using the interstitial glucose measurement and the determined diffusion time.

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In-vivo glucose monitoring system with a sensor implanted under the skin that can operate for extended periods without calibration. The sensor is connected to an on-body electronic device that processes the glucose signals. Data is stored and retrieved internally instead of calibration. Analyte levels are accurately converted without external references. The implanted sensor can communicate wirelessly to a separate display device for readings. The system eliminates the need for external calibration by using internal algorithms to accurately convert sensor signals into glucose levels.

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Single-use disposable sensor device for continuous glucose monitoring that integrates the sensor, transmitter, and insertion tool into a simple, all-in-one device. The device has a flexible case that adheres to the skin and contains the electronics, battery, and sensors. It eliminates mismatching of separate sensors and transmitters. The device also has visual indicators to show glucose levels and trends. This simplified, integrated design aims to make continuous glucose monitoring easier and more accessible for diabetic patients.

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Wearable blood glucose monitoring system that provides reliable, continuous glucose monitoring without the need for blood samples. The system uses a wearable device with a sweat glucose sensor, body temperature sensor, display, and communication components. The sensor adheres to the skin and transmits sweat glucose measurements to the wearable device. The device displays glucose and body temperature, sends data to a mobile app, and performs predictive modeling to anticipate blood glucose levels. This allows proactive alerts and interventions before blood glucose spikes or dips. The wearable also has a metformin injection component triggered by high glucose levels.

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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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Wearable device for predicting blood glucose levels without blood draws. The device is a ring that attaches to the skin with an adhesive. It has a sweat glucose sensor inside the ring. The sensor monitors sweat glucose levels and transmits the data to a connected mobile device. The mobile device calculates predicted blood glucose levels based on the sweat glucose data. This allows continuous, non-invasive glucose monitoring without needing blood draws.

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A medical sensor assembly for long-term wear on the skin to continuously monitor physiological parameters like glucose levels. The assembly has a flexible adhesive patch attached to the skin and a sensor inserted into it. The sensor has a measuring part that goes into the skin and a contact part to connect to a monitoring device. The patch has a flap that folds up to provide an opening for the sensor to pass through. This allows the sensor to be inserted into the skin without needing a separate entry point. The flap is permanently attached to the sensor to keep it in place.

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Handheld diabetes manager that optimizes power consumption while collecting and displaying continuous glucose monitoring (CGM) data. The device has separate processors for CGM data collection and user interface. The CGM processor periodically receives glucose measurements from a CGM device and stores them. It operates at a low power rate. The user interface processor receives the stored measurements and displays them. It operates at a higher power rate. This allows the CGM processor to asynchronously collect data without draining the battery while the user interface only wakes up when needed. This reduces power consumption compared to having one processor handle both tasks.

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A blood glucose monitoring system that displays the blood glucose level on a portable device like a smartphone or digital photo frame. It involves a separate blood glucose sensor worn on the body to measure the glucose level. The sensor wirelessly sends the glucose readings to the portable device which then displays and records the glucose levels. This allows real-time monitoring of blood glucose levels using a device that people already carry and check frequently.

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Continuous real-time monitoring of blood glucose levels in the body while also automatically detecting the user's activity state. The system uses implantable blood glucose sensors and motion sensors to continuously monitor blood glucose levels in real-time. It can also detect when the user is active or inactive. This allows analyzing blood glucose changes during different activities. It provides more complete blood glucose data for disease diagnosis and treatment. The system also alerts when glucose levels become dangerous during inactive periods.

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