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130
resultados
Última actualización
29/03/2026 [06:59:00]
Resumen de: WO2026064554A1
Provided herein are methods of treating various eye disorders, including, for example, wet age-related macular degeneration (wAMD) or diabetic retinopathy (DR), using an anti-VEGF therapy, such as an anti-VEGF antibody conjugate.
Resumen de: WO2025046158A1
The invention relates to a method for controlling glucose in a flexible-structure bihormonal artificial pancreas that manages optional meal and/or exercise alerts by means of coordinated control actions, comprising: measuring a plasma glucose signal; calculating an incremental plasma glucose measurement (y); defining a model for incremental plasma glucose; defining a carbohydrate ingestion as dependent on a carbohydrate content estimated by the patient; defining an expected postprandial incremental plasma glucose y*(s) according to an insulin bolus that has been administered; defining a corrected incremental plasma glucose y̅(s), a corrected insulin infusion ū(s) and a corrected carbohydrate ingestion d̅(s); defining a virtual control action μ(s), divided between regulatory actions μ r and counterregulatory actions μ cr ; and calculating the control actions using a 2-DOF feedback controller with a prefilter having a nominal value F r (s).
Resumen de: WO2026062700A1
The present disclosure relates to a system and method to predict the post- prandial glucose response in the individuals type 2 diabetes mellitus (T2DM) in India by taking sample of patients with T2DM from various locations across India and fitting them with continuous glucose monitors (CGM) and calculating the postprandial glucose response based on the different meal intakes by the patients. The present disclosure further relates to the utilization of k-means clustering models to classify food types based on nutritional information and classification of patients. The present disclosure also relates to utilizing XGBoost to predict postprandial blood glucose responses based on patient phenotypes and food categories and providing personalized recommendations taking into account meal type, preferences, and regional influences which would allow patients with T2DM to eat and drink foods to maintain their blood sugar within prescribed limits and prevent disease progression.
Resumen de: US20260088150A1
Techniques disclosed herein relate to operating a fluid delivery device in a personalized manner based at least in part on historical data of a patient. In some embodiments, the techniques involve obtaining historical meal data for the patient associated with historical meal events for the patient; determining a meal content based at least in part on the historical meal data; obtaining nutritional information associated with the meal content and historical meal events for the patient; determining, by a control system, a dosage of insulin based at least in part on the nutritional information and the historical meal events; and operating, by the control system, an actuation arrangement of the infusion device to deliver the dosage of the insulin to the patient.
Resumen de: US20260088171A1
An ambulatory glucose profile (AGP) intelligent interpretation and insulin adjustment method based on an expert system includes: establishing a knowledge base in an inference mechanism; constructing an interpretation and decision support expert system with a simplified expert system architecture based on the knowledge base; constructing a patient problem analysis tree in three dimensions of hypoglycemia, blood glucose fluctuation, and hyperglycemia of patients; expanding each rule with expert AGP interpretation and empirical data; constructing a basal insulin dosage adjustment rule and a mealtime insulin dosage adjustment rule based on an interval type-2 fuzzy expert system; and adjusting a node of the patient problem analysis tree based on the interpretation and decision support expert system and a group of the patient, and providing a decision suggestion in combination with the basal insulin dosage adjustment rule and the mealtime insulin dosage adjustment rule.
Resumen de: US20260083358A1
In implementations of systems for determining a similarity of sequences of glucose values, a computing device implements a similarity system to receive input data describing a sequence of user glucose values measured by a continuous glucose monitoring (CGM) system. The similarity system computes similarity scores for a plurality of sequences of glucose values by comparing each glucose values included in the sequence of user glucose values with ever glucose value included in each sequence of the plurality of sequences. A particular sequence of glucose values that is associated with a highest similarity score is identified. The similarity system determines an externality associated with the particular sequence. The similarity system generates an indication of the externality for display in a user interface.
Resumen de: US20260083363A1
This document describes medical systems for detecting biological analytes. For example, this document describes sensors for the continuous monitoring of biological analytes, such as glucose and/or lactate, in aqueous solutions and body fluids (e.g., blood) based on a readout of fluorescence or luminescence signals.WO
Resumen de: US20260083910A1
Methods of insulin delivery may include selecting a basal insulin delivery rate responsive to a projected blood glucose level that approximates a target blood glucose level. Methods of insulin delivery may further include generating insulin delivery instructions for an insulin delivery device, the insulin delivery instructions corresponding to the basal insulin delivery rate and for a variable time duration relative to an intended time duration.
Resumen de: US20260083909A1
A reinforcement learning process with self attention is used for insulin dosing decisions in an automated medical system. The State-Action-Reward-Next State (SARS) sequence is used. The state represents the current condition, including recent continuous glucose monitoring readings, insulin doses, meal information, and potentially other relevant factors like time of day or physical activity levels. Based on this state, the agent takes an action by deciding on an insulin dose. It then receives a reward, a numerical value quantifying the quality of the action, based on resulting glucose levels and their proximity to the target range. This leads to a new state, and the process repeats. Through this iterative process, the algorithm updates the neural network weights, allowing the agent to learn which actions lead to better outcomes in different states.
Resumen de: AU2024351716A1
A method of non-invasive determination of the blood glucose concentration in the patient's tissue based on a radio noise signal received using an antenna brought close to the patient's skin according to the invention involves use of the radio noise signal is measured using a passive radiometer and additionally the method includes the following steps: a step of obtaining transformation coefficients, a step of measuring the temperature of the tissue surface, a step of measuring the temperatures of the active elements of the receiving chain of the radiometer, a step of measuring the currents consumed by the active elements of the receiving chain of the radiometer, a step of measuring the power of the radio noise signal originating from the tissue, and a step of determining the blood glucose concentration based on the aforementioned values. The invention also relates to a computer program, a radiometer, and a device for determining glucose concentration.
Resumen de: US20260083911A1
Enclosed herein are methods and systems for establishing communication protocols between wireless devices in infusion pump systems. Infusion pump systems can include a number of components capable of wireless communication with one or more other components including an infusion pump, a continuous glucose monitoring (CGM) system, and a smartphone or other multi-purpose consumer electronic device (i.e., remote control device). Communications among these devices can be coordinated to ensure reliable and consistent transmission of medical data.
Resumen de: US20260083912A1
Exemplary embodiments account for differing needs of a user over the menstrual cycle of the user to better control the blood glucose concentration of the user. The exemplary embodiments may be realized in control systems for medicament delivery devices that deliver medicaments, such as medicaments that regulate blood glucose concentration levels. Examples of such medicaments that regulate blood glucose concentration levels include insulin, glucagon, and glucagon peptide-1 (GLP-1) agonists. The exemplary embodiments are able to better tailor the dosages of the medicament delivered to the user with the medicament delivery device to reduce the risk of hyperglycemia and hypoglycemia and help reduce blood glucose concentration excursions.
Resumen de: US20260083357A1
Systems and methods for determining a glucose value for a user are disclosed herein. The method includes receiving a plurality of data inputs associated with biometric data of the user, the plurality of data inputs including at least one data input representative of a past estimated glucose value of the user and processing the plurality of data inputs with a multi-headed temporal convolutional neural network to generate a blood glucose value for the user. The method also includes providing a notification to the user based at least in part on the blood glucose value.
Resumen de: US20260089162A1
Systems, devices, and methods are disclosed for wireless communication of analyte data. In embodiments, a method of using a diabetes management partner interface to configure an analyte sensor system for wireless communication with a plurality of partner devices is provided. The method includes the analyte sensor system receiving authorization to provide one of the partner devices with access to a set of configuration parameters via the diabetes management partner interface. The set of configuration parameters is stored in a memory of the analyte sensor system. The method also includes, responsive to input received from the one partner device via the diabetes management partner interface, the analyte sensor system setting or causing a modification to the set of configuration parameters, according to a system requirement of the one partner device.
Resumen de: EP4715836A1
A meal monitoring apparatus according to an embodiment of the present invention includes a data receiving unit configured to receive measurement data of parameters related to an ear of a target object and blood glucose data of the target object; a first estimated time calculating unit configured to calculate a first estimated time estimated as a food intake activity time of the target object based on the measurement data; a second estimated time calculating unit configured to calculate a second estimated time estimated as a glucose absorption time of the target object based on the blood glucose data; and a meal time calculating unit configured to calculate a meal time of the target object based on the first estimated time and the second estimated time.
Resumen de: EP4715554A2
One or more embodiments of the present disclosure may include an insulin delivery system that includes an insulin delivery device, a user interface that includes multiple user-selectable icons or buttons each representing different meal characteristics, memory to store one or more user-specific dosage parameter, and a processor in communication with the memory and adapted to receive blood glucose data. The processor may also be adapted to determine initial meal characteristics associated with each of the user-selectable icons or buttons based on at least one of the user-specific dosage parameters. The processor may also be adapted to update the meal characteristics associated with each of the user-selectable icons or buttons based upon the blood glucose data.
Resumen de: EP4671882A2
The present disclosure relates to a system for closed loop control of glycemia. In one arrangement, the system comprises: an insulin delivery device; a user interface for inputting patient data, the patient data including a basal insulin profile, an insulin-to-carbohydrate ratio, and meal data; and a controller in communication with the user interface and the insulin delivery device and configured to receive glucose data. The controller is further configured to execute: estimating an amount of active insulin in the patient, the active insulin not including the basal insulin profile, determining a meal carbohydrate value from the meal data, estimating a physiological glucose for the patient and a rate of change of physiological glucose based in part on the glucose data, determining an attenuation factor based on the physiological glucose and the rate of change of the physiological glucose, determining a meal bolus based on meal data, the insulin-to-carbohydrate ratio, and the determined attenuation factor, modifying the determined meal bolus based on the estimated amount of active insulin in the patient, and transmitting a request to deliver the modified meal bolus to the insulin delivery device.
Resumen de: US20260076591A1
Systems, devices and methods are provided for incorporating a medication delivery device into an integrated management system. The integrated management system may be an integrated diabetes management system and may include a glucose monitor, a connected insulin pen, and software. The integrated management system may produce a plurality of reports that may include data related to analyte levels (e.g., glucose levels) and medication delivered (e.g., insulin delivered). The integrated system may also include a mode in which certain types of data are no longer shared and/or stored if the user is not signed into an account. The types of data shared and/or stored when the user is not signed into an account may differ from the types of data shared and/or stored when the user is signed into an account.
Resumen de: WO2026060397A2
An analyte sensor system may include an analyte sensor configured to generate a raw sensor signal associated with an analyte concentration of a host. Sensor electronics may be configured to generate estimated analyte values from the raw sensor signal, determine a rate of change for the estimated analyte values or the raw signal, determine a working electrode temperature, and determine an elapsed time since sensor insertion. The sensor electronics may improve sensor performance by determining a prediction horizon as a function of at least one of the elapsed time and the working electrode temperature, determining a time-lag- compensated estimated analyte value for one of the estimated analyte values as a function of the determined prediction horizon and the rate-of-change, and adjusting estimated analyte values by applying a correction that is a function of the estimated analyte values.
Resumen de: AU2026201602A1
Systems and methods disclosed provide ways for Health Care Professionals (HCPs) to be involved in initial patient system set up so that the data received is truly transformative, such that the patient not just understands what all the various numbers mean but also how the data can be used. For example, in one implementation, a CGM device is configured for use by a HCP, and includes a housing and a circuit configured to receive a signal from a transmitter coupled to an indwelling glucose sensor. A calibration module converts the received signal into clinical units. A user interface is provided that is configured to display a measured glucose concentration in the clinical units. The user interface is further configured to receive input data about a patient level, where the input data about the patient level causes the device to operate in a mode appropriate to the patient level. ar a r
Resumen de: US20260077116A1
An infusion system is disclosed comprising: a device for delivering insulin to a user, the device including a reservoir and a micropump for pumping the insulin from the reservoir into tissue of a user; and a cartridge for securing a cartridge insert that includes (a) an infusion needle configured to infuse the insulin and introduce a CGM sensor into the user or (b) an introducer needle for introducing an infusion catheter and the CGM sensor into the user, the cartridge configured to move from (1) a first position, wherein the infusion needle or an introducer needle is above the tissue of the user to (2) an second position, wherein the infusion needle or the introducer needle is in a deployed position inserted into tissue of the user, wherein the cartridge includes a locking mechanism to lock the cartridge insert into the cartridge.
Resumen de: US20260076590A1
The present disclosure relates to a continuous blood sugar measuring sensor member, wherein: since an electrode layer formed on one surface of a substrate is connected to a sensor contact point part on the other surface of the substrate through a via hole and thus two electrode layers may be formed on different opposite surfaces without having to be formed on the same surface of the substrate, the width of the substrate may be further reduced and an overall minimized and simplified structure may be ensured; since an electrode connection layer formed at the via hole is not formed in a shape of filling the via hole but is formed only on the inner circumferential surface, a filling defect occurring in a process of filling the via hole and a fault in electrical connection according thereto may be prevented and thus a more stable structure may be ensured; and since a plurality of via holes are formed, despite damage to or the occurrence of a defect in an electrode connection layer formed at one of the via holes, electrical connection is maintained by electrode connection layers formed at the remaining via holes, and thus more stable performance may be maintained.
Resumen de: US20260076628A1
A system is provided comprising external device(s), tracking device(s) configured to generate blood glucose level data for tracked individual(s), and an alert device for management of alerts generated at the external device(s). The alert device comprises processor(s) and memory device(s). The memory device(s) comprise computer readable code that, when executed by the processor(s), causes the processor(s) to receive input data comprising blood glucose level data received from the tracking device(s), to determine an alert setting for an alert to be generated at an external device of the external device(s) based on the input data, and to generate a signal that causes the alert to be generated at the external device. The alert setting includes an identification of the external device where the alert is to be generated, an alert magnitude, and/or the alert type, with the alert type including an audible alert, a haptic alert, and/or a visual alert.
Resumen de: WO2026059033A1
Disclosed, according to various embodiments of the present invention, is a method for adjusting an insulin injection amount based on predicted blood glucose. The method may comprise the steps of: predicting a future blood glucose value on the basis of the current blood glucose value and an insulin injection history; determining a future blood glucose state on the basis of the future blood glucose value and a predefined correction factor; and adjusting an insulin injection amount so as to correspond to the future blood glucose state.
Nº publicación: EP4710855A2 18/03/2026
Solicitante:
MEDTRONIC MINIMED INC [US]
Medtronic MiniMed, Inc
Resumen de: EP4710855A2
A method for optional external calibration of a calibration-free glucose sensor uses values of measured working electrode current (Isig) and EIS data to calculate a final sensor glucose (SG) value. Counter electrode voltage (Ventr) may also be used as an input. Raw Isig and Vcntr values may be preprocessed, and low-pass filtering, averaging, and/or feature generation may be applied. SG values may be generated using one or more models for predicting SG calculations. Complex redundancy may be employed to take operational advantage of disparate characteristics of two or more dissimilar, or non-identical, sensors, including, e.g., characteristics relating to hydration, stabilization, and durability of such sensors. Fusion algorithms, EIS, and advanced Application Specific Integrated Circuits (ASICs) may be used to implement use of such redundant glucose sensors, devices, and sensor systems in such a way as to bridge the gaps between fast start-up, sensor longevity, and accuracy of calibration-free algorithms.
BOPI
Sede Electrónica
