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154
resultados
Última actualización
27/09/2024 [07:41:00]
Resultados 25 a 50 de 154
Resumen de: US2024304327A1
It is disclosed a blood glucose prediction system and method. According to one example embodiment, the blood glucose prediction system may include a learning modeling unit for learning a blood glucose variability inference model to infer a correlation between a physical indicator and blood glucose variability, and learning a blood glucose inference model to infer a correlation between sugar of saliva and blood glucose; a target information acquiring unit for acquiring a physical indicator and sugar of saliva of a target; a blood glucose variability estimating unit for estimating blood glucose variability of the target by using the blood glucose variability inference model with the physical indicator of the target as an input parameter; and a blood glucose predicting unit for predicting blood glucose of the target by using the blood glucose inference model with the sugar of the saliva and the estimated blood glucose variability of the target as an input parameter.
Resumen de: US2024304319A1
Disclosed are systems and methods for providing automated or semi-automated technical support for patients using medical devices, such as continuous glucose monitoring systems. Disclosed embodiments of automated tech support system include collection and storage of copies of streams of medical device data on multiple servers, analysis and comparison of data streams, remote tech support initiation and usage of the automated tech support system for providing improved products and services by storing and analyzing historical tech support data.
Resumen de: US2024304336A1
Methods, systems and circuits evaluate a subject's risk of developing type 2 diabetes using defined mathematical models of short term risk (STR) and longer term risk of progression. The evaluations can stratify risk for patients having the same glucose measurement, particularly those with intermediate or low (normal) fasting plasma glucose (FPG) values. The STR or IR (insulin resistance) model(s) may include an inflammatory biomarker such as an NMR derived measurements of GlycA and a plurality of selected lipoprotein components of at least one biosample of the subject. Embodiments of the invention also provide methods, systems and circuits that generate STR scores as a marker of beta-cell dysfunction or impairment.
Resumen de: US2024304305A1
Disclosed herein are techniques related to product consumption recommendations. In some embodiments, the techniques may involve determining, based on glucose data of a user and activity data indicating movement of the user during an activity, a recommendation associated with a consumption of a product by the user to maintain a glucose level within a target range during the activity, and, in response to the recommendation indicating that the consumption of the product is recommended, providing the recommendation to the user.
Resumen de: US2024304324A1
Provided are methods, devices and systems for determining blood glucose levels using a voice sample and associated embodiments. The analysis of voice samples using a statistical classifier was demonstrated to discriminate between subjects with different blood glucose levels. The described embodiments provide an easy-to-use and non-invasive alternative or supplement to conventional blood glucose monitors. The described embodiments can be integrated into various applications for providing information to users or medical professionals such as information related to diabetes or prediabetes.
Resumen de: WO2024186147A1
This method for analyzing the state of a user by using ketone body information comprises steps in which an analysis device: acquires ketone body information of the user; calculates state information of the user on the basis of the ketone body information of the user; and visualizes the calculated state information of the user and outputs same. The ketone body information includes information about the concentration of ketone body included in the exhalation of the user measured using a ketone body measurer. The state information of the user includes at least one from among body fat change amount of the user, weight change amount of the user, blood glucose level of the user, and cholesterol content of the user.
Resumen de: AU2024216338A1
A method of calculating at least one physiological parameter using a reticulocyte production index (RPI) value can include: measuring a plurality of first glucose levels over a first time period; measuring a first glycated hemoglobin (HbAlc) level corresponding to an end of the first time period; measuring the RPI value; calculating a red blood cell elimination constant (kage) based on the RPI value; and calculating the at least one physiological parameter selected from the group consisting of: a red blood cell glycation rate constant (kgiy), a red blood cell generation rate constant (kgen), and an apparent glycation constant (K), based on (1) the plurality of first glucose levels, (2) the first HbAlc level, and (3) the kage. Further, one or more related analyses (e.g., personalized target glucose range, personalized-target average glucose, cHbAlc, and the like) can be estimated and/or adjusted based on the at least one physiological parameter.
Resumen de: AU2023227868A1
Disclosed herein is a combination of an automated insulin delivery system and a continuous glucose monitor integrated into a single, wearable package. The system may use any combination of delivery methods and detection methods, wherein the delivery methods include a cannula, a microneedle array, and a transdermal patch, and wherein the detection methods include electrochemical methods, opto-fluorescent methods, and spectrographic methods.
Resumen de: AU2023224275A1
Certain aspects of the present disclosure relate to methods and systems for providing decision support around kidney disease. In certain aspects, a method includes monitoring one or more analytes of the patient during a plurality of time periods to obtain analyte data, the one or more analytes including at least potassium and the analyte data containing potassium data, processing the analyte data from the plurality of time periods to determine at least one rate of change of potassium for the patient based on the potassium data, and generating a disease prediction using the analyte data for the one or more analytes, including the potassium data and the at least one rate of change of potassium for the patient.
Resumen de: US2024299660A1
The exemplary embodiments attempt to identify impending hypoglycemia and/or hyperglycemia and take measures to prevent the hypoglycemia or hyperglycemia. Exemplary embodiments may provide a drug delivery system for delivering insulin and glucagon as needed by a user of the drug delivery system. The drug delivery system may deploy a control system that controls the automated delivery of insulin and glucagon to a patient by the drug delivery system. The control system seeks among other goals to avoid the user experiencing hypoglycemia or hyperglycemia. The control system may employ a clinical decision support algorithm as is described below to control delivery of insulin and glucagon to reduce the risk of hypoglycemia or hyperglycemia and to provide alerts to the user when needed. The control system assesses whether the drug delivery system can respond enough to avoid hypoglycemia or hyperglycemia and generates alerts when manual action is needed to avoid hypoglycemia or hyperglycemia.
Resumen de: US2024299655A1
Embodiments are directed to portable infusion devices, systems, and methods of using the same for dispensing materials. In some cases, the devices, systems and methods may be used for infusing a material such as medicament, e.g., insulin, into a body in need thereof.
Resumen de: US2024299669A1
Diabetes management systems include an insulin delivery device and a monitoring device for detecting at least one characteristic relating to the insulin delivery device. Monitoring devices may comprise pen caps.
Resumen de: US2024299149A1
Disclosed herein are medical products, including an implantable device coated with an extracellular matrix comprising Type IV collagen and laminin, wherein the implantable device comprises at least one member selected from the group consisting of sensors, meshes and cannulas, and the extracellular matrix contains no more than 0.024 mg/ml total concentration of glucose, amino acids and salts having a molecular weight of 2000 daltons or less. Corresponding systems and method also are disclosed.
Resumen de: US2024298931A1
A blood glucose measurement device capable of measuring a blood glucose in the blood while suppressing the influence of light absorption by water in a living body. The blood glucose measurement device includes a light source that irradiates light having a wavelength selected from a wavelength band of 800 to 950 nm, and a sensor that receives light transmitted, reflected, or scattered in a living body and outputs information according to the amount of light received. A blood glucose acquisition unit acquires the blood glucose in the blood in the living body based on the information obtained by the sensor.
Resumen de: EP4427771A2
Diabetes management systems may include a glucose monitoring device adapted to transmit glucose data and at least one accessory in communication with the glucose monitoring device and adapted to provide at least one alarm or alert based on the glucose data.
Resumen de: CN118175960A
Certain aspects of the present disclosure relate to methods and systems for predicting a patient's glycemic event induced by physical activity. In certain aspects, a method includes continuously monitoring a plurality of analytes of the patient during a period of time to obtain analyte data, the plurality of analytes including at least glucose and lactate. The method also includes processing the analyte data from the time period to determine an intensity level of physical activity participated by the patient during the time period. The method also includes generating a glycemic event prediction using the analyte data for at least the plurality of analytes and the determination of physical activity intensity. The method further includes generating one or more treatment recommendations for the patient based at least in part on the glycemic event prediction.
Resumen de: US2022168254A1
The present disclosure relates to a sterile medical product for parenteral nutrition comprising a polymeric container having at least a first and a second chamber which are separated by a non-permanent peel seal, wherein the first chamber contains a composition of amino acids and optionally electrolytes, and wherein the second chamber contains a dextrose solution, and wherein the product is characterized by a high protein (nitrogen) content per volume. The reconstituted solution is configured to be administered peripherally or centrally for the treatment of patients suffering from malnutrition and/or having a need for increased uptake of amino acids.
Resumen de: WO2024178575A1
An automatic monitoring method based on a rate of change of a difference between actual blood glucose values, and a closed-loop artificial pancreas. The method comprises: acquiring an actual blood glucose value of a user at a current moment (201); acquiring a historical actual blood glucose value of the user at a previous moment, and calculating a difference between the actual blood glucose values at the current moment and the previous moment (202); calculating a rate of change of the difference of the actual blood glucose value at the current moment (203); and comparing the rate of change of the difference of the actual blood glucose value at the current moment with a preset threshold, and determining an event type according to the comparison result. According to the determined event type, the artificial pancreas can automatically adjust a corresponding infusion strategy, thereby achieving closed-loop control of the artificial pancreas.
Resumen de: LU506525B1
The invention discloses a smart medical uniform for monitoring blood glucose in real time, comprising a top and a trouser body, wherein the inside of the front of the top is provided with a blood glucose monitoring device. When the patient puts on the medical uniform according to the invention, the blood glucose value can be continuously collected efficiently and painlessly, reducing the patient's pain, allowing the electronic components to be effectively combined with the garment to meet the individual needs of the patient.
Resumen de: WO2024180385A1
Artificial Intelligence (AI) and Machine Learning (ML) enabled systems and methods for detecting, marking, and differentiating pancreatic lesions and pancreatic parts from endoscopic ultrasound (EUS) images is disclosed. The system may receive and analyze endoscopic ultrasound images (EUS-images) and patient demographic data to detect, mark and classify anatomic-features. The anatomic-features may be images of pancreatic solid masses (benign or malignant), cystic lesions, and anatomic features of normal pancreas. The EUS-images may include color Doppler or power Doppler EUS-images. The detection-methods may include AI-processing methods which may use machine learning techniques to analyze the EUS-images and to extract relevant information, such as the size, shape, and location of the solid masses (benign or malignant tumor) or cysts. This information may be used to make medical predictions and to determine whether it is necessary or advisable to perform certain medical procedures, such as EUS-guided fine-needle aspiration biopsy (FNAB).
Resumen de: WO2024179895A1
The invention relates to a system for regulating the concentration of glucose in the blood of a person, comprising: - a device for selectively supplying insulin and glucagon, - at least two infusion sets; - at least one sensor for measuring a glucose concentration in the blood of said person, and - a controller for controlling said device such that a certain amount of insulin and glucagon is supplied per time unit, wherein said certain amount is chosen in accordance with the measured glucose concentration as prescribed by an insulin injection curve and a glucagon injection curve, wherein said controller is further arranged to determine if glucagon is supplied to said person in a chosen time frame, and wherein the controller is arranged to re-assess and optionally adjust the insulin injection curve based on the determination if glucagon is supplied to said person in said chosen time frame.
Resumen de: US2024293088A1
Systems and methods for predictive glucose in accordance with embodiments of the invention are illustrated. One embodiment includes glucose management device, including a brain signal recorder, and a controller, including a processor, and a memory, the memory containing a glucose monitoring application configured to direct the processor to record a brain activity signal of a user's brain using the brain signal recorder, and decode the brain activity signal to predict future glucose levels of the patient.
Resumen de: US2024293048A1
Blood glucose states based at least on sensed brain activity data. Blood glucose states may be predicted states using prediction models, and may be real-time or future glucose states. One or more wearable sensors, optionally adapted for use in either single channel or dual channel sensing, can record brain activity signals and communicate brain activity signal data to a remote device.
Resumen de: US2024293052A1
The present disclosure relates to a sensor member for continuous blood glucose measurement, wherein a first electrode layer and a second electrode layer are laminated to be misaligned from each other in the process of forming an electrode layer of the sensor member for continuous blood glucose measurement, so that an electrical contact phenomenon between the first electrode layer and the second electrode layer, which may occur in the process of cutting both side surfaces of the sensor member in the widthwise direction, is prevented, and accordingly, product defects are prevented and the stability of the sensor performance is improved.
Nº publicación: US2024293047A1 05/09/2024
Solicitante:
UNIV OF VIRGINIA PATENT FOUNDATION [US]
University of Virginia Patent Foundation
Resumen de: US2024293047A1
Provided are a method, system and computer-readable storage medium for quantitative physiological assessment and prediction of clinical subtypes of glucose metabolism disorders, including but not limited to, Type 1 diabetes, obesity, pre-diabetes, gestational diabetes, or variants of Type 2 diabetes. The method allows a virtual population of in silico entities to be created, reproducing faithfully the clinical subtype distributions observed in vivo. Potential applications of this method may include, but are not limited to: (a) enabling in silico experiments assessing and/or predicting, for a real patient, treatment or intervention outcomes for a given population/clinical-subtype level; (b) pre-clinical testing of properties of new medications; (c) augmenting limited clinical trial data with in silico experiments to an extent that the domain of their validity and test corner cases may not be observed in vivo.
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