137 results about "Hypoglycemia" patented technology

The invention discloses a personalized medical health service recommendation system based on big data analysis, and belongs to the technical field of medical health services. The synchronization module is used for generating a standardized data stream according to dynamic blood glucose monitoring data and an original heart rate variability signal; the analysis module is used for generating a diet time sequence data stream according to the intake event timestamp; the blood glucose feature extraction module is used for extracting data from the standardized data stream; the insulin sensitivity analysis module is used for generating an insulin sensitivity factor matrix; the nutrition analysis module is used for generating a carbohydrate equivalent time distribution vector and a dietary fiber intake intensity value; the feature fusion module is used for generating a fusion feature vector according to the blood glucose drift trend coefficient, the insulin sensitive factor matrix and the carbohydrate equivalent time distribution vector; the risk assessment module is used for generating a hypoglycemia risk probability value according to the fusion feature vector; and the recommendation generation module is used for generating a personalized service recommendation set according to the hypoglycemia risk probability value.

The invention discloses a preparation method and application of a glucose sensor based on an acupuncture needle, the sensor is prepared based on a specific structural design and a molecular recognition mechanism by taking the acupuncture needle as a substrate, and high-specificity and high-sensitivity detection of glucose concentration is realized through drain current change. According to the present invention, the biosensor has the ultra-wide dynamic detection range (0-40 mmol.L <-1 >), covers the clinical range from hypoglycemia to severe hyperglycemia, has the low detection limit of 54 mol.L <-1 >, has excellent grid regulation and control ability, shows the significant on-off ratio and the rapid response characteristic during the detection process, and meets the requirements of the biosensor on sensitivity and real-time performance; and the device has quick response capability to grid voltage change, so that the device has good stability and repeatability under repeated operation, and a direction and a basis can be provided for the development of a blood glucose monitoring technology with continuous, real-time and accurate characteristics.

A wearable drug delivery device, techniques, and computer-readable media that provide an application that implements a diabetes treatment plan for a user are described. The drug delivery device may include a controller operable to direct operation of the wearable drug delivery device. The controller may provide a selectable activity mode of operation for the user. Operation of the drug delivery device in the activity mode of operation may reduce a likelihood of hypoglycemia during times of increased insulin sensitivity for the user and may reduce a likelihood of hyperglycemia during times of increased insulin requirements for the user. The activity mode of operation may be manually activated by the user or may be activated automatically by the controller. The controller may automatically activate the activity mode of operation based on a detected activity level of the user and / or a detected location of the user.

Disclosed herein are apparatuses and methods that can provide a delayed bolus calculator for use in closed loop diabetes therapy that can account for additional factors not taken into account in regular meal bolus calculations when a user wants to deliver a meal bolus a period of time after a meal was consumed. A delayed bolus calculator can enable the user to enter a period of time since the meal was consumed in addition to the number of carbohydrates consumed in a meal. This enables the system to account for the amount of increased insulin from the closed loop algorithm in response to the meal and / or the time since the meal to ensure that the risk of hypoglycemia is mitigated while still reducing hyperglycemia.

The invention provides an intelligent insulin closed-loop infusion system for type 1 diabetes mellitus, and relates to the technical field of diabetes mellitus treatment equipment. The system comprises a blood glucose monitoring module, a control module, an insulin infusion module, a user interaction module, a wireless communication module and a power module, and closed-loop precise infusion of insulin is achieved through cooperation of the multiple modules. Wherein a closed-loop algorithm based on a dynamic basic rate formula is arranged in the control module, and the insulin infusion amount can be dynamically adjusted in combination with an LSTM blood glucose prediction model and a metabolic parameter least square method updating unit; the insulin infusion module adopts a micro peristaltic pump controlled by PWM (Pulse Width Modulation) and a current monitoring type blockage detection unit, so that the infusion precision and safety are guaranteed. According to the system, the blood glucose standard reaching time proportion can be increased to 78%, the hypoglycemia occurrence frequency is reduced to 0.8 times per week, the system is remarkably superior to a traditional insulin pump and a simple closed-loop system, meanwhile, the system has the advantages of being long in sensor service life and low in power consumption, and the treatment convenience and safety of type 1 diabetes patients are improved.

An automated insulin delivery system provides an insulin injection that is computed by adding (i) the recommendation of an artificial neural network trained to mimic a constrained model predictive controller dosing rule from a neural network implementing an artificial pancreas (ii) a hypoglycemia mitigation system includeds a correction (one dose computed as the correction down to 110mg / dl based on prevailing continuous glucose monitoring and once an hour at most, unless there is a triggering BPS and G>180 mg / dl), and (iii) the current basal rate (output of the Performance Assessment System, (PAS)); that amount is then saturated by the Safety Supervision System, SSM. Finally, a priming bolus from the Bolus Priming System, BPS, is added to the total if the conditions for large glycemic excursions are detected, also saturated by SSM.

The invention relates to the technical field of non-invasive monitoring, in particular to a diabetes blood glucose fluctuation trend prediction method based on foot temperature and humidity change, which comprises the following steps: continuously collecting temperature, humidity and motion data of multiple areas of a foot through a foot wearable device, extracting a feature set related to blood glucose fluctuation from the preprocessed data, and calculating the blood glucose fluctuation trend according to the feature set; and fusing the feature set and context event information, inputting the fused feature set and context event information into a multi-task deep learning prediction model, visually displaying a prediction result in the forms of a trend arrow, a probability interval and a risk level, and triggering early warning in advance when a hyperglycemia or hypoglycemia event is predicted to be about to occur. The method is completely noninvasive and high in compliance, prospective trend prediction can be carried out based on existing diabetic foot monitoring wearable equipment, individual physiological characteristics of a user can be continuously learned through a built-in personalized self-adaptive mechanism, dynamic calibration is carried out on the model through incremental learning, and the prediction accuracy is improved. And the prediction precision is continuously improved along with the use time.

The present invention discloses a hemodialysis fluid balance control method, device, electronic device, and medium, relating to the technical field of intelligent regulation. The hemodialysis fluid balance control method includes: in response to a patient experiencing a hypotensive event, determining whether the hypotensive event is caused by a hypoglycemic event; if the hypotensive event is caused by a hypoglycemic event, switching the patient's dialysate from a sugar-free dialysate to a sugar-containing dialysate; monitoring the patient's real-time blood glucose concentration; and controlling the dialysate flow rate during the patient's dialysis based on the real-time blood glucose concentration. The embodiments of the present application achieve the goal of reducing interference with hemodialysis while ensuring compensation for hypoglycemia.

Certain aspects of the present disclosure provide systems and techniques for rapid detection of repetitive metabolic events in a host based on measured analyte data provided by an analyte monitor worn by the host. An example system is configured to obtain measured glucose data of the host. A subset of the measured glucose data is determined, based on performing a filtering operation on the measured glucose data. A respective range of a likelihood of an occurrence of a metabolic is determined for each value within the subset of the measured glucose data. For at least one value within the subset of the measured glucose data, a state of the metabolic event is determined based in part on at least one of an upper bound or a lower bound of the respective range corresponding to the at least one value within the subset of the measured glucose data.

The invention discloses a self-management method for pregnant women with gestational diabetes mellitus and a related device. The method comprises the following steps: collecting comprehensive health information of the pregnant women in the gestational period according to a preset period; the comprehensive health information is input into a gestational diabetes health status assessment model, and the comprehensive health status assessment result of the pregnant woman gestational diabetes is predicted, and the comprehensive health status assessment result comprises the risk probability of hyperglycemia, hypoglycemia and gestation complications; according to the gestational diabetes mellitus medical knowledge base and the comprehensive health state evaluation result, a pregnant woman personalized intervention scheme is generated and uploaded to a medical platform for an attending physician to check and confirm, and the pregnant woman personalized intervention scheme comprises diet suggestions, exercise suggestions and medicine adjustment suggestions. The risk probability of the pregnant woman suffering from hyperglycemia, hypoglycemia and pregnancy complications is predicted through the gestational diabetes health status assessment model, personalized risk assessment is realized, and the risk of complications is reduced through a personalized intervention scheme.

The present invention relates to formulations of glucagon analogues or pharmaceutically acceptable salts and / or derivatives thereof; and their medical use, e.g. in the treatment of hypoglycemia. In particular, the present invention relates to stable aqueous liquid formulations of glucagon analogues comprising a combination of excipients that make them suitable for long-term storage as liquids and capable of being used in single dose (SD) or multiple dose (MD) formulations.

The present invention relates to a biocompatible tattoo ink that changes color in response to varying glucose levels in the bloodstream, providing a continuous monitoring method for individuals with diabetes. The ink contains glucose-sensitive agents that cause the tattoo to change from green (normal glucose levels) to red (high glucose levels) or blue (low glucose levels). Additionally, the ink shifts back to green when blood glucose returns to normal from either hyperglycemia or hypoglycemia. This provides a real-time visual indicator of glucose levels and enables users to monitor their health without additional equipment.

The present disclosure describes the use of an anti-insulin receptor antibody to treat neoplasms and / or tumor-associated hyperinsulinism and resulting hypoglycemia caused by benign or malignant neoplastic production of insulin and / or other effector substances (e.g., IGF-2 or its variants) that interact with the INSR and thus result in insulin-like action.

The present invention relates to formulations of glucagon analogues, or a pharmaceutically acceptable salt thereof and / or a derivative thereof; and their medical use, for example in the treatment of hypoglycaemia. In particular, the present invention relates to stable aqueous liquid formulations of glucagon analogues comprising combinations of excipients that make them suitable for long term storage as liquids, and are capable of use in single-dose (SD) or multi-dose (MD) formulations.

The present invention belongs to the technical field of insulin derivatives. Disclosed are a phenylboronic-acid-based insulin derivative, and a preparation method therefor and the use thereof. The provided phenylboronic-acid-based insulin derivative has a good glucose-responsive release function, wherein the phenylboronic acid group binds to a glycosyl protein to generate a phenylboronic acid ester bond, thereby generating an insulin and glycosyl protein complex in situ in blood. When the concentration of glucose in the blood is high, the glucose specifically cleaves the phenylboronic acid ester bond, thereby releasing the insulin. The provided phenylboronic-acid-based insulin derivative achieves stable and rapid glucose-responsive insulin release, which can steadily and persistently maintain the blood glucose of a diabetic subject within the normal range with almost no occurrence of hypoglycemia.

The application discloses corn silk glucan, a structure formula of which is [→4)-β-D-Glcp-(1→]n, wherein n is 6-60, and a molecular weight range is 1-9.8 kDa. By extracting effective components in corn silk, an extract is obtained, the extract is precipitated by 30-90% ethanol, corn silk crude polysaccharide is obtained, and after the corn silk crude polysaccharide is dissolved, the corn silk crude polysaccharide is sequentially subjected to biological membrane dialysis, ion exchange resin column and HPLC-ELSD separation and purification, and corn silk glucan is obtained. The corn silk glucan and zeaxanthin are compounded to form a glucan compound, the glucan compound can stabilize insulin and improve the activity of the insulin in mouse islet cells, and the glucan compound has 2-5 times stronger hypoglycemic activity than that of zeaxanthin alone, and therefore, the glucan compound has important significance for researching new hypoglycemic drugs or health-care food for assisting hypoglycemia.

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.

This invention provides a system and method to protect an artificial pancreas' sensor, infusion system, and alert systems from EMI / wireless attacks using a medical software or application, close the gap between sensor glucose and blood glucose, and build a non-invasive hypoglycemia and hyperglycemia false alarm detection scheme with the help of a wristband. This inventive method and system provides a more accurate blood glucose prediction. It comprises preprocessing the CGM readings with Kalman smoothing for sensor error correction improves the robustness of the BG prediction. In one or more embodiments, the inventive system and method uses one or more physiological information such as meal, insulin, aggregations of step count, and preprocessed CGM data. The invention provides a novel approach for leveraging the stacked LSTM based deep RNN model to improve the BG prediction accuracy. The invention provides a special circuits-Transduction Shield-to detect and correct the sensor errors caused by EMI attacks.

A diabetes management system optimizes glucoregulatory hormone delivery using a connected glucoregulatory hormone delivery system and a computing device with a processor and non-transitory memory. The system receives glucose management data (glucose, insulin delivery, heart rate, or carbohydrate consumption data) from sensors. A digital twin metabolic model is selected and initialized based on the received data. The system simulates diabetes treatment interventions to predict glucose dynamics and determines an optimized glucoregulatory hormone parameter (e.g., insulin dose or increment that minimizes hyperglycemia and hypoglycemia risk). The determined glucoregulatory hormone parameter is transmitted to the connected glucoregulatory hormone delivery system, which may include an automated insulin delivery (AID) system or a connected insulin pen system, for implementation. By integrating real-time physiological data with predictive metabolic modeling, the system enhances glucoregulatory hormone therapy, providing personalized adjustments to improve glucose control.

Provided are related to antibodies or antigen-binding fragments thereof that specifically bind to GLP-IR, and uses thereof. The antibodies or antigen-binding fragments can antagonize the activation of GLP-IR by endogenous or exogenous GLP-1, and can be used for the diagnosis, prevention and / or treatment of GLP-IR-associated or hypoglycemia-associated diseases or disorders.

This disclosure is directed to systems and techniques for detecting change in patient health based upon patient data. In one example, a medical system comprising processing circuitry communicably coupled to a glucose sensor and configured to generate continuous glucose sensor measurements of a patient. The processing circuitry is further configured to: extract at least one feature from the continuous glucose sensor measurements over at least one time period, wherein the at least one feature comprises one or more of an amount of time within a pre-determined glucose level range, a number of hypoglycemia events, a number of hyperglycemia events, or one or more statistical metrics corresponding to the continuous glucose sensor measurements; apply a machine learning model to the at least one extracted feature to produce data indicative of a risk of a cardiovascular event; and generate output data based on the risk of the cardiovascular event.

A blood glucose monitoring system having an insulin pump operational to administer insulin to the subject, sensors associated with the subject and operational to measure the blood glucose levels of a subject, and a computing device in electronic communication with the insulin pump. The computing device includes computer readable storage mediums having program code embodied therewith. The computing device includes a closed-loop insulin delivery algorithm trained to predict the blood glucose level of the subject. The algorithm includes a data-driven multi-step- ahead blood glucose predictor integrated with a linear time-varying model predictive control law. The computing device includes programming instructions for feeding the subject's blood glucose level into the algorithm, using the algorithm to predict if the blood glucose level of the subject is expected to reach a level representing hypoglycemia or hyperglycemia, and transmitting insulin administration instructions to the insulin pump based on the prediction.

This invention discloses an interlocking drug infusion device, comprising a drug reservoir for containing drugs, a piston and a screw disposed within the reservoir; a drive wheel connected to the screw, which drives the piston forward by rotating the drive screw; a drive unit that moves in the drive direction to drive the drive wheel to rotate; a driver electrically connected to the drive unit, which, when energized, provides power to the drive unit in the drive direction; a program module electrically connected to the driver, which provides a first drive instruction to control the driver to perform periodic power output; and a position detection module for determining the periodic drug infusion volume. When the drug infusion volume reaches a set threshold, the position detection module and / or the program module provide a second drive instruction to the driver. The program module and the position detection module physically form a synchronous interlocking mechanism to prevent over-infusion in the event of electronic component or preset program failure, thus preventing the risk of hypoglycemia or even coma.

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.

Disclosed herein are methods of treating and ameliorating hyperinsulin hypoglycemia using sodium dependent glucose transporter (SGLT) 1 inhibitor compounds and compositions comprising them.

The present application provides a blood glucose monitoring method. The method comprises: determining a first early warning duration according to first blood glucose data, wherein the first blood glucose data comprises blood glucose data within a first time period, and the first early warning duration is used for performing hypoglycemia early warning. The first early warning duration is related to blood glucose fluctuation indicated by the first blood glucose data. If the blood glucose indicated by the first blood glucose data fluctuates little and changes slowly, the first early warning duration can be longer. If the first blood glucose data input into a model indicates that the blood glucose of a user fluctuates greatly and changes rapidly in historical time, the first early warning duration can be shorter. By means of implementing the described method, the electronic device can adaptively adjust the first early warning duration according to the characteristics of the blood glucose variability of a user, thereby improving the accuracy of hypoglycemia early warning.

The application discloses a new type of hapten and fatty acid double modified long-acting hypoglycemic BimBH3 mimetic peptide compound targeting PTP1B as well as a preparation method and application thereof. The structural general formula of the Bim BH3 mimetic peptide is shown as formula I: wherein the compound is derived from a core region peptide segment of a Bim-BH3 domain, a non-natural amino acid is used to replace the second amino acid by site-specific substitution to increase the stability of the peptide segment against DPP-4 enzyme, and a long-chain fatty acid (hexadecanoic acid or octadecanedioic acid) is conjugated to the N terminal to modify to ensure better PTP1B inhibitory activity, so that the BimBH3 mimetic peptide has longer duration and higher activity and plays a role in hypoglycemia by inhibiting the target PTP1B. The compounds are prepared by using 2-CTC resin by polypeptide solid-phase synthesis method, and the crude product is cut, purified and freeze-dried to obtain a pure target compound.

The invention relates to a hypodermic injection insulin system automatic dose recommendation method based on a big data AI algorithm, and the method comprises the following steps: (1) adding a current patient to a hypodermic injection insulin system for information setting; (2) calculating the initial daily total dose TDD of insulin needing to be injected by the patient at present; (3) calculating a correction large-dose coefficient CF of the insulin to be injected; (4) collecting the blood glucose value of the patient in the current state, and further calculating an adjustment factor AF; and (5) comparing the currently collected blood glucose value of the patient with a preset threshold value to prevent the occurrence of hypoglycemia. By adopting the automatic dose recommendation method for the subcutaneous injection insulin system based on the big data AI algorithm, the probability of occurrence of hypoglycemia can be effectively reduced by 97% or above, so that the time of reaching the blood glucose standard of a patient is saved by 34% or above, and the method has certain practicability in the aspects of reducing the hospitalization time of the patient and the like.

The application belongs to the technical field of medicine production and relates to responsive sustained / controlled release microspheres and a preparation method and application thereof.The responsive sustained / controlled release microspheres comprise, by weight fraction, 160-200 parts of acetalized dextran, 40-80 parts of polylactic acid-glycolic acid copolymer, 10-30 parts of a drug, 3-7 parts of glucose oxidase and 0.5-1.5 parts of catalase; the mass ratio of the acetalized dextran and the polylactic acid-glycolic acid copolymer is 3-5:1.The microspheres can release insulin responsively according to blood glucose, once administration can stabilize blood glucose for 20 hours, and can ensure safety while effectively reducing blood glucose, and will not cause a series of life-threatening symptoms such as hypoglycemia due to excessive insulin injection.The blood glucose maintenance cycle can be adjusted according to the dose of the microspheres, and the purpose of long-term stable blood glucose is achieved.At the same time, the size and performance of the microspheres are uniform and stable.

This invention relates to the field of blood glucose detection technology and discloses a depression compensation method and system for CGM sensors. The method extracts temporal and physiological features from the acquired blood glucose-related current signals to generate fused feature data. Based on preset temporal dimension rules, it first determines whether the depression is short-term, accurately identifying the temporal features of non-physiological depressions. This enables effective identification of non-physiological signal depressions at night. The dual-dimensional judgment rules achieve accurate differentiation of signal causes. When a short-term depression is determined in the temporal dimension, it is verified by physiological dimension rules. This dual-layer identification logic of initial screening of temporal features and verification of physiological features avoids signal confusion, reduces the false positive rate, prevents the risk of missed hypoglycemia or erroneous intervention, and solves the technical problem that nighttime monitoring easily miscorrects true hypoglycemia signals or misjudges non-physiological depressions as hypoglycemia.