45 results about "Diabetes management" patented technology

The invention provides a physiological data monitoring report generation method and system applied to diabetes management. The physiological data monitoring report generation method comprises the following steps: acquiring physiological monitoring data of a diabetic patient in a preset monitoring period; state fragment division and mode recognition are conducted on the physiological monitoring data, a time sequence state fragment set of the diabetic is obtained, metabolic load and steady-state migration quantitative characterization is conducted on the basis of the time sequence state fragment set, a metabolic evolution graph of the diabetic is generated, and the metabolic evolution graph of the diabetic is obtained by combining a preset medical knowledge base and historical health data of the diabetic. Semantic analysis is carried out on the metabolic evolution map, and a health condition key insight set of the diabetic patient is output; and according to the personalized context and expression preference of the diabetic patient, converting the health condition key insight set into a health guidance report conforming to the personalized context and expression preference. The accuracy, comprehensiveness and user acceptability of the physiological data monitoring report in diabetes management can be effectively improved.

The invention relates to the technical field of cloud data synchronization, in particular to a diabetes management-oriented cloud data synchronization method, which comprises the following steps: based on a blood glucose monitoring record, unifying a time zone and verifying a device serial number, generating a terminal version identifier, comparing a cloud version to screen missing entries, and identifying time abnormality and a device source. And forming a version difference mark, judging a missing range and a conflict identifier, updating a synchronization state after sorting, and counting the number of synchronization entries. According to the method, the problems of additional recording of historical data and version conflicts in data synchronization are effectively solved by introducing a dynamic rollback mechanism and timestamp difference comparison, clock differences between devices are automatically detected and adjusted in the synchronization process, timely updating and consistency of data are ensured, invalid synchronization operations are reduced through an intelligent conflict resolution mechanism, and the synchronization efficiency is improved. The accuracy and timeliness of data in diabetes management are ensured, and the data stability and consistency in a multi-terminal environment are improved.

A diabetes management system adapted to determine adherence for a subject in treatment according to a basal insulin regimen, the system being adapted to receive regimen data. BG data and insulin injection data. If one or more insulin injections have not been received in accordance with the prescribed regimen and thus are missing, the system is adapted to calculate for each missing injection an expected dose response BG value. By comparing received BG data, corresponding to the missing insulin injections, it can be determined for a given confidence interval whether or not the subject has been in adherence with the basal insulin regimen.

The invention discloses a blood glucose data analysis system and method based on artificial intelligence, relates to the technical field of diabetes management, and aims to solve the problems of blood glucose data distortion and poor blood glucose monitoring suitability of gestational diabetes patients and children diabetes patients in a motion scene. The method comprises the following steps: acquiring blood glucose original data, exercise intensity data, skin impedance data, blood perfusion index data and special crowd exclusive physiological data, preprocessing, calculating three types of interference weight factors, substituting into a calibration formula to obtain corrected blood glucose data, generating a structured report, updating the calibration formula according to a period, and optimizing a special crowd model. By means of the method, motion multi-dimensional interference can be eliminated, the small sample modeling problem of special crowds is solved, and the blood glucose data precision and clinical practicability are improved.

The invention discloses a sweat induction and multi-parameter detection integrated sensor and a preparation method and application thereof, and belongs to the technical field of flexible biosensing, a PDMS flexible substrate is adopted to construct a multi-layer integrated structure, the sweat induction and multi-parameter detection integrated sensor comprises a sweat guide layer, a sweat collection layer, a detection electrode layer and a micro-fluidic chip layer, sweat secretion is promoted by accurately controlling the temperature to be less than or equal to 40 DEG C; the detection electrode layer adopts a silk-screen printing process to prepare a three-electrode system, comprises a specifically modified glucose working electrode and a beta-hydroxybutyric acid working electrode and can synchronously detect the concentration of glucose and beta-hydroxybutyric acid in sweat, and the micro-fluidic chip layer is integrated with a Bluetooth transmission module to realize real-time wireless transmission of detection data to a mobile terminal; the biosensor has the advantages of being good in biocompatibility, high in detection sensitivity and comfortable to wear and can tolerate bending with the curvature radius larger than 5 mm, and a non-invasive and continuous metabolism monitoring solution is provided for diabetes management.

The invention provides a personalized diet recommendation method for pregnancy diabetes management, and the method comprises the steps: processing diet option data inputted by a patient through an optimized blood glucose response model, and generating an alternative diet recommendation list if the carbohydrate content in the diet option data causes a predicted blood glucose fluctuation trend to exceed a safety range, determining a personalized diet scheme; analyzing the matching degree of the historical blood glucose fluctuation sequence and the personalized dietary scheme according to an iterative blood glucose reaction model, and if the matching degree is judged to be lower than a preset threshold value, re-classifying interaction modes among dynamic factors to obtain refined blood glucose influence weight analysis; and integrating multi-dimensional data from the obtained refined blood sugar influence weight analysis to generate final real-time personalized diet recommendation, and if it is judged that the final implementation of the personalized diet recommendation can stabilize the abnormal blood sugar fluctuation during pregnancy, outputting a complete diabetes management guidance sequence.

The invention provides a diabetes abnormal index early warning system and method based on a recurrent neural network. The system comprises a data acquisition module which is responsible for collecting various health data including blood sugar, heart rate, blood pressure, body weight, body fat, exercise amount, sleep quality and heart rate variability from health monitoring equipment of a patient; the data preprocessing module is used for denoising and normalizing the collected health data and detecting and correcting abnormal values; the feature extraction module is used for extracting time sequence features, statistical features and principal component features from the preprocessed health data; the convolutional gating recurrent neural network model module is used for analyzing the extracted features; and the early warning generation module generates early warning information according to the prediction result. Through the system and the method, the real-time monitoring of the multi-dimensional health data of the diabetic patient and the early warning of the abnormal indexes can be realized, and the diabetes management effect and the life quality of the patient can be improved.

The application discloses a guidance text generation method and system based on diabetes management strategy recommendation. The method performs entity recognition on each text to obtain multiple entities, and extracts the relationship between the entities from each text. A knowledge graph is constructed according to the multiple entities and the relationship between the entities. A multi-layer attention layer is used to aggregate the entities and the relationship in the knowledge graph to obtain a first embedding representation. Text embedding of the entities and the relationship in the knowledge graph is generated, and a multi-layer attention layer is used to aggregate the text embedding into a second embedding representation. The first embedding representation and the second embedding representation are aligned and fused to obtain a target embedding representation. According to the target embedding representation and a target problem, multiple management strategy candidate vectors are determined. A target management strategy is selected from the multiple management strategy candidate vectors, and a diabetes management guidance text is generated according to the target management strategy. The application can improve the real-time performance, personalization and intelligentization of diabetes management.

Adaptive on board estimation of exogenous pharmacon responsive to transient (i.e., impermanent) physiological effects is provided. Dynamically estimating an equivalent amount of an exogenous pharmacon on board (XOB), such as insulin and / or carbohydrates, left in the subject, is based on predictions of glucose time-series data. These estimated values, such as insulin on board (IOB), are useful for diabetes management software, including decision support and / or artificial pancreas (AP) algorithms, for example.

A method for generating a diabetes management parameter user interface, the method comprising providing stored program instructions of a first diabetes management application (DMA), the first DMA configured to be stored in a memory of an electronic device and, when executed by a processor, the first DMA configured to: generate a first output display of a plurality of diabetes management parameters corresponding to a time series of analyte data, the plurality of diabetes management parameters depicting trends in diabetes management parameter levels over time; generate a graphical indicator of a link to a second DMA stored in the memory; and activate the second DMA in response to an input selection of the link, wherein the second DMA is configured to be executed by the processor to generate a second output display of current time diabetes management parameters corresponding to the time series of analyte data stored in the memory.

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.

An insulin delivery system for diabetes management includes a patch-based insulin pump configured to deliver insulin to a user, a user input button disposed on the patch-based insulin pump, a processor configured to execute a hybrid closed loop algorithm that automatically controls insulin delivery based on glucose levels. The user input button is configured to receive user input comprising a sequence of button presses that communicate contextual information about user activities to the hybrid closed loop algorithm, the contextual information being distinct from direct insulin bolus delivery commands. The contextual information may include meal intake, physical activity, and sleep status communicated through different sequences of button presses. The system includes confirmation mechanisms that provide feedback and allow cancellation of inputs, enabling discrete real-time communication of personalized data to enhance diabetes management.

This invention discloses a low glycemic index (GI) Hericium erinaceus (monkey head mushroom) steamed bun, belonging to the field of food processing and functional food applications. By weight, it is prepared from the following raw materials: 45-55 parts all-purpose flour, 28-35 parts Hericium erinaceus extract powder, 0.3-0.35 parts yeast, 15-18 parts water, 0.3-0.6 parts oil, and 0.7-0.9 parts sugar. This invention partially replaces the flour with Hericium erinaceus extract powder, fully utilizing the multiple mechanisms of action of Hericium erinaceus polysaccharides in forming a viscous gel in the digestive tract to slow down the contact between amylase and substrate, inhibiting α-amylase and α-glucosidase activity, and improving intestinal microecology and enhancing insulin sensitivity through dietary fiber. This allows the product to meet the low-GI food standard (GI<55), effectively filling the gap in low-GI steamed buns with Hericium erinaceus functional components as the core active ingredient. It has significant application value in the fields of diabetes management, weight control, and healthy staple foods.

Embodiments of the invention provide amperometric analyte sensors having elements selected to optimize enzymatic activities associated with such sensors including polymers functionalized with enzymatic mediators as well as methods for making and using such sensors. While embodiments of the invention can be used in a variety of contexts, typical embodiments of the invention include glucose or ketone sensors used in the management of diabetes.

The invention discloses an account association method for a diabetes management system, which comprises the following steps: searching information of a patient account in other accounts, if the patient account does not exist in a patient list of other accounts, sending an account association application to the patient account, and after the patient account receives the account association application, confirming the account association application; according to the method and the system, the association with the patient account can be realized, the patient only needs to confirm the association application, and other personnel do not need to skip among different platforms, so that the association between other accounts and the patient account is realized through a simple operation mode.

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.

1.The name of the design product: graphical user interface of a diabetes child blood glucose management system of an electronic device. 2.The use of the design product: the design product is an electronic device. 3.The design points of the design product: the interface content of the graphical user interface in the screen. 4.The picture or photo that best indicates the design points: interface change state diagram 1. 5.The electronic device is a conventional design, and the rear view, left view, right view, top view, and bottom view are omitted. 6.The use of the graphical user interface: the design product is used to provide child diabetes management services for users. 7.The human-computer interaction mode of the graphical user interface: after entering the mobile phone number, password, and verification code in the main view, clicking the “login” button, displaying interface change state diagram 1; clicking the “custom AI recipe” button in interface change state diagram 1, displaying interface change state diagram 2; clicking the corresponding recipe picture in interface change state diagram 2, displaying interface change state diagram 3.

A method for increasing functional and organoleptic properties of compositions having elements of biological origin more particularly herbal formulations is disclosed. Nutraceutical formulations for diabetes management and fortification of pulses and grains to lower oil absorption during frying are also disclosed. These foods are effective for weight management.

Ambulatory infusion pump systems can integrate a CGM sensor with an ambulatory infusion pump via a pump holder or tray that releasably holds the pump and is configured to be worn by a user. A direct electrical connection between the pump and the CGM can be facilitated by providing a sensor nest within the pump holder that causes an electrical connector on the pump to directly interface with the sensor. By combining the CGM and insulin pump into one integrated system with a direct electrical connection, a more aesthetically pleasing, convenient and reliable system is provided. Diabetes management is simplified by consolidating two essential devices into one.

The invention discloses a diabetes mellitus personalized nursing intelligent medical management system based on an AI algorithm, and belongs to the crossing field of intelligent medical treatment and artificial intelligence. According to the system, a three-layer dynamic coupling architecture of data perception, AI decision making and interactive execution is adopted, algorithms such as a space-time diagram convolutional network, hierarchical reinforcement learning and differential privacy federated learning are fused, and multi-source data intelligent fusion, 72-hour complication prospective early warning, minute-level personalized nursing scheme generation and model adaptive evolution are achieved. Clinical verification shows that the system can remarkably reduce the glycosylated hemoglobin level of a patient, improve the blood glucose standard-reaching rate and the scheme execution rate, reduce diabetes related emergency treatment and relieve the workload of medical care, and is low in deployment cost, convenient to operate, high in privacy, suitable for management of various diabetes mellitus and capable of being expanded to other chronic diseases, such as diabetes mellitus, diabetes mellitus, diabetes mellitus and diabetes mellitus. The system is suitable for multiple scenes such as medical institutions, communities and families.

The invention discloses a biomarker for predicting the effect of improving blood glucose through diet intervention of a type 2 diabetes patient and application of the biomarker. The biomarker is composed of the following metabolite markers: 16 [alpha]-hydroxy dehydroepiandrostene-3-sulfate, 1-palmitoyl-2-linoleyl phosphatidylinositol glycerol (16: 0 / 18: 2), 1-oleoyl-2-arachidonyl phosphatidyl ethanolamine (18: 1 / 20: 4), 3-methoxy tyrosine and methyl succinyl carnitine, and the pH value of the biomarker is 7-8. The method is used for predicting the blood glucose improving effect of diet intervention of the type 2 diabetes patients, the prediction efficiency of traditional clinical indexes can be remarkably improved, the success rate of long-term blood glucose control is increased, accordingly, the treatment efficiency is improved, and application of precise medicine in type 2 diabetes management is achieved.

The application provides a kind of army diabetic patient intelligent remote management method, device, equipment and medium, comprising: obtaining the initial health data of army diabetic patient, the initial health data is desensitized, and the initial health data after desensitization is distributed in cloud security database using blockchain node network Storage;The initial health data after desensitization is input into the diabetes management large model for analysis, and a health management scheme is generated;According to the monitoring index in the health management scheme, the real-time health data of the patient is collected through the wearable device, and the diabetes management large model is input for risk analysis and updating the health management scheme;In response to the natural language interaction request of patient end or medical expert end, human-computer interaction is carried out through medical expert digital avatar, and visual medical advice is output, to solve the problem of intelligent, safe and closed-loop remote management of diabetic patients under the condition of high confidentiality requirement of army and lack of medical resources in border areas.

The invention discloses an intelligent health monitoring system focusing on diabetic groups. The non-invasive health monitoring system comprises a non-invasive data acquisition module, a main control module, a core algorithm module, a communication module, a display module, a mobile terminal APP and a portable shell. The noninvasive module is used for respectively acquiring blood glucose related data and pulse waveform, heart rate and blood pressure original data through an AS7341 spectrum sensor and an MKS-141 module; the main control module adopts an STM32 chip, and guarantees real-time processing and transmission of data through multi-task scheduling; the core algorithm module comprises a KAN neural network and a PPG algorithm and accurately outputs physiological indexes. The communication module supports bidirectional data transmission, the OLED screen displays key information in a layered manner, and the portable shell adapts to ergonomics. The APP integrates a DeepSeekAI model, provides blood sugar fluctuation analysis, sugar control suggestions and abnormal early warning, and supports data export. The system is non-invasive and convenient, integrates multiple parameters, reaches the precision standard, adapts to daily monitoring and clinical assistance, and improves the diabetes management effect.

The application discloses a diabetes management and health data statistical analysis system, relates to the field of medical information technology, and comprises a cohort screening module, a interface alignment module and a rule alignment module. The cohort screening module arranges filing information and follow-up main index into a patient portrait card and performs equivalent cohort screening, generates an equivalent reference cohort mapping table and loads parameters. The interface alignment module calls the loading parameters to connect blood glucose, medication and test interfaces and completes standardization and time alignment, generates a blood glucose monitoring time index table and a complication index availability index table. The rule alignment module arranges clinical standard rules and prescription constraint rules into a verification rule table, and executes rule checking in combination with a deviation site marking table, and executes cohort alignment in combination with the equivalent reference cohort mapping table, generates a node exception list and an executable transaction list. The application solidifies clinical standard rules and prescription constraint rules into a verification rule table and completes rule checking and cohort alignment, and improves the explainability of abnormal identification and the feasibility of disposal suggestions.

The utility model relates to the technical field of diabetes management. The insulin needle detacher comprises a first mounting rod, and the outer surface of one end of the first mounting rod is connected with a second mounting rod in a hinged mode. By rotating the bolt, the clamping pieces can be driven to move synchronously, meanwhile, the limiting rod is driven to move in the limiting groove, the direction of the clamping pieces in the moving process can be stabilized, meanwhile, the clamping pieces can be prevented from rotating along with rotation of the bolt in the moving process by rotating the rotating ring in the rotating groove, and the clamping pieces can be prevented from rotating along with rotation of the bolt. According to different specifications and sizes of needles needing to be detached, after the distance between the two sets of clamping pieces is adjusted to be appropriate, the needles can be clamped and rotated to be detached, meanwhile, through anti-skid tooth grooves in the outer surfaces of the clamping pieces, the friction force generated when the clamping pieces clamp the needles can be increased, and the needle detaching efficiency is improved. And the situation that the needle head slides down when the needle head is detached is avoided, and the usability of equipment is improved to a certain extent.

This invention provides a control device, method, and program for determining the recommended amount of carbohydrates (RC). [Solution] In the system (10), the control device (30) includes an acquisition unit (32) configured to acquire user data, an outlier unit that determines whether or not the user data is considered an outlier, an RC unit (36) that estimates an RC recommendation using a mathematical function of the user data, and a transmission unit (38) that transmits the RC recommendation. The transmission unit (38) transmits the RC recommendation only if the last user data is not determined to be an outlier.

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.

The invention discloses a method applied to a diabetes management system and used for searching for lost equipment. The diabetes management system comprises at least one wearable medical device. At least one personal management device and a secondary management device, at least one of the personal management device and the secondary management device can be used for controlling the wearable medical device, and the personal management device is in communication connection with the secondary management device; when one of the personal management equipment and the secondary management equipment is determined to be lost, the lost equipment is found through the other one of the personal management equipment and the secondary management equipment, and a user can easily find the lost equipment.

The invention discloses a diabetes decision-making method, device and equipment fusing blood glucose monitoring and clinical data, and relates to the field of intelligent data management.The method comprises the steps that blood glucose related data of a target object is collected in real time, and the data is uploaded to a central database and preprocessed; based on a signal processing technology and a machine learning algorithm, extracting features related to diabetes management from the preprocessed data so as to identify and obtain key clinical events; according to the key clinical event obtained through recognition, in combination with medical knowledge and clinical guidelines in a pre-created evidence-based medical knowledge base, clinical decision suggestions are generated and visually displayed. According to the application, deep combination of patient data and evidence-based medical knowledge can be realized, and a real-time, scientific and individualized clinical intervention scheme is provided.

The invention discloses a predictive marker for improving the blood sugar effect through exercise intervention of a type 2 diabetes patient and application of the predictive marker. The predictive marker is formed by combining the following metabolite markers: creatine, spermidine, 4-oxo-tretinoin, S-methylcysteine sulfoxide, 3-phosphoglyceric acid / 2-phosphoglycerol, vitamin C3-sulfosulfone, salicyloyl urea glucuronide and gamma-glutamyl isoleucine, and the metabolite markers are used for detecting the content of the metabolite markers. The method is used for predicting the movement intervention of overweight or obese type 2 diabetes patients to improve the blood sugar obviously, the treatment efficiency is improved, and the application of precision medicine in type 2 diabetes management is realized.