29 results about "Health reporting" patented technology

Embodiments provide for data input methods and systems for computer record storage and retrieval. In embodiments, an artificial intelligence system or a computer-based nodal analysis system allows for scanning or document acceptance, sorting, deletion of duplicate materials, storage and retrieval of data for use by individuals, such as health care professionals. Access to the methods and systems may be monitored or allowed according to different criteria such as the satisfaction of a payment criteria.

The technical scheme of the present application discloses a kidney transplantation single disease follow-up database system based on a hospital intranet environment, comprising a data integration layer, an intelligent analysis layer and a doctor-patient linkage layer. Through the cooperative operation of the three-layer technical architecture designed by the present application, the three core problems of the prior art are comprehensively solved, and the following technical effects are achieved: at the data integration level, automatic and real-time integration of multi-port medical data of kidney transplantation patients is realized, the data integration efficiency is improved by 90%, the accuracy rate reaches 99.5%, and the traceability and privacy security are significantly improved; at the data analysis level, the AI-driven analysis model realizes automatic generation of patient whole-cycle health reports, large-sample group feature mining and real-time abnormality early warning, and the doctor data analysis workload is reduced by 80%, and the abnormal data response time is shortened to the minute level.

The application discloses a kind of campus health management system and method based on group benchmark analysis, comprising: data acquisition module, for collecting the health and behavior data of student individual, and implementing data anonymization processing;Data processing and analysis module, including group clustering unit, for clustering the anonymized student individual data into homogenization analysis group according to student group attribute;Benchmark generation unit, for calculating the dynamic statistical benchmark band of one or more health indicators in each analysis group based on historical data within the set time window;Individual comparative analysis unit, for comparing each student individual data with the dynamic statistical benchmark band of corresponding health indicators of its analysis group, and calculating the relative deviation of individual health indicators;Early warning and report generation module, for triggering hierarchical early warning according to individual comparative analysis result, and generating visual health report. It can be widely applied to the field of campus health management technology.

The invention discloses a health detection system and method. The system comprises a server and health detection equipment, the health detection equipment comprises a control module, a communication module and a health detection module; the health detection module comprises a detection module used for obtaining health data; the comparison module is used for comparing the health data with a health standard and outputting a health result; the health standards at least comprise health judgment standards, and if the health data meet the health judgment standards, the health result is normal; if the health data does not meet the health judgment standard, the health result is abnormal; the health detection equipment transmits health data and / or health results to the server through the communication module; the server comprises a report generation module which is used for receiving the health data and / or the health result and generating a health report in combination with historical data of the health data and / or the health result; and the data storage module is used for storing the health data, the health result and the health report.

This application relates to the field of nebulizer technology, and more particularly to a health monitoring method and system based on a nebulizer. The method includes: acquiring the nebulizer's on / off frequency; acquiring the user's current respiratory rate based on the on / off frequency; determining whether the current respiratory rate meets preset health requirements; if the current respiratory rate does not meet the preset health requirements, acquiring the user's target information, current status, and historical diagnostic records; acquiring a frequency calibration coefficient based on the target information, current status, and historical diagnostic records; acquiring a calibrated respiratory rate based on the current respiratory rate and the frequency calibration coefficient; generating a health report based on the calibrated respiratory rate, and sending the health report to the user terminal. This application helps improve the accuracy of health reports, meeting the user's need for real-time and accurate monitoring of respiratory rate and obtaining health reports during nebulizer treatment.

1. Name of the product in this design: Body of a graphical user interface for health management of electronic devices. 2. Purpose of this design: An electronic device. 3. The key design features of this product are: the parts within the graphical user interface, with the area outside the dotted lines being the protected area. 4. The picture or photo that best illustrates the key design points: Design 1 front view. 5. Design 1 is designated as the basic design. 6. Purpose of the graphical user interface: The overall interface is used for health management; it is required that a portion of the interface be protected for importing examination reports, using an AI model to interpret and analyze the body's health abnormalities and risks, and generating a follow-up examination plan to remind users to manage their health. 7. Human-computer interaction method of graphical user interface: In the main view of Design 1, users can click the "+Family" control to add family members, click the "Review" control to view the review plan, view the health overview data on the left side of the interface, click on various indicator controls to enter the corresponding data analysis page, click on the "Supplementary Report" or "View Risk" controls to enter the corresponding function details page, click on the organ controls in the human body model on the right side of the interface to enter the corresponding organ status details page, and click on the body part partition controls in the tab bar at the bottom of the interface to enter the corresponding details page. In the main view of Design 2, users can click the circular avatar control to switch the display of the corresponding family member's health report, click the "+" circular control to add family members, click the "Review" control to view the review plan, view the health overview data information on the left side of the interface, click on various indicator controls to enter the corresponding data analysis page, click on the "Supplementary Report" or "View Risk" controls to enter the corresponding function details page, click on the organ controls in the human body model on the right side of the interface to enter the corresponding organ status details page, and click on the body part partition controls in the tab bar at the bottom of the interface to enter the corresponding details page. In the main view of Design 3, users can switch between Chinese and English language modes, add family members by clicking the "+Family" control, and import inspection reports by clicking the arrow control in the bubble box at the bottom of the interface. In the main view of Design 4, when the user clicks on the chest area of ​​the human body model on the right side of the interface, the interface changes to a different state.

The invention relates to a city-wide dual-active trackside security platform system, a main and standby arbitration method and equipment, the system comprises two independently deployed centers and a distributed arbitration point, and each center internally comprises a plurality of copies of redundant design; main and standby negotiation messages are exchanged among all the copies of the double centers, and the copies make a main copy decision according to a main and standby updating rule based on the main and standby negotiation messages and update own main and standby states; the double centers can only have one main copy, and other copies are redundant standby copies; the copies send heartbeat to a distributed arbitration point, and the distributed arbitration point periodically sends a health report to each copy to inform each copy of the health state and the main / standby state; and when the replica cannot receive the central message of the opposite side, the main replica is decided through the health report and the main / standby state assistance, and the main replica outputs data to the outside. Compared with the prior art, the method has the advantages of quickly deciding the primary copy, ensuring the unique primary copy when the communication between the centers is abnormal, and the like.

The invention belongs to the technical field of health monitoring, and particularly relates to a senile dementia risk home monitoring method based on multi-modal behavior analysis, which comprises the following specific steps: monitoring human body postures in real time, analyzing repeated actions, synchronously early warning abnormal movement, and carrying out voice interaction operation through a built-in AI dialogue terminal; performing behavior, emotion and physiology correlation modeling, executing cognitive decline dynamic evaluation through cognitive function self-test, and judging a risk level according to an analysis and evaluation result; executing a multi-level early warning mechanism based on the risk level information, and automatically taking corresponding emergency measures; the threshold value is dynamically calibrated by integrating user habit data, a closed-loop feedback mechanism is designed to realize false alarm suppression, and a monthly health report is synchronously generated to assist a doctor in adjusting an intervention scheme. The problems that in a traditional monitoring mode, tiny behavior changes are difficult to capture, rescue is delayed due to subjective evaluation hysteresis and passive response, the screening frequency is low, and the scene is limited can be solved.

A resource deployment health report graph that defines a first plurality of resource dependencies set as a needed resource dependency type and a second plurality of resource dependencies set as an optional resource dependency type is generated prior to resources being connected in a container-based environment. An analysis of the resource deployment health report graph is performed to determine a status of each of the first plurality of resource dependencies and each of the second plurality of resource dependencies. It is determined whether each of the first plurality of resource dependencies and the second plurality of resource dependencies is marked ready in the resource deployment health report graph based on the analysis. In response to determining that each of the first plurality of resource dependencies and the second plurality of resource dependencies is marked ready, it is determined that an actual deployment is successfully implemented in the container-based environment.

The invention relates to an Internet of Things platform health monitoring and analysis method and system, and belongs to the technical field of health monitoring and analysis, and the method comprises the steps that an intention analysis module receives a user natural language query, and extracts a structured monitoring intention; a PromQL generation module matches a preset template library according to the structured monitoring intention to generate a compliant PromQL; the monitoring source intelligent selection module determines a priority monitoring source according to the structured monitoring intention and the compliance PromQL, and defines a switching rule; the HTTP request module sends a parameter acquisition request to the priority monitoring source to acquire original JSON data; the result judgment module judges that the state of the original JSON data is successful and the data result is non-null, and determines that the original JSON data is valid data; the multi-dimensional data analysis module analyzes the original JSON data to obtain an analysis result and an optimization suggestion, and outputs the analysis result and the optimization suggestion; and the report generation module integrates the process information according to a preset structure and outputs a health report.

A resource deployment health report graph that defines a first plurality of resource dependencies set as a needed resource dependency type and a second plurality of resource dependencies set as an optional resource dependency type is generated prior to resources being connected in a container-based environment. An analysis of the resource deployment health report graph is performed to determine a status of each of the first plurality of resource dependencies and each of the second plurality of resource dependencies. It is determined whether each of the first plurality of resource dependencies and the second plurality of resource dependencies is marked ready in the resource deployment health report graph based on the analysis. In response to determining that each of the first plurality of resource dependencies and the second plurality of resource dependencies is marked ready, it is determined that an actual deployment is successfully implemented in the container-based environment.

The invention discloses a health report generation method, wearable equipment and a storage medium, and relates to the technical field of physiological signal processing, and the method comprises the steps: obtaining a target physiological signal detected by a target user in a current time period based on the wearable equipment, and determining a target physiological feature according to the target physiological signal; collecting detection environment parameters of the wearable device in the current time period; according to the target physiological signal, blood pressure change factor information causing change of the blood pressure value level of the target user is obtained through recognition; a health report is generated according to the obtained first blood pressure baseline feature, the target physiological feature, the detection environment parameters and the blood pressure change factor information, and the first blood pressure baseline feature is a reference value corresponding to each physiological feature in the standard human body state. According to the method and the device, the convenience of the wearable equipment is utilized, and the blood pressure change factor information, personalized reference characteristics and other information are comprehensively considered, so that the detection cost is reduced, and meanwhile, the accuracy of health optimization suggestion generation is improved.

The invention provides an intelligent prediction and analysis system for a group health trend, and the system carries out the real-time collection, intelligent analysis and prediction of group health data through a big data technology and an artificial intelligence algorithm, generates a group health trend report, and carries out the health risk assessment. The system comprises a health data acquisition module, a data storage and management module, a health trend analysis module, a group health risk assessment module and a health report output module, can provide an effective health intervention strategy for public health departments and medical institutions, and improves the accuracy and efficiency of group health management. The system can generate a personalized health report according to the real-time health data of a group, and ensures that group members can obtain the latest health state at any time through multi-platform sharing.

The invention provides a personalized health report generation method and device, and relates to the technical field of medical health, and the method comprises the steps: collecting multi-dimensional customer data of a target customer; inputting the multi-dimensional customer data into a disease risk prediction model, performing prediction analysis on customer disease risks, and integrating prediction results to obtain disease risk prediction data; wherein the disease risk prediction model is obtained through pre-training by the following method: respectively constructing initial models corresponding to different data dimensions; according to the historical patient data sample set, carrying out mapping relation training of patient data of corresponding dimensions and disease risks on the initial models corresponding to different data dimensions to obtain disease risk prediction models corresponding to the data dimensions; and fusing the disease risk prediction data and the multi-dimensional guidance data, performing semantic understanding and personalized analysis on fused information based on a large language model, and generating a personalized health report.

The present application relates to the intelligent monitoring and feeding method based on the linkage of pet defecation-diet-health data, and belongs to the technical field of pet intelligent monitoring.The present application comprises the following steps: step one: data acquisition stage, the step one is specifically as follows: S1: defecation information acquisition; S2: food intake information acquisition; S3: image and weight information acquisition; step two: data processing stage, the step two is specifically as follows: S1: pretreatment of the collected information; S2: extraction of image information, identification of feces form; S3: establishment of correlation analysis model, generation of health score; step three: intelligent feeding control stage, the step three is specifically as follows: S1: triggering of feeding; S2: detection of residual amount; step four: health early warning stage, the step four is specifically as follows: S1: triggering of early warning when data reaches an abnormal value; S2: provision of diet adjustment suggestions according to the health report.

The embodiment of the invention provides a health management method and device, equipment, a medium and a product. The method comprises the steps of obtaining activity data and / or work and rest data and heart rate data of a user; determining abnormal items in the activity data and / or the work and rest data and the heart rate data according to a preset health threshold value; performing association analysis on the activity data and / or the work and rest data and the heart rate data, and establishing a first association relationship between the change trend of the activity data and the change trend of the heart rate data and / or a second association relationship between the change trend of the work and rest data and the change trend of the heart rate data; and according to abnormal items in the activity data and / or the work and rest data and the heart rate data and the first association relationship and / or the second association relationship, generating health guidance suggestions, and outputting a health report. Health guidance can be accurately and reliably provided for the user based on the activity data and / or the work and rest data and the heart rate data.

A system (100) for real-time environment monitoring and health tracking is provided. The system includes a wearable mask (110) adapted to fit on a user's face. A sensor unit (120) obtains a plurality of parameters from the user and surrounding environment. A receiving module (150) receives data from a plurality of sensors. A processing module (160) processes the data received from the plurality of sensors by utilizing an artificial intelligence model. A notification module (170) triggers an alert to a user device (270) if the fall detection sensor detects a sudden fall of the user, generates the alert to the user device if abnormal cough patterns are detected. A feedback module (180) transmits a health report of the user to the user device. A tracking module (185) enables the user to locate the wearable mask if misplaced by activating a buzzer positioned in the wearable mask via the user device.

The embodiment of the invention provides a centralized collaborative cluster retry request generation method and device, equipment, a medium and a product, and relates to the field of big data, and the method comprises the steps: dynamically updating a server information list based on health report information, so as to sense the operation state of a server in real time; and the updated state list and the retry application are combined to carry out accurate resource allocation, and finally a retry request containing the number of allocated tokens, a compliance permission identifier and effective time is generated, so that the dynamic coordination of retry request generation, the server state and the service demand is realized; the generation of the retry request can dynamically adapt to the real-time health state of the server and the service priority demand of the client, the retry request generation efficiency and the scene adaptability are improved, and the accurate allocation of the number of allocated tokens ensures that the resource utilization is matched with the load capacity of the server. The design of the permission identifier and the valid time ensures the compliance and validity of the retry request, and improves the generation efficiency of the retry request.

A wearable electronic airway device for wellness-focused and medical-focused application can integrate adjustable mandibular support for OSA management or sensor-based concussion monitoring. Embodiments can include modular sensors (e.g., PPG, accelerometers), AI analytics, and a companion app with health reports for metrics such as sleep duration, restfulness, average SpO2, resilience, and diagnostic thresholds (AHI, impacts). Embodiments thereby can assist with enhancing health outcomes through non-invasive, AI-enhanced technology.

A system is provided.SOLUTION: The system includes a means for acquiring a video image of a face, a means for analyzing the video image of the face to measure biological information, a means for performing voice interaction with a user, a means for analyzing voice data to evaluate a health state, a means for integrating acquired data to perform comprehensive health evaluation, a means for generating a health report, and a means for displaying the generated health report.SELECTED DRAWING: Figure 1

A cardiac monitoring system with sleep and activity correlation is described. In one or more implementations, measurements of a user generated by a wearable monitoring device during an observation period are obtained, the measurements including accelerometer data and electrical potential measurements. Sleep periods and wake periods are detected based on the accelerometer data. Sleep stage classifications and activity level classification are generated based on the accelerometer data during the detected sleep periods. The electrical potential measurements are processed using a machine learning model trained to correlate patterns in the electrical potential measurements to cardiac rhythm classifications. Arrhythmia correlations may be generated and output based on the sleep stage classifications and the activity level classifications and concurrent cardiac rhythm classifications. The arrhythmia correlations may describe temporal relationships between detected cardiac arrhythmias and specific sleep stages of the sleep stage classifications and may be output in a health report.

The application discloses a kind of intelligent application health monitoring method, device and medium, the method includes: starting health monitoring process reads preset configuration parameter, creates corresponding health state queue for each target application according to preset configuration parameter, and records recent reporting timestamp, the preset configuration parameter includes fatal level threshold, maximum historical number, time window length, timeout threshold and warning threshold and serious abnormal threshold of times / time dimension;Receive the current health state uploaded by each target application through health reporting component, the current health state includes discrete level, text description and reporting timestamp;According to current health state, update recent reporting timestamp, and utilize preset configuration parameter to judge the health condition of target application.The application can comprehensively multidimensional index, real-time evaluation application health state, and can be linked with quick recovery mechanism, to improve application high availability and realize quick failure perception and recovery.

In one example, an ambulatory medical device is provided. The ambulatory medical device includes a plurality of subsystems, at least one sensor configured to acquire data descriptive of a patient, a user interface and at least one processor coupled to the at least one sensor and the user interface. The at least one processor is configured to identify subsystem status information descriptive of an operational status of each subsystem of the plurality of subsystems and to provide a device health report for the ambulatory medical device via the user interface, the device health report being based on the operational status of each subsystem.

A cardiac monitoring system with sleep and activity correlation is described. In one or more implementations, measurements of a user generated by a wearable monitoring device during an observation period are obtained, the measurements including accelerometer data and electrical potential measurements. Sleep periods and wake periods are detected based on the accelerometer data. Sleep stage classifications and activity level classification are generated based on the accelerometer data during the detected sleep periods. The electrical potential measurements are processed using a machine learning model trained to correlate patterns in the electrical potential measurements to cardiac rhythm classifications. Arrhythmia correlations may be generated and output based on the sleep stage classifications and the activity level classifications and concurrent cardiac rhythm classifications. The arrhythmia correlations may describe temporal relationships between detected cardiac arrhythmias and specific sleep stages of the sleep stage classifications and may be output in a health report.

The invention relates to the technical field of senile chronic disease management, and discloses a discovery and management system based on senile chronic diseases. The system comprises a health data acquisition module, a risk sensitivity assessment module, a disease risk positioning module, a management instruction generation module and a health report generation module. The health data acquisition module obtains real-time physiological signals through a wearable sensor, and precise multi-scale health features are obtained through layered feature extraction; and the risk sensitivity evaluation module calculates a deviation degree, recognizes an abnormal region and fuses environmental data to generate a sensitivity index. The disease risk positioning module classifies diseases according to indexes, determines high-risk nodes and extracts time sequence data; and the management instruction generation module analyzes the key event and outputs a personalized executable instruction. And the health report generation module receives the feedback data, evaluates the index trend and generates a dynamic report. The system realizes early discovery, fine evaluation and strong intervention of chronic diseases, and improves the management efficiency and the health guarantee level of patients.

Generating resource deployment health report graphs for specific virtual deployments is provided. A resource deployment health report graph that defines each respective resource dependency and a status of each respective resource and each respective dependency resource in a virtual deployment of a container-based environment is generated prior to a plurality of resources corresponding to the virtual deployment being connected in the container-based environment. An analysis of information contained in the resource deployment health report graph is performed. It is determined whether each respective resource and each respective dependency resource in the virtual deployment is in a ready state based on the analysis. In response to determining that each respective resource and each respective dependency resource in the virtual deployment is in a ready state based on the analysis of the information, it is determined that an actual deployment reflected by the virtual deployment is in a healthy state.

Generating resource deployment health report graphs for specific virtual deployments is provided. A resource deployment health report graph that defines each respective resource dependency and a status of each respective resource and each respective dependency resource in a virtual deployment of a container-based environment is generated prior to a plurality of resources corresponding to the virtual deployment being connected in the container-based environment. An analysis of information contained in the resource deployment health report graph is performed. It is determined whether each respective resource and each respective dependency resource in the virtual deployment is in a ready state based on the analysis. In response to determining that each respective resource and each respective dependency resource in the virtual deployment is in a ready state based on the analysis of the information, it is determined that an actual deployment reflected by the virtual deployment is in a healthy state.

The invention relates to the field of medical instruments, and particularly discloses an intelligent health assessment and multi-mode intervention control method for an abdominal diagnosis and treatment instrument, and the method comprises the steps: initializing the power supply of an abdominal belt electronic box; the Bluetooth module controls the electronic box to be connected with the APP; the intervention control module controls and confirms that the conductive silica gel, the graphene heating sheet and the natural moxibustion sheet are normal, and feeds back the result to the APP; the resistance acquisition module acquires eight preset azimuth resistances of the abdomen at regular time to generate a data packet; the Bluetooth module transmits data to the APP; the APP stores data, displays a real-time resistance value and generates an initial health report; the intervention control module controls the conductive silica gel to output low-frequency pulses and the graphene heating sheet to heat according to an APP instruction, after the natural moxibustion sheet is attached, the natural moxibustion sheet is linked with the graphene to keep the basic temperature, and the APP displays parameters in real time; the resistance acquisition module acquires the intervened resistance; and the APP compares the data before and after and makes a change report.