194 results about "Health problems" patented technology

The invention relates to the technical field of health management, in particular to a psychological risk early warning method and system based on multi-dimensional emotion data of a user. The method comprises the following steps: acquiring user multi-dimensional emotion data corresponding to a user emotion expression image, a user emotion voice signal and a user emotion physiological index, and performing multi-source time sequence alignment processing on the user multi-dimensional emotion data to obtain user multi-dimensional time sequence synchronous emotion data; an emotion three-level feature extraction framework is constructed, modal emotion feature extraction and cross-modal fusion are carried out, and cross-modal fusion psychological features of the user are obtained; and obtaining user environment data and user social network data, and performing emotional psychological dynamic graph reasoning and psychological risk early warning on the user cross-modal fusion psychological features based on the user environment data and the user social network data to generate corresponding user emotional psychological risk early warning response measures. According to the invention, early recognition and intervention of psychological health problems can be realized.

The invention relates to the technical field of health early warning, in particular to a human health early warning method and system based on physical examination data analysis, which comprises the following steps: collecting physical examination data of a human body, analyzing index changes of blood pressure, blood sugar, cholesterol and body mass index of the human body, sorting the physical examination data of the human body through time sequence sorting, and generating a time sequence sorting result. According to the method, time sequence sorting and spatial dimension evaluation are performed on the physical examination data, so that the health risk can be accurately identified and the early warning level can be dynamically evaluated, the data analysis precision is improved, the risk prediction dimension is increased, early warning is more timely and accurate, and the accuracy of early warning is improved by performing layout evaluation on the physical examination data points in a finite dimension space. Potential health abnormalities can be identified on multiple levels, and multi-dimensional analysis provides a new way for identifying complex health problems, so that health management is more active and predictable, health monitoring and risk management are optimized, and the health condition of a patient is improved.

The invention provides a pet health monitoring method, device and equipment, a medium and a product, and is applied to the technical field of pet health management.The method comprises the steps that pet monitoring data of multiple modes is acquired; fusing the pet monitoring data of the multiple modes to obtain fused monitoring data, and analyzing the fused monitoring data by adopting a large model to obtain a health analysis result corresponding to each mode; according to a health analysis result, determining a health anomaly probability corresponding to each mode, and performing weighted summation on the health anomaly probabilities by adopting weight information corresponding to each mode to obtain a health risk value; according to the health risk value, pet health early warning is carried out, pet health monitoring is carried out according to the data of multiple modes, the requirements for comprehensive monitoring and early warning of pet health are met, the pet monitoring data of multiple modes are fused and analyzed through a large model, and the requirement for accurate recognition of potential health problems of pets is met.

A network management system (NMS) configured to attribute a health issue of an access point (AP) to a classifier or sub-classifier and remedy the health affecting a user's experience. The NMS obtains network data associated with an AP device of a site. The NMS also determines whether the network data satisfies one or more criteria corresponding to a classifier of a service level expectation (SLE) metric for determining a health issue of the AP device. In response to determining the network data does not satisfy the criteria associated with the classifier, NMS attributes the health issue of the AP device to the classifier. In response to attributing the health issue of the AP device to the classifier, NMS performs a remedy action based on the classifier.

The invention provides an intelligent underwear data processing method and system based on artificial intelligence. The method comprises the steps that intelligent underwear collects physiological and environmental data of a user through a built-in sensor; the edge computing chip preprocesses the collected data to obtain first data, performs sensitivity grading marking to obtain second data, performs processing according to sensitivity grades to obtain third data, and selects fourth data needing to be uploaded from the third data; the server receives and decrypts the fourth data, integrates the multi-source data according to a timestamp to construct a health data set, inputs a preset model for analysis, and sends a result to the intelligent underwear; the edge computing chip provides health suggestions through a feedback device according to the analysis result, and collects a user feedback optimization model; and the server simulates the health state of the user by using a digital twinning technology, predicts the health problem and formulates a management scheme. According to the invention, the accuracy of intelligent underwear data analysis is improved, and the security and privacy protection of the user data in the transmission and processing process are enhanced.

The invention relates to the technical field of intelligent inquiry, in particular to a hospital intelligent inquiry method and system based on natural language processing, and the method comprises the following steps: based on the input text of a patient, analyzing the relation between text content and medical terms, identifying key symptom description, carrying out term adaptation, correcting context errors, and obtaining a context adjustment result. According to the method, the adaptation degree and correlation of medical terms are evaluated through accurately analyzed data, it is ensured that deduced medical suggestions are highly matched with patient symptoms, in the aspect of physical parameter analysis, through real-time monitoring and fluctuation analysis of physiological indexes of patients, health risks can be recognized earlier, medical responses can be adjusted in time, and the medical treatment effect is improved. Not only is the workload of medical staff relieved, but also the individuation level and efficiency of medical services are improved, and remarkable advantages are provided for accelerating the inquiry process and accurately positioning the health problem.

The invention relates to the technical field of water quality monitoring, in particular to a distributed raw water quality real-time monitoring system which comprises an underground water sampling module, a sample analysis module, a water quality feedback terminal and a data storage terminal. And finally, the water body quality corresponding to the underground water quality in the target raw water body area is fed back to a system interface for interface display, the water quality evaluation can guarantee the safety and sustainability of the water resource, and the water quality evaluation efficiency is improved. Health risks and economic losses caused by water quality pollution are avoided, and underground water quality evaluation has direct influence on public health. Various health problems may be caused by drinking or using the water for a long time, the drinking water safety of residents can be guaranteed, health risks can be found and treated in time, and therefore the health of the residents is protected.

The invention provides a system and a method for cow health early warning, which are applied to the technical field of animal husbandry health monitoring, perform individual identification and behavior recording by collecting cow activity data, environmental parameters and management operation data, analyze a behavior mode and identify health problems in combination with environmental management data, and have the advantages of realizing automatic monitoring and improving the efficiency of cow health early warning. Non-contact data acquisition, individual identification, individual behavior recording, integration of environment parameters and management event data, analysis based on behavior and environment management data, identification and indication of a behavior mode of a health problem, and early health early warning are realized.

The embodiment of the invention provides a nurse station ward information collection method and system based on a wireless network. A flexible electronic skin network is integrated in a patient mattress, pressure and temperature data are captured through distributed piezoresistive units, a multi-modal thermodynamic diagram is generated, and data synchronization is achieved through a wireless ad hoc network protocol. And driving an air cushion bed actuator to perform gradient compensation according to a matching result of the pressure gradient track and the physiological parameters, transmitting a compressed hierarchical data packet to a nurse station gateway by adopting a remote wide area network protocol, reconstructing a three-dimensional pressure model and generating an early warning instruction. According to the technical scheme provided by the embodiment of the invention, the occurrence probability of health problems such as bedsore caused by long-time bed lying is remarkably reduced, and the nursing quality of the patient is improved.

The invention relates to the technical field of health management, and discloses a health state determination method and system and a program product. The method comprises the following steps: acquiring physical physiological data and physical environment data of a monitored person; matching the physical and physiological data with the physical environment data according to the time attribute and the space attribute, and determining an association relationship between the physical and physiological data and the physical environment data; and based on the association relationship, performing data processing on the physical physiological data and the physical environment data locally to generate health state information. By implementing the technical scheme of the invention, the health problem of the monitored person can be found in time, and the health state information is generated.

The invention relates to a historical building-oriented real-scene three-dimensional GIS-based health monitoring data prediction method, and belongs to the technical field of building monitoring, and the method comprises the steps: obtaining modeling data and monitoring data, and constructing a building geometric model based on the modeling data; matching the monitoring data with the building geometric model so as to map the monitoring data to a corresponding position of the building geometric model; based on a preset prediction and early warning model, learning the monitoring data, and predicting and outputting the change trend of the monitoring data in a specified time period in the future; and analyzing monitoring data corresponding to the building geometric model based on a pre-constructed health analysis model, and outputting a structural damage assessment result of the building geometric model. The method has the advantages that the historical building is efficiently monitored, potential health problems of the historical building are found in time, and the maintenance efficiency of the historical building is improved.

The invention particularly relates to an old people health condition monitoring system based on a wristband oximeter. The system comprises a state determination module; a motion index module; a fatigue index module; and an analysis processing module. According to the system, the wrist strap type oximeter obtains the exercise step number, monitors key physiological parameters such as the blood oxygen saturation degree, the pulse rate and the perfusion index, and deeply analyzes the parameters in different exercise states to obtain the exercise index, the fatigue index and the cooperation index, so that the multi-dimensional comprehensive monitoring of the health condition of the old people is realized; the physical state of the old people can be reflected more accurately, and potential health problems can be found in time.

The invention provides a health education resource RPA interaction system and method based on a knowledge graph, and the system comprises a multi-source data fusion module which is used for summarizing health data of medical literatures, electronic cases and monitoring equipment, calling a pre-training model for entity recognition and relation extraction, and constructing a dynamically updated health knowledge graph; the RPA process management module is used for generating an automatic process according to the health knowledge graph and allowing a user to dynamically adjust a generation rule; the multi-modal interaction module provides texts, languages and / or visual charts for the user for real-time interaction according to the generated automatic process; and the feedback optimization module is used for optimizing the knowledge graph and the RPA process according to the user behavior log. According to the invention, the RPA system is combined with the AI, the health problem of the patient is intelligently analyzed, task scheduling is automatically carried out, personalized and accurate health education service is provided, and the intelligence and practicability of health education are improved.

The invention discloses a health information management platform for an inflammatory bowel disease patient. The health information management platform comprises the following steps: step 1, user registration and information input; 2, data preprocessing and feature extraction; 3, constructing and training a model; step 4, a real-time prediction and early warning mechanism; according to the scheme, by actively monitoring the health data of the patient and applying the real-time analysis capability of the machine learning model, potential health problems can be recognized in advance, timely early warning is achieved, the risk of acute symptom attack is reduced, and therefore the life quality of the patient is improved, multi-dimensional data analysis is utilized, and the accuracy of the patient is improved. Customized health management suggestions are provided for each patient, individual requirements of the patient are met, the control ability of the patient to the illness state of the patient is enhanced, the treatment effect is improved, the system can provide more basis treatment suggestions for doctors through continuous learning and optimization, clinical decisions are helped to be improved, and the accuracy and effectiveness of overall treatment are improved.

The invention relates to the technical field of health education, and particularly discloses a digital one-stop health education platform based on artificial intelligence and a construction method thereof, and the platform comprises a health data management module which is used for collecting health data of a user from a plurality of data sources, and automatically generating a health file of the user in combination with personal health information inputted by the user; the health portrait generation module is used for generating a personalized health portrait based on the health file, and performing personalized demand analysis according to the health portrait in combination with a target set by a user; according to the invention, based on the established health portrait, customized health education content is obtained according to personal requirements, and a health scheme is adjusted at any time according to health data changes, so that individuation and dynamics of health management are ensured; the user can ask questions at any time to obtain real-time health guidance and professional suggestions; by means of artificial intelligence and big data analysis, the health trend can be predicted, early warning can be given out when potential health problems are found, and effective health intervention measures are provided.

The invention discloses an exercise health monitoring method and system of a smart watch, and relates to the technical field of smart watches, and the method comprises the steps: carrying out the time synchronization of continuous data, and enabling all monitoring indexes to be aligned on the same time axis; carrying out real-time analysis and anomaly detection on the heart rate and blood oxygen saturation data by utilizing a machine learning algorithm; the heart rate variability index of the user is evaluated, the blood oxygen saturation data and the body surface temperature data are integrated, and a pressure evaluation model is constructed; in combination with height and weight information input by the user, constructing a deep learning model to identify a motion mode of the user; the heart rate and blood oxygen health indexes of the user are tracked and analyzed by utilizing a time sequence analysis technology, the future health trend is predicted, and potential health problems are explored. By arranging the data prediction module, the heart rate, blood oxygen and other health indexes of the user can be tracked and analyzed, the future health trend is predicted, and potential health problems are explored.

The present invention relates to the field of power grid monitoring technology, and specifically discloses a distributed power grid node health monitoring and prediction method, the method comprising: obtaining distributed power grid nodes, marking them as each power grid node, and obtaining health monitoring data of each power grid node; processing the equipment status data to obtain the equipment status abnormality evaluation index of each power grid node, and comprehensively analyzing to obtain the data accuracy evaluation value of each power grid node; screening to obtain each normal monitoring power grid node according to the data accuracy evaluation value of each power grid node; and providing evaluation feedback according to the health status evaluation value of each normal monitoring power grid node. By providing a distributed power grid node health monitoring and prediction method, the present invention can timely discover and handle health problems of power grid nodes, help prevent power outages or safety accidents caused by equipment failures, can more reasonably allocate power resources, improve the operating efficiency of the power grid, and help provide better power output and stability.

The invention discloses a mental stress assessment and intelligent dredging method and system, and belongs to the technical field of digital medical treatment and health informatics. Multi-modal physiological signals are continuously collected through the wearable device, medical diagnosis level pressure state evaluation is carried out based on the personalized physiological baseline, and personalized pressure indexes and levels are generated; secondly, when it is diagnosed that the pressure level exceeds the standard, the system serves as an intelligent decision support system, the environment and schedule information after privacy protection processing is fused, and an optimal grooming action is dynamically selected from a predefined intervention action library and executed; finally, the system serves as a continuous learning system, the intervention efficiency is evaluated in real time according to feedback data of the pressure index after execution, the decision model is updated, and collaborative self-optimization of the diagnosis strategy and the intervention strategy is achieved. According to the method, medical diagnosis, personalized treatment decision and adaptive learning are integrated, and the systematicness, accuracy and intelligent level of mental stress related health problem management are improved.

The technology disclosed herein provides a digital health privacy platform (Platform) and digital health passport (Passport) that together equip consumers to avoid unauthorized surveillance as they engage with their many authorized and variously located healthcare providers in information exchange and transactions for healthcare goods and services across episodes of care for diverse health problems while managing health-related self-maintenance, legal and financial matters.

The invention discloses a household collaborative nursing management system for diabetic sleep disorders and an implementation method, relates to the technical field of nursing management, and aims to automatically establish and adjust a layered nursing structure according to health data of a patient, realize correlation analysis among multiple targets, ensure that the most urgent health problem is effectively intervened firstly, and improve the nursing efficiency. The information collaboration degree is utilized to fuse related data of a plurality of nursing targets, accuracy and high efficiency of the data are ensured, so that treatment and nursing strategies are optimized, mutual support and coordination of various nursing targets are ensured, conflicts among targets in a traditional treatment scheme are avoided, dynamic adjustment is carried out through a self-adaptive optimization algorithm, and the treatment efficiency is improved. According to the health state change of the patient, the nursing scheme is adjusted in real time, it is guaranteed that the patient can obtain personalized and continuously-optimized nursing management, the treatment effect of diabetes and sleep disorder dual management is remarkably improved, and the life quality and treatment compliance of the patient are improved.

The present invention relates to the field of health management technology, and in particular to a psychological risk warning method and system based on user multi-dimensional emotional data. The method comprises the following steps: obtaining user multi-dimensional emotional data corresponding to user emotional expression images, user emotional voice signals, and user emotional physiological indicators, and performing multi-source time series alignment processing on the user multi-dimensional emotional data to obtain user multi-dimensional time series synchronized emotional data; constructing a three-level emotional feature extraction architecture and performing modal emotional feature extraction and cross-modal fusion to obtain user cross-modal fusion psychological features; obtaining user environmental data and user social network data, and performing emotional psychological dynamic graph reasoning and psychological risk warning on the user cross-modal fusion psychological features based on the user environmental data and user social network data to generate corresponding user emotional psychological risk warning response measures. The present invention can achieve early identification and intervention of mental health problems.

The invention relates to the technical field of big data analysis and community old-age service management, in particular to a community old-age service management method based on big data, which comprises the following steps: step 1, collecting basic information of old people; step 2, a data storage and integration module; step 3, a data analysis module; step 4, a service resource configuration module; step 5, a service supervision and feedback module; by collecting and analyzing big data information such as living habits, physical conditions and medical service requirements of the elderly, personalized elderly care service scheme customization can be realized, the pertinence and effectiveness of the service are effectively improved, the health risk degree of the elderly is evaluated, the influence degree of different factors on the health risk is determined through big data analysis, and the health risk management efficiency is improved. The health problem of the old people can be found and processed in time, the life quality and happiness of the old people are improved, meanwhile, the nursing burden of families and society is relieved, and the community nursing service is more user-friendly and intelligent.

The invention relates to the technical field of mental health management, in particular to a mental health intervention effect assessment method and system. Collecting demographic basic information, psychological health problem types, psychological state improvement evaluation values before and after intervention and intervention feature information of each intervention object; for any intervention object, screening a historical intervention object matched with the intervention object from a historical intervention database as a reference object according to the demographic basic information, the psychological health problem type and the intervention feature information of the intervention object; calculating a deviation difference value between the psychological state improvement evaluation value of the intervention object and the psychological state improvement evaluation value of the reference object, comparing and judging the deviation difference value based on a preset deviation threshold value, and judging whether the intervention object is a suspected effect abnormal object or not; and for any suspected effect abnormal object, obtaining intervention behavior data during the intervention period.

The invention discloses an intelligent nursing monitoring system for health care, and belongs to the technical field of intelligent nursing. The intelligent nursing monitoring system for health care comprises a monitoring module, an analysis module, an early warning module and a mobile terminal. According to the system, the problems that in the prior art, comprehensive and intelligent monitoring cannot be carried out on the dangerous condition of a household nursed object, and then all-weather health condition analysis and alarm cannot be carried out are solved, and the AI camera and the millimeter wave radar are used for carrying out real-time data acquisition; any expression change or limb movement of the nursed object can be captured in time, health problems can be found and processed in time, the safety of the nursed object is guaranteed, and an alarm signal is sent out in time when it is monitored that the health state of the nursed object is abnormal. It is ensured that family members or nursing personnel of the nursed object can rapidly receive the abnormal information and take corresponding countermeasures, and the safety and health of the nursed object are effectively guaranteed.

The invention relates to the field of cold-proof equipment, and particularly discloses high and cold protection heating equipment with a physiological monitoring structure, which comprises a wearable heating garment, a waterproof heat preservation layer is arranged outside the wearable heating garment, a heating layer is arranged inside the waterproof heat preservation layer, and a fireproof layer is arranged inside the heating layer; the physiological health monitoring module is arranged in the wearable heating clothes and used for detecting and recording real-time physiological health data of a wearer, and the real-time physiological health data include but not limited to heart rate, blood pressure and body temperature; key physiological data such as the heart rate, the blood pressure and the body temperature of a wearer can be monitored and recorded in real time through the built-in physiological health monitoring module, and the data have important significance in evaluating the health condition of the wearer and finding potential health problems in time; abnormal changes of the physiological data may indicate that the wearer faces a health risk, and at the moment, the equipment can remind the wearer or related personnel to take necessary measures through an early warning system.

In the homes where elderly people are accustomed to living, the knee joints are subjected to a lot of stress when going up and down stairs, especially when going down them, which causes frequent falls and can lead to serious health problems such as fractures, hospitalization, and even becoming bedridden or experiencing the progression of dementia. [Solution] Hydraulic bags containing hydraulic oil are placed under the treads of each staircase, and the hydraulic bags are connected to each other by hoses with control valves. When the operating lever inside the handrail is gripped, the wire opens the control valve, and the hydraulic oil is pushed out by the user's weight, causing the treads to descend. The pushed-out hydraulic oil is injected into an empty hydraulic bag container on the floor below, causing the treads on the lower floor to rise and be at the same floor height. This provides an inexpensive, non-powered elevator "specialized for descending," allowing users to easily descend to the floor below without bending their knees.

The invention discloses a method and a system for processing comprehensive health assessment data of old people based on digital twinning, and relates to the technical field of data processing, the method comprises the following steps: fusing multi-source health data of a target old people group, establishing a health knowledge graph, and storing the health knowledge graph; constructing a digital twinborn health model based on the health knowledge graph, performing a simulation test in the constructed digital twinborn health model, and identifying health risks existing in the health data; calculating the health feature similarity between the target elderly group and the reference group by using a similarity algorithm; and analyzing health problem risks existing in the target elderly group by using the health feature similarity, and making a comprehensive health assessment report based on an analysis result. According to the method, the health knowledge graph is established by fusing the multi-source health data, and the digital twinborn health model is constructed, so that the quality and comparability of the data are improved, and a solid foundation is provided for subsequent simulation tests and risk identification.

The invention provides a method and a system for reading human body pulse health data based on a face video. The method comprises a method for reading the human body pulse health data and a pulse condition health intelligent detection system. The invention discloses a method for reading human pulse health data based on a face video. The method comprises the steps of S1, collecting the video, S2, positioning and tracking an area of interest, S3, extracting a photoelectric volume pulse wave PPG original signal, S4, carrying out pulse wave signal denoising processing, S5, carrying out pulse wave signal feature analysis, S6, carrying out a mixed feature selection algorithm, S7, carrying out optimal feature classification, and S8, outputting a pulse condition classification analysis result. The pulse condition health intelligent detection system comprises a physiological acquisition layer, a signal transmission layer, a cloud server layer and an application interaction layer. The method is convenient and fast to operate, can visualize the physiological indexes such as the pulse condition of the human body, helps a user of the health detection system to conveniently and timely know the own physiological health condition and timely see a doctor for treatment under the condition that the body has a health problem, and reduces the delay of an illness state.

The invention provides a wireless link automatic scheduling method based on equipment health diagnosis, and the method comprises the steps: creating a wireless link resource queue which comprises integrated channel terminal waveform information and antenna module information in an antenna matrix; performing health prediction on the integrated channel terminal waveform information and the antenna module information in the antenna matrix by using a pre-constructed health diagnosis model to obtain a health level value; and under the condition that the health level value is smaller than a threshold value, acquiring an idle wireless link of which the health level value is greater than or equal to the threshold value from the wireless link resource queue as a current link. According to the method, the problems that the health problem of the wireless link equipment in the wireless channel integration environment is difficult to check, the link scheduling efficiency is low and the like can be solved.

The invention relates to the technical field of ship control, in particular to a ship display and control console carrying an intelligent bracelet and a control method of the ship display and control console. The intelligent bracelet is used for monitoring the health state of a warship member in real time, the health state comprises physiological data and sensory data, and the intelligent bracelet is in wireless communication connection with a display control computer through a Bluetooth interface; the control unit is used as a device for interaction between a ship crew and the display and control console, and the control unit is in communication connection with the display and control computer; the display control computer is used for receiving and processing the physiological data and the sensory data and sending the processed data to the display; the display is used for displaying the processed data; and the power supply control unit is used for supplying power to the display control computer, the display and the control unit. According to the invention, by carrying the smart bracelet and adopting a falling-into-water detection and smart bracelet clustering method, real-time monitoring of the health state of the ship crew is realized, timely health data is provided for a ship commander, the health problem of the ship crew can be prevented and dealt with, and the combat effectiveness of the ship is improved.