152 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 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 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 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 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 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 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 belongs to the technical field of service management platforms of pension institutions, and provides a digital intelligent journey service management platform for old people in a pension institution, and the platform comprises an old people port which provides a one-key call service reservation function; a service reminding function; a health assessment function; the medical seeking function is facilitated; the footprint function is realized; the nursing end has a calling early warning function; a health assessment function; a doctor-seeing transfer function; and an opinion feedback function. According to the invention, through various functional designs of the elderly port and the nursing end, the service response speed is obviously improved, a personalized health management scheme is provided, nursing resources are reasonably distributed and optimized, potential health problems are predicted and prevented, and comfortable and personalized comprehensive service experience is realized; therefore, the life quality of the old people is effectively improved, the operation cost of a pension institution is reduced, and convenient, accessible, safe, reliable and sustainable development of comprehensive services of the pension institution is promoted.

The present application relates to the technical field of training scheduling, in particular to a basketball training intelligent scheduling system, which comprises a performance deviation analysis module, a health condition evaluation module, a training scheduling adjustment module and a training effect analysis module. The present application analyzes the training performance data of athletes, identifies their specific weaknesses in skills, reasonably evaluates the importance of each skill according to the role played by athletes in the team, sorts the training priorities, ensures the optimal allocation of training resources, discovers health problems or potential injury risks in time by comparing the physiological data of athletes with the average level of athletes in the same position, makes the training adjustment more scientific and safe, continuously monitors the training effect and analyzes the effect, enables the coach to quickly capture possible problems in training, adjusts the strategy in time, effectively avoids excessive or insufficient training, and improves the safety and effectiveness of training.

Systems and methods for diagnosing a user's condition based on his gait. A sensor module with multiple sensors is placed inside a user's shoe and biometric data is gathered from the sensors when the user takes a step or walks. The data is used to generate loops as the various sets of data is plotted against each other. The loops obtained from the data are then compared against stored loops previously obtained. Based on the results of the comparison, the user's condition is diagnosed using predetermined indicators of specific health issues. Using the biometric data and in conjunction with data from various databases, it can be determined whether the user has a specific condition, whether a specific condition is worsening, or whether a specific condition is improving.

A method includes contacting one or more volatile organic compounds (“VOCs”) evolved from a sample to one or more detection regions configured for sensitivity against one or more VOCs. The contacting causes a change to the detection regions that is visible to the human eye. The method also includes determining the presence or absence of a VOC by comparing the change to the detection regions to a key, with the key being a visible change. A system utilizing the method is also described.

The invention discloses a user health state recognition method and system based on an intelligent wearable device, and relates to the technical field of wearable health monitoring, and the method comprises the steps: S1, carrying out the real-time data collection of a multi-dimensional physiological signal through a built-in sensor of the wearable device, and obtaining a preliminary multi-dimensional signal data set, S2, carrying out the recognition of the health state of a user according to the preliminary multi-dimensional signal data set, s3, constructing a signal synchronous acquisition framework for the processed unified signal data set, carrying out alignment verification on different signals through timestamp marks, if a time deviation is found to exceed a preset threshold value, carrying out interpolation completion on related signals, and if the time deviation is found to exceed the preset threshold value, carrying out data synchronization on the related signals. Acquiring a signal set after synchronous calibration; according to the user health state identification method and system based on the intelligent wearable device, accurate evaluation and personalized feedback of the user health state are realized, and health problems can be found in time and intervention measures can be taken.

The invention relates to the technical field of intelligent robots, in particular to a monitoring method and device for safety and health of home elderly and an intelligent robot system. According to the method, sensor data are acquired in real time, and the next step is executed when numerical values are abnormal; acquiring physiological data, and judging whether the physiological data is changed or not; acquiring an image of a position where the old person is located, inputting the image into a tumble monitoring convolutional neural network model, extracting features, and generating a tumble vector set; according to the tumble vector set, judging whether the old person is in a tumble state or not; performing language interaction, inquiring whether help is needed or not, if an instruction is received, executing the instruction content, and ending the process; if the instruction is not received beyond the set threshold time, entering the next step; entering an exception handling process, contacting an emergency contact person, ending if the contact is successful, and entering the next step if the contact is not successful; and starting an alarm unit, and dialing 110. According to the invention, accidents and health problems possibly occurring in the elderly living alone are solved.

The invention relates to the technical field of breeding, in particular to a three-dimensional pig health monitoring method and system based on deep learning, which replace traditional subjective observation depending on artificial experience through automatic acquisition of an inspection robot and real-time analysis of edge calculation, and realize 24-hour uninterrupted and objective monitoring of pig health conditions. Specifically, video, audio and environmental data are subjected to multi-dimensional fusion analysis by using deep learning, and abnormal behaviors, cough indexes and environmental risks of pigs can be accurately and timely identified, so that potential health problems can be found in an early stage, and the automation degree of monitoring, the timeliness of early warning and the accuracy of judgment are remarkably improved; manual dependence and misjudgment risks are effectively reduced, and an efficient and low-cost intelligent solution is provided for disease prevention and control and health management of large-scale breeding.

A technique to monitor device health of endpoints in a VLAN is disclosed. A security appliance is set as the default gateway for intra-LAN communication. Message traffic is analyzed and anomalies are detected relative to normal message traffic that correspond to device health problems that may require service by a field technician.

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 utility model provides a personalized drinking liquid management device used after a weight loss metabolism operation, which relates to the technical field of medical instruments and comprises a bottle body, a bottle cap and a drinking cup. The bottle body is used for storing quantitative liquid according to a postoperative drinking liquid management scheme; the bottle cap is detachably mounted at a bottle opening of the bottle body and is used for opening and sealing the bottle body; the drinking cup is detachably installed on the top of the bottle body and used for containing liquid with the single drinking amount for drinking. A color-changing temperature-measuring patch is attached to the outer side of a cup body of the drinking cup, and the color-changing temperature-measuring patch is arranged at the bottom of the drinking cup and used for detecting the temperature of liquid in the drinking cup. The individual drinking liquid management device used after the weight loss metabolic surgery can assist patients under different conditions in executing respective postoperative drinking liquid management schemes, health problems caused in the postoperative rehabilitation process of the patients are avoided, and meanwhile cleaning is convenient.

The invention discloses an adjustable nursing bed which comprises a base and a mounting frame, a first stabilizing plate is arranged above the mounting frame, a drooping block is fixedly connected to the side face of the first stabilizing plate, the drooping block is rotationally connected with a third stabilizing plate, shaft columns are symmetrically arranged above the third stabilizing plate, the shaft columns are rotationally connected with a shell, and thin rods are fixedly mounted in the shell. According to the invention, the health problems of amyotrophy, soreness of waist and back pain, bedsore and the like caused by long-term lying in bed are solved, on one hand, a patient can drive the lower limbs to move by treading the pedal, and meanwhile, a back massage structure and a second cam are linked to rotate, so that the pressure on the muscles of the lower back can be relieved, and the blood circulation of the limbs can be promoted; on the other hand, the treading action can trigger the fan blades to rotate, air is blown to the buttocks through the breathable plate to cool the buttocks, dynamic pressure reduction and breathability are achieved in combination with the air circulation design, and the occurrence risk of bedsores at the parts such as the sacrococcygeal region and the heels is effectively reduced.

An object of the system according to the embodiment is to monitor the behavior of a pet, detect a health problem, and take appropriate measures.SOLUTION: A system includes a Web camera, a behavior analysis part, a health detection part, a nutrition management part, and an emergency call part. The web camera monitors the behavior of the pet. The action analysis part analyzes video data acquired by the Web camera. The health detection unit detects a health problem based on the data analyzed by the behavior analysis unit. The nutrition management unit supports daily nutrition management based on the health problem detected by the health detection unit. The emergency call unit automatically transmits an emergency call in an emergency.SELECTED DRAWING: Figure 1

The invention relates to the technical field of medical health information, and particularly discloses an esophageal cancer postoperative rehabilitation education strategy construction method and system based on a knowledge graph. A field ontology model fused with a diet tendency entity is constructed, a structured postoperative rehabilitation knowledge graph is created, a patient rehabilitation state model is designed, evaluation and tagging processes of individualized diet tendency jointly influenced by genetic and environmental factors are particularly integrated, and an educational strategy matching engine is used for matching the individualized diet tendency with an educational strategy. And according to the patient multi-dimensional state instance including the diet tendency label, activating the corresponding matching rule, intelligently retrieving and filtering the education content which not only conforms to the current rehabilitation stage and health problem, but also adapts to the specific diet tendency from the knowledge graph, and finally integrating to generate a highly personalized rehabilitation education strategy. According to the invention, the conversion from universal education to precise and individualized guidance is realized, and the pertinence and practicability of rehabilitation education are remarkably improved.