135 results about "Aging care" patented technology

The invention discloses an emotional interactive intelligent nursing system and method based on multi-modal perception, and belongs to the technical field of intelligent medical treatment and intelligent old-age care crossing. The matrix type pressure sensor array is integrated in the nursing mattress, multi-point pressure distribution of the body of the old people on the bed surface is obtained in real time, and high-resolution body pressure mapping is achieved. Compared with an existing single-point type or linear pressure monitoring structure, the system can accurately recognize the spatial position of a local pressed area, and early recognition and quantitative evaluation of a bedsore risk area are achieved. By fusing the pressure matrix, the heart rate, the blood oxygen, the environment temperature and humidity, the urine wetting and other multi-mode sensing data, the monitoring dimension is remarkably expanded, the health condition can be comprehensively evaluated from multiple physiological indexes, compared with a single physiological parameter monitoring mode, the more comprehensive information obtaining capacity is achieved, and the monitoring precision and the nursing efficiency are effectively improved.

The invention relates to the technical field of old-age care monitoring, and discloses an intelligent old-age care monitoring method and system based on wearable equipment. According to the method, original physiological data such as heart rate signals, oxyhemoglobin saturation and body movement frequency are collected through a plurality of wearable devices, multi-modal feature extraction is conducted on the original physiological data, and a physiological feature vector set is generated. A to-be-analyzed health event sequence containing a periodic abnormal mode and a non-periodic burst mode is screened out, and a health knowledge base is called to retrieve a matched candidate health event entry set. And inputting the two health events into a health event aggregator for cross-modal semantic fusion analysis, generating a health event decision coding matrix, obtaining an intervention measure instruction set for each health event to be analyzed through hierarchical decoding, and finally generating a response operation queue executable by the pension monitoring terminal. According to the method, the health condition of the old people can be comprehensively and accurately monitored, intervention measures can be timely and effectively provided, and the quality and efficiency of old-age care monitoring are greatly improved.

The invention discloses an old people fall monitoring and multi-terminal linkage emergency response system, and relates to the technical field of medical treatment, and the system comprises the steps: carrying out the non-inductive collection of human body dynamic information in a weak light visual blind area environment; the voice interaction verification judgment module comprises a far-field voice excitation unit; and setting a priority queue management mechanism, and confirming a behavior perception output tumble instruction. According to the invention, closed-loop management of fall monitoring and emergency treatment of the old people is realized, and the system has remarkable beneficial effects; the privacy of the user is effectively protected, and the false alarm rate and the invalid scheduling of nursing resources are obviously reduced; the event discrimination accuracy and the individual suitability are improved, and it is ensured that high-risk events are not missed; the timeliness and accuracy of emergency response are improved, and safe, intelligent and humanized technical support is provided for intelligent old-age care and home health monitoring.

The invention discloses a nursing scene data enhancement and generation method for intention recognition model training, and belongs to the technical field of artificial intelligence and smart old-age care. The method aims at solving the problems that in the prior art, high-quality nursing scene training data is deficient, and the obtaining cost is high. According to the core technical scheme, the method comprises the steps that firstly, a staring sequence and other context information (such as time, place and physiological signals) of a user are processed through a multi-modal information fusion model, and a structured initial situation vector is generated; secondly, inputting the vector into a scene generation model combined with a nursing knowledge base, and automatically generating a batch of basic nursing scene data with intention labels; key points are that a data enhancement module is introduced, and a plurality of innovative strategies such as situation element disturbance, virtual physiological data synthesis, gaze path variation and virtual scene deduction are adopted to deeply process basic data, so that the diversity and complexity of a data set are greatly enriched; and finally, combining the basic data with the enhanced data to construct a final comprehensive training data set. According to the method, large-scale and high-fidelity training data can be generated in a low-cost and high-efficiency manner, and the accuracy and robustness of the intention recognition model in a real nursing environment are remarkably improved.

The invention belongs to the technical field of smart old-age care product behavior debugging, and particularly discloses a smart old-age care product behavior dynamic adjustment method based on interactive data perception. According to the method, a sole mechanical fragment, a lower limb movement fragment and a heart rate fragment are extracted based on gait cycle alignment, gait stability, gait coordination and physiological conformity indexes are calculated, and coupling sensing of user movement behaviors and physiological states in the dynamic walking assisting process is achieved; the gait stability and the physiological conformity are fused to construct a gait physiological synchronism criterion, a hierarchical adaptive control strategy is implemented accordingly, and the limitation that a traditional supporting robot only depends on kinematics feedback control is broken through, so that on the premise that the user safety is guaranteed, response type physical and mental collaborative intelligent assistance is achieved, and the user experience is improved. And the risk prevention and control capability of rehabilitation training is effectively improved.

The invention provides a big-data-based Alzheimer's disease old-age care platform management method and system, and relates to the technical field of old-age care platform management.The method comprises the steps that patient behavior data information is received, missing data points are deduced according to pre-stored patient behavior file historical behavior pattern data and patient behavior data information, and the missing data points are sent to a server; by evaluating the reliability degree of the event chain and comparing the event chain with a dynamically generated reliability evaluation threshold value, when a comparison result reaches an early warning standard, early warning information with a reliability quantitative index is generated, and the problem that an existing platform is poor in reliability under a non-ideal operation condition is effectively solved. The problems of reliable transmission and accurate interpretation of key information are solved, and early warning failure caused by data deviation or missing is avoided, so that the nursing quality and safety of the Alzheimer's disease patient are remarkably improved, and the optimal time for early intervention and intervention is provided for nursing personnel.

The invention relates to the technical field of artificial intelligence, and discloses a man-machine cooperation-based old-age care practical training evaluation system, which comprises a sensor, data preprocessing, feature extraction and fusion, clustering analysis and practical training evaluation. According to the system, capability group division is realized under double constraints of an interactive structure and attribute similarity by using a double-graph diffusion-contour weighted K-Means clustering method; in combination with a GNN-Transformer model, through joint asymmetric loss function optimization formed by cross entropy, focus loss and passive asymmetric q-norm loss, cross-modal and time-sequence-dependent deep modeling is realized, and multi-dimensional evaluation indexes such as standardization, proficiency and humanistic care degree are output; finally, the evaluation result is visualized and fed back through a human-computer interaction interface, a perception-analysis-feedback-improvement collaborative closed loop is formed, and the scientificity and guidance of nursing training of the aged are improved.

The invention discloses an intelligent community health care monitoring system based on cloud computing, relates to the technical field of intelligent community health monitoring, and aims to solve the problems of difficulty in multi-source heterogeneous data fusion, insufficient real-time performance and remarkable service response delay. The system comprises a multi-modal data acquisition terminal, a data fusion and preprocessing gateway, a core intelligent analysis engine and an interactive response terminal, and efficient and accurate health monitoring and early warning are realized through standardized fusion of multi-source data and behavior pattern recognition and hierarchical risk assessment based on deep learning. And the pension service response efficiency and reliability are obviously improved.

The invention relates to the technical field of old-age service management, in particular to an integrated old-age service management system based on end-cloud collaboration, and aims to solve the problems that in the prior art, multi-source data of physical signs, medication and living habits cannot be integrated to predict the health change trend, abnormal fluctuation of four high cannot be perceived in advance, short-term risks cannot be pre-judged, and the service quality is poor. And a personalized intervention scheme cannot be formulated in combination with reinforcement learning. Multi-source data of physical signs, medication and living habits are integrated through the chronic disease management module, LSTM is used for predicting the health change trend, four-high abnormal fluctuation is perceived in advance, short-term risks are pre-judged, a personalized intervention scheme is formulated in combination with reinforcement learning, diet and exercise suggestions and medication reminding are covered, and the system has the advantages of being simple in structure and convenient to use. User compliance is improved by outputting custom prompts through natural languages, the system forms a complete closed loop, the system is suitable for long-term management of diabetes and hypertension diseases, the risk of acute events is reduced, and the self-management ability of patients is enhanced.

The invention discloses an intelligent old-age care digital management system and an intelligent old-age care digital management method based on a cloud platform. The acquisition module is used for acquiring basic health data information of the old and sending the information to the cloud platform; the path comparison module is used for acquiring real-time positions of the old people, generating real-time paths of the old people according to the real-time positions, and performing similarity calculation on the real-time paths and historical paths to obtain path similarity; the emotion recognition module is used for recognizing the emotional state of the elderly and giving an emotional state label; the health state recognition module obtains real-time health data information of the elderly, constructs a health state recognition model, trains the health state recognition model to obtain a trained health state recognition model, and recognizes the health state of the elderly to obtain a recognition result; the cloud platform judges the behavior of the old person according to the identification result, and performs early warning if the behavior is abnormal; and under the unattended condition, management personnel or family members can quickly find the abnormal state of the old people and process the abnormal state in time.

The invention discloses a home-based care intelligent dynamic early warning system based on distributed digital identity and artificial intelligence. The system generates a verifiable digital identity (DID) to realize credible authentication of the old people and the Internet of Things equipment. Various terminals are fused to collect health, physiology and environment data, space-time correlation analysis is carried out based on an AI algorithm, and an individualized risk model is constructed. Local processing is realized by adopting edge computing, and data privacy and integrity are guaranteed in combination with a block chain. The system dynamically corrects a health threshold value according to historical behaviors and equipment data, improves the anomaly detection accuracy, automatically triggers alarm and rescue response when risks occur, and constructs a safe and intelligent old-age care monitoring system.

The invention discloses a functional capability and nursing risk-based elderly care method and related equipment, and relates to the field of medical nursing, and the method comprises the steps: obtaining multi-dimensional functional capability information and nursing risk indexes of an elderly patient, carrying out the structural integration through a weighted scoring model, and generating a joint evaluation file; and outputting the function baseline value, the risk category and the comprehensive risk index. The system calls a nursing intervention rule base according to the file, and a personalized intervention list is automatically generated to serve as an execution baseline for trend monitoring. Continuously updating function and risk data in the nursing process, and generating a time sequence trend chart and a risk level change curve; when a drop in function or an increase in risk is detected, the system triggers reevaluation and automatically adjusts the intervention list. According to the method, fusion of function evaluation and risk identification and automatic generation and dynamic adjustment of intervention suggestions are realized, and the intelligent and individualized levels of elderly care are improved.

The invention relates to the technical field of intelligent old-age care monitoring, and discloses a method for identifying abnormal behaviors of home elderly based on millimeter-wave radar and vision fusion, which comprises the following steps: S1, multi-modal data acquisition and privacy protection configuration: deploying a configurable sensing suite in a home environment of the elderly, comprising a millimeter wave radar, a visual sensor (infrared and visible light), environment sensors (doors and windows, water, illumination and ground vibration) and wearable equipment (such as a smart bracelet / chest card). According to the method and the system for identifying the abnormal behaviors of the home elderly based on millimeter-wave radar and vision fusion, all-around behavior monitoring is realized on the premise of guaranteeing the privacy of the elderly through multi-modal sensor fusion and a hierarchical privacy protection mechanism, and the millimeter-wave radar and the vision sensor are complementarily fused, so that the privacy worry of a pure vision technology is overcome, and the safety of the home elderly is improved. And the limitation of a single radar on complex behavior identification is solved, and meanwhile, a configurable sensing suite and a hardware-level privacy switch are adopted.

The application relates to the field of old-age care equipment, and discloses a state recognition navigation recommendation method based on artificial intelligence and an old-age terminal device. The method comprises the following steps: acquiring terrain features, speed features, gait features and physiological features of a user in multiple walking trips when the user uses an intelligent walking stick, and acquiring map information and a walking destination of the user; wherein the terrain features, the speed features and the gait features are detected by a motion detection component of the intelligent walking stick; through a state recognition-navigation recommendation model, a navigation route and a walking guidance suggestion of the user in the next walking trip are determined according to the terrain features, the speed features, the gait features, the physiological features, the map information and the walking destination in the multiple walking trips; and the walking guidance suggestion comprises matters needing attention information when the user walks. The application can identify and detect the physical state of the old people and improve the nursing effect on the old people.

The embodiment of the invention discloses an intelligent old-age care monitoring method and device, electronic equipment and a storage medium, and relates to the technical field of intelligent old-age care guardian.The method comprises the steps that physiological indexes are collected in real time through physiological monitoring equipment, environment data are monitored through an environment sensor, and behavior data are captured through a behavior capturing terminal; analyzing the environment data by using a time sequence clustering algorithm to obtain an environment abnormal value, analyzing the physiological indexes and the behavior data based on a Bi-LSTM model and an Attention model to obtain a behavior sequence, and calculating a physiological deviation value; analyzing the behavior data through MFCC feature extraction and a Transform model to obtain an emotion fluctuation value, and generating a comprehensive risk score; and carrying out risk grade division, carrying out data recording and monitoring when the risk is low, carrying out family member early warning when the risk is medium, and triggering an emergency response mechanism to carry out multi-device linkage when the risk is high. According to the invention, the problems of high false alarm rate, response lagging, lack of psychological monitoring and personalized service and weak privacy and security mechanism in the prior art are solved.

The utility model belongs to the technical field of building design, and particularly relates to a research tool for old-age care facility building design, which comprises a packaging mechanism, the packaging mechanism comprises a bottom plate, an outer frame is arranged on the bottom plate, a turning plate is arranged at one end of the outer frame, and a limiting bottom frame is arranged in the outer frame. When in use, the assembled research tool is brought to the site of the building design of the pension facilities, the tool is used for carrying out field measurement and evaluation, recording the position and combination condition of each component, adjusting the turning plate and the limiting bottom frame to adapt to different measurement requirements, and recording data and observation results of each measurement point in detail; and finally, after the investigation is completed, the buckle mold, the buckle column plate and the limiting bottom frame are sequentially disassembled, classified and stored, the turning plate is folded, the outer frame is folded and placed on the bottom plate, and a complete packaging mechanism is formed and is properly stored for use next time.

The utility model discloses an old-age care bathroom base plate, an old-age care bathroom unit and an assembly type old-age care integrated bathroom, and belongs to the technical field of assembly type home decoration. The old-age care bathroom base plate comprises a base plate body which comprises a back plate and a frame arranged on the periphery of the back plate, and the frame is higher than the surface of the back plate; the long-strip-shaped floor drain is arranged in the middle of the upper surface of the chassis body; the panel is contained in the frame of the upper surface of the chassis body and divided into two parts which are located on the two sides of the long-strip-shaped floor drain respectively to form a dry and wet area, and the upper surface of the side, away from the long-strip-shaped floor drain, of the panel is higher than the upper surface of the side, close to the long-strip-shaped floor drain, of the panel. The long-strip-shaped floor drain is arranged in the middle of the base plate body, the two sides of the face plates on the two sides are arranged to be different in height, the gradients of the two sides and the design gradient of the middle of the floor drain opening are uniform, drainage is easy, the long-strip-shaped floor drain effectively prevents water in a wet area from flowing to a dry area, and the long-strip-shaped floor drain can be used for small-gradient drainage. No step is arranged in the middle, so that the slipping risk of old people is reduced.

The utility model discloses an effective barrier-free handrail, which relates to the technical field of intelligent pension and comprises a vertical rod, a movable block is slidably arranged on the outer surface of the vertical rod, a lug seat is fixedly arranged on one side of the movable block, a rotating rod is fixedly arranged in the lug seat, a connecting seat is rotatably arranged on the outer surface of the rotating rod, and the connecting seat is fixedly connected with the vertical rod. A handrail rod is fixedly arranged on one side of the connecting base, a sponge sleeve fixedly sleeves the outer surface of the handrail rod, an insertion rod is movably inserted into the movable block, a through groove is formed in the vertical rod, the insertion rod is movably inserted into the through groove, a nut is fixedly arranged on one side of the movable block, and the movable block slides on the outer surface of the vertical rod, so that the handrail rod is fixed to the outer surface of the vertical rod. At the moment, the groove corresponds to one of the through grooves, then the insertion rod is inserted into the groove and the corresponding through groove again, and the threaded part is inserted into the nut, so that the height of the grab rail can be conveniently adjusted according to the condition of the old, and the requirements of different users can be met.

The invention relates to the technical field of medical biological materials, and discloses a mussel mucin-chondroitin sulfate composite hydrogel and a preparation method and application thereof, and the preparation method comprises the following steps: respectively preparing a mussel mucin aqueous solution and a chondroitin sulfate aqueous solution; the mass volume concentration of the mussel mucoprotein aqueous solution is 1%-10%, the mass volume concentration of the chondroitin sulfate aqueous solution is 1%-10%, the mass ratio of the mussel mucoprotein to the chondroitin sulfate is 3: 1-1: 3, the two solutions are mixed and stirred or oscillated under the conditions that the temperature is 4-37 DEG C and the pH value is 7.0-9.0, a cross-linking reaction is conducted, and hydrogel is formed; the cross-linking mode is physical cross-linking, chemical cross-linking or physical-chemical dual cross-linking; according to the invention, excellent tissue adhesion, injectability, self-healing property and biodegradability are realized, cell adhesion and proliferation can be effectively promoted, and the gel is suitable for various medical beauty scenes such as skin filling, wound repairing and anti-aging nursing.

The invention relates to the technical field of smart home and Internet of Things, in particular to a solitary elderly guard monitoring method and system based on an air source heat pump water heater, a storage medium and a computer program product. According to the method, multi-source data such as water flow switching pulse, compressor current and water tank temperature difference are collected, feature vectors are constructed, a lightweight neural network is executed at the edge end to infer the physical activity state of the elderly, a personalized water use base line is updated in combination with a cloud recurrent neural network, and accurate recognition and graded warning of behavior abnormity are achieved. The system has the functions of national standard alarm, remote communication, self-calibration and energy-saving control, has the advantages of accurate effect, timely response, energy conservation, high efficiency, low deployment cost and the like, and is suitable for smart old-age care and home security scenes.

This invention discloses an IoT-based sleep monitoring device and management system for elderly healthcare, belonging to the field of sleep monitoring technology. The IoT-based sleep monitoring device for elderly healthcare includes a sleep monitor connected to a sleep monitoring belt via a data cable. The sleep monitoring belt is equipped with a sleep monitoring module, which monitors the user's sleep in real time, collects multi-source sleep data, and transmits the collected data to a cloud platform via an IoT communication module. This invention solves the problem that existing methods cannot achieve real-time monitoring and health risk warning management of the elderly, thus reducing the sleep quality and health level of the elderly population. This invention enables real-time monitoring and health risk warning management of the elderly's sleep, improving their sleep quality and health level.

The invention belongs to the technical field of medical instruments and intelligent nursing, and discloses multifunctional nursing equipment suitable for aging and based on multi-modal monitoring and a nursing method.The nursing equipment comprises a nursing bed body, a multi-modal monitoring unit, a nursing supporting unit, an excretion supporting unit and an intelligent control unit, and the multi-modal monitoring unit, the nursing supporting unit, the excretion supporting unit and the intelligent control unit are arranged on the nursing bed body; a complete closed loop of monitoring-prediction-control-execution is constructed, the multi-mode monitoring unit comprehensively collects physiological-behavior-environment data, the intelligent control unit prejudges nursing requirements through a pre-trained AI model of a front-end computer, and a PLC drives all the units to execute nursing actions such as body position adjustment, pressure sore prevention and excretion without leaving a bed. Safety protection and remote cooperation functions are matched. The problems of few monitoring and nursing functions, response lag and the like of existing equipment are solved, the nursing accuracy and safety are improved, the nursing burden is reduced, and the system is suitable for nursing scenes such as hospitals, old-age nursing institutions and families.

The invention relates to an elderly self-care ability assessment method and system, electronic equipment and a storage medium, and relates to the technical field of smart pension, and the self-care ability assessment method comprises the steps: obtaining the physical condition of a supervision object according to a physical examination report and a figure posture image, and generating a body health state table; according to the psychological health test table, the home audio set and the key behavior mode, quantifying the psychological state of the supervised object to obtain a psychological health state table; according to the life behavior indexes, daily life habits of the supervision object are obtained, and a social health state table is generated; according to the body health state table, the psychological health state table and the social health state table, constructing personal portrait information of the supervised object in combination with drug compliance; adopting a self-care evaluation model to judge the self-care ability level of the supervised object according to the personal portrait information; the overall evaluation process is simplified, the information evaluation efficiency and the evaluation accuracy are improved, and the personalized service matching accuracy is improved.

The invention relates to the technical field of artificial intelligence and building safety management, in particular to an intelligent electric leakage detection and grading early warning system and method for an old-age care building, and the method specifically comprises the steps: deploying a current transformer in a distribution box of the old-age care building, and carrying out the classification marking, and forming a training set; preprocessing the original current waveform data to obtain a processed fusion feature vector; constructing an intelligent electric leakage detection model, fusing the feature vectors, inputting the fused feature vectors into the model, outputting the prediction probability of each category through modules in each model, then calculating a loss function of the model, and carrying out iterative training on the model to obtain a trained model; and inputting newly collected current waveform data into the trained model, outputting a detection result, triggering a corresponding alarm in real time according to the detection result, and visually displaying the detection result. According to the invention, high-precision and high-stability detection of multiple types of electric leakage is realized, and reliable technical support is provided for power distribution safety of pension buildings.

1. The name of the design product: wheeled humanoid dual-arm machine. 2. The use of the design product: the design product is a wheeled humanoid dual-arm machine, which is used for material handling operations, part sorting operations and other fine operation operations in industrial scenes, and can also be used for inspection, escort and other service operations in high-end old-age care scenes. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

The invention discloses an intelligent bed APP system suitable for aging based on a large language model, and belongs to the technical field of intelligent home control and intelligent health old-age care. The system comprises a user interaction layer, a multi-mode perception layer, a heterogeneous data layer, an intelligent algorithm layer and a closed-loop feedback layer, physiological state data of a user are collected through a non-intrusive sensor, and combined analysis is performed on touch or voice input of the user and the physiological state data based on a large language model. And a structured control instruction is generated to drive a bed body execution mechanism and environment equipment to execute corresponding operation, so that self-adaptive adjustment of the bed body state and comfort parameters is realized. The intelligent bed system improves the interaction intelligence level and the use experience suitable for the aged, and is suitable for home-based care for the aged and intelligent health management scenes.

The invention relates to the technical field of old-age care assistance, in particular to a supervision system for an old-age care robot, and the system is characterized in that an intelligent sensing module collects vital sign data, daily behavior characteristics and robot operation parameters of old people in real time; the emotion interaction supervision unit fuses voice semantic analysis, facial micro-expression recognition and behavioral habit data to carry out personalized care reminding and psychological state monitoring; the AI decision center module evaluates the health state of the old people, carries out early warning for different emergency situations and potential risks, and intelligently recognizes robot service abnormity; the emergency linkage unit generates a co-processing strategy for emergencies and robot faults; the dynamic health archive integrates health data, forms a dynamically updated personal health portrait, optimizes a co-processing strategy, and performs data encryption and access traceability through a block chain, so that a user autonomously authorizes a third party to query specific data. Therefore, the problems of single supervision strategy, poor early warning precision, poor service adaptability and the like in the prior art are solved.

1. The name of the design product: intelligent health care instrument. 2. The use of the design product: the design product is used for intelligent health care, covering different needs such as family, rehabilitation agency and old-age care scene. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective drawing.

The invention discloses a data real-time analysis method and system for an intelligent old-age care community, and the method comprises the following steps: collecting the heart rate, blood pressure, body temperature and other sign data of old people, generating a multi-channel time sequence data stream, carrying out the data preprocessing and standardization, inputting the standardized data into a TabPFN model, and carrying out the health state prediction. An improved TinyML algorithm is combined to realize real-time anomaly detection and risk assessment of the health data; through analysis of health state deviation and change trend, a health risk assessment result can be generated, and health early warning information can be pushed in time. According to the invention, the precision, real-time performance and adaptability of health monitoring can be significantly improved, and more intelligent health monitoring service is provided for the elderly.

The invention relates to the technical field of artificial intelligence, is applied to business scenes needing to generate images, such as financial science and technology, medical health care and the like, can accurately, continuously and controllably obtain relighting images under different illumination conditions, and effectively improves the image quality of the relighting images. Relates to an image relighting method and device, equipment and a medium, and the method comprises the steps: obtaining an object image to be relighting, and obtaining a first illumination image and a second illumination image, the first illumination image and the second illumination image being illumination images under different illumination conditions; carrying out image content extraction on the object image to obtain content latent space information corresponding to the object image; performing illumination information extraction on the first illumination image and the second illumination image to obtain target illumination submerged space information; and performing image generation according to the content submerged space information and the target illumination submerged space information to obtain a relighting image corresponding to the object image.