218 results about "Nursing homes" patented technology

The invention discloses a vital sign and sleep monitoring method and system based on a millimeter-wave radar, the method utilizes the millimeter-wave radar to realize non-contact sleep monitoring, and the millimeter-wave radar is firstly used to collect radar echo signals obtained by vibration of a chest wall in a sleep state; determining the position of a monitored object and extracting a vital sign signal of the target; then accurately detecting a first amplitude body movement and a second amplitude body movement of the target; whether an apnea event happens to the target is detected in real time, and alarm information is prompted under the condition that the event happens for a long time; three sleeping postures of supine, side-lying and prostrate are detected; and finally, sleep state monitoring is formed, a user sleep quality analysis report is formed in combination with the monitored information, and health suggestions are given. The method is simple, convenient, accurate, economical and efficient, is suitable for various application scenes such as families, hospitals and nursing homes, and provides all-weather health monitoring services for users.

The invention relates to the technical field of intelligent building environment control and energy management, and provides a building ventilation regulation and control method and equipment based on multi-target space-time analysis in order to solve the problems of high energy consumption, uncontrollable infection risk and response lag in the prior art. Original data and the spatial-temporal features are combined into a multi-modal fusion data set, an air quality change rule is learned based on an LSTM model, a future air quality state matrix is output, a multi-target dynamic optimization function is constructed, an optimal regulation and control strategy of a fan, fresh air and purification equipment is generated, and the optimal regulation and control strategy of the fan, the fresh air and the purification equipment is obtained. The response speed is improved while energy consumption is reduced and infection risks are controlled, and the system is particularly suitable for public places such as hospitals, schools and nursing homes with high requirements for indoor gas environments.

The invention belongs to the technical field of artificial intelligence, and particularly relates to a multi-mode early cognitive impairment screening method and system based on medical history information.The method comprises the steps that a first electrode plate and a second electrode plate are arranged at the forehead position and the occipital position of the brain of a user to be detected in advance; the third electrode plate and the fourth electrode plate are arranged on the left side of the brain side by side, and the fifth electrode plate and the sixth electrode plate are arranged on the right side of the brain side by side. And obtaining a disturbance coefficient set of the to-be-detected user under the reference detection mode combination, inputting the disturbance coefficient set into a pre-trained early cognitive impairment screening model, and predicting to obtain a prediction probability value of the early cognitive impairment of the to-be-detected user, and by adopting the scheme to screen the early cognitive impairment, the accuracy is high, the universality is strong, and the accuracy is high. The method can be applied to screening of people in communities, nursing homes and the like on a large scale.

A system for delivering inactivated pathogens to an enclosure includes an air delivery system, the air delivery system comprising: (a) an air intake; (b) an air conditioning unit; (c) an air mover; (d) a UVC disinfection unit; (e) an enclosure; (f) an enclosure air entry vent; (g) an enclosure air discharge vent; and (h) an air circulation pathway going from the air intake through an air duct connected at one end to the air intake and at a second end to the enclosure air entry vent that opens into the enclosure, wherein the air duct provides a passageway through the air delivery system. A pathogen loading inlet is connected to the air circulation pathway. The enclosure is a room, a nursing home, an airplane, a train, a ship, or a critical care unit in a hospital. The enclosure can also be a free-standing and / or mobile unit.

The invention relates to the field of identification and detection, in particular to a fall identification method based on millimeter wave radar point cloud data and a height threshold, which comprises the following steps of: 1, acquiring radar point cloud data; 2, extracting accurate point cloud data from target point information; 3, calculating three-dimensional point cloud data through an algorithm; 4, height information extraction and dynamic height threshold value fitting; 5, tumble identification is carried out; according to the method, the high-precision perception capability of the millimeter wave radar and the dynamic fitting model of the height threshold are combined, the accuracy of fall detection can be effectively improved, and the method has high environmental adaptability and privacy protection characteristics and is suitable for families, nursing homes, hospitals and other scenes.

The invention relates to the technical field of lighting devices, in particular to an intelligent lighting device with a fall monitoring function and a use method thereof. According to the technical scheme, the system comprises a filtering module, a PLC module, a central control unit, a posture recognition camera, an LED driving module, an LED light source module and an alarm, the posture recognition camera collects moving images of personnel in a monitoring area in real time, the central control unit analyzes the posture of the personnel based on an AI training model and judges whether a tumble event occurs or not, and if tumble is detected, the alarm gives an alarm. If yes, an alarm is started to give an acousto-optic alarm, and alarm information is pushed to a guardian terminal device through the Internet. According to the device, the power line carrier communication technology is adopted, additional wiring is not needed, the structural integration degree is high, non-contact and high-precision recognition of a falling event is achieved through the method, and the device has the lighting and safety monitoring functions and is suitable for families, nursing homes and other places.

The invention discloses an intelligent early warning method and system for falling in a nursing home scene, and relates to the technical field of medical health, and the method comprises the steps: obtaining the static and dynamic data of an old person, carrying out the preprocessing and feature extraction of a data set, and forming a feature data set; classifying the feature data according to the data type, constructing a classification feature data set, and establishing an old man falling prediction model through a logic regression model, a linear combination of classification features and a Sigmoid function; and carrying out processing and feature extraction by using a pre-constructed old people tumble data set, and inputting the tumble data set into the prediction model for training to minimize a loss function value so as to obtain an optimized tumble prediction model. And finally, inputting the classification feature data into the optimized model, and outputting an old man falling prediction result.

The invention discloses a multi-radar vital sign monitoring system applied to a fixed crowd place. The multi-radar vital sign monitoring system comprises a horizontal layer 24 GHz radar network, a vertical layer 60 GHz radar array and an auxiliary sensor module. Through three-dimensional collaborative deployment of heterogeneous radars, an improved variational mode decomposition algorithm and a joint probability data association tracking technology are combined to realize separation of breathing, heart rate and behavior characteristics of multiple targets in a dense scene. The system adopts a space-time diagram convolutional network to extract individual gait periodic features, establishes a unique biological feature coding file through dynamic gesture track matching, and completes non-contact identity binding. A multi-band radar chip and a dual-mode communication interface are integrated in hardware design, and a lightweight AI model is deployed in software architecture to realize localized real-time analysis. The embodiment covers nursing home tumble monitoring, hospital postoperative monitoring and kindergarten safety management and control scenes, the radar distance and the beam direction can be dynamically adjusted, and the problems of privacy disclosure and target confusion existing in a traditional monitoring system are solved.

The invention relates to the technical field of medical equipment, and particularly discloses an accompanying-free infusion intelligent management method based on the Internet of Things. The method comprises an alarm liquid stopping device (1), an Internet of Things transmission module (2), a cloud platform (3) and a nurse receiving end (4). When the alarm liquid stopping device (1) detects that the infusion liquid level is lower than a preset position, an infusion tube is automatically locked, and an alarm signal is generated; the Internet of Things transmission module (2) encrypts the signal and uploads the signal to the cloud platform (3) through an operator network such as 4G / 5G / NB-IoT; and the cloud platform (3) analyzes the signal and matches corresponding bed information, and pushes the information to the nurse receiving end (4) for audible and visual alarm. Through the automatic liquid stopping and intelligent notification functions, the problems of dependence on accompanying personnel and low nurse patrol efficiency in the prior art are solved, meanwhile, the system does not need to be connected with a hospital information system, deployment is fast, cost is low, and safety is high. The system is specially used for solving the pain point that accompanying and nursing are needed and a patient calls a nurse after waiting for infusion completion on site, intelligent management of the infusion process is achieved, the infusion experience degree of the patient is improved, the labor use cost is reduced, and the public praise of hospitals, old-age care institutions and the like is improved.

A medical monitoring system for use in residential facilities, nursing homes, or home environments is disclosed. The system utilizes a variety of modules and wearable medical devices that convey vital patient information to a series of smart hubs which are connected to the cloud. In the event a change in medical status of a patient occurs, the health care workers receive an Alert notifying them of which specific patient needs attention. The system is monitored using a specialized dashboard.

The invention discloses a low-cost and multi-scene adaptive AI health auxiliary mechanical arm which comprises a six-degree-of-freedom lightweight joint module. A multi-mode sensing system integrating a millimeter wave radar and a binocular camera; the quick-release base supporting toggle clip / magnetic attraction / bolt installation can achieve quick switching installation of a bed, a wheelchair, a wall face and other scenes. Through modularized hardware and an open source algorithm, core functions such as support, object delivery and remote medical treatment are realized, the selling price can be controlled within 20,000 yuan, and the problems of high cost and poor flexibility of a traditional nursing robot are solved. The device is suitable for daily life care of special groups such as old people, patients and disabled people. The auxiliary care robot is mainly applied to the bedside of a residential family or a hotel apartment and the bedside of a nursing home and a sickroom to be used as the auxiliary care robot, can also be installed on a dining table, a sofa, a bathroom, a toilet and other occasions needing auxiliary care of people, and can be movably installed on an automobile and an outdoor camping facility after being disassembled.

The invention discloses an elder dysphagia alarm system based on a multi-modal artificial intelligence model. The elder dysphagia alarm system comprises a data acquisition module, a multi-modal fusion module, an artificial intelligence analysis module, an alarm module and a background management system. The data acquisition module acquires video image data, wearable equipment data and environment data of the elderly; the multi-modal fusion module carries out fusion processing on the collected data of different modals to generate a multi-modal feature vector; the artificial intelligence analysis module analyzes the feature vectors based on a multi-modal artificial intelligence model, and outputs the probability and confidence of dysphagia of the old; when the elder is dysphagia and the confidence reaches a preset threshold, the alarm module starts to give an alarm; and the background management system configures, manages and monitors the system. The dysphagia condition of the old people is efficiently and accurately detected and timely alarmed by fusing various modal data and utilizing a deep learning technology, a powerful guarantee is provided for the safety and health of the old people, and the dysphagia condition detection method is suitable for the scenes of old people institutions, community old people service centers, families of the old people living alone and the like.

The invention relates to the technical field of smart old-age care, and discloses a personalized information rehabilitation task generation method, which comprises the following steps: acquiring rehabilitation data of old people in a nursing home and interaction data of visitors to form basic data; based on the rehabilitation data and the interaction data, constructing comprehensive portraits of the old and the visitors; comprehensive features of the comprehensive portrait are extracted, and initial task matching is carried out in a rehabilitation task library; performing multi-target weighted calculation on the initial tasks based on the old and visitors to obtain matching degrees corresponding to the initial tasks, and selecting three tasks from high to low according to the matching degrees as selection tasks; the senior side and the visitor side perform satisfaction scoring on the selected task, and the task with the highest comprehensive satisfaction is selected as a final rehabilitation task; the optimal rehabilitation task is generated through multi-target weighted calculation and a bidirectional scoring mechanism, dynamic accurate matching and safety intensity control are achieved, and the method has the advantage that the matching accuracy and safety of the rehabilitation task are improved.

The invention includes apparatus for holding medical equipment such as poles holding intravenous bags in a set position, relative to other medical equipment such as walkers, so that the user can move and walk more easily and use all the equipment while the user is moving. The user can, for example, use the invention to hold an intravenous bag pole to a walker and use both at the same time. The invention can also help with physical therapy, with nursing home patients, and with helping patient recovery in general. The invention also includes multiple methods for capturing data created by the apparatus and using the data to improve users' physical therapy. Some of the methods use non-fungible tokens to keep data about the use of the apparatus.

The invention relates to a nursing home priority service response method, system and device based on digital twinning, and the method comprises the following steps: collecting health data of old people and state data of nursing personnel, and carrying out the preprocessing of the data; constructing an old people health state dynamic model, a nursing resource dynamic model and an environment path model; coupling the three models to form a digital twin model; calculating a service response priority based on the health score, the waiting time attenuation and the medical history characteristics of the elderly; according to the service response priority, scheduling the matched nursing personnel to carry out service response; and collecting a service execution result after the nursing personnel completes the task, updating the digital twinborn model based on the service execution result, and dynamically adjusting a scheduling strategy. According to the invention, real-time mapping and dynamic optimization of the health state of the elderly, the position of the nursing personnel and the environment path information in the nursing home are realized, and the service response efficiency, the resource scheduling accuracy and the nursing quality are remarkably improved.

The invention discloses a nursing home night safety management method and equipment, and the method and equipment are applied to an autonomous patrol robot, the autonomous patrol robot comprises an edge calculation unit and a multi-mode sensor, and the method comprises the steps: when the autonomous patrol robot patrols to a monitoring distance of a door, the edge calculation unit calculates the monitoring distance of the door; the edge calculation unit performs outdoor non-contact monitoring through a multi-modal sensor and acquires multi-modal sensing data; determining physical sign data of a human body according to the multi-modal sensing data; and carrying out association analysis on the physical sign data of the human body to obtain physical sign deviation information of the human body so as to carry out risk prediction on the old. Night safety management can be carried out on the nursing home more efficiently, and risk early warning can be carried out quickly and accurately.

The invention discloses an old man falling alarm system based on a multi-modal artificial intelligence model. The old man falling alarm system comprises a data acquisition module, a multi-modal fusion module, an artificial intelligence analysis module, an alarm module and a background management system. The data acquisition module acquires video image data, wearable equipment data and environment data of the elderly; the multi-modal fusion module carries out fusion processing on data of different modals to generate a multi-modal feature vector; the artificial intelligence analysis module analyzes the feature vectors based on a multi-modal artificial intelligence model, and outputs the probability and confidence of falling of the old; when it is judged that the old fall down and the confidence reaches a preset threshold, the alarm module starts to give an alarm; and the background management system configures, manages and monitors the system. According to the invention, by fusing various modal data, efficient and accurate detection and timely alarm of the falling condition of the elderly are realized by using a deep learning technology, a powerful guarantee is provided for the safety and health of the elderly, and the method is suitable for the scenes of old-age care institutions, community old-age care service centers, families of the elderly living alone and the like.

A nursing worker housekeeping law enforcement instrument image processing system disclosed by the present invention comprises a law enforcement instrument terminal which comprises a central controller, a camera, a motor, an edge processor and a battery, the camera is connected with the central controller and is used for collecting an image of a hand position of a service worker, and the motor is used for driving the camera to move and adjusting an image collection angle; the edge processor is used for primarily processing images acquired by the camera, and the battery is connected with the central controller; and the cloud storage module is used for storing and processing the image which is acquired by the camera and is uploaded after primary processing. The invention further discloses an image processing method of the nursing worker housekeeping law enforcement instrument. Compared with the prior art, the technical problem that it is difficult to quickly screen image data collected by an existing law enforcement instrument to obtain effective information is solved.

The invention discloses an intelligent medicine chest management system based on multi-modal perception and adaptive learning, which obtains medicine visual information and millimeter wave feature codes through a rotary scanning platform, analyzes taking rules in combination with an edge side large model, and dynamically optimizes a reminding strategy based on user behavior learning. The system innovatively comprises a non-standard medicine multi-mode fusion recognition technology, a context-aware self-adaptive reminding engine and a hardware-level privacy protection architecture, can effectively improve family medicine taking compliance, obviously reduces the medicine taking error rate of a nursing home, and has great social value.

The invention relates to the field of natural language processing, and provides a pension institution recommendation method, device and equipment based on a large language model.The method comprises the steps that a dialogue is received based on a short-term portrait extraction large language model, and a short-term portrait of a user is constructed according to the dialogue; constructing a long-term portrait of the user according to the basic attributes of the user; determining a reasonable user portrait according to the short-term portrait and the long-term portrait; performing feature extraction on the reasonable user portrait to generate a user embedding vector; obtaining an institution embedding vector according to the attribute information of the pension institution; and performing similarity matching on the user embedded vector and the mechanism embedded vector, and determining a personalized recommendation result of the pension mechanism according to a matching result. According to the method, the problem of recommendation deviation caused by the fact that a static portrait cannot dynamically capture implicit demands of the old people in the prior art is solved, and personalized old-age care institution recommendation is realized.

The invention provides a federal learning system based on a medical, nourishing and health data lake, and the system comprises a hospital node, a nursing home node and a rehabilitation center node which respectively obtain data governance rules issued by a medical, nourishing and health data lake center, and carry out the feature extraction of local data of a target user; the federal learning server sends the initial global model to a hospital node, a nursing home node and a rehabilitation center node; the following steps are iteratively executed: a hospital node, a nursing home node and a rehabilitation center node respectively carry out local training based on feature vectors and an initial global model; the federal learning server updates the global model based on the uploaded model gradient information; the federated learning server determines whether the current global model is converged or not; if not, the updated global model is sent to a hospital node, a nursing home node and a rehabilitation center node, so that the hospital node, the nursing home node and the rehabilitation center node continue training and upload model gradient information; and if so, determining that the medical auxiliary model is generated.

The invention relates to the field of intelligent medical diagnosis, in particular to a wearable intelligent urinalysis method, device and system and a wearable urinalysis instrument. According to the intelligent urinalysis method, the urinalysis instrument is worn on a patient by using a wearable design, urination and urine collection rules are judged through a sensing technology and an algorithm, basic conditions of urine are preliminarily detected by using a near-infrared technology, visible components of the urine are secondarily detected by using an image processing technology, and an upper computer is combined for contrastive analysis, so that an intelligent urinalysis result is obtained. And the result of the urine test of the patient is obtained and displayed in the wearable device, so that urine test of non-hospital patients such as home nursing or nursing homes is facilitated, the convenience of urine test of the non-hospital patients is improved, medical test resources are optimized, meanwhile, early recognition of patients with abnormal urinary tract indexes is greatly improved, and the accuracy of urine test is improved. And dynamic tracking can be realized and can be used as a reference basis for internet diagnosis and treatment.

1. Name of the Design Product: Nursing Work Platform. 2. Use of the Design Product: This product is applicable to various environments that require continuous care, such as hospitals, nursing homes, and medical institutions. By integrating Internet of Things (IoT), artificial intelligence (AI), and big data analysis technologies, the platform can monitor the health status of patients in real time, automatically process call requests, record and analyze data, evaluate the nursing needs of patients, and provide personalized nursing plans and more accurate and efficient nursing services, realizing the intelligent management of the nursing process. 3. Design Key Points of the Design Product: Lies in the shape. 4. Picture or Photograph that Best Illustrates the Design Key Points: Front View.

The present invention relates to the field of information processing technology, and specifically discloses a method for constructing a social graph and warning of abnormal behavior for the elderly, wherein the method for constructing a social graph for the elderly comprises the following steps: S1, continuously collecting location data of the elderly; obtaining a pre-constructed place semantic knowledge graph; for each two elderly people, determining whether there is a location co-occurrence relationship between the two, and calculating the location co-occurrence strength when there is a location co-occurrence relationship; calculating the social interaction intensity score between the elderly based on the location co-occurrence strength and the social function weight of the place; constructing a social graph of the elderly community based on the social interaction intensity score and the place function information; the method for constructing a social graph of the elderly community can effectively mine social interaction information from location data, and then construct a social graph of the elderly community, so as to more accurately identify and quantify the real social interactions between the elderly, and provide data support for optimizing care services and activity arrangements for nursing homes.

To detect the positional information of staff at higher accuracy, and make it possible to estimate action of the staff more appropriately.SOLUTION: An action estimation system 100 that estimates action of care workers who works in a nursing home comprises: UWB tags 10 which are provided at predetermined positions of the nursing home; a care worker terminal 20 having a sensor part 21 which performs UWB-method radio communication to acquire distance measurement information showing a distance and a direction between the care workers and the UWB tags 10; an action estimation device 30 which calculates the positional information of the care workers on the basis of distance measurement information acquired from the sensor part 21, and estimates action of the care workers; and a manager terminal 40. The action estimation device 30 is equipped with a control part 31 having a distance measurement information acquisition part 311, a positional information calculation part 312, an action estimation part 313, an action estimation result output part 314 and an action recording creation part 315.SELECTED DRAWING: Figure 1

The invention discloses an old people abnormal behavior identification method and system based on multi-modal fusion, and the method comprises the steps: an edge end synchronously collects visual, inertial and environmental heterogeneous data, and extracts each modal feature after time alignment and preprocessing; vision and inertia feature weights are dynamically corrected through a cross-modal attention adapter, and modal unbalance is relieved; constructing a multi-modal fusion graph, executing a graph attention mechanism (HLGAtt) in a hyperbolic Lorentz space, and depicting a behavior hierarchical relationship; and detecting anomaly based on the graph attention network, positioning a root cause node through random walk, and outputting an anomaly category and root cause interpretation. Compared with the prior art, the method has the advantages that the anomaly identification F1 score is increased by more than 6%, the false alarm rate is lower than 0.7 times per day, and the method has the characteristics of high reliability and interpretability, can be widely applied to nursing homes, communities and family scenes, and provides technical support for intelligent nursing for the aged.

The invention relates to a construction comprising a floor and a ceiling as well as: at least one enclosed space (3) extending at least from the floor to the ceiling and into which at least one technical equipment and / or at least one network (4) opens, at least one sanitary appliance or a water feature (1) located outside the enclosed space (3) and connected to the technical equipment and / or the network through at least one partition (2) of the enclosed space (3), and it is particular in that it comprises at least one partition (6) device (6) capable of connecting both to said sanitary appliance(s) or to said water feature(s) (1) and to said technical equipment(s) and / or to said network(s) (4). In concrete terms, this construction can be a hospital, a nursing home, a retirement or health home, an apartment building, an office, a detached house, etc.

The invention discloses a video-based omni-directional remote rehabilitation training system, a video-based omni-directional remote rehabilitation training method and a medium, which are characterized in that a digital standardized training video library classified according to four stages of PT physical therapy is established, and more than 700 digital standardized training videos such as joint activity, balance training, gait correction and the like are covered; it is ensured that the training content is scientific and covers the whole period and all directions of rehabilitation training; rehabilitators generate personalized training schemes in combination with rehabilitation scene types (hospitalization / home / community / old-age care institutions) and clinical data and in combination with remote video evaluation of the rehabilitators, and training requirements in different environments are met. By capturing actions of limb joint angles, joint point motion trails and muscle force changes, a training action deviation rate is calculated and is fed back and output to a rehabilitation teacher in a grading manner, so that the training standardability is remarkably improved; rehabilitators can manage multiple patients online at the same time, remotely check training percentage data, adjust schemes and generate rehabilitation notes, and efficient, accurate and personalized rehabilitation guidance services are provided for the patients.

This invention relates to the field of nursing equipment, and more particularly to a mobile intelligent bathing device for elderly care, comprising: a movable base plate with casters at its bottom for supporting the device for movement; a shower chamber fixed to the upper part of the movable base plate; an extension chamber fixed to one side of the shower chamber, the top of which is provided with a cover plate, and the extension chamber having a clean water chamber and a wastewater chamber respectively; a support unit including a set of supports symmetrically arranged on both sides inside the shower chamber; a chest cleaning section including a mounting plate folded and installed between elbow pads on both sides; and a back cleaning section including a fixing plate fixed to the inner wall of the shower chamber. This invention has a compact overall structure, complete functions, strong protection, and is easy for the elderly to use. It is suitable for various environments such as homes, nursing homes, and hospitals, and can help the elderly achieve efficient showering and skin care for their chest and back.

An air flow delivery system for delivering conditioned air to an enclosure housing infectious disease patients, includes: (a) an air intake pipe having a first bidirectional valve therein, wherein when the bidirectional valve is in an open state, ambient air enters the enclosure; (b) an air handler, the air handler coupled to the air intake pipe; and (c) an air supply duct installed within at least one wall of the enclosure, wherein the air supply duct delivers conditioned air from the air handler to one or more air supply vents positioned at or near a bottom surface of the enclosure. The enclosure is selected from a group consisting of a pavilion, a building, a room, a nursing home, an airplane, a vehicle, a train, a ship, a critical care unit in a hospital, and a free-standing, mobile enclosure.