142 results about "Care protocols" patented technology

The invention relates to the technical field of medical monitoring, in particular to a multi-mode intelligent management system for monitoring and preventing stress injury. The system comprises a multi-modal data acquisition and preprocessing module, a deep fusion risk prediction model module, an intelligent path planning and resource allocation module, a personalized intelligent intervention module and a data security module, so as to acquire time sequence physiological data and generate a body pressure thermodynamic diagram in real time, and realize standardization through normalization; a risk prediction model is generated through modeling, the contribution degree of each modal feature is calculated, and a risk level is determined according to a preset early warning grading mechanism; an optimal path is generated through intelligent planning, a nursing scheme is dynamically optimized and generated according to the risk level, and the nursing scheme is encrypted and transmitted to a cloud platform through HTTPS to be regularly subjected to security vulnerability scanning and repairing. According to the invention, the skin condition, the body position change and the pressure distribution of the patient can be accurately monitored, so that the closed-loop management of the pressure injury is realized.

The invention relates to the technical field of medical aid decision making, in particular to a system and method for generating an individualized nursing scheme based on the comprehensive evaluation condition of the elderly. According to the method, various physiological time sequence data of the old people in a specific life scene are collected and the periodic fluctuation characteristics of the data are extracted, so that the subtle change trend of the daily rhythm of the old people can be accurately identified, the dynamic influence of the chronic disease progress on the physiological state is revealed by further comparing the rhythm deviation degree and continuity in different time periods, and the accuracy of the physiological state of the old people is improved. Then, in combination with the trend change rate and directionality thereof, an interaction mode between physiological changes and chronic disease indexes is described in continuous observation, so that the measurement of the coupling adaptation degree between individual physiological responses and chronic disease conditions is achieved, through normalized amplitude difference and matching interval screening, individual physical ability and chronic disease adaptation labels are accurately given, and the accuracy of the physical ability and chronic disease adaptation labels is improved. And further comprehensively measuring the adaptation priority of each intervention element in the individual in a multi-dimensional scoring mode, and constructing a nursing intervention combination oriented to a specific crowd state.

The invention discloses a traditional Chinese medicine nursing management system and method based on a cloud follow-up visit management platform, and belongs to the technical field of intelligent nursing. The management system comprises the following modules: a dynamic data acquisition module for acquiring physiological parameters, living habits and environmental data of a patient in real time and performing primary processing; the dynamic health archive construction module is used for constructing and continuously updating an individualized health archive of the patient based on the data collected in real time; the traditional Chinese medicine knowledge map and reasoning module depends on the traditional Chinese medicine nursing knowledge map and combines an intelligent reasoning technology to realize accurate traditional Chinese medicine syndrome differentiation and treatment analysis and automatically generate a personalized nursing scheme; the multi-dimensional patient feedback module is used for constructing a feedback mechanism fusing objective data, patient subjective feeling and medical care evaluation so as to extract key nursing effect information; and the nursing scheme iterative optimization module dynamically adjusts and optimizes the traditional Chinese medicine nursing scheme based on the feedback data, and realizes personalized and self-adaptive continuous improved nursing.

A wearable electronic device, a system and methods of monitoring with a wearable electronic device. The device includes a hybrid wireless communication module with wireless communication sub-modules to selectively acquire location data from both indoor and outdoor sources, as well as a wireless communication sub-module to selectively transmit an LPWAN signal to provide location information based on the acquired data. The device may also include one or more sensors to collect one or more of environmental data, activity data and physiological data. The device may transmit some or all of its acquired data to a larger system, including a cloud-based server to, in addition to providing location-based data, be used as a part of a predictive health care protocol to correlate changes in acquired data to salient indicators of the health of a wearer of the device. In one form, the predictive health care protocol uses a machine learning model.

The invention discloses a rehabilitation nursing auxiliary system based on multi-modal data driving. The problems that in the prior art, data collection is single, a nursing scheme lacks individuation, and a feedback mechanism is insufficient are solved. The system comprises a multi-modal data acquisition module, a data processing and fusion module, an intelligent analysis and decision support module, a feedback and adaptive adjustment module and a patient interaction and nurse assistance interface module. According to the system, physiological data, behavior data, image data and environment data of a patient are collected in real time through Internet of Things equipment, cross-modal features are extracted through a deep learning model, and a comprehensive state vector S (t) is generated. Based on a reinforcement learning algorithm, a personalized nursing scheme C (t) is dynamically generated, and a multi-modal data weight theta and the nursing scheme are optimized through patient historical data and real-time feedback F (t); through the rehabilitation progress evaluation function P (t), the system can adjust the nursing plan in real time, and the rehabilitation effect is improved.

The embodiment of the invention provides a trauma nursing scheme generation method and system based on artificial intelligence, and the method comprises the steps: obtaining first basic medical data of a target object to be subjected to trauma nursing, and the first basic medical data comprises individual feature data, gene data, trauma text data and medical history text data; and performing data preprocessing and reconstruction operation on the first basic medical data to generate second basic medical data of the target object. And inputting the second basic medical data into a pre-constructed nursing analysis model to obtain at least one subsequent nursing stage label of the target object. And based on the subsequent nursing stage label, a nursing knowledge base and historical nursing data of a plurality of reference objects, determining a wound nursing recommendation scheme of the target object, thereby improving the accuracy of wound nursing scheme generation.

The invention relates to the technical field of medical care, and provides a patient risk dynamic assessment system in medical care teaching, which comprises a data acquisition module used for acquiring multi-modal image data of a postoperative gastric organ anastomosis area of a patient; the data processing module is used for preprocessing the multi-modal image data, establishing a three-dimensional model of organs around the anastomotic stoma and analyzing edge features of the anastomotic stoma; and the risk assessment module is used for constructing an anastomotic stoma state assessment model and outputting comprehensive scores of an anastomotic stoma blood perfusion condition, a tissue metabolism abnormal probability, an anastomotic stoma leakage risk, anastomotic stoma scar hyperplasia and healing trend prediction. A quantum dot fluorescence image, a Raman spectrum image, a CT image and an intraoperative high-definition white light image are enhanced through the system and evaluated, a nursing scheme is obtained in combination with opinions of medical staff, and compared with manual evaluation of the medical staff, the accuracy is higher, the feasibility of the nursing scheme is higher, and medical nursing use is facilitated.

The invention discloses a self-adaptive analysis nursing method based on a wound image. The method comprises the following steps: S1, acquiring multi-modal image data of a wound; s2, performing fusion processing on the acquired multi-modal image data to generate a fused image; s3, analyzing the fused image by using a deep learning target detection model, identifying boundary, type, area and depth information of the wound, and forming a wound information set; s4, according to the identified wound information set, combining the physical condition data of the patient, and generating a model through a self-adaptive nursing strategy to formulate a personalized nursing scheme; s5, in the nursing process, the change condition of the wound is monitored in real time, the multi-modal image data are collected again at regular intervals, the steps S2 to S4 are repeated, and the nursing scheme is dynamically adjusted according to a new analysis result. According to the method, wound information is accurately obtained, a personalized nursing scheme is formulated, dynamic adjustment is achieved, and the accuracy, effectiveness and intelligent level of wound nursing are remarkably improved.

The invention discloses a pediatric nursing quality prediction and optimization method based on transfer learning, and the method comprises the following steps: S1, collecting target pediatric nursing data, and carrying out the preprocessing; s2, selecting source data, and extracting source data features; s3, constructing and training a nursing quality prediction model; s4, carrying out migration and fine tuning on the nursing quality prediction model by adopting an improved fine tuning method; s5, inputting target pediatric nursing data to the fine-adjusted nursing quality prediction model, calculating a nursing quality index, and evaluating a prediction result; s6, generating a nursing scheme based on the prediction result, and optimizing the nursing scheme according to the execution effect; and S7, applying the optimized nursing scheme to actual nursing work, and establishing an updating mechanism, so that the nursing quality prediction model is combined with new data to carry out iterative optimization. The pediatric nursing quality prediction and optimization are realized by adopting transfer learning and deep learning methods, and the pediatric nursing quality prediction and optimization method has the advantages of high data adaptability, high prediction accuracy and intelligent optimization of the nursing scheme.

The invention discloses an integrated management system and method for postoperative care of orthopedic patients, and relates to the technical field of medical treatment. Comprising a bone mineral density dynamic monitoring value, six-dimensional mechanical parameters of a joint movement track, emotion spectrum characteristics in voice interaction, microenvironment temperature and humidity changes collected by wearable equipment and skin surface pressure distribution; inputting the recovery data into a multi-modal decision-making model based on orthopedic biomechanics improvement, and generating a nursing scheme including a skeleton stress safety interval, a virtual rehabilitation scene dynamic parameter and an interdisciplinary intervention priority; the scheme parameters are dynamically optimized through a layered reinforcement learning framework special for the orthopedics department, and the deformation logic of the 3D printing brace and the correction strategy of the nursing robot are synchronously controlled; based on the postoperative complication space-time prediction map, a multidisciplinary collaborative response instruction strictly matched with the rehabilitation stage of the patient is triggered.

The invention relates to the technical field of medical care, and particularly discloses an oral cancer perioperative nursing decision method, which comprises the steps of image acquisition, model generation, preoperative evaluation, dynamic nursing, risk evaluation and decision support. According to the scheme, the tumor area is extracted from the three-dimensional image data based on the U-Net model, the tumor area is separated from surrounding healthy tissue, complex tumor forms are automatically processed, higher segmentation precision and robustness are provided, and finally the accurate three-dimensional anatomical model is generated; according to the scheme, the individualized data, the real-time physiological indexes and the treatment progress of the patient are obtained, the intelligent optimization algorithm is used for calculating the priority of each nursing measure, the individualized nursing decision is dynamically generated according to the priority, the most suitable nursing scheme is automatically provided for the patient, and individualized requirements of different patients are better met.

The invention relates to the technical field of traditional Chinese medicine nursing or health improvement, in particular to a method for generating a traditional Chinese medicine personalized nursing scheme for preventive treatment of diseases. The method comprises the following steps: firstly, screening out all initial reference individuals of a current individual based on a similar condition between corresponding physique information of the individuals; further determining all concerned symptoms and corresponding concerned coefficients of the current individual according to the universality and change condition of each symptom of the current individual in the initial reference individual; screening out all reference individuals according to the attention coefficient of the common attention symptom of the current individual and each initial reference individual; and finally, generating a personalized nursing scheme of the current individual based on the nursing schemes of all the reference individuals. According to the method and the device, the reference individuals capable of providing similar nursing references are accurately screened out from the historical disease prevention individuals based on the similar physical conditions of the individuals and the similar conditions of the symptoms which are mainly concerned during nursing, so that the generation effect of the personalized scheme of the current individual is improved.

The invention discloses a chronic wound nursing scheme recommendation method and system based on clustering and a knowledge graph, and relates to the technical field of chronic wound nursing, chronic wound nursing associated data is collected to obtain chronic wound nursing multi-source data, and the chronic wound nursing multi-source data is preprocessed; and analyzing the preprocessed chronic wound nursing multi-source data, clustering the core demand problem and the nursing scheme data, and establishing a correlation database between the core demand problem and the nursing scheme. Through a technical path from multi-source data fusion to semantic cluster generation by layer clustering to cluster-level map construction to dynamic semantic matching, three major pain points of knowledge fragmentation, inaccurate demand matching and lack of recommendation basis in chronic wound nursing are solved. Compared with a traditional method, image volume accumulation captures multi-dimensional association, and semantic noise is reduced through cluster mapping; the evidence chain runs through the whole process of problems, schemes, wound types and literature sources.

A wearable electronic device, a system and methods of monitoring with a wearable electronic device. The device includes a hybrid wireless communication module with wireless communication sub-modules to selectively acquire location data from both indoor and outdoor sources, as well as a wireless communication sub-module to selectively transmit an LPWAN signal to provide location information based on the acquired data. The device may also include one or more sensors to collect one or more of environmental data, activity data and physiological data. The device may transmit some or all of its acquired data to a larger system, including a cloud-based server to, in addition to providing location-based data, be used as a part of a predictive health care protocol to correlate changes in acquired data to salient indicators of the health of a wearer of the device. In one form, the predictive health care protocol uses a machine learning model.

The invention discloses a rehabilitation nursing intelligent monitoring method and system based on image acquisition, and belongs to the technical field of rehabilitation nursing intelligent monitoring, and the method comprises the steps: collecting limb image data of a patient and a synchronous pain response value to generate a monitoring model; processing the current image data based on a monitoring model to evaluate and output a pain risk value; analyzing the fluctuation trend of a pain response curve formed based on the pain risk value to generate and output a nursing scheme; collecting subsequent image data in the process of executing the nursing scheme, monitoring a limb recovery state and outputting recovery feedback information to adjust the nursing scheme; according to the method, continuous assessment of pain risks is achieved by establishing quantitative association of visual features and pain responses, the nursing scheme is generated based on dynamic fluctuation trend analysis, a closed-loop management process is formed by recovering feedback information, and the efficiency and safety of rehabilitation nursing are improved.

The invention relates to the technical field of medical care, in particular to a patient pressure sore recognition and nursing auxiliary system based on PDA and deep learning, and the system comprises PDA equipment which has a double-photographing function and is used for photographing a human face, uploading the human face to the system, inputting human face information, photographing a skin image of a patient and uploading the skin image; the server side is provided with a deep learning algorithm model and a nursing scheme database; the server side is used for analyzing the skin image of the patient uploaded by the PDA so as to judge the pressure sore condition; and the nursing scheme database provides corresponding scientific nursing measures according to the judgment result of the server side. According to the system, accurate pressure sore recognition is achieved by means of a deep learning algorithm and a thermal imaging technology, personalized nursing measures are generated by means of a nursing scheme database, accurate patient identity recognition is guaranteed by means of face recognition, medical risks are comprehensively reduced, and nursing efficiency and quality are remarkably improved.

The invention relates to a traditional Chinese medicine nursing data intelligent management method and system, and the method comprises the steps: collecting traditional Chinese medicine nursing data, and converting the traditional Chinese medicine nursing data into structured semantic data and a standardized sign data set; constructing a dynamic knowledge graph according to the structured semantic data and the standardized physical sign data set; constructing a syndrome evolution model based on the dynamic knowledge graph, and generating an initial nursing scheme; conflict detection and intervention effect prediction are carried out on the initial nursing scheme, and a self-adaptive strategy feedback model is formed based on evaluation data after nursing implementation; generating nursing decision suggestions by utilizing case reasoning according to the self-adaptive strategy feedback model and the dynamic knowledge graph; in the execution process of the steps, federal learning is adopted to realize distributed processing of data, and a differential privacy mechanism is combined to guarantee dynamic desensitization and privacy security of the traditional Chinese medicine nursing data. The intelligent effect of traditional Chinese medicine data management can be improved.

The invention discloses an integrated management system for postoperative care of orthopedic patients, and belongs to the technical field of medical systems. The system is implemented based on a plurality of patient terminals, and each patient terminal is connected to a local motion monitoring platform; the local exercise monitoring platform comprises an exercise amplitude detection unit used for detecting the current exercise amplitude of a patient; the pain monitoring unit is used for monitoring the current pain index of the patient; each patient terminal is also provided with a postoperative care comprehensive management App realized based on a cloud platform; the post-operation nursing comprehensive management App comprises a narration unit for matching the post-operation nursing scheme to be executed currently based on the current state data of the user, and a display unit for displaying the post-operation nursing scheme. According to the invention, the postoperative nursing comprehensive management of orthopedic patients can be realized through narrative nursing and a continuous incentive mechanism according to the individual states of the patients and group recommendation, the scientificity and standardization of medical nursing work are embodied, and the medical nursing work can be understood and matched by the patients.

The invention discloses a postoperative chest cold and hot compress integrated nursing pad for a thoracic surgery patient. The postoperative chest cold and hot compress integrated nursing pad comprises a heating layer, a refrigerating layer, a nursing pad sensor, a physiological sensor, an intelligent control unit and a man-machine interaction system. The heating layer is composed of a liquid circulation heating cushion layer and a small heating pump, the refrigerating layer is composed of a liquid circulation refrigerating cushion layer and a miniature refrigerating pump, the nursing pad sensor layer is located between the heating layer and the refrigerating layer, and the physiological sensor is used for collecting the physiological state of a patient. The intelligent control unit integrates an artificial intelligence algorithm, intelligently regulates and controls work of the heating layer and the refrigerating layer according to feedback signals of the sensor, and achieves automatic switching and precise adjustment of the cold and hot compress modes. And the man-machine interaction system is convenient for medical personnel and patients to operate and feed back. Through multi-sensor data acquisition and intelligent algorithm analysis and in combination with a remote monitoring function, a personalized and intelligent chest cold and hot compress nursing scheme is provided for a patient after the thoracic surgery, recovery of the patient is effectively promoted, and the nursing quality is improved.

The invention discloses a hypertension nursing system based on a remote AI monitoring technology, and particularly relates to the technical field of telemedicine, the hypertension nursing system comprises a data acquisition module, a data fusion module, a risk assessment module, a dynamic intervention module and a cloud management module, and physiological data, behavior data and environmental data are acquired through heterogeneous sensors; the method comprises the following steps: preprocessing the data, transmitting the preprocessed data to a data fusion module and a cloud management module, carrying out alignment and feature extraction on heterogeneous data from different sources to obtain comprehensive risk assessment features, carrying out blood pressure fluctuation risk prediction through an LSTM model, aggregating multi-center cases through cloud federated learning, and generating personalized long-term risk scores. Performing risk level judgment according to the long-term health risk score of the patient, outputting a customized nursing scheme in combination with historical data of the patient, performing privacy protection and storage on the collected data, supporting consultation between the patient and a doctor, automatically generating a dialogue abstract, and updating the dialogue abstract to an electronic health file.

The invention relates to the technical field of intelligent medical care, and discloses a drainage port nursing recommendation method and system for a patient with bile leakage. The system comprises a data acquisition module used for acquiring bile drainage data and state data of skin around a drainage port in real time; the cloud decision module is internally provided with a nursing scheme recommendation model associated with a bile leakage nursing knowledge graph, and is used for carrying out fusion analysis on the multi-modal data and generating a personalized nursing plan; the local execution terminal is used for receiving and displaying the nursing plan and guiding nursing personnel to execute and record actual nursing operation data; and the closed-loop feedback module is used for returning the actual execution data and the post-nursing state data so as to optimize the nursing scheme recommendation model and the bile leakage nursing knowledge graph. The technical problems that in traditional nursing, evaluation is subjective, decision-making depends on experience, execution is not standard, and knowledge is difficult to accumulate are solved, and standardization, individuation and continuous self-optimization of bile leakage drainage opening nursing are achieved.

The invention provides a multi-mode intelligent analysis internal fistula postoperative rehabilitation nursing method and system, and belongs to the technical field of medical nursing and artificial intelligence crossing. The application aims to solve the problems of single monitoring dimension, subjective risk judgment and static homogenization of the nursing scheme in the existing internal arteriovenous fistula postoperative nursing. The method comprises the following steps: acquiring multi-modal data related to a wound state and a hemodynamic state of an internal arteriovenous fistula; processing the multi-modal data to generate standardized feature data which can be analyzed; generating a risk assessment result about the health condition of the internal arteriovenous fistula; and a preset nursing scheme is dynamically adjusted based on a risk assessment result. According to the method and the device, multi-modal data are fused and an intelligent algorithm is used for collaborative analysis, so that the accuracy and early stage of risk identification can be realized, the individuation and high efficiency of a nursing scheme are realized, and the nursing quality is improved.

The invention discloses an intelligent nursing decision generation auxiliary system based on medical record data analysis, and relates to the technical field of medical information. The medical record data sharing cloud is in communication connection with an input terminal, a feature extraction module, a nursing scheme recommendation module, a nursing effect feedback module, a data mining analysis module and a nursing scheme recommendation module; the input terminal is used for collecting medical record data of a patient; the feature extraction module is used for constructing a medical record feature set of the medical record data; the nursing scheme recommendation module is used for generating a nursing scheme according to the medical record feature set of the patient; the nursing effect feedback module is used for acquiring the nursing effect level of each nursing process sub-sequence; the data mining analysis module is used for obtaining medical record feature mode combinations and dividing the medical record feature mode combinations into large sample medical record feature mode combinations and small sample medical record feature mode combinations; the nursing scheme recommendation module is used for generating a nursing scheme recommendation model, and the scientificity and effectiveness of a nursing recommendation scheme are remarkably improved.

The invention discloses a neurosurgery postoperative care system and method based on AI, and particularly relates to the technical field of medical care. According to the method, the basic parameter set and the characteristic parameter set of the patient are constructed, the basic parameter set is encoded, nursing cases of the same type of patients in the nursing database are accurately matched, and the adaptive scheme is screened; further calculating an effect-like comprehensive coefficient, namely preferentially selecting a scheme which is highly matched with the individual characteristics of the current patient and has an excellent effect as a preliminary scheme by combining the deviation degree of the physiological indexes of the patient and the case, the complication score of the case, the recovery efficiency, the rehabilitation score and the like, and sending the preliminary scheme to medical personnel to secondarily edit the preliminary scheme; finally, a personalized nursing scheme completely fitting the individual condition of the patient is formed, and the problems that in the prior art, most of traditional nursing schemes are formulated by medical staff based on a universal nursing guide, the formulating efficiency is greatly reduced, and the nursing effect cannot be guaranteed are solved.

The present application relates to the technical field of medical auxiliary decision-making, in particular to a system and method for generating individualized nursing plans based on comprehensive assessment of the elderly. In the present application, by collecting multi-class physiological time series data of the elderly in a specific life scene and extracting the periodic fluctuation characteristics, the subtle change trend of the daily rhythm can be accurately identified. Further, by comparing the rhythm deviation degree and persistence in different time periods, the dynamic influence of the progress of chronic diseases on the physiological state is revealed. In combination with the trend change rate and its directionality, the interaction mode between physiological changes and chronic disease indicators is depicted in continuous observation, thereby realizing the measurement of the coupling adaptation degree between individual physiological response and chronic disease condition. Through normalized amplitude difference and matching interval screening, the individual physical ability and chronic disease adaptation label are accurately assigned. Then, the adaptation priority of each intervention element in the individual is comprehensively measured in a multi-dimensional scoring manner, and a nursing intervention combination for a specific population state is constructed.

The invention discloses a tumor intervention postoperative auxiliary nursing system based on real-time health data, and particularly relates to the technical field of medical nursing, and the system comprises the following modules: a data collection module obtains physiological parameters, behavior data and equipment states of a patient in real time; the data processing module cleans, formats and stores the collected data; the efficacy evaluation module evaluates the treatment cooperation efficacy of the patient; the matching evaluation module evaluates the matching degree of the equipment and the physiological state of the patient; the classification model construction module performs classification according to the evaluation result and determines a nursing type; and the nursing intervention module executes a corresponding intervention strategy according to the classification result. The system realizes intelligent and personalized postoperative care; according to the physiological data, the treatment adaptability and the equipment adaptability of the patients, personalized nursing strategies are intelligently matched, and it is ensured that each patient is nursed most suitable for the health condition of the patient after an operation. The personalized nursing scheme is beneficial to accelerating the recovery of the patient and reducing postoperative complications and adverse reactions.

The invention relates to the technical field of medical data processing, and provides a wound nursing data intelligent analysis method and device, equipment and a medium, and the method comprises the steps: carrying out the preprocessing of wound nursing data collected by a medical sensor, and obtaining a data subset; acquiring a multi-source medical data set of other medical devices of the patient; processing various medical data through a wound feature extraction model to obtain a feature data set; fusing the feature data; generating severity and type of trauma assessment information based on the fusion data and the trauma assessment model set; and generating a personalized wound nursing scheme in combination with the wound nursing data, the evaluation model set and the evaluation information. The accuracy and efficiency of wound nursing can be improved.

The invention relates to the technical field of nursing in the rheumatism and immunology department, in particular to an intelligent patient personalized nursing path management system in the rheumatism and immunology department, which comprises a joint activity-inflammation data acquisition unit, a path generation and dose binding unit, a cross-modal verification feedback unit and a closed-loop priority regulation and control unit, multi-modal data such as joint angles and inflammatory factors are collected through detection and fusion of a nine-axis inertial sensor and a biomarker, the morning stiffness period is recognized through a time sequence segmentation model, the dosage of prednisone is dynamically adjusted in combination with a hormone dosage response rule base, and the effectiveness of rehabilitation actions is verified based on a dynamic time warping algorithm. When the medicine taking time deviation exceeds one hour or the action execution is abnormal, a sensor is triggered to enhance the acquisition and dose increment mechanism, and meanwhile, the priority of a nursing instruction is optimized through a conflict arbitration mechanism, so that the full-process intelligence of data acquisition, path generation, verification feedback and priority regulation is realized, and an accurate nursing scheme is provided for patients in the rheumatism immunology department.

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 invention relates to the field of intelligent auxiliary nursing, and particularly discloses a hemodialysis auxiliary nursing system and method.The hemodialysis auxiliary nursing method comprises the steps that firstly, a temperature and humidity information collection module obtains humidity and temperature data in a dialysis area through sensing equipment; the blood pressure influence parameter module analyzes the influence of the data on the blood pressure of the patient to obtain blood pressure influence parameters, and then the dialysis influence parameter calculation module obtains dialysis influence parameters. Meanwhile, the comfort level parameter calculation module evaluates the influence of the environmental factors on the comfort level of the patient, and comfort level perception influence parameters are obtained. The proportion calculation module determines the environmental comfort influence proportion by analyzing the perceptual image array of the patient. Finally, the scheme generation module synthesizes all parameters and formulates an optimal auxiliary nursing scheme. According to the scheme, personalized and precise nursing scheme optimization is achieved, and the stability of the dialysis effect and the comfort degree of a patient are improved.