74 results about "Nursing management" patented technology

The invention relates to an intelligent nursing management system based on artificial intelligence, in particular to the field of intelligent nursing services, and realizes efficient and personalized nursing services by integrating multi-source heterogeneous data and an advanced artificial intelligence technology. According to the system, wearable equipment, physiological signals, environment data and emotion data are fused into low-dimensional spatiotemporal features by using a dynamic graph convolutional network, the data processing efficiency is greatly improved, an LSTM model is trained locally through a federated learning framework and a gradient distillation mechanism, the communication burden is reduced while privacy protection is optimized, and the user experience is improved. A dynamic path generation module analyzes user behaviors, generates personalized nursing paths and marks potential risks, and finally, a meta-reinforcement learning mechanism dynamically adjusts a feature weighting coefficient to ensure that a new user is adaptive within 15 minutes, so that the intelligence, accuracy and efficiency of nursing services are remarkably improved.

The invention relates to the technical field of intelligent medical treatment, in particular to a urinary surgery postoperative risk layering intelligent nursing management system which comprises the steps of preprocessing dynamic sign flow data of a patient to obtain regular sign time sequence data; and separating a core vital sign track, a wound exudation quantitative sequence and an autonomous perception discomfort record through modal analysis. The feature calculation module compares the vital sign trajectory with a standard recovery trajectory library to generate a sign bias spectrum, analyzes the exudation sequence to obtain a wound humidity distribution vector, and calculates a time attenuation factor of the pain event according to the discomfort record. And the space construction and layering module combines the features to construct a multi-dimensional risk base space, and identifies boundary coordinates of high-risk, medium-risk and low-risk risk clusters through clustering. And the strategy generation module divides risk levels and allocates corresponding monitoring and intervention measures according to the risk levels. According to the system, dynamic and multi-dimensional quantitative evaluation of the postoperative recovery state and objective automatic layering of risks are achieved.

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

The invention discloses a nursing information online management system based on multi-source data fusion, which belongs to the field of nursing and comprises modules of data acquisition, access, standardization, compatible processing, storage, privacy protection, intelligent fusion and the like. The system collects multi-protocol data through edge nodes, uniformly converts the multi-protocol data into an intermediate format and performs standardized processing, so that semantic consistency and structure unification are realized. A structure mapping and primary key synchronization mechanism is adopted, and a heterogeneous system data barrier is broken through. Nursing information storage is based on a column database, and performance and reliability are enhanced by combining cold and hot stratification and replica redundancy. The encryption module supports field-level encryption and auditing traceability, and data privacy is guaranteed. The fusion engine utilizes a graph neural network and time sequence modeling to aggregate multi-maintenance information and predict risks. Asynchronous communication and a Protobuf protocol are adopted among the modules, so that low-delay and high-throughput data flow is realized. The intelligent nursing management system has the beneficial effects that the intelligence, precision and safety of nursing management are remarkably improved.

The invention relates to the technical field of medical information, in particular to an interventional operation patient perioperative period nursing information intelligent interaction and management system which comprises the steps that through an integrated data collection module, a timeline generation module, a risk identification module, a nursing intervention module and an interaction management module, time axis alignment and structured coding are conducted on scattered physiological data and diagnosis and treatment events; and a dynamic comprehensive nursing timeline is formed. And performing real-time analysis on the timeline based on a preset risk knowledge graph, identifying an abnormal data mode and generating an early warning. The system automatically matches a nursing rule base, pushes individualized intervention suggestions including specific operations, priorities and bases, synchronizes information and collects feedback through a multi-role interaction channel, and realizes closed-loop management. According to the system, fragmented nursing information can be integrated into a continuous dynamic view, and risk early warning and structured nursing actions are directly linked, so that the collaboration, accuracy and timeliness of nursing management are improved.

The invention relates to the technical field of nursing informatization, and particularly discloses an alarm system and method for intelligent nursing management. The system comprises a data acquisition module, a threshold judgment module, an intelligent analysis module, an alarm push module and a record archiving module. The data acquisition module is used for acquiring multiple physiological parameter data of a patient in real time; the threshold judgment module judges whether to trigger a primary alarm or not according to a set standard value and tolerance; the intelligent analysis module calculates an alarm comprehensive risk index in combination with the primary alarm result, the historical health state of the patient, the nursing grade and the medication condition; the alarm pushing module synchronously pushes the alarm information to the nurse terminal, the doctor workstation and the electronic medical record system according to the risk index level; and the recording and archiving module performs whole-process recording and automatic archiving on the alarm response process.

The invention discloses a rehabilitation nursing management system, and particularly relates to the technical field of medical rehabilitation, and the system comprises a patient intelligent evaluation module which is used for comprehensively evaluating the physiological, psychological and motor function states of a patient through multi-dimensional data collection and intelligent analysis. Physiological, psychological and motion function data of a patient are collected in a multi-dimensional mode through the patient intelligent evaluation module, rehabilitation requirements are predicted based on the data, the personalized rehabilitation plan module formulates a personalized rehabilitation plan according to an evaluation result, immersion rehabilitation guidance is provided through a virtual rehabilitation coach and AR auxiliary training, and the rehabilitation effect is improved. Meanwhile, the training intensity and effect are dynamically optimized, real-time monitoring and risk early warning are achieved through a remote and cooperation module, efficient cooperation among doctors, patients and family members is ensured, the rehabilitation progress is continuously recorded and analyzed through a data driving optimization module, optimization suggestions are provided for the doctors, rehabilitation knowledge is continuously accumulated and updated, and therefore the rehabilitation effect is comprehensively improved; and the safety and effectiveness of training are ensured.

The invention discloses an elderly nursing management optimization system based on artificial intelligence. The elderly nursing management optimization system comprises a nursing data management module, a nursing plan enhancement module, a behavior health guidance module, a psychological health nursing module and an elderly nursing optimization module. The invention belongs to the technical field of old-age nursing optimization, and particularly relates to an artificial intelligence-based old-age nursing management optimization system, which adopts a reinforcement learning method combined with a multi-task deep neural network to enhance nursing plans, and performs time sequence modeling through innovative shared feature learning and emotional state. Efficient information sharing among a plurality of tasks (health assessment, chronic disease management and the like) and mutual optimization among the tasks are realized; performing behavior health guidance by adopting a bidirectional long-short-term memory neural network combining time sequence convolution and an improved support vector classifier; and generating an optimization network by adopting an emotion dynamic modeling strategy, and carrying out psychological health care.

The invention belongs to the technical field of nursing management, and particularly relates to a remote nursing management method and system based on data analysis, which can make up for the defects of the prior art by integrating multi-dimensional nursing data, carrying out deep intelligent analysis and realizing accurate early warning and dynamic scheme adjustment based on comprehensive evaluation, quantify intraday blood pressure fluctuation and improve the nursing efficiency. According to the method, the deviation between the actual blood pressure and the target value is fused, symptom feeling risk calculation is introduced, subjective symptoms are objectively and quantitatively processed, health risks caused by symptom combinations or key symptoms can be effectively recognized, and the accuracy of the health risk is improved. Through multi-dimensional data fusion, innovative risk assessment, a comprehensive effect scoring mechanism and an intelligent closed-loop management process, the defects of fragmentation, one-sided and static states of an existing remote nursing technology are effectively overcome; a more comprehensive, more intelligent and more accurate remote nursing management solution is provided for chronic disease patients, especially crowds needing long-term management such as hypertension.

The invention discloses a traditional Chinese and western medicine cooperative emotion nursing management system and a physiotherapy robot applying the same, and aims to solve the technical problems in the aspects of traditional Chinese and western medicine theory deep cooperation and dynamic personalized nursing in the prior art. The system is realized through the following steps: collecting physiological, behavior, traditional Chinese medicine and other multi-modal data of a user, and constructing a unified traditional Chinese and western medicine cooperative emotional state vector; reasoning by using a traditional Chinese and western medicine fusion knowledge graph to generate an interpretable traditional Chinese medicine macroscopic treatment target; a double-layer hierarchical reinforcement learning model is adopted for decision making, a macroscopic intervention combination is generated through a high-layer strategy, and an accurate robot control instruction containing emotional tactile parameters is generated through a low-layer strategy; and finally, driving the physiotherapy robot to execute the instruction, and continuously optimizing the strategy through closed-loop feedback. According to the method, the artificial intelligence decision theory and the traditional Chinese medicine syndrome differentiation treatment thought are combined, and an automatic and emotional traditional Chinese and western medicine cooperative nursing solution is provided for mood-related functional disorders.

The application discloses a kind of management methods and systems to cope with nursing rehabilitation service, it is related to nursing management technical field;The method includes the steps of: collecting and maintaining the personal information of all users;Regular health assessment is carried out to target user, and obtains rehabilitation state data set;Its technical points are: the daily nursing time length fine tuning operation when the nursing level has reached the limit is constructed, and the ideal range deviation degree of Barthel index, PEI value and body state evaluation value is introduced therein, so that the overall scheme can flexibly adjust the nursing time length under the premise that the nursing level is unchanged or cannot continue to adjust, to adapt to the rehabilitation trend change, on the one hand, individualized nursing resource allocation is realized according to functional state difference, while maintaining the stability of nursing level, enhance service flexibility, on the other hand, avoid the nursing disjointedness phenomenon caused by level limit, complete the optimization management operation of nursing operation.

The present application relates to the technical field of Internet of Things, and particularly relates to an intelligent clinical nursing management and control method and system based on Internet of Things, which comprises the following steps: collecting multi-source data in a clinical nursing environment, and completing timestamp alignment and data encapsulation through an Internet of Things gateway to form multi-source data; after data cleaning, HL7 FHIR format unification and mapping based on an OMOP model, standard nursing data is generated; based on the standard nursing data, a pre-trained LSTM-Autoencoder-based time series anomaly detection model is used to identify collaborative anomaly patterns, and a risk assessment module combining a logistic regression classifier and a gradient boosting decision tree is used to generate a risk level and an occurrence probability; the system generates nursing early warning information and automatically generates nursing management and control instructions according to early warning rule templates, and sends the instructions to nursing equipment or nursing staff terminals through an MQTT network. The present application realizes intelligent clinical nursing management and control, and significantly improves the timeliness, accuracy and intelligent level of clinical nursing.

The invention discloses an intelligent monitoring and tracing system for intravenous medication allocation nursing quality, and relates to the technical field of intelligent nursing management, and the system comprises a time anchoring module, a conflict sensing module, a number fusing module, a dual-factor code forming module and an entropy gate regulation and control module. The time anchoring module is used for constructing a unified time anchoring chain and establishing a number pool monitoring system; and recording traceability code generation request frequency and request node distribution in a time slice corresponding to the unified time anchoring chain, and generating a high-concurrency interval list according to a recording result. Dynamic hierarchical management of traceability code generation is realized through time anchoring and a conflict perception mechanism, a high-concurrency area is identified in advance, dispersed scheduling is carried out, and code uniqueness and traceability chain continuity are ensured. In combination with serial number fusing, two-factor coding and entropy gate regulation and control mechanisms, cross-node non-repeated coding and adaptive load adjustment are realized, the collision risk is reduced, and the safety and stability of medication tracing are improved.

This item is a care management sheet designed to organize the user's medical and treatment history and ensure they receive appropriate care in nursing and medical settings. As shown in the front diagram illustrating the use of this item, the right half of the item contains sections for the user's specific information, emergency contact information, a visual representation of their treatment history, allergy information regarding food and drugs, regular medication information, other precautions, information on care management-related organizations, and the name of the issuing organization. The left half of the item also contains sections for the user's specific information, emergency contact information, medical and treatment history, regular medication information, information on care management-related organizations, and the name of the issuing organization.

The invention relates to an infectious tophus ulcer wound nursing scheme assessment method and system, and the method comprises the steps: collecting the standardized electronic medical record data of a patient through a medical information system, including demostatistics, wound characteristics, laboratory inspection index sequences and nursing records; after structured processing, timestamp unification and missing value filling are conducted on the data, the data are input into a pre-trained deep learning model, expected wound healing probabilities, predicted healing time and complication risk scores corresponding to different nursing schemes are output, then a comprehensive assessment report is generated, the report is stored in a database, and a visual query interface is provided. And meanwhile, collecting actual nursing result data for continuous optimization and updating of the model. According to the invention, quantitative evaluation and prediction of the nursing scheme are realized, clinical decision making is effectively assisted, and the accuracy of nursing management and the resource utilization efficiency are improved.

The application discloses a rural elderly mild cognitive impairment risk prediction and stratified nursing management auxiliary system and method, and belongs to the technical field of intelligent nursing and mobile health auxiliary screening. The system comprises an application path selection module, a data acquisition module, a data preprocessing module, a nursing evaluation and scale automatic scoring module, a risk prediction module, a risk stratification module, an explanation output module, a nursing suggestion generation module and a mobile terminal display module. Through the rapid screening version, simple variables are collected; through the standard evaluation version, GDS-15, IADL, PSQI, SSRS and other scale items are embedded and automatically scored; a pre-trained machine learning model is called to output MCI risk prediction probability, low, medium and high risks are divided, and corresponding reevaluation frequency and stratified nursing management suggestions are generated. The application can display the results through a webpage calculator or a WeChat applet, is used for primary screening assistance and risk communication, and does not replace clinical diagnosis.

This invention relates to the field of urine glucose monitoring technology, and more particularly to a method and system for monitoring urine glucose data from adult diapers. The method first interacts with a nursing management system to obtain daily care milestones for the patient, and connects to a wearable terminal to generate a visual monitoring interface. Secondly, at preset milestones, multiple sensors integrated into the inner layer of the diaper collect data, combining health parameters to identify abnormalities and predict the level of blood glucose abnormalities. Subsequently, based on historical data from multiple milestones, a blood glucose fluctuation trend curve is generated on the interface. Finally, a personalized intervention plan is formulated based on the abnormality level and the trend curve, implementing targeted nursing care. This invention achieves non-invasive continuous monitoring through multi-source signal fusion to combat interference; it possesses the ability to predict blood glucose trends, transforming passive alarms into proactive prevention; and through a visual interface and intelligent decision-making closed loop, it significantly improves the accuracy, efficiency, and comfort of nursing care for diabetic patients.

The invention belongs to the technical field of patient nursing layered management, and provides a patient nursing layered intelligent management system based on drainage liquid data, which comprises the steps of performing real-time continuous monitoring on the drainage liquid data of a postoperative patient, establishing a drainage liquid amount prediction model, and taking the monitored drainage liquid data as input, outputting a drainage liquid amount predicted value in a future preset time period; performing drainage liquid trend analysis on the drainage liquid amount predicted value in the future preset time period, and judging whether the drainage liquid amount in the future preset time period shows a descending trend or not; targeted monitoring, evaluation and intervention schemes are provided for patients with different risk levels, the distribution efficiency of nursing resources is optimized, limited resources are preferentially inclined to high-risk patients, medical staff can be helped to timely discover postoperative abnormal conditions of the patients and take corresponding measures, dynamic optimal configuration of the nursing resources is achieved, and the nursing efficiency is improved. The scientificity and the refinement level of nursing management are improved, and the method has a remarkable management application value.

This invention relates to the field of data processing technology, specifically to an intelligent rehabilitation and nursing management system based on data analysis. The system includes: a motion state acquisition module that acquires raw electromyographic signals and joint torque and angle values; a physiological characteristic analysis module that extracts the median frequency sequence in the frequency domain and constructs an electromyographic fatigue gradient; a motion compensation calculation module that calculates the end-effector driving torque and generates a motion compensation coefficient; and an adaptive control execution module that calculates the resistance increment based on the fatigue gradient and calculates virtual wall parameters to construct a control strategy when the compensation coefficient exceeds the limit. In this invention, by combining frequency domain analysis to construct a fatigue gradient, using a dynamic model to calculate the compensation ratio, adjusting resistance based on the compensation coefficient and fatigue state, and constructing virtual wall constraints, quantitative analysis of physiological characteristics and motion states is achieved. This ensures adaptive matching of the optimal strategy while guaranteeing safety, thereby improving the intelligence and accuracy of training.

The application discloses a kind of chronic infectious disease digital people health management system construction method, it relates to AIDS nursing management technical field.Based on Triangle model, the management classification and characteristics of HIV patients are determined by latent profile and association rule analysis, and it is embedded into applet using agile development;Based on the basic nursing framework, the commonality and difference of patients in different levels are explored Care needs;Through the preliminary construction of AIDS hierarchical case management program by range review and focus group interview, the final draft is formed by revising and improving through written evaluation and field demonstration, and the well-constructed management program is embedded into a digital human interaction platform based on artificial intelligence.The application protects the privacy of patients, alleviates the shortage of medical human resources, meets the growing health needs of HIV patients, improves patient satisfaction and improves the quality of HIV care services.

This application provides a method for optimizing nursing tasks in a smart hospital, comprising: S1. Real-time acquisition of multidimensional physiological signals of patients and ward nursing workflow status data; inputting the multidimensional physiological signals of patients and the ward nursing workflow status data into a risk assessment model to generate a true risk value reflecting the patient's risk status; using the multidimensional physiological signals of patients, the ward nursing workflow status data, and the true risk value as initial state parameters, simulating and pre-visualizing the nursing task conflict state in future time periods through a ward digital twin, dynamically optimizing the nursing task queue according to the system entropy minimization criterion, and distributing the optimized task flow to the nurse's terminal. By introducing deep learning and multi-source data fusion technology into smart hospital nursing management, a proactive nursing management system with risk prediction, task conflict perception, and dynamic scheduling optimization capabilities is constructed, which can effectively improve the efficiency of nursing resource allocation.

The invention discloses an augmented reality thoracic surgery postoperative patient nursing management method, and relates to the technical field of postoperative nursing, and the technical scheme is characterized by comprising the following steps: collecting cognitive ability data, home nursing scene adaptation data and remote medical support data of a thoracic surgery postoperative patient; constructing a three-dimensional linkage model, inputting the cognitive competence data, the home nursing scene adaptation data and the remote medical support data into the three-dimensional linkage model, and performing score division through the adaptation degree of the three-dimensional linkage model to obtain a high-dependence nursing area, a collaborative nursing area and an autonomous nursing area; and judging the patient cognitive deviation data, the scene adaptation conflict data and the remote support response data of the high-dependence nursing area to obtain a first nursing feature set, so that the nursing support can be adjusted in real time along with the change of the cognition, scene and capability of the patient, and the accuracy and the flexibility of nursing management are improved; and finally, efficient rehabilitation of thoracic surgery postoperative patients is assisted, and the complication risk is reduced.

The invention relates to a comprehensive nursing management system based on big data analysis, which belongs to the technical field of artificial intelligence model treatment and comprises a fairness data management unit, a fairness quantitative evaluation unit, a risk trend early warning unit and a self-adaptive intervention response unit. The fairness data management unit is used for dividing medical data nodes into a preset number of medical resource level groups, and collecting the average prediction error rate and the total population of each medical resource level group; and the fairness quantitative evaluation unit is used for receiving the average prediction error rate and the total population sent by the fairness data management unit, performing fairness quantitative analysis, and generating a medical resource allocation deviation index. The risk management system and method ensure the continuity and the high efficiency of risk management.

This invention discloses a method and system for constructing a disaster resilience classification training program for clinical nurses, belonging to the fields of disaster nursing management and computer image recognition technology. It involves acquiring facial micro-expression image sequences of nurses in standardized disaster simulation scenarios; extracting the activation frequency, activation duration, and left-right facial activation symmetry features of the zygomaticus major and orbicularis oculi muscles and inputting them into a preset resilience classifier; outputting subtype labels based on a fixed mapping relationship between the spatiotemporal features of muscle activity and resilience subtypes; retrieving the corresponding basic training framework based on the labels; comparing the activation duration features with a threshold; and generating reinforcement training labels on the framework using image overlay technology to form a personalized classification training program. This invention achieves objective and real-time subtype identification of clinical nurses' disaster resilience and can automatically generate differentiated training content targeting resource deficiencies in different subtypes, significantly improving the accuracy and automation level of disaster resilience training.

The invention relates to the technical field of intelligent nursing, and discloses a disease intelligent nursing auxiliary system based on evidence-based data, comprising: an evidence-based knowledge base module integrating multi-source evidence-based data to form a specialized knowledge graph; the model training optimization module carries out base model field fine tuning and multi-algorithm fusion according to the multi-source evidence-based data so as to carry out intelligent decision-making assistance and generate a personalized nursing scheme; the multi-scene intelligent interaction module carries out knowledge pushing, consultation and question answering through multi-terminal interaction; the full-period nursing management module performs staged nursing execution and dynamically adjusts a nursing plan; the quality control early warning module carries out risk early warning, medication verification and flow quality control; and the multi-dimensional effect evaluation module generates a multi-level evaluation report, and drives update of the evidence-based knowledge base and algorithm iteration. According to the invention, an accurate and adaptive whole-cycle nursing scheme and standardized guidance are provided, the nursing risk is reduced by means of real-time quality control early warning, and the treatment compliance and medical experience of a patient are improved.

The application provides a traditional Chinese and western medicine combined whole-process nursing management system for tumor patients, relates to the field of intelligent health management, and first collects physiological, exercise, diet and psychological condition data of the tumor patients, then identifies potential health risks of the tumor patients by analyzing the physiological, exercise and diet data, simultaneously evaluates the positivity of the patients according to the psychological condition data, and subsequently inputs all the collected data and the identification and evaluation results into a traditional Chinese and western medicine combined nursing health management suggestion engine based on a large language model to generate traditional Chinese and western medicine combined nursing health management suggestions conforming to the actual conditions of the tumor patients. In this way, comprehensive and personalized health management services can be provided for the tumor patients.

The invention relates to a door-to-door nursing management method, device and system, computer equipment and a computer readable storage medium. The method comprises the following steps: establishing communication connection between a user account end and a doctor account end; receiving inquiry record information sent by the doctor account end, and generating and filing an electronic medical record based on the inquiry record information; and sending a nursing task to the first nursing account end, after the first nursing account end starts the nursing task, sending an electronic medical record associated with the user account end to the first nursing account end, and after the first nursing account end completes browsing of the electronic medical record, establishing a video communication connection between the first nursing account end and the second nursing account end. The first nursing account end and the second nursing account end are enabled to perform nursing information checking based on the video communication connection; and after the first nursing account end and the second nursing account end complete nursing information checking, generating a nursing document based on the nursing record information, and archiving the nursing document. By adopting the method, the home care service quality can be improved.

The invention relates to the field of nursing management, and discloses a neurosurgical nursing management system based on cloud computing, which is used for solving the problem of data conflict or data synchronization delay when nursing management is carried out according to patient information, and comprises the following steps: monitoring and collecting initial multi-source data; the multi-source data comprises vital sign data, postoperative medication records, nursing observation records and postoperative image data, performing synchronous processing on the initial multi-source data to obtain synchronous multi-source data, performing data conflict processing on the synchronous multi-source data to obtain actual multi-source data, and storing the actual multi-source data into a database; according to the method, the actual multi-source data is subjected to data integration to obtain patient integration information, data analysis is performed according to the patient integration information, health early warning is generated, personalized nursing tasks are designed according to the patient integration information, and the tasks are allocated to related nursing personnel, so that the accuracy of acquiring the patient information is effectively improved, and the nursing quality and the treatment effect are improved.

The invention provides a PD classification identification optimization method based on I-III stage drug clinical test nursing, and relates to the technical field of drug clinical test nursing management. The method comprises the following steps: collecting I-III phase drug clinical test nursing related data, and screening PD data; dividing the PD into three categories, namely test drug configuration or use deviation, sample collection or treatment deviation and vital sign detection deviation, and judging the severity; the PD core root is analyzed in combination with test item types, medicine dosage forms and nursing working modes; the matching system comprises a data acquisition module, a classification identification module, a root analysis module, an optimization strategy output module and a dynamic monitoring module. According to the method, the defects of fuzzy PD classification, inaccurate root analysis and insufficient prevention and control strategy pertinence in the prior art are overcome, the PD risk point can be accurately positioned, the PD occurrence rate is effectively reduced, the clinical test nursing quality is improved, the test risk is reduced, and the method has good practicability and popularization value.

The invention discloses a psychological nursing management method and system based on electroencephalogram biofeedback, and belongs to the field of cognitive disorder nursing and rehabilitation management. According to the method, case basic information, cognitive function evaluation and electroencephalogram related data are obtained and are classified and divided into a joint intervention data set and a conventional intervention data set, individualized electroencephalogram biological feedback parameters and targeted psychological nursing schemes are matched for the joint intervention set, data are collected in stages to generate a comparison data set, and the comparison data set and the conventional intervention data set are matched. An analysis result is output after multi-dimensional analysis; the system comprises a data acquisition module, a data processing module, an intervention data generation module and a result analysis module which interact in sequence. According to the method and the system, the standardization of the whole process of nursing management is realized, the data quality and intervention suitability are guaranteed, the change trend of cognitive function indexes is accurately analyzed, reliable support is provided for intervention effect evaluation and scheme optimization, and the scientificity and normalization of nursing management are improved.