317 results about "Clinical nursing" patented technology

The invention provides a neurology clinical nursing potential safety hazard analysis method and device, and relates to the technical field of neurology clinical nursing, and the method comprises the steps: inputting a risk feature matrix generated based on multi-source heterogeneous nursing data into a rule engine and graph neural network model, and outputting a preliminary screening risk event set; taking the primary screening risk event set and the risk feature matrix as input, and constructing a causal conduction map through a causal discovery algorithm; performing risk conduction quantitative integration on each risk event in the primarily screened risk event set based on a causal conduction map to generate a quantitative risk list; based on the dynamic risk priority number and the conduction path chain, reversely tracing to a root cause node along a directed conduction edge, and generating a targeted intervention strategy packet bound with the root cause node; the targeted intervention strategy package is pushed to the nursing responsible person terminal, the strategy execution effect and the risk evolution data are recorded, and a closed-loop disposal database is generated, so that the dynamics and the effectiveness of potential safety hazard analysis of clinical nursing of the neurology department are improved.

The invention provides a patient pathological data analysis and evaluation method for clinical nursing, and relates to the technical field of nursing informatization. Comprising the steps of collecting biochemical and pathological data of a patient and standardizing units and reference values, analyzing the dynamic trend of detection values and classifying change directions and amplitudes, matching pathological labels and establishing association with nursing items, comparing differences between nursing records and the pathological data and establishing a transverse index relationship, and judging whether the nursing task difference exceeds a threshold value or not and adjusting a nursing path generation scheme. By integrating multi-source pathological data and standardizing units and reference intervals, data consistency and comparability are ensured, the index fluctuation trend is dynamically tracked, the change direction and amplitude are quantitatively analyzed, disease course evolution is accurately captured, direct mapping between pathological categories and nursing items is established, logic binding is clear, intervention precision is improved, and the method is suitable for clinical application. Differences between nursing records and pathological data are transversely compared, nursing dynamic adaptation is optimized, a path scheme is rapidly adjusted through threshold judgment, and the lagging or misjudgment risk is reduced.

The invention relates to the technical field related to anesthesia nursing data processing, in particular to an anesthesiology department clinical nursing data management method and system, and the method comprises the steps: collecting anesthesiology department clinical nursing data, configuring a first data mapping table and a second data mapping table through static features and dynamic features according to a platform end and an application end, and generating a nursing knowledge graph, adjacent event features are obtained, and multi-scale risk assessment is combined with dynamic threshold reminding. The technical problems that time sequence correlation and cooperative influence of all events in the anesthesia process are not fully considered, risk assessment standards cannot be dynamically adjusted for different anesthesia stages, and risk misjudgment is likely to be caused are solved, and by configuring a first data mapping table and a second data mapping table and combining time entropies and correlation rule support degrees corresponding to time intervals of adjacent events, the risk assessment standard can be dynamically adjusted according to the time entropies and the correlation rule support degrees. Layered management and accurate mapping of static and dynamic characteristics in clinical nursing data of the anesthesiology department are realized, the risk threshold is dynamically adjusted according to time sequence characteristics of different anesthesia stages, and the accuracy and timeliness of risk assessment are remarkably improved.

The invention discloses a postoperative drainage device for clinical nursing and a monitoring system, and belongs to the technical field of biomedical engineering. The problems that an existing device manually monitors drainage liquid data, consequently, the monitoring precision is insufficient, and the complication probability cannot be predicted are solved, drainage liquid and patient vital sign data are collected in real time through the micro spectrograph, the character multi-parameter sensor, the micro pressure sensor and the intelligent bracelet and transmitted to the remote monitoring platform, and the monitoring accuracy is improved. Medical staff can check real-time data of a patient at any time and adjust a treatment scheme in time, so that the nursing efficiency and quality are improved; multi-parameter data such as color, metering and property of drainage liquid and vital sign data are analyzed through a risk prediction model, intervention measures are dynamically adjusted according to different complication types and probabilities in combination with patient condition changes and real-time monitoring data, accurate intervention on the complication is achieved, and the occurrence rate and severity of the complication are reduced.

The invention relates to the technical field of medical treatment, in particular to a multi-parameter collaborative infusion process intelligent monitoring and priority calling method, which comprises the following steps of: acquiring four-dimensional monitoring data through a liquid level pressure sensor array, an infrared dripping speed detection module, a flexible temperature patch and a photoelectric heart rate sensor, and combining an LSTM (Long Short Term Memory) anomaly prediction model, and outputting the pipeline state score, the allergy risk index and the infusion progress prediction value in real time. And generating a real-time risk value through a weight configuration mechanism and stage identification logic, judging a risk level according to a dynamic threshold value, and outputting a corresponding early warning level signal. And the system further maps the early warning level signals into common, emergency and critical call instructions, and distributes the common, emergency and critical call instructions to a multi-channel execution terminal to construct a multi-level linkage response mechanism of closed-loop feedback. According to the invention, the accuracy and response efficiency of infusion risk identification can be significantly improved, and the method is suitable for intelligent reconstruction and automatic early warning response scenes of a clinical nursing information system.

The invention discloses an intelligent off-bed monitoring system and method based on polymorphic perception, relates to the technical field of medical monitoring, and breaks through the misjudgment bottleneck of a single sensor by synchronously collecting a body pressure center point coordinate sequence and a breathing waveform amplitude time sequence of a patient and dynamically associating a body movement frequency feature vector with a breathing waveform interruption feature. Real off-bed and on-bed activities are effectively distinguished, and the false alarm rate is effectively reduced; the early warning accuracy is counted in real time, when the false alarm rate exceeds the standard, the mahalanobis distance between a false alarm event and a real off-bed event is calculated to generate a feature offset, a judgment threshold value is dynamically corrected, and the system is adaptive to individual differences of patients; a real-time feedback mechanism improves long-term stability of the system, and sensitivity and reliability are both considered. The system is especially suitable for precise monitoring requirements of high-risk patients, and provides intelligent decision support for clinical nursing.

The invention relates to a clinical nursing shift change system and method, and relates to the technical field of data processing, and the system comprises a nurse terminal module which is used for inputting shift change information through a standardized template, carrying out the continuous visualization of shift change, and carrying out the butt joint with an electronic medical record system, so as to automatically capture the abnormal and real-time data of a patient; the patient end module is used for generating a two-dimensional code scanning interface for a patient and family members to check nursing propaganda and education, guidance and diagnosis and treatment routes, and feeding back an abnormal state through a voice or graphical interface; the doctor end module is used for synchronously displaying key medical parameters in shift change data, so that a doctor can mark a risk level and trigger a secondary confirmation process; the quality control management end module is used for generating a traceable responsibility definition coefficient; and the data analysis module is used for calculating a shift-change integrity score representing shift-change information integrity and a global shift-change quality index representing shift-change quality in real time. The system can improve the accuracy and efficiency of clinical nursing shift change.

The invention relates to the technical field of clinical nursing, in particular to a clinical nursing system for interventional operations, which can accurately identify and predict potential complications by performing deep neural network analysis in combination with preoperative medical history, intraoperative real-time physiological data and operation types. It is ensured that a nursing scheme can be finely adjusted based on individual differences of patients, complex physiological data can be processed through a deep neural network, key physiological data are recognized from the complex physiological data, the scheme is dynamically adjusted in the nursing process through a long-short-term memory network, and the nursing accuracy is improved. The change trend of data in the operation is deeply mined, the fluctuation of physiological indexes is tracked, the abnormity is timely identified, the potential risk is predicted, the nursing decision and the physiological state of the patient can be synchronously updated, the working efficiency of nursing personnel is optimized, and the postoperative recovery effect and comfort of the patient are improved.

The invention provides a full-scene nursing task dynamic generation method, and relates to the technical field of medical treatment. The method comprises the steps of obtaining medical data of a target user in a preset medical institution; performing event identification according to the medical data of the target user and a trigger condition of at least one preset clinical event associated with each clinical nursing business scene in the plurality of clinical nursing business scenes; if the trigger conditions of the target clinical event associated with the clinical nursing business scene are identified to be matched, loading a target event template corresponding to the target clinical event, and extracting a standardized nursing activity set corresponding to the target clinical event and a nursing task set of each nursing activity under the standardized nursing activity set from the target event template; and instantiating the target clinical event by adopting the target event template according to the medical data of the target user, the standardized nursing activity set and the nursing task set of each nursing activity, and generating a full-cycle nursing task for the target clinical event. Therefore, the efficiency is improved.

The invention relates to a generative AI-based nursing case intelligent teaching question and answer robot and application thereof.A current teaching task is executed through an RAG enhanced retrieval module, question and answer knowledge is retrieved from a nursing knowledge base based on keywords in user question and answer information, and LLM is used for performing enhanced retrieval on the question and answer knowledge; the learning dynamic evaluation module performs learning performance evaluation on answer information in user question and answer information by using LLM, and the workflow management module pushes teaching tasks with corresponding learning strength to the RAG enhanced retrieval module in a matching manner to perform personalized learning path and branch scheduling. Clinical nursing cases can be created based on the generative AI, the nursing key points are answered and answered in a guiding mode, the clinical nursing thinking of students is improved in repeated practice, and the nursing teaching effect is improved. And nursing cases of different specialities are generated according to a rule enhancement formula, so that students are gradually guided to strengthen learning, and the autonomous learning ability and clinical thinking of the students are improved.

According to the clinical nursing patient information monitoring and inputting method and system, the data accuracy, the data inputting efficiency and the privacy protection safety are improved; the method comprises the following steps: firstly, collecting and preprocessing vital sign data of a patient in real time through various physiological sensors; then, acquiring a nursing record image, acquiring nursing record data through an OCR model, acquiring nursing information voice, transwriting the nursing record data and the nursing information voice into nursing information data through a medical scene voice transwriting model, and performing unified standardization processing on the three groups of data to generate patient information data; and finally, when patient information data is input, symmetric encryption is carried out by adopting a national cryptographic SM4 algorithm, encrypted data is obtained, a dynamic encryption key is generated through an ECDH key distribution technology, and the dynamic encryption key can be called to carry out decryption operation after authentication of a dual protection mechanism of Hash value pre-verification and identity authentication is passed.

The invention relates to the technical field of medical care, and particularly discloses a massage device for clinical care. Bionic massage mechanisms are mounted on the outer walls of the two sides of the massage bed, and a stimulation massage mechanism is mounted in the middle of the bottom end of the massage bed; the bionic massage mechanism comprises a multi-degree-of-freedom mechanical arm, a mounting mechanism, a massager, a moving block, a moving screw rod, a fixed frame and a driver, the mounting mechanism is mounted at one end of the multi-degree-of-freedom mechanical arm, and the massager is clamped and mounted at the other end of the mounting mechanism; through cooperative operation of the multi-degree-of-freedom mechanical arm and the driver, complex actions of kneading, pushing and pressing, tapping and the like of a professional rehabilitatrist can be simulated, massage manipulations are greatly enriched, the massage effect is remarkably enhanced, a pressure sensor arranged on the massager can monitor local pressure intensity changes of a massage part in real time, and the massage effect is improved. When the pressure intensity reaches a preset threshold value, the controller can automatically adjust the massage intensity, and it is ensured that the massage process is effective and safe.

The invention relates to the technical field of respiratory lung sound recognition, in particular to a respiratory lung sound auxiliary recognition method and system for clinical nursing. The invention provides a respiratory lung sound auxiliary identification method and system for clinical nursing, solves the technical problems of data scarcity, complex noise interference and insufficient cross-device generalization ability in lung sound signals through generative data enhancement and cross-modal migration, and combines self-supervised comparative learning and causal feature discovery to identify the respiratory lung sound. Multi-source signal feature fusion and noise robustness improvement are realized, a real-time noise environment is dynamically adapted, the limitation that a traditional method depends on annotation data and feature extraction is easily influenced by hybrid noise is broken through, a full-link closed-loop system from synthetic data generation, cross-modal alignment to causal-driven decision is constructed, and multi-source signal feature fusion and noise robustness improvement are realized. And the accuracy and clinical applicability of clinical lung sound analysis are effectively improved.

The utility model relates to the technical field of compression hemostasis devices, in particular to a compression hemostasis device for clinical nursing, which comprises a fixing plate and a compression hemostasis rubber head, the fixing plate is semicircular, the inner wall of the bottom of the fixing plate is fixedly connected with a fixing block, and the outer wall of the top end of the fixing block is fixedly connected with an arc-shaped plate. A sponge pad is bonded to the inner wall of the arc-shaped plate, a second clinical nursing compression belt is fixedly connected to the outer wall of one side of one side of the top end of the fixing plate, and a first clinical nursing compression belt is fixedly connected to the outer wall of the other side of the other side of the top end of the fixing plate. The top compression hemostasis rubber head can slide on the compression belt and can be conveniently and accurately adjusted to a bleeding position, the limb bottom supporting structure can be bent and folded, so that the side face of the limb is attached and limited, the compression stability is further improved, and hemostasis failure caused by limb sliding is prevented; and the use efficiency of the compression hemostasis device for clinical nursing is improved.

The invention relates to a clinical symptom nursing strategy intelligent recommendation system and method based on artificial intelligence, and the method combines historical clinical symptoms and nursing big data to construct a corresponding nursing strategy intelligent recommendation model, thereby enabling the nursing strategy intelligent recommendation model to recognize the feature relationship between different symptom features and corresponding nursing strategies. And enabling the model to recognize the symptom characteristics of a clinical patient and intelligently recommend a corresponding nursing strategy. The system can also combine model output and nurse feedback, fuse and recommend a clinical symptom nursing strategy most related to patient symptoms, so that nurses can make preliminary assessment and deal with the appearing symptoms to confirm nursing problems, sort critical and urgent conditions, develop nursing measures, highlight nursing key points and improve the nursing efficiency. And potential complications can be prevented or treated in time. In clinical nursing work, clinical nurses can be effectively guided to perform judgment thinking and carry out predictive nursing, so that the nursing work is homogenized, and the nursing quality and safety are improved.

The invention relates to the technical field of clinical nursing management, and discloses an intelligent nursing system and method based on clinical big data, and the system comprises a clinical nursing node supervision module, a clinical nursing personnel allocation module, and a clinical nursing execution module. According to current nursing time point information, in combination with an intelligent search algorithm and target patient clinical nursing plan information, patient clinical nursing project information is accurately extracted, clinical nursing projects are efficiently customized and supervised for patients at different clinical nursing time nodes, and the service quality and efficiency of clinical nursing are improved; the optimal clinical nursing personnel is accurately and scientifically screened based on the clinical nursing project information of the target patient, the working state of the clinical nursing personnel and the spatial distance information between the clinical nursing personnel and the patient, intelligent allocation of the clinical nursing personnel is achieved, and the response speed and scientificity of clinical nursing are improved.

The present application relates to the technical field of clinical nursing, in particular to a clinical nursing system for interventional surgery, in the present application, through the combination of preoperative medical history, intraoperative real-time physiological data and operation type, depth neural network analysis can accurately identify and predict potential complications, and the nursing plan can be adjusted according to the individual differences of patients, the nursing plan can be adjusted according to the individual differences of patients, the depth neural network can process complex physiological data and identify key physiological data, the long short-term memory network can dynamically adjust the scheme in the nursing process, the change trend of intraoperative data is deeply mined, the physiological index fluctuation is tracked, the abnormality is identified in time and the potential risk is predicted, the nursing decision can be updated synchronously with the physiological state of the patient, the working efficiency of the nursing staff is optimized, and the postoperative recovery effect and comfort of the patient are improved.

The invention discloses an intelligent analysis and early warning system for potential safety hazards of clinical nursing, and relates to the technical field of intelligent nursing monitoring. Physiological data of a patient is collected in real time and preprocessed, a physiological data set S is constructed and summarized and calculated, characteristic indexes are obtained, and a microcirculation disturbance index Wxh is calculated according to the characteristic indexes; the method comprises the following steps: evaluating the current body state of a patient, constructing a time sequence analysis model, predicting a microcirculation disturbance index Wxh of the patient in a future period of time, evaluating the health state of the patient in the future period of time, carrying out risk early warning, carrying out nursing strategy grading, and carrying out nursing intervention on the patient. The physiological data of the patient in the clinical nursing process are monitored in real time, the clinical nursing effect is optimized, and the nursing efficiency and the nursing safety are improved.

The invention relates to the technical field of medical care, in particular to a clinical care information recording method and equipment of an intelligent medical system and a medium. The method comprises the following steps: acquiring a patient category of a current patient, taking other patients in the patient category as target patients, and acquiring a nursing effectiveness degree according to a target achievement condition and a physical sign stability condition of the target patients; screening low-score patients through nursing plan satisfaction scoring, obtaining contrast patients of the low-score patients, and obtaining reference weights of the low-score patients according to differences between the low-score patients and the contrast patients; and presetting reference weights of other target patients except the low-score patient, obtaining a nursing evaluation degree according to the reference weights, the nursing effectiveness degree and nursing plan satisfaction scoring, and judging whether the nursing plan of the current patient is reasonable or not. By acquiring the nursing assessment degree, whether the nursing plan of the current patient is reasonable or not is accurately judged, and the nursing plan of the current patient is adjusted in time, so that the current patient is effectively treated.

The invention relates to the technical field of intelligent teaching and medical nursing, and discloses a clinical nursing teaching and training intelligent interaction system based on a large language model. According to the system, teaching behaviors and text data are collected, and multi-dimensional evaluation and quantification are carried out, so that an evaluation result containing a capability label is generated. Based on this result, the system dynamically constructs a personalized progressive teaching knowledge stream from the clinical care knowledge map. And meanwhile, the system carries out context-aware intention hierarchical analysis on the interactive content to form a hierarchical graph containing a core intention and a derivative demand. And fusing the knowledge flow and the analysis atlas, and driving the large language model to generate and execute a series of teaching instructions. The system achieves the dynamic adjustment of teaching contents along with the performances of students, can deeply understand the teaching intention for intelligent guidance, and improves the individuation and adaptability of training.

The invention relates to the technical field of medical care information, in particular to a clinical nursing monitoring information input method, system and equipment, and the method comprises the steps: obtaining to-be-input clinical nursing monitoring information and historical clinical nursing monitoring information, and carrying out the word segmentation extraction of the monitoring information, the real-time segmented words of the to-be-input clinical nursing monitoring information and the historical segmented words of the historical clinical nursing monitoring information are obtained; the method comprises the following steps: analyzing real-time segmented words of to-be-input clinical nursing monitoring information and historical segmented words of historical clinical nursing monitoring information, screening out high-frequency segmented words in all real-time segmented words of descriptive information in the to-be-input clinical nursing monitoring information, and determining the to-be-encrypted degree of each high-frequency segmented word; determining an optimal encryption round number group of each high-frequency segmented word; and based on the optimal encryption round number group, encrypting all real-time segmented words in the to-be-input clinical nursing monitoring information, and inputting encrypted data. The encryption input efficiency of the clinical nursing monitoring information is effectively improved.

The invention provides a tracheal catheter fixing and patient falling prevention linkage nursing device. The device comprises a tracheal catheter fixing module, a falling prevention detection module, an alarm intervention module and an interaction management module. The tracheal catheter fixing module is used for ensuring that the tracheal catheter does not slip or shift in the body position change or nursing process of a patient; the anti-falling detection module is used for monitoring the body position change of a patient on the nursing bed in real time; the alarm intervention module is used for giving an alarm to medical staff when potential dangers are monitored; the interaction management module is used for optimizing a risk reminding strategy in combination with medical care feedback of the device in the use process; by means of the linkage mechanism of catheter fixing and body position monitoring, accurate recognition and intelligent early warning of tracheal catheter slipping and the risk that a patient falls off a bed are achieved, and the safety and the active intervention capacity of clinical nursing are remarkably improved.

The invention relates to the technical field of electric digital data processing, in particular to an ophthalmology department clinical nursing data preprocessing method and system. The method comprises the following steps: realizing stage clustering of pathological images through a K-Medoids algorithm based on predefined typical images; carrying out deformable image registration on the images in the same stage, and extracting key focus features through group difference analysis and structural pattern recognition; generating a weighted mask by using the lesion features, and realizing local enhancement processing of the original image; further extracting non-image modal data corresponding to the image and carrying out structured coding; and finally, constructing a time axis taking the image acquisition time as a reference, and aligning and fusing the image modality and the non-image modality to generate multi-modality comprehensive information. The system supports co-processing and feature enhancement of multi-source data, provides more accurate input for subsequent intelligent analysis and nursing intervention, and improves clinical aid decision-making efficiency and reliability.

The invention relates to an intelligent nursing and monitoring device used after glaucoma filtration, and belongs to the technical field of medical instruments, the intelligent nursing and monitoring device comprises a rigid main frame, the inner side of the rigid main frame is provided with a flexible sealing gasket, the upper portion of the rigid main frame is integrated with a self-adaptive positioning system, and the left side and the right side of the rigid main frame are connected with directional physical nursing execution systems; a microenvironment humidity monitoring system is embedded in the ball head, and the rear side of the frame is connected with an intelligent central control system. The self-adaptive positioning system accurately recognizes eyeball and filtered bubble areas, the directional physical nursing execution system reproduces standardized nursing operation, the microenvironment humidity monitoring system verifies the nursing effect in real time, and the intelligent central control system overall plans all the systems to cooperate and supports remote data transmission. The device can solve the problems of inaccurate postoperative nursing, lagged effect feedback and poor patient compliance, improves the nursing quality, assists in improving the success rate of an operation, and is suitable for families and clinical nursing scenes.

The utility model provides a kind of multifunctional air bed, belong to medical instrument technical field, including air cushion main body, temperature regulating pad, temperature control piece and water supply part. Among them, temperature regulating pad is set on the upper surface of air cushion main body, and temperature regulating pad has the flow channel for water flow inside. Temperature control piece has the heating cavity for heating water and the cold cavity for cooling water. Water supply part has the first pipeline being communicated with flow channel, the second pipeline being communicated with heating cavity and the third pipeline being communicated with cold cavity. Water supply part has control part, and control part is used to control the communication of first pipeline with second pipeline or third pipeline. The utility model provides a kind of multifunctional air bed, effectively solves the problem that traditional air bed cannot carry out body temperature intervention, realizes the double function of body pressure distribution optimization and body temperature management, significantly improves the adaptability and comfort of clinical nursing.

The utility model relates to the technical field of postoperative rehabilitation, in particular to a bone lumbar puncture postoperative compression hemostasis device and a lumbar puncture postoperative compression hemostasis device.The bone lumbar puncture postoperative compression hemostasis device comprises a hemostasis unit which comprises a transparent patch, a hemostasis assembly arranged at the bottom of the transparent patch and a pressing assembly arranged on the upper portion of the transparent patch; the hemostasis assembly and the pressing assembly are matched with each other, and the hemostasis assembly comprises sponge arranged at the bottom of the transparent patch, antibacterial gel arranged on the sponge and a pasting part arranged on the transparent patch. The compression hemostasis device used after bone lumbar puncture has the advantages that the hemostasis assembly is matched with the pressing assembly, the operation that a third party needs to assist in pressing is omitted, manpower of clinical nursing staff is greatly saved, accuracy of the pressing position can be improved, a specially-assigned person is not needed for pressing, time of medical staff is saved, and the working efficiency of the medical staff is improved. The pressing time can be adjusted according to the actual condition of the patient.

The invention discloses a reminding device for clinical nursing and monitoring in a ward, relates to the field of clinical nursing, and solves the problem that an existing reminding device is difficult to ensure that a patient or surrounding people are prompted in time, the reminding device comprises a device shell and a shooting probe installed at the top of the device shell, and a display screen is fixedly installed on the outer side of the device shell; a calling button is arranged below the display screen, a microphone and a loudspeaker are fixedly installed on the two sides of the display screen respectively, and the two sides of the device shell are each provided with two moving wheels which are symmetrically distributed; the prompting mechanism is used for enabling the device shell to call and prompt surrounding personnel in time, and the prompting mechanism is mounted on the inner side of the device shell; by means of the prompting mechanism, when a patient is abnormal, the four moving wheels can drive the device shell to move along the bed head of the ward, two loudspeakers make sounds in time, people around the ward can find the abnormal conditions in time, the safety is higher compared with a traditional loudspeaker, and therefore the safety prompting effect is achieved.

The utility model discloses a clinical sterile nursing bag for gynecological reproduction, and relates to the technical field of medical instruments. The clinical sterile nursing bag for gynecological reproduction comprises a nursing bag body, isolation belts are fixedly connected to the interior of the nursing bag body and divide the interior of the nursing bag body into a plurality of storage spaces, sealing covers are arranged on the outer wall of the nursing bag body, a sealing cover is arranged above each storage space, and hidden buckles are fixedly connected to the sealing covers and the outer wall of the nursing bag body. The front side and the rear side of the nursing bag are fixedly connected with a second connecting belt and a first connecting belt respectively. And a waistband is arranged on one side of the nursing bag. The inside of the nursing bag is divided into a plurality of storage spaces through the isolation belts, gynecological reproductive clinical nursing articles can be stored in a classified mode, the elastic tool fixing belts can fix tools, the containing bag can contain small articles, and meanwhile the sealing cover of each storage space and the outer wall of the nursing bag are clamped, fixed and sealed through the hidden buckles. And the articles are ensured to be in a relatively sterile environment.

This invention relates to the field of smart healthcare technology and discloses a method and system for verifying clinical nursing information based on speech recognition. The method includes the following steps: an edge device acquires a nursing item script; responds to a voice wake-up command, driving the terminal to read the script item by item; collects real-time voice recordings and performs beamforming noise reduction, using semantic vectors to accurately extract assessment information and fill in the slots; intelligently identifies missing items and triggers dynamic follow-up questions; summarizes and generates structured confirmation information for repetition; if a modification command is detected, a pointer callback is triggered to jump to re-record, and after confirmation, the information is encrypted and uploaded to the cloud. This invention, through a cloud-edge-device collaborative architecture and breakpoint protection technology, achieves contactless entry and closed-loop verification of nursing records. This solution supports interrupted resume transmission and non-linear logic jumps, effectively solving the pain points of easily interfered clinical operations and cumbersome manual recording. While ensuring aseptic operation, it significantly improves the efficiency and accuracy of clinical document generation.

The invention provides a clinical nursing work intelligent distribution method and system based on a VRP model, and belongs to the technical field of clinical nursing. Comprising the steps of obtaining nursing demands and priorities of patients in real time, and regarding the obtained nursing demands as distribution demands; dynamically analyzing the working attribute state of each nurse in the department, and regarding the working attribute state of each nurse as the vehicle state; performing path resource optimization based on a VRP model in combination with a distribution demand and a vehicle state, namely, designing a target function by taking minimization of total resource consumption as a final target; calculating an optimal path by solving a target function; and determining the driving path of each vehicle according to the optimal path, namely determining the work task of each nurse in the department. According to the invention, the minimization of manpower, time and material consumption in the department can be realized on the basis of ensuring reasonable task distribution of clinical nursing work.