61 results about "Medical team" patented technology

The invention provides a medical material distribution method and system based on an offshore medical rescue unmanned aerial vehicle. Wherein a marine environment model is generated; according to the marine environment model, an AI scheduling algorithm is applied to analyze the specific demand, priority and emergency degree of a marine receiving point, and an optimized task sequence and a material loading scheme are obtained; establishing a cooperative communication mechanism between offshore medical rescue unmanned aerial vehicle formations through an AI-driven distributed consensus algorithm, and dynamically adjusting a flight path and generating a distribution path by using an AI path planning technology in combination with real-time situation awareness and obstacle detection analysis; and after arriving at a specified receiving point, automatically calibrating the landing coordinates, and synchronizing the material state, handover information and environmental data to a medical team and a central scheduling system through a low-delay wireless transmission mode according to the distribution path. According to the technical scheme provided by the invention, the efficiency and reliability of offshore material distribution are greatly improved.

Data captured during a surgical procedure can include video streams, such as from a laparoscopic camera. Technical solutions are described to facilitate online surgical phase recognition from the captured video stream(s). Surgical phase recognition is key in developing context-aware supporting systems for surgeons and medical teams in general. The technical solutions describe taking temporal context in videos into account by precise modeling of temporal neighborhoods in a video.

The invention discloses a coronary intervention postoperative risk prediction model construction method and system, and belongs to the technical field of medical care information and health monitoring. A coronary intervention postoperative risk prediction model construction method comprises the steps of constructing an attending doctor experience scoring system and a nursing personnel ability scoring system, and performing weighted fusion on results of a doctor experience model and a nursing personnel model to form a final additional model for output. According to the coronary intervention postoperative risk prediction model construction method and system provided by the invention, the main model is combined with the additional model, the main model is comprehensively modeled through the regression model and the time sequence model based on the static and dynamic characteristic data of the patient, and the individual health state change of the patient is captured; the additional model evaluates the influence of medical teams and relatives on the postoperative risk by quantifying the experience of doctors and the ability of caregivers, and overcomes the defect that a traditional model only depends on patient data.

Carriers for embodying radioactive seeds, as well as a device for loading and customizing brachytherapy carriers based on the principles of optimizing a more precise and predictable dosimetry, and adaptable to the geometric challenges of a tumor bed in a real-time setting. The present disclosure relates to a specialized loading device designed to enable a medical team to create a radionuclide carrier for each patient and tumor reliably, reproducibly and efficiently.

The invention discloses a complete-cycle information interaction system for a breast reconstruction patient, and relates to the technical field of information interaction of the breast reconstruction patient, and the system comprises the steps: collecting patient information and expert literature information, and carrying out the preprocessing of the collected information; creating a breast reconstruction patient rehabilitation exercise virtual simulation model for visual display, and synchronizing patient information in real time; calculating a patient rehabilitation coefficient, and evaluating a patient rehabilitation state; the patient and family members are assisted in virtual patient nursing learning; and encrypting the patient information, and storing the patient information. The rehabilitation state of the patient is evaluated, nursing skill training is performed on the patient and family members, the rehabilitation state of the patient is monitored in real time, the nursing risk prevention consciousness and the coping capacity of the patient and the family members are improved, nursing risks caused by misoperation and improper coping are reduced, problems occurring in the rehabilitation process are found in time, the treatment strategy is adjusted, and the rehabilitation effect of the patient is improved. A medical team is helped to formulate a personalized rehabilitation plan according to the unique condition of each patient, and long-term health and stability of the patients are maintained.

The invention discloses a pain grade evaluation method and an evaluation system thereof. According to the method and the system, the pain condition of the patient can be comprehensively and accurately evaluated by integrating various evaluation tools. The combined use of e-VAS, EIAS, AIS and PMS not only considers the intensity and physiological influence of pain, but also covers the influence of psychological state and life quality, thereby providing a multi-dimensional pain assessment perspective for medical staff. And meanwhile, by introducing digital and remote monitoring technologies, the convenience and efficiency of pain management are greatly improved. The digital operation of the e-VAS is simple and visual, the patient can easily complete self-evaluation, and the remote monitoring system allows the patient to continue to participate in pain management after being discharged from the hospital and keep continuous communication with a medical team. The continuity and convenience not only improve the treatment compliance of the patient, but also enable the medical staff to adjust the treatment scheme in time so as to cope with the dynamic change of the pain, thereby achieving the effects of optimizing the patient experience and enhancing the treatment effect.

The utility model belongs to the technical field of medical equipment for field operations, particularly relates to a comprehensive guarantee trailer of a field operation vehicle, and aims to solve the problems that an existing medical vehicle is time-consuming and labor-consuming to unfold and carried matched medicines are easy to freeze, and adopts the following scheme that the comprehensive guarantee trailer comprises a trailer assembly and a corridor assembly, and is provided with the trailer assembly and the corridor assembly, when the corridor assembly is in the unfolded state, the front end of the corridor assembly can extend and be tightly attached to the position of a rear channel of a compartment body after the field operation vehicle is unfolded, inconvenience caused by repeated material loading and unloading is avoided in the unfolding and folding process, the unfolding and folding time of a field medical team is greatly shortened, and rapid unfolding and folding of the whole operation process are achieved; the problem that related medicines in the operation in the cold region are easy to freeze is fundamentally solved; the driving assembly has a manual driving mode or an electric driving mode, manual driving or electric driving unfolding or folding of the shear fork type telescopic corridor frame can be selected in a targeted mode according to specific use conditions, and the requirement for use in different field operation environments is met.

The invention discloses a medical image diagnosis auxiliary system based on deep learning, and relates to the technical field of medical image processing. According to the method, through integrity verification, exclusive noise suppression and space standardization processing, dynamic changes of focus characteristics are captured through a time sequence attention mechanism, meanwhile, a medical pathology professional knowledge graph is called to achieve accurate matching of the time sequence focus characteristics, an anatomical structure and pathology type nodes, and the risk of missed diagnosis and misdiagnosis is greatly reduced; the confidence coefficient of a diagnosis assistance conclusion is evaluated through a multi-dimensional factor, manual review is automatically prompted for a low-confidence-coefficient result, dual management and control of system assistance and manual check are formed, meanwhile, standardized focus positioning, pathological type candidate and diagnosis basis can be provided for basic-level or inexperienced doctors, and the diagnosis accuracy is improved. Repeated work such as data arrangement can be reduced for experienced doctors, the doctors are assisted to focus on complex case judgment, the diagnosis and treatment level of a medical team is integrally improved, medical risks are effectively reduced, and the diagnosis and treatment quality and efficiency are improved.

The invention belongs to the technical field of medical rehabilitation, and discloses a rehabilitation treatment monitoring system based on multi-modal sensing and AI evaluation. A multi-dimensional skeleton key point confidence evaluation mechanism is established by integrating three types of sensing data of visual skeleton tracking, an inertial measurement unit and pressure distribution, and potential tracking interruption risk frames and error recognition candidate frames are recognized in real time. And a multi-modal fusion correction model is adopted to carry out accurate compensation on error recognition, missing data are reconstructed in combination with a skeleton motion mode memory bank and a bidirectional time sequence prediction algorithm, and a continuous and complete all-day skeleton motion sequence is generated. On the basis of the calculation, the time-phased activity level index and the rehabilitation action completion degree score of the patient are calculated, and an objective and quantitative rehabilitation evaluation basis is provided. According to the invention, the stability and continuity of skeleton tracking in a complex rehabilitation environment are improved, so that a medical team can obtain a real and complete all-day activity portrait of a patient, accurately position a rehabilitation bottleneck, formulate a personalized treatment scheme and promote functional recovery of the patient.

The invention discloses a cardiovascular medicine nursing remote monitoring system, and relates to the field of medical information technology and remote medical technology, the cardiovascular medicine nursing remote monitoring system comprises a remote electrocardio monitoring center, the remote electrocardio monitoring center is in communication connection with a cardiovascular data acquisition module, a cardiovascular risk prediction module and a cardiovascular health visualization module; the cardiovascular data acquisition module collects physiological data through a wearable sensor, the cardiovascular risk prediction module predicts the cardiovascular disease risk by using an elastic network regression analysis model and provides personalized suggestions, and the cardiovascular health visualization module displays the health trend and updates cloud data in real time. According to the remote nursing monitoring system for the cardiovascular medicine department, through real-time monitoring and data analysis, the precision and efficiency of cardiovascular disease management are improved, optimal configuration of medical resources is promoted, individuation and continuity of health management of patients are enhanced, communication and cooperation among medical teams are enhanced, and the medical management efficiency is improved. And higher-quality remote medical service is provided for the patient.

The invention belongs to the field of pesticide poisoning prognosis, and particularly discloses a method for establishing an acute diquat pesticide poisoning prediction death risk index, which comprises the following steps: collecting data; establishing a death risk index model based on demographic characteristics and blood routine test results; and carrying out model training, internal verification and external verification. The death risk index provided by the invention comprehensively considers age, diquat blood concentration, leukocyte count and glutamic oxalacetic transaminase concentration, and aims to accurately evaluate the death risk of acute diquat pesticide poisoning patients in an index form. Through deep analysis of large-scale clinical data, the death risk index of the invention not only has scientificity and accuracy on the data level, but also can play an important role in clinical practice, can be applied to construction of acute diquat pesticide poisoning death risk prediction terminal equipment, helps medical teams to distribute medical resources more reasonably, and has a good application prospect. High-risk patients are preferentially processed, so that the overall treatment effect and the survival opportunity of the patients are improved.

The invention relates to the technical field of doctor-patient communication, in particular to an acute pancreatitis doctor-patient communication risk management system based on interactive data analysis, which comprises a patient condition dynamic database, a condition deterioration prediction module, a communication closeness evaluation module and a resource dynamic allocation module, the storage module is used for storing patient physiological indexes, behavior data and medical records; the condition deterioration prediction module is used for predicting the condition deterioration probability of a patient, identifying a high-risk time period and guiding resource pre-allocation; the communication closeness evaluation module is used for quantifying the communication demand closeness between the patient and the medical team and generating a patient priority; and the resource dynamic allocation module is used for automatically allocating resources according to the predicted deterioration probability and the patient priority.

This utility model relates to a multi-channel working device for minimally invasive surgery, belonging to the field of minimally invasive surgical equipment technology. It includes a base plate, a tray mounted on top of the base plate, an electric rail mounted on the side of a support column on the tray, a slide on the electric rail, and a support arm connected to the slide. A platform and a hanging plate are respectively mounted at both ends of the support arm. A medication tube is fixedly placed on the platform. A disinfection tube is fixedly installed on the top outer side of the hanging plate, and a tube plate is fixedly installed on the bottom outer side of the hanging plate. A medication delivery tube, a disinfection tube, and a vertical rod are fixedly installed inside the tube plate. A endoscopic probe is fixedly installed at the bottom of the vertical rod. This utility model allows for medication delivery, disinfection, and surgical image control during minimally invasive surgery, greatly reducing the number of medical staff involved and making surgical scheduling more timely and flexible. Simultaneously, this utility model significantly improves the efficiency of medical team collaboration, thereby ensuring high-quality surgical completion and reducing the failure rate of minimally invasive surgery.

Cardiopulmonary resuscitation demands rapid and precise responses, particularly in hospital emergency departments. The "Automated Resuscitation Trolley Alert and Drug Dosage System" is designed as an add-on compatible with various resuscitation trolleys. The system features a powerful central processing unit, a liquid-resistant capacitive touchscreen, an audio-visual alert system with high-power LEDs, and communication modules for hospital network integration. It uses artificial intelligence and machine learning algorithms to calculate drug dosages based on patient information and monitoring data. The audio-visual alert system reduces medical team response times in emergencies. Connectivity to hospital information systems enables quick access to patient data and automatic logging of actions. By enhancing precision and speed in drug administration, minimizing human errors, and improving team coordination, this invention significantly improves the quality of emergency services and the success rate of resuscitation procedures.

The invention provides an emergency response method, system and device and a storage medium, and relates to the technical field of emergency response, a plurality of sub-behavior interaction items are determined according to the recognition of behavior interaction events, and a collision part and a corresponding collision level of a person to be subjected to emergency treatment are determined according to the recognition of each sub-behavior interaction item. According to the position of each collision part of the to-be-rescued person, the corresponding collision level and the previous medical record information of the to-be-rescued person, the preliminary emergency state of the to-be-rescued person is predicted, and the accuracy of the preliminary emergency state of the to-be-rescued person is improved. Determining a corresponding first-aid response process according to each piece of illness state representation information, the initial first-aid state of the to-be-rescued person and the position of the to-be-rescued person; according to the invention, the plurality of sub-first-aid items are determined based on the recognition of the first-aid process of the to-be-rescued person, and the emergency response event is determined according to the plurality of sub-first-aid items, the corresponding medical team and the current state of the to-be-rescued person, so that the accuracy of the emergency response event is further improved.

The invention provides an applet system for communication between a patient and family members in an ICU (Intensive Care Unit), and relates to the technical field of ICU patient management. The system comprises a subject entry notice and information list module which is used for providing image-text interpretation for assisting in understanding ICU and key information for representing the health condition of a patient; a medical staff information and cost management module; the visiting appointment module is used for appointment visiting time for remote video visiting with the patient; the remote visiting module integrates a video call technology and a short message sending technology and is used for supporting remote video visiting of family members and patients at visiting time; a disease progress and daily report module; a health education and psychological support module; a family member interaction and experience sharing module; and an emergency contact and assistance module. Through the system, the unknown fear of family members to the ICU can be eliminated, the time for the family members to search for medical staff is shortened, the trust of the family members to a medical team is enhanced, and the emotional communication requirements of patients and the family members are met.

The present invention discloses a temporal lobe epilepsy resection surgery efficacy evaluation system based on brain image fusion features. The system collects and pre-processes multimodal brain imaging data before and after surgery, including T1-weighted images, diffusion tensor imaging (DTI), and functional magnetic resonance imaging (fMRI), and uses multi-time series analysis methods such as recurrent neural networks (RNN) and long short-term memory networks (LSTM) to generate a postoperative recovery model. The personalized efficacy evaluation module combines the patient's clinical characteristic data. The report generation and visualization module uses visualization technology to generate easy-to-understand reports from the evaluation data for the medical team to review and make decisions. Through multimodal data fusion and advanced algorithm models, the present invention improves the accuracy and reliability of efficacy evaluation, comprehensively reflects the changes in the patient's brain structure and function, has broad clinical application prospects, and significantly improves the patient's quality of life after surgery.

The present invention belongs to the field of prognosis of pesticide poisoning. Specifically disclosed is a method for establishing a mortality risk prediction index for acute diquat pesticide poisoning, comprising: collecting data; establishing a mortality risk index model based on demographic characteristics and routine blood test results; and training, internally validating, and externally validating the model. The mortality risk index provided by the present invention comprehensively considers age, blood concentration of diquat, white blood cell count, and aspartate aminotransferase concentration, aiming to accurately evaluate, in the form of an index, the mortality risk of patients suffering from acute diquat pesticide poisoning. Through in-depth analysis of large-scale clinical data, the mortality risk index of the present invention possesses scientific validity and accuracy at the data level, and can also play an important role in clinical practice. Further, the present invention can be applied to construct a terminal device for predicting the mortality risk of acute diquat pesticide poisoning, assisting medical teams in more reasonably allocating medical resources and prioritizing high-risk patients, thereby improving overall treatment outcomes and the patients' chances of survival.

The utility model belongs to the technical field of medical material car, concretely relates to a vehicle-mounted box group fixing frame, the utility model discloses a plurality of layers of storage layer, and each layer of storage layer is used for placing box group, a plurality of pieces of rotary blocking piece are respectively arranged on the upper edge of each layer of storage layer, and one end of each piece of rotary blocking piece is connected with the upper edge of storage layer, the lower dead point position of rotary blocking piece corresponds the upper edge position of box group, and the horizontal position of rotary blocking piece is higher than the upper edge position of box group, the utility model is used for solving the technical problem that the fixing mode of the frame in medical material car to box group leads to the inconvenient and quick removal of medical material, hinders the timely rescue of medical team under the emergency.

The present invention discloses a method and system for intelligent monitoring of surgical incisions, which relates to the technical field of intelligent monitoring methods. The state of the surgical incision is determined according to temperature data, exudate data, tension data, and the corresponding type of surgery, and the overall consideration of temperature data, exudate data, tension data, and the corresponding type of surgery is compatible, thereby ensuring the accuracy of the state of the surgical incision and realizing intelligent monitoring of the surgical incision. If the state of the surgical incision is an abnormal state, the abnormal level is determined based on the temperature data, exudate data, and tension data, and the early warning event of the surgical incision is determined according to the abnormal level and the current image of the surgical incision, further realizing intelligent monitoring of the surgical incision. The corresponding incision repair event is determined according to the early warning event of the surgical incision, the change roadmap of the surgical incision, and the personnel status of the corresponding medical team, thereby ensuring the accuracy of the incision repair event.

The embodiment of the invention provides a method and a device for determining a key video frame in an operation event. The method and the device are used for solving the problem that a medical team cannot automatically store an image under the condition that the operation is not interfered. The method comprises the following steps: acquiring a video stream collected when a target operation event is executed, wherein the video stream comprises a plurality of video frames to be detected; performing target detection on each to-be-detected video frame, and determining a target object included in each to-be-detected video frame; determining a target operation stage in the target operation event corresponding to each to-be-detected video frame according to a feature map obtained by object features in the to-be-detected video frames; determining a standard object corresponding to the target operation stage based on a preset association relationship between the operation stage and the standard object; and when it is determined that the target object is not included in the standard object, determining that the to-be-detected video frame is a key video frame when a target operation event is executed.

The present invention relates to the field of medical prediction technology, specifically a system for predicting general anesthesia symptoms based on patient data, the system comprising: a state monitoring module that collects the patient's heart rate and blood pressure parameters, records the continuous time point data during the operation, tracks the state changes, and obtains the state change tracking results. In the present invention, by analyzing the continuous physiological data of the patient during the operation, the accuracy of the prediction of anesthesia complications is improved, the slight changes in the physiological state are monitored in real time and the correlation analysis is performed with the effects of anesthetics, so that the ability to predict potential risks is enhanced, and through the real-time updated conditional probability calculation, not only the insight into key risk points is increased, but also data support is provided for the decision-making of the medical team, thereby effectively reducing the probability of patients encountering adverse events during the operation, and optimizing the risk assessment in combination with historical data, the overall safety of the operation process is guaranteed, and the treatment effect on the patient is significantly improved.

The application provides a medical material distribution method and system based on a marine medical rescue unmanned aerial vehicle. A marine environment model is generated; according to the marine environment model, an AI scheduling algorithm is applied to analyze the specific needs, priority and urgency of the marine receiving point, and an optimized task sequence and material loading scheme are obtained; a cooperative communication mechanism between the formations of marine medical rescue unmanned aerial vehicles is established through an AI-driven distributed consensus algorithm, and an AI path planning technology is used in combination with real-time situation awareness and obstacle detection analysis to dynamically adjust the flight path and generate a distribution path; after arriving at the designated receiving point, the landing coordinates are automatically calibrated and processed, and the material state, handover information and environmental data are synchronized to the medical team and the central dispatching system through a low-delay wireless transmission mode according to the distribution path. The technical scheme provided by the application greatly improves the efficiency and reliability of marine material distribution.

The application discloses an emergency response device for medical staff and electronic equipment, and relates to the technical field of medical information processing. The device comprises a team construction unit, which is used for calculating the total score of the medical staff according to the skill matching coefficient, the response time coefficient, the on-duty load rate and the qualification coefficient of the medical staff; the medical staff is divided into a first-level or second-level standby medical team according to the total score of the medical staff and the response time; a monitoring unit is used for monitoring the department manpower load rate, the department critical patient proportion, the hospital load rate or the public health event identifier; an activation unit is used for obtaining the emergency response level according to the monitored data, and the activation medical staff list is obtained and output from the standby medical team according to the emergency response level and the current manpower gap, so that the precision, automation and high timeliness of the emergency trigger are realized, and the technical problems of the existing technology, such as the untimely emergency medical response and the resource mismatch, are solved.

The invention provides a medical resource optimization matching method and system for emergency and critical disease rescue, and relates to the technical field of software testing, and the method comprises the steps: obtaining microcirculation perfusion data, wound characteristics, inspection data and basic illness state data of a target patient; obtaining a microcirculation perfusion index dynamic gradient of the target patient according to the microcirculation perfusion data; processing the microcirculation perfusion index dynamic gradient, the trauma characteristics, the test data and the basic illness state data of the target patient by using an illness state grading model to obtain an illness state grade and an organ failure risk probability of the target patient; inputting the disease grade, the organ failure risk probability, the medical resource state matrix, the medical team energy efficiency coefficient and the space-time constraint parameter of the target patient into a resource optimization model to obtain a medical resource scheduling scheme of the target patient; and performing medical resource scheduling according to the medical resource scheduling scheme. By applying the method provided by the invention, patient condition grading and resource requirements can be accurately identified.

A large language model system for automatic clinical guide updating and customization belongs to the technical field of medical information management, and comprises a data collection and processing module, a natural language (NLP) processing module, a model training and updating module, a guide updating and customization module, a knowledge base and intelligent recommendation module, and a user interface and interaction module. The method can quickly and accurately analyze, update and customize clinical guidelines and provide personalized treatment suggestions, and has the advantages that wide medical literatures and clinical data can be integrated and processed, automatic decision support is carried out in combination with expert knowledge, latest medical research results are quickly applied to clinical practice, and the method has a good application prospect. Therefore, doctors and medical teams can be helped to make treatment decisions more effectively, and medical quality and patient nursing are improved.

The invention discloses a postoperative recovery time determination method and device, equipment, a medium and a program product, and is applied to the technical field of artificial intelligence. The method comprises the following steps: acquiring user parameters of a user; the user parameters comprise physiological feature parameters used for representing the physiological state of the user, disease risk level parameters used for representing the disease of the user, operation related parameters, anesthesia related parameters and medical team ability evaluation parameters; the user parameters are input into an intraoperative anesthesia mode determining model, an intraoperative anesthesia mode output by the intraoperative anesthesia mode determining model is obtained, and the intraoperative anesthesia mode comprises a non-general anesthesia mode or a general anesthesia mode; according to the intraoperative anesthesia mode and the user parameters, the postoperative recovery time of the user is determined. According to the method, the postoperative recovery time of the user is determined through the user parameters of the user in multiple dimensions and the intraoperative anesthesia mode, and the problem that the accuracy is low when the postoperative recovery time of the user is predicted only through the physiological feature data in a single dimension can be solved.

The utility model relates to the technical field of nursing appliances, and discloses a postoperative sickbed nursing frame which comprises a bed body, a hidden groove is formed in the lower end of the bed body, limiting grooves are formed in the inner walls of the two sides of the hidden groove, limiting blocks are arranged in the two limiting grooves in a sliding mode, a fixing base is fixedly connected between the two limiting blocks, and a fixing rod is arranged on the fixing base. A movable groove is formed in the upper end of the fixing seat, a storage rack is movably arranged in the movable groove, and two fixing racks are fixedly connected to the position, close to the hidden groove, of the lower end of the bed body. According to the utility model, the nursing frame can be directly folded under the bed body according to the use condition, so that the requirements of a medical team can be quickly responded, the operation space around the sickbed is saved, the risk of collision with a patient or other equipment is reduced, the safety and efficiency of operation are improved, and when the nursing frame is required to be used, the nursing frame is convenient to use. The foldable nursing frame can be quickly pulled and unfolded, and meanwhile, the position of the folded or unfolded nursing frame can be fixedly limited.

The present teachings include optical systems and methods for detection of peritonitis in early stages for patients undergoing a peritoneal dialysis (PD) treatment. An initial measurement of optical extinction of effluent fluid may be stored as a baseline value for a patient, e.g., to compensate for color, density, and similar optical factors related to the specific patient's physiology. Optical extinction through the effluent may be periodically measured over the course of a PD treatment, and extinction of signal relative to the baseline is analyzed, primarily for early indicators of potential peritonitis. The system may be externally connected to an effluent conduit, e.g., via a clip. A technique of ratioing an optical signal through effluent to a reference optical signal for measurements may provide high sensitivity while filtering out significant noise, enabling early detection of infection. Alerts of potential infection may be provided to the patient, caregiver, and / or medical team.

The invention discloses an intelligent monitoring method and system for a surgical incision, and relates to the technical field of intelligent monitoring methods. The state of the surgical incision is determined according to temperature data, percolate data, tension data and corresponding surgical types; the temperature data, the percolate data, the tension data and the corresponding operation types are considered integrally, the accuracy of the state of the surgical incision is guaranteed, and intelligent monitoring of the surgical incision is achieved. And if the state of the surgical incision is an abnormal state, determining an abnormal level based on the temperature data, the percolate data and the tension data, and determining an early warning event of the surgical incision according to the abnormal level and the current image of the surgical incision, thereby further realizing intelligent monitoring of the surgical incision. And the corresponding incision repair event is determined according to the early warning event of the surgical incision, the change route map of the surgical incision and the personnel state of the corresponding medical team, so that the accuracy of the incision repair event is ensured.