175 results about "Patient satisfaction" patented technology

The invention relates to the technical field of medical rehabilitation, in particular to an artificial intelligence-based orthopedic full-cycle rehabilitation management system, which comprises a rehabilitation demand evaluation module, a three-dimensional pathological modeling module, a multi-modal training generation module, a rehabilitation effect prediction module, a dynamic parameter adjustment module and a full-cycle management module. Multi-dimensional data such as bone mineral density, joint motion range, gait mechanics and psychological state of a patient are collected, an artificial intelligence algorithm is combined for analysis, a personalized rehabilitation scheme is generated, and rehabilitation parameters are predicted and adjusted in real time. The system can dynamically correct the training intensity, the nutritional supplement dosage, the psychological intervention mode and the rehabilitation schedule, and the safety and reliability of data are guaranteed through the block chain technology; according to the system, biomechanics, nutriology, psychology and environmental factors are comprehensively fused, the system has strong adaptive ability and full-period management ability, real-time optimization can be performed according to the rehabilitation process of a patient, and the rehabilitation effect of the orthopedics department and the satisfaction degree of the patient are remarkably improved.

The invention provides an operating room high-value consumable management system based on artificial intelligence, and relates to the technical field of artificial intelligence, an intelligent sensing module collects position information, state information and use conditions of high-value consumables in real time through RFID tags and sensors, and identification and tracking of the consumables are achieved. And the artificial intelligence analysis module analyzes the use frequency of the consumables and the relevance between the operation type and the demand based on a deep learning algorithm so as to predict the future consumable demand. And the inventory management module dynamically adjusts the inventory according to the actual use condition and the predicted demand. The operation auxiliary module automatically generates a consumable list according to the operation type and the patient condition, and medical staff is reminded to prepare. And the compliance supervision module records full life cycle data of the consumables, provides a traceability report and ensures compliance. Through the technical means, the operation cost of a hospital is remarkably reduced, the operation safety and the satisfaction degree of a patient are improved, and wide application prospects and important social value are achieved.

The invention discloses an oral diagnosis and treatment patient service platform based on reinforcement learning, and relates to the technical field of diagnosis and treatment services, and the platform comprises a health scoring module which integrates multi-source data, generates personalized oral health scores through a dynamic weight distribution model, and displays high-risk items in combination with 3D visualization; the patient management and marketing module tracks patient behaviors, clusters and classifies the patient behaviors, generates a dynamic follow-up visit path by using multi-target reinforcement learning, and matches a precise marketing verbal skill through a knowledge graph; the in-diagnosis auxiliary module synchronizes health data of the patient to the doctor terminal in real time, detects prescription conflicts and performs early warning, and generates personalized communication verbal skills in combination with historical preferences of the patient and real-time emotion analysis; through multi-dimensional data integration and intelligent processing, the whole oral diagnosis and treatment process is optimized, the diagnosis and treatment efficiency and the patient satisfaction degree are improved, the operation cost is reduced, and remarkable innovativeness and practicability are achieved.

The invention relates to a human body posture capture-based disabled assisting robot planning method and system, and the method comprises the following steps: S1, a patient is fixed to a system main body through a flexible fixing device, so that the posture capture precision is ensured, and accidental sliding is prevented; s2, a high-definition RGB camera and a depth sensor are used, real-time posture joint point data of the patient are obtained based on a human body posture estimation algorithm, and the real-time posture joint point data comprise the head position, the limb position and the trunk position; s3, resolving the captured data in real time, and referring to a posture database to generate a most suitable initial rehabilitation posture; s4, collecting visual, voice and physiological signals by using a camera, a microphone and other sensors, and performing feature extraction and fusion by using a convolutional neural network to improve the recognition accuracy; s5, judging the satisfaction degree of the patient to the current posture through an emotion recognition technology in combination with voice emotion analysis, and adjusting the system according to the satisfaction degree of the patient; the motion parameters of rehabilitation training of the patient are obtained quickly, the effectiveness and rehabilitation efficiency of rehabilitation training are improved, and the participation degree and enthusiasm of the patient are increased.

The invention discloses a patient medical satisfaction evaluation system based on big data, and relates to the technical field of big data analysis. The medical satisfaction evaluation system comprises a data acquisition and processing module, an evaluation index management module, a satisfaction questionnaire survey module, a multi-dimensional evaluation module, a satisfaction grading module and a service quality optimization module. According to the big data-based patient doctor-seeing satisfaction degree evaluation system, through real-time collection and analysis of patient satisfaction degree data including a medical quality evaluation index and a doctor-seeing experience evaluation index, registration waiting time, diagnosis and treatment waiting time and an endemic area environment score are monitored, service bottlenecks and patient dissatisfaction fields are rapidly identified, and the patient satisfaction degree evaluation efficiency is improved. The hospital can adjust resource distribution in time, the overall quality of medical services is evaluated through the patient complaint score and the doctor-patient communication transparency score, effective communication between doctors and patients is promoted, transparency is improved, and therefore the satisfaction degree and credibility of the patients for the medical services are improved.

The invention discloses a refined health care management and control method and management and control platform for pregnancy preparation people, and relates to the technical field of health care, and the method comprises the steps: building a full-period pregnancy preparation health care system, and obtaining a plurality of health treatment and nursing nodes; constructing a pregnancy preparation health nursing patient education knowledge base, and obtaining a patient education nursing node partition knowledge base; obtaining a target health care risk parameter; and obtaining health care consultation knowledge, and performing refined health care management and control on the target user. The problems that existing pregnancy preparation health care lacks refined and personalized adjustment and risk assessment for individual health conditions, living habits and specific requirements, accurate, objective and comprehensive health care knowledge is difficult to obtain, consequently, tension and anxiety of a patient cannot be effectively relieved, the overall medical experience is poor, and the patient experience is poor are solved. The technical problems are solved, and the technical effects of improving the overall working efficiency, the medical experience and satisfaction of the patient and the treatment effect are achieved.

The present invention discloses an artificial intelligence-based (or AI-based) system and method for providing personalized treatment plans to individuals suffering from mental health disorders. By leveraging EEG measurements, patient data, and AI algorithms, this system addresses the unique needs of each patient and enhances the overall quality of mental health care. The AI-based personalized treatment system has the potential to revolutionize mental health care. By amalgamating EEG measurements and an extensive range of patient-specific factors, it enables a tailored, dynamic approach to mental health treatment that takes into account the complete patient profile. The integration of this system into existing electronic health record (EHR) systems or patient monitoring platforms creates a patient-centered experience that enhances treatment outcomes, patient satisfaction, and reduces the strain on healthcare professionals.

The invention relates to the technical field of medical decision assistance, and particularly discloses a doctor-patient co-decision multi-issue negotiation method and system and a readable storage medium, and the method comprises the following steps: firstly collecting preference information and behavior characteristics of a doctor and a patient for a plurality of negotiation issues; constructing a fuzzy constraint and satisfaction function based on preference information and behavior characteristics; constructing a proxy behavior model based on the fuzzy constraint and the satisfaction function, and forming a distributed negotiation problem; and dynamically optimizing the negotiation strategy through a value function by adopting an ADP (adaptive dynamic programming) algorithm until the negotiation is consistent to generate a common negotiation result or the negotiation fails and terminates the negotiation, and sending a recommendation scheme to the doctor agent and the patient agent. According to the doctor-patient co-decision multi-issue negotiation method and system and the readable storage medium, the negotiation success rate and efficiency are improved, the medical specialty and patient individuation requirements are balanced, the doctor-patient satisfaction is remarkably improved, and the doctor-patient co-decision multi-issue negotiation method and system are suitable for a multi-issue medical decision scene.

The invention provides a hospital bed dynamic allocation optimization method, system and device, and relates to the technical field of hospital bed data processing, and the method mainly comprises the steps: collecting historical multi-source data; defining a constraint condition and a target function of bed deployment; constructing a global optimization model; constructing a current bed state matrix based on the current bed allocation scheme; based on the demand of the current patient, constructing a patient bed arrangement demand vector; collecting current hospital historical data; initializing the priority of the global optimization model; randomly distributing current idle beds, generating an initialized bed allocation scheme, inputting the initialized bed allocation scheme into the global optimization model, and obtaining a global optimal solution; constructing and training a deep reinforcement learning model; and collecting current multi-source data in real time, inputting the current multi-source data into the deep reinforcement learning model, and iteratively predicting a bed allocation scheme and transmitting the predicted bed allocation scheme out until an iteration termination condition is met. According to the scheme, the bed utilization rate and patient satisfaction can be effectively improved.

The invention discloses a hospital nursing quality evaluation system based on hospital information terminal data, and relates to the technical field of medical information, and the system comprises a data acquisition module which extracts index data based on a hospital terminal, and the index data comprises patient satisfaction subjective index data, nursing personnel working life data, performance data and adverse event occurrence probability; after preprocessing the data, constructing a data set; and the analysis module performs correlation analysis on the data of the data set based on the Pearson's correlation coefficient, constructs a nursing quality evaluation model through a neural network, and performs training optimization on the quality evaluation model. The comprehensive evaluation level is efficiently and objectively output through the evaluation module, the result is presented through a visual chart, managers can conveniently master the comprehensive evaluation level, hospitals accurately position nursing service short boards according to the evaluation result, targeted optimization is implemented, the nursing system is continuously improved, the requirements of patients are met, and it is ensured that the nursing quality is kept at a high level; and data in a hospital can be fully utilized.

The invention discloses an intelligent feedback type encephalopathy rehabilitation guidance training system which collects physiological data of a patient in real time through a wearable device or a brain-computer interface, carries out accurate evaluation and generates a personalized training plan in combination with individual differences and rehabilitation progress of the patient. In the training process, the system provides immediate feedback and guidance, and correctness and effectiveness of training are ensured. Meanwhile, the system also integrates comprehensive rehabilitation guidance functions, including cognition, language and motion function recovery, psychological support, life skill training and the like; through the cloud data processing center, medical personnel can remotely monitor the rehabilitation condition of a patient and adjust a training plan in time. The system not only improves the pertinence and effectiveness of rehabilitation training, but also enhances the rehabilitation confidence and participation degree of the patient. In a word, the intelligent feedback type encephalopathy rehabilitation guidance training system provides all-around and personalized rehabilitation services for encephalopathy patients, and the rehabilitation effect and the satisfaction degree of the patients are remarkably improved.

The invention discloses an internet-based physical hospital comprehensive information management system, which relates to the technical field of hospital information management and comprises a data acquisition module, a data processing module, a calculation module and an analysis module. According to the method, factors such as resource types, use frequency and maintenance cost are comprehensively considered, a visual resource utilization situation overview is provided for hospitals, resource allocation can be optimized to a certain extent, resource waste is reduced, the resource use efficiency is improved, and the method combines multiple dimensions such as medical service quality and patient satisfaction, so that the medical service quality and the patient satisfaction are improved. The medical service efficiency is comprehensively evaluated to provide an improvement direction for hospitals, the system comprehensively evaluates the information management efficiency from multiple aspects of information management cost, information processing capability, information security and the like, and the hospitals can clearly see the actual effect of an information management strategy through quantitative analysis, so that the strategy is adjusted, the cost is reduced, and the medical service efficiency is improved. And the information management efficiency is improved.

The invention provides an intelligent triage method and system based on comparative learning and a cross attention mechanism, and relates to the technical field of medical information processing. According to the system, through a sign-in module, a queue module, a data acquisition module, a data preprocessing module, a multi-modal feature extraction module, a contrast learning module, a cross attention mechanism module and a triage decision-making module, precise classification and intelligent triage of patient conditions are realized, light-symptom patients, light-severe patients and severe patients can be effectively distinguished, triage and shunting of the patients are realized, and the accuracy of the triage of the patients is improved. Therefore, unnecessary waiting time of mild patients is reduced, necessary treatment time of critical patients is prolonged, medical resources are reasonably distributed, and hospital service efficiency and patient satisfaction are improved. Meanwhile, doctors can be assisted in disease diagnosis, and the accuracy and efficiency of diagnosis are improved.

The invention provides a hospital health education intelligent question and answer method based on a large language model and a knowledge base, and belongs to the technical field of intelligent question and answer, and the method comprises the steps: collecting hospital health education related document data for preprocessing, and converting a text block into a vector form through a vector embedding model, storing in an AI native database in combination with metadata, and constructing an index to form a hospital health education knowledge base; receiving health consultation questions input by a user, performing semantic analysis and keyword extraction, and retrieving related knowledge fragments from a hospital health education knowledge base; carrying out fusion reordering on the retrieved knowledge fragments, calculating correlation scores, and selecting the first K knowledge fragments with the highest scores; and substituting the selected knowledge fragments and the user question into a preset cue word engineering template, generating a cue word input large language model, generating an answer for the user question, and feeding back the answer to the user. The acceptability and practicability of the patient on health knowledge are enhanced, and the efficiency of hospital health education and the satisfaction degree of the patient are improved.

The invention relates to the technical field of medical data management, and particularly discloses an acute postoperative pain assessment and management decision-making system based on a patient report result, which is used for solving multiple challenges facing postoperative acute pain management, including subjectivity of a traditional assessment method, lack of personalized treatment, insufficient intervention coordination and lack of real-time monitoring ability. The problems that an existing decision support system is insufficient in intelligence and complex in user interaction experience, so that the efficiency of medical staff is low, and finally rehabilitation and life quality of a patient are affected are solved, and the system comprises a patient pain data collection module, a data analysis and processing module, a decision support module and a user interface. The data analysis processing module analyzes the collected data by adopting a machine learning algorithm so as to evaluate the severity of the pain; according to the invention, individualized pain assessment is realized through a machine learning algorithm, patient pain data is analyzed in real time, a management scheme is rapidly adjusted, patient satisfaction is improved, a pain management scheme is optimized, and manual intervention is reduced.

The invention relates to the technical field of internet information, and provides an order sending method, system, device and medium for remote consultation, and the method comprises the steps: obtaining the details of a patient, the details of the patient comprise the information of the patient, the specialist of the illness state, and the priority of the condition of the patient; generating an order sending queue of doctors according to patient information and illness conditions; dynamically generating a scheduling amount in batches in an order dispatching queue according to patient condition priorities, and dispatching orders in sequence; the doctor who obtains the dispatched order receives the consultation call application; collecting patient feedback, and updating the comprehensive score of the doctor. The most suitable doctor is quickly matched, the waiting time is shortened, and the consultation efficiency is improved; factors such as geographic positions, professional competence and service evaluation are comprehensively considered, and reasonable distribution of doctor resources is realized; based on a comprehensive scoring mechanism, doctors are motivated to improve service quality, and patient satisfaction is enhanced.

The invention provides a method for intelligent medicine warehouse-in and warehouse-out management based on big data of medicine use of a patient, and the method comprises the steps: constructing an intelligent prediction model used for outputting a medicine replenishment period and a safety stock dynamic threshold value based on the big data of the medicine use of the patient, and deploying the intelligent prediction model on a medicine stock cloud server; monitoring medication time sequence characteristics of corresponding types of stored medicines in real time through the medicine inventory cloud server, inputting the medication time sequence characteristics into the intelligent prediction model, identifying the medication time sequence characteristics through the intelligent prediction model, and predicting replenishment suggestions of the corresponding types of medicines; and according to the replenishment suggestion, generating a warehouse-in and warehouse-out strategy of the corresponding type of medicine, and issuing the warehouse-in and warehouse-out strategy of the corresponding type of medicine to a terminal APP of a warehouse manager. According to the invention, inventory prediction can be carried out based on the medication time sequence characteristics of each medicine, intelligent supervision and dynamic replenishment of the whole life cycle of the medicine are realized in combination with a dynamic inventory optimization algorithm, and the turnover efficiency of hospital medicines and patient satisfaction are improved.

The present disclosure relates to a call light monitoring system designed to enhance response efficiency and patient care management in healthcare facilities. This system includes unobtrusive monitoring capabilities that detect the activation of call lights without interfering with existing facility infrastructure. The system features a real-time display that provides immediate visual feedback on the duration of active call lights, enabling staff to prioritize responses based on urgency and elapsed time. Additionally, the system includes a comprehensive reporting module that records and analyzes the history of call light durations. This historical data can be used for performance evaluations, optimizing staff allocations, and identifying patterns that may indicate areas needing process improvement. The integration of these features into a single system provides a robust tool for improving patient satisfaction and operational efficiency in healthcare settings.

The invention relates to the field of medical care informatics, in particular to a doctor-patient collaborative management system and method based on a perioperative period. Comprising the steps of collecting and preprocessing all necessary information of a patient, and performing structured processing on preprocessed medical data to obtain structured medical data; based on the login request of the doctor and the patient, verifying the access authority of the doctor and the patient to obtain a verified login request; based on the verified login request, calling structured medical data; performing real-time analysis and predictive analysis based on the structured medical data to obtain a risk assessment report; based on the risk assessment report, different treatment schemes are assessed and sorted, and doctors are helped to formulate the treatment schemes; and generating a comprehensive report in combination with the treatment scheme, the operation result and the patient satisfaction survey result. The technical problems that when doctor-patient collaborative management in the perioperative period is achieved, medical data cannot be accurately processed, patient health risks cannot be accurately predicted, and management individuation is insufficient are solved.

The invention discloses an accurate value incentive accounting method for a DIP disease category subdivision value portrait under DRG, and belongs to the technical field of medical payment and hospital management, and the method comprises the following steps: 1) a data fusion model: integrating DRG grouped data, a DIP score, a clinical path execution rate, cost accounting and patient satisfaction data, and constructing economic, clinical and social three-dimensional value portraits; 2) dynamic grouping optimization: introducing a machine learning algorithm, and dynamically subdividing DIP disease species into subgroups according to complication severity, treatment mode difference and resource consumption dispersion; after disease category subdivision, the matching degree of the DIP score and the actual cost is improved by 20%-30%, the medical insurance payment refusal risk is reduced, payment accuracy improvement is achieved, through strategic disease category support, the CMI value is averagely improved by 0.15, the difficult case recovery rate is increased by 12%, medical quality optimization is achieved, and through linkage excitation of the balance contribution rate and the patient satisfaction degree, the medical quality is improved. The medicine consumption ratio is reduced by 5-8%, the hospitalization day is shortened by 1.2 days, and the operation efficiency is improved.

The invention relates to the technical field of medical management, and discloses a medical specialist ability index evaluation method, which is characterized by comprising the following steps: data acquisition: collecting multi-dimensional information; constructing an index system, and establishing a multi-dimensional evaluation system; weight distribution: determining a weight coefficient by adopting a scientific method; and calculating a specialist ability index through comprehensive scoring model calculation. The system is characterized in that data acquisition is completed through a hospital system and a database; the basic capability indexes comprise equipment configuration and the like; clinical ability indexes comprise diagnosis and treatment quantity and the like; the scientific research capability indexes comprise scientific research projects and the like; the service capability indexes comprise patient satisfaction and the like; the specialized ability index has a specific calculation formula. The method has the advantages that comprehensive, scientific and dynamic assessment of the clinical specialized ability of the medical institution is realized through the specialized ability assessment method based on multi-dimensional data acquisition, objective weight distribution and a quantitative scoring model.

The utility model relates to a heating device, and specifically to a mesh-type infusion heating device and a nutrient solution infusion device, including a bottle sleeve mechanism for sleeve an infusion bottle, an electric heating wire mesh I, and the electric heating wire mesh I is laid in the bottle sleeve mechanism; an infusion set sleeve mechanism, the infusion set sleeve mechanism is used to sleeve an infusion set, the infusion set sleeve mechanism is arranged corresponding to the bottle sleeve mechanism, and the infusion set sleeve mechanism is laid with an electric heating wire mesh II. The utility model heats the nutrient solution in the infusion bottle through the electric heating wire mesh I in the bottle sleeve mechanism, and through the electric heating wire mesh II in conjunction with the infusion set sleeve mechanism, the temperature of the nutrient solution is prevented from decreasing after passing through the infusion set, and the temperature of the nutrient solution is maintained at 38-40°, achieving stable heating during the infusion process, and having the beneficial effects of improving safety, increasing patient satisfaction, and reducing the burden of nursing.

The present invention provides a service optimization management system for telemedicine services, which relates to the field of data processing technology. The system includes: retrieving multiple queue information sets based on the reception window, extracting multiple queue personnel characteristics for differential identification of consultation time, generating multiple consultation time prediction data, monitoring queue conflicts based on the appointment queue information set and the online queue information set, building a queue time prediction model, generating a consultation queue time data set, formulating multiple exclusive channels, performing feedback response through the user terminal, optimizing the multiple consultation time prediction data according to the feedback response results, updating the consultation queue time data set, and realizing the optimization management of telemedicine services. The technical effects of more accurate resource allocation and service optimization, improving service efficiency and quality, reducing patient waiting time, and improving patient satisfaction are achieved.

The invention discloses a keloid postoperative intelligent monitoring system, which relates to the technical field of medical monitoring and comprises a database, a patient information input module, an image management module, an operation processing standard making module, a postoperative management evaluation module, a re-diagnosis reminding module and a communication module. The patient information input module is used for inputting patient information and generating a unique patient ID after inputting; the image management module comprises an image acquisition unit, an image processing unit and an image marking unit; the operation processing standard making module is used for generating personalized operation processing standard suggestions for doctors; the postoperative management evaluation module generates a postoperative management report; the re-visit reminding module generates a re-visit plan; the communication module is used for communicating with a patient or a contact person; the technical effects that postoperative management evaluation is carried out no longer depending on subjective judgment of doctors, a unified evaluation standard is formed, and therefore the postoperative management effect and the patient satisfaction degree are improved are achieved.

The invention relates to the field of dental restoration, in particular to a tooth colorimetric method, system and device, and the tooth colorimetric method comprises the following steps: step 1, determining a plurality of predetermined materials, and presetting an adjustment value delta L corresponding to each predetermined material; step 2, obtaining reflection spectrum data S1 (lambda) of the surface to be measured, and obtaining an initial lightness value L1 according to the reflection spectrum data S1 (lambda); step 3, preprocessing the reflection spectrum data S1 (lambda); step 4, comparing the preprocessed reflection spectrum data S1 (lambda) with standard spectrum data S2 (lambda) corresponding to each predetermined material, and outputting a comparison result; 5, determining the material type of the surface to be detected according to the comparison result; and step 6, determining a corresponding adjustment value delta L according to the determined material type of the surface to be measured, and calibrating the initial lightness value L1 through the adjustment value delta L to obtain an actual lightness value L2. According to the invention, the aesthetic property of tooth restoration and patient satisfaction are guaranteed.

The present invention relates to a method for treating TNFα-related diseases by subcutaneously administering an antibody (anti-TNFα antibody) that binds to TNFα or an antigen-binding fragment thereof. A treatment method, a composition, a kit, or a use according to the present invention provides the advantage that administration time is reduced compared to intravenous injections and the amount of time that patients stay in hospitals is reduced, and thus patient satisfaction is increased through improved convenience and improved quality of life. In particular, the present invention has the advantage of providing a therapeutic agent that is highly effective in improving medication convenience, disease treatment effects, growth disorders, and the like with respect to pediatric / adolescent patients suffering from autoimmune diseases.

This invention belongs to the field of medical wristband technology, specifically disclosing a translation method for bidirectional communication between medical staff and patients based on multimodal interaction, including the following steps: Step S1, the multimodal interaction unit receives multimodal input signals; Step S2, the multimodal interaction unit fuses the multimodal input signals to generate comprehensive input information; Step S3, the comprehensive input information is identified and translated based on a medical-specific translation engine; Step S4, the context-aware module analyzes the dialogue content, identifies the scenario, and dynamically adjusts the translation results; Step S5, the adjusted translation results are synchronously output bidirectionally and broadcast via voice. This invention achieves three core breakthroughs in clinical cross-language communication through a translation mechanism combining multimodal signal fusion and context awareness: enabling real-time, accurate, and private barrier-free communication between doctors and patients, reducing the risk of medical errors due to language barriers, improving consultation efficiency and patient satisfaction, and reducing the risk of misdiagnosis.

An improved atomizing core and a medical vaporizer manufactured based on the atomizing core are characterized in that the atomizing core comprises a base and a conical column integrally connected with the base, the peripheral edge of the bottom of the base extends downwards to form a convex edge, and a plurality of capillary tube openings are annularly formed in the convex edge; the surrounding cylinder is matched with the inner wall of the atomization tank, namely, the surrounding cylinder is attached to the inner wall of the atomization tank, the bottom of the surrounding cylinder is fixedly connected with the base, and a plurality of aerial fog holes are formed in the side wall of the surrounding cylinder in a penetrating mode. The atomizing core and the medical atomizer are ideal in structural design, the design that a plurality of capillary tube openings are combined with a plurality of aerial fog holes is adopted, the atomizing effect is ideal, the capacity of changing liquid medicine into tiny fog drops in unit time is enhanced, and the atomizing efficiency is high; the use scene of the atomizer is improved, atomization treatment can be carried out on different body positions, and the atomization treatment effect is also improved; the drug administration accuracy is improved, and the patient satisfaction degree is improved; and the working efficiency of medical staff is also improved.

The invention discloses a vibratory massage intelligent control eye care device, and belongs to the technical field of medical care equipment. The problems that an existing eye massager is single in function and cannot meet various scene requirements are solved, real-time monitored intraocular pressure, temperature and myoelectricity activity data are compared with threshold values to calculate error values, massage parameters are dynamically adjusted through a PID algorithm, it is ensured that the vibration frequency and intensity are always within a safe and effective range, and the effect of improving the quality of the eye massager is achieved. Therefore, the individuation and adaptability of the eye massage instrument are improved, and a patient is ensured to obtain comfortable and effective massage experience. By analyzing and calculating intraocular pressure, temperature and myoelectricity activity data and vibration frequency and intensity parameters of a patient, it is ensured that each treatment is adjusted based on the previous treatment effect, and therefore fine management and personalized adjustment of the eye nursing process of the patient are achieved; and the satisfaction degree of the patient and the pertinence and effectiveness of massage treatment are improved.

The utility model relates to an arc-shaped knife handle for an endoscopic breast surgery. The arc-shaped knife handle is suitable for being combined with a scalpel to form an arc-shaped flap free knife for the single-hole endoscopic breast surgery. Distance scales are arranged on the side walls of the arc-shaped handle and the blade holder main body; the arc-shaped handle is provided with a lengthened handle so as to extend the operation range; the arc-shaped handle is beneficial for being tightly attached to the curve of the breast and the thorax and conveniently complies with and crosses the natural radian of the breast and the thorax, precise dissociation of the skin flap blocked by the nipple and areola complex during skin flap separation in the operation is achieved, the amount of bleeding in the operation is reduced, and the operation efficiency is improved. Damage to a nipple and areola complex and a breast duct behind the nipple and areola complex in the operation process is remarkably reduced, and the risk of skin flap necrosis is reduced; distance scales are convenient for measuring the radial width of the breast base along the thoracic radian in an operation, and accurate operation positioning and prosthesis selection reference is provided for doctors; therefore, the operation area can be accurately and efficiently determined in the endoscopic operation, and the success rate of the operation and the satisfaction degree of a patient are improved.