A method for controlling the flow rate of an infusion pump based on a matching model

Abstract

The application relates to a matching model-based infusion pump flow rate control method, which comprises the following steps: an information collection end collects diagnosis results, drug information and patient conditions; a server establishes a matching model according to the information collected by the information collection end; an analysis module generates a recommended infusion pump flow rate according to the matching model established by the server and related information stored in the server; a staff member checks or implements artificial intervention on the generated infusion pump flow rate; the analysis module compares the confirmed infusion pump flow rate with the maximum flow rate of an infusion tube to determine whether the infusion pump starts to work or performs an alarm reminder; and the analysis module calculates the maximum flow rate v of the infusion tube by substituting the numerical values of the dynamic viscosity mu, the friction coefficient f, the diameter D of the infusion tube and the fluid density rho of a known fluid into an infusion tube flow rate model. The matching model-based infusion pump flow rate control method realizes intelligent control of an infusion process by comprehensively applying advanced technologies such as a matching model, machine learning, real-time monitoring and data analysis, and has the remarkable effects of improving infusion safety, accuracy and efficiency.

Description

Technical Field

[0001] This invention belongs to the field of medical technology and is mainly applied to clinical treatment methods and other scenarios. It relates to drug delivery and treatment technology, specifically an infusion pump flow rate control method based on a matching model. By collecting diagnostic results, drug information and patient conditions through the infusion pump, it aims to improve the precision control and adaptability of drug delivery and treatment, and realize intelligent operation. Background Technology

[0002] With the development of technology, more and more fields require precise control of fluid flow rate or velocity. For example, in the chemical industry, the detection and analysis of trace chemical elements often requires precise flow control. In the healthcare field, the flow rate and velocity of medication solutions sometimes also need precise control. Intravenous infusion is one of the most commonly used clinical treatment methods and a frequently used drug administration technique in nursing. Clinically, the appropriate infusion rate should be determined according to the different drugs and the patient's condition. Infusion that is too fast may lead to poisoning, and in more serious cases, edema and heart failure; infusion that is too slow may result in insufficient drug dosage or unnecessarily prolonged infusion time, affecting treatment and adding unnecessary burden to patients and nursing staff. Routine clinical infusions generally use hanging bottles, relying on visual observation and manual clamps to control the drip rate, which makes it difficult to precisely control the infusion rate and is labor-intensive.

[0003] Infusion pumps are common devices in the medical industry, primarily used to deliver medications, nutritional solutions, and other fluids into patients' bodies. Infusion pumps achieve constant infusion rates by controlling the flow rate. There are two main principles for controlling the flow rate of infusion pumps: First, flow rate is controlled by changing the pump's rotational speed. This can be achieved by adjusting the speed of the DC motor, thus regulating the flow rate. Since the relationship between speed and flow rate varies between different pump models, adjustments need to be made based on the pump's parameters. Second, flow rate is controlled by changing the structure of the pump core assembly. The pump core assembly is another crucial factor affecting the infusion pump's flow rate. Different pump core assembly structures can achieve different flow rates. For example, replacing components such as springs and valves in the pump core assembly can alter its structure, thereby changing the flow rate of the medication. A pressure sensor is one of the key components for controlling the flow rate of an infusion pump. It collects the pressure difference across the infusion tubing and converts it into an electrical signal. By calculating the pressure difference, the current flow rate can be determined. The pressure sensor feeds back the flow rate signal to the control system, which then adjusts the pump's rotational speed or the structure of the pump core assembly based on the feedback signal, thereby adjusting the flow rate of the medication.

[0004] The control system is the core component of an infusion pump for controlling flow rate. It uses signals from pressure sensors to control the pump's rotational speed or the structure of the pump core assembly, thereby controlling the flow rate. Control systems typically offer multiple control modes, such as constant flow and constant pressure modes. Different control modes can be selected to achieve different flow rate controls under different operating conditions. In short, an infusion pump can control its flow rate by changing the pump's rotational speed and the structure of the pump core assembly. By collecting the pressure difference before and after the pump, calculating the flow rate, and feeding it back to the control system, precise flow rate control is achieved. In practical applications, adjusting the control parameters can meet the infusion requirements of different medications.

[0005] Existing infusion pump technologies mainly include peristaltic pumps, plunger pumps, and gravity infusion pumps. These pumps control the infusion rate and volume through different mechanisms, meeting most clinical needs. However, most of them rely on preset programs or manual adjustments by medical staff, and cannot intelligently determine the infusion pump flow rate based on diagnostic results, drug information, and patient conditions. Although existing infusion pumps are relatively mature in operation, they still have some limitations, such as a lack of personalization, failing to automatically adjust the infusion rate according to the patient's real-time physiological changes; reliance on monitoring, requiring medical staff to conduct regular checks and adjustments, increasing their workload; safety issues, as existing infusion pumps may not respond promptly in emergencies; and safety hazards, as data management is lacking, and the lack of systematic management and analysis of infusion data limits a deeper understanding of patient treatment outcomes. Summary of the Invention

[0006] The purpose of this invention is to provide an infusion pump flow rate control method based on a matching model, which solves the problem that existing infusion pumps cannot intelligently determine the flow rate based on diagnostic results, drug information, and patient conditions.

[0007] To address the above problems, this invention provides a method for controlling the flow rate of an infusion pump based on a matching model, characterized by comprising:

[0008] The information collection terminal collects the doctor's diagnosis results, medication information, and patient information; the diagnosis results include at least the examination results and the doctor's confirmed diagnosis; the medication information includes at least the drug type and dosage; and the patient information includes at least the patient's age, past medical history, and family history of genetic diseases.

[0009] The server builds a matching model based on the information collected by the information collection terminal. The matching model includes the diagnosis results, drug information, and patient information.

[0010] The analysis module generates a recommended infusion pump flow rate based on the matching model established by the server and by retrieving relevant information stored in the server. The relevant information stored in the server includes infusion pump flow rates corresponding to different diagnostic results, drug information and patient conditions entered in advance by humans, and can also be generated based on big data and historical data analysis.

[0011] Staff members should check the generated infusion pump flow rate or intervene manually. No manual intervention is required if staff members approve the infusion pump flow rate. Manual intervention is required if staff members do not approve the recommended infusion pump flow rate. The manual intervention method is to directly select or input the infusion pump flow rate value.

[0012] After verifying that the infusion pump flow rate is correct or after manual intervention, a confirmation operation is performed. The analysis module compares the confirmed infusion pump flow rate with the maximum flow rate that the infusion tubing can achieve. If the confirmed infusion pump flow rate is less than or equal to the maximum flow rate of the infusion tubing, the infusion pump starts to work. If the confirmed infusion pump flow rate is greater than the flow rate of the infusion tubing, an alarm is triggered to remind staff to modify the infusion pump flow rate value or replace the infusion tubing.

[0013] The method by which the analysis module calculates the maximum flow velocity in the infusion tubing includes:

[0014] Based on the relationship between the flow of viscous fluid in an infusion tube and the actual flow of fluid in an infusion tube, a flow velocity model for the infusion tube is constructed:

[0015]

[0016] Rearrange the flow velocity model of the infusion tube and solve for the maximum flow velocity v of the infusion tube:

[0017]

[0018] f is the coefficient of friction;

[0019] L is the length of the infusion tube (unit: meter, m);

[0020] D is the diameter of the infusion tube (unit: meter, m);

[0021] v is the flow velocity in the infusion tube (unit: meters per second, m / s);

[0022] μ is the dynamic viscosity of the fluid (unit: Pa·s).

[0023] ρ is the fluid density (unit: kg / m³). 3 );

[0024] Substituting the known values ​​of the fluid's dynamic viscosity μ, friction coefficient f, infusion tube diameter D, and fluid density ρ into the above equation, the maximum flow velocity v in the infusion tube can be calculated.

[0025] Furthermore, the information acquisition terminal further includes at least one physiological parameter monitoring device for real-time monitoring of the patient's vital signs and transmitting the monitoring results to the server.

[0026] Furthermore, the matching model established by the server also includes the patient's vital signs data, which is used to more accurately determine the infusion pump flow rate.

[0027] Furthermore, the analysis module includes a machine learning algorithm for continuously optimizing and adjusting the infusion pump flow rate recommendation model.

[0028] Furthermore, the analysis module can adjust the infusion pump flow rate based on the patient's real-time feedback.

[0029] Furthermore, staff can input specific instructions or data through the user interface to override automatically generated infusion pump flow rate recommendations.

[0030] Furthermore, the infusion pump also includes a safety module for monitoring abnormal situations during the infusion process and automatically adjusting or stopping the operation of the infusion pump when necessary.

[0031] Furthermore, the infusion pump can adjust its flow rate based on the patient's medication history and drug interactions.

[0032] Furthermore, the infusion pump also includes a data storage module for storing the patient's infusion records and historical data for future analysis and reference.

[0033] Furthermore, the infusion pump also includes a communication module, which allows multiple infusion pumps to exchange data and communicate with the central monitoring system to achieve centralized management and control.

[0034] The present invention has the following beneficial effects:

[0035] (1) The infusion pump flow rate control method based on the matching model of the present invention can automatically generate or adjust the infusion rate according to the patient's specific condition and drug characteristics, ensuring that the drug enters the patient's body at the most appropriate rate and improving the treatment effect; the present invention can also generate personalized infusion rate recommendations based on the patient's age, past medical history, family history of hereditary diseases and other information to meet the treatment needs of different patients; through automated infusion rate recommendation and adjustment, the manual adjustment and monitoring work required by medical staff is reduced, which helps to reduce the workload of medical staff, improve safety, accuracy and work efficiency, and improve the level of nursing care; by comparing the confirmed infusion pump flow rate with the maximum flow rate of the infusion tube, the present invention can promptly alarm when the flow rate exceeds the safe range, reminding staff to replace the infusion tube, effectively avoiding potential risks in the infusion process.

[0036] (2) In this invention, staff can check the recommended infusion pump flow rate and intervene manually when necessary, which can reduce infusion errors caused by automated system errors and improve infusion safety. Through the infusion records and historical data stored in the data storage module, this invention provides data-driven decision support for medical staff, which helps to continuously improve infusion plans. By analyzing historical data and big data, the system can provide more scientific and accurate infusion rate recommendations, providing decision support for medical staff. By monitoring the patient's vital signs and abnormal conditions during the infusion process in real time, the system can adjust the infusion rate or stop the infusion in a timely manner, thereby reducing the risks that may occur during the infusion process and improving patient safety.

[0037] (3) The data storage module of the present invention can save the patient's infusion records and historical data, providing valuable data resources for future medical analysis and research; through machine learning algorithms, the system can continuously learn and optimize the infusion rate recommendation model, improving the system's adaptability and accuracy; staff can view the infusion status in real time through the user interface and provide feedback or intervention when necessary; through the communication module, multiple infusion pumps can exchange data and communicate with the central monitoring system, realizing centralized management and control of the infusion process and improving management efficiency. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a flowchart of the infusion pump flow rate control method based on a matching model according to an embodiment of the present invention;

[0040] Figure 2 This is a flowchart of the flow rate determination process in the analysis module of the infusion pump flow rate control method based on a matching model, according to an embodiment of the present invention.

[0041] Figure 3 This is a schematic diagram of the matching model information in an embodiment of the present invention. Detailed Implementation

[0042] In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the invention. However, it will be apparent to those skilled in the art that the invention can be practiced without one or more of these details. In other instances, certain technical features well-known in the art have not been described in order to avoid obscuring the invention.

[0043] To fully understand this invention, detailed steps and structures will be presented in the following description to illustrate the technical solution of this invention. Preferred embodiments of the invention are described in detail below; however, in addition to these detailed descriptions, the invention may have other embodiments.

[0044] like Figures 1 to 3 The embodiment of the infusion pump flow rate control method based on a matching model of the present invention shown herein includes:

[0045] S1: The information collection terminal collects the doctor's diagnosis results, medication information, and patient information;

[0046] S2: The server builds a matching model based on the information collected by the information collection terminal;

[0047] S3: The analysis module generates a recommended infusion pump flow rate based on the matching model established by the server and by retrieving relevant information stored in the server.

[0048] S4: Staff members check the generated infusion pump flow rate or implement manual intervention;

[0049] S5: The analysis module compares the confirmed infusion pump flow rate with the maximum flow rate of the infusion tubing to determine whether the infusion pump should start working or issue an alarm.

[0050] In step S1, the information collection terminal collects the diagnosis results, medication information, and patient information prescribed by the doctor; the diagnosis results include at least the examination results and the doctor's confirmed diagnosis; the medication information includes at least the drug type and drug dosage; the patient information includes at least the patient's age, past medical history, and family history of genetic diseases; the information collection terminal can automatically collect the diagnosis results, medication information, and patient information through doctor input or integration with the hospital information system (HIS).

[0051] In step S2, the server builds a matching model based on the information collected by the information collection terminal. The matching model includes the diagnosis results, drug information, and patient condition. The server uses this data to build a matching model. This system is a virtual model that can reflect the patient's medical condition and infusion needs.

[0052] In step S3, the analysis module generates a recommended infusion pump flow rate based on the matching model established by the server and by retrieving relevant information stored on the server. The relevant information stored on the server includes infusion pump flow rates corresponding to different pre-entered diagnoses, medication information, and patient conditions, and can also be generated based on big data and historical data analysis. This analysis module uses advanced algorithms to generate a recommended infusion pump flow rate based on data from the matching model and historical infusion data stored on the server, including infusion pump flow rates corresponding to different diagnoses, medications, and patient conditions. Furthermore, the analysis module can continuously optimize the flow rate recommendation using machine learning through big data and historical data analysis.

[0053] In step S4, the staff checks or manually intervenes in the generated infusion pump flow rate. No manual intervention is needed if the staff approves the infusion pump flow rate; manual intervention is required if the staff does not approve the recommended flow rate. The manual intervention method is to directly select or input the infusion pump flow rate value. During this process, the staff receives the recommended infusion pump flow rate through the user interface and checks it. If the recommended infusion pump flow rate meets clinical requirements, no intervention is needed; if it does not, the staff can directly input a new infusion pump flow rate value or select a preset flow rate scheme through the interface.

[0054] In step S5, after verifying that the infusion pump flow rate is correct or after manual intervention, a confirmation operation is performed. The analysis module compares the confirmed infusion pump flow rate with the maximum flow rate of the infusion tubing. If the confirmed infusion pump flow rate is less than or equal to the maximum flow rate of the infusion tubing, the infusion pump starts working. If the confirmed infusion pump flow rate is greater than the maximum flow rate of the infusion tubing, an alarm is triggered to remind staff to replace the infusion tubing and adjust the flow rate.

[0055] The method by which the analysis module calculates the maximum flow velocity in the infusion tubing includes:

[0056] Based on the relationship between the flow of viscous fluid in an infusion tube and the actual flow of fluid in an infusion tube, a flow velocity model for the infusion tube is constructed:

[0057]

[0058] Rearrange the flow velocity model of the infusion tube and solve for the maximum flow velocity v of the infusion tube:

[0059]

[0060] f is the coefficient of friction;

[0061] L is the length of the infusion tube (unit: meter, m);

[0062] D is the diameter of the infusion tube (unit: meter, m);

[0063] v is the flow velocity in the infusion tube (unit: meters per second, m / s);

[0064] μ is the dynamic viscosity of the fluid (unit: Pa·s).

[0065] ρ is the fluid density (unit: kg / m³). 3 );

[0066] Substituting the known values ​​of the fluid's dynamic viscosity μ, friction coefficient f, infusion tube diameter D, and fluid density ρ into the above equation, the maximum flow velocity v in the infusion tube can be calculated.

[0067] For specific flow conditions and pipe configurations, the friction coefficient f can be considered relatively constant. It can be determined based on experimental data or empirical formulas, or numerical simulations can be performed using computational fluid dynamics (CFD) software to simulate the flow of fluid in the pipe and calculate the friction coefficient.

[0068] In one embodiment of the present invention, the information acquisition terminal further includes at least one physiological parameter monitoring device for real-time monitoring of the patient's vital signs and transmitting the monitoring results to the server; the information acquisition terminal is equipped with necessary physiological parameter monitoring devices, such as an electrocardiogram (ECG) monitor, a pulse oximeter, a blood pressure monitor, etc., which can monitor the patient's physiological parameters in real time.

[0069] In one embodiment of the present invention, the matching model established by the server also includes the patient's vital signs data, which is used to more accurately determine the flow rate of the infusion pump; the matching model not only includes the patient's basic information, but also integrates vital signs data obtained from real-time monitoring, such as heart rate, blood pressure, respiratory rate and body temperature. By monitoring the patient's vital signs in real time, the matching model can respond to any changes in the patient's condition in a timely manner, adjust the infusion flow rate and reduce the risk of infusion.

[0070] In one embodiment of the present invention, the analysis module further includes a machine learning algorithm for continuously optimizing and adjusting the infusion pump flow rate recommendation model. The analysis module collects patient diagnosis results, drug information, patient condition, and vital sign data from the matching model and physiological parameter monitoring equipment. The collected data is cleaned, standardized, and feature extracted to provide high-quality input for the machine learning algorithm. Using historical infusion data and patient feedback, the machine learning model is trained to identify key factors affecting the infusion flow rate. The model may employ regression analysis, decision trees, neural networks, or other suitable algorithms. Real-time monitored vital sign data can also be input into the machine learning model as dynamic features to participate in flow rate recommendation. The machine learning algorithm can identify complex patterns and relationships, improving the accuracy of the infusion pump flow rate recommendation model.

[0071] In one embodiment of the invention, the analysis module can adjust the infusion pump flow rate based on real-time patient feedback. The infusion pump system also integrates patient-reported feedback, such as pain and discomfort, which can be input via a patient handheld device or bedside terminal. The analysis module receives and processes real-time monitoring data and patient feedback, analyzes the data using preset algorithms or machine learning models, identifies potential problems during the infusion process, and automatically adjusts the infusion pump flow rate based on the analysis results to adapt to the patient's current state. For example, if an abnormal heart rate is detected, the system may automatically reduce the flow rate. Medical staff can view the patient's feedback and the system's adjusted flow rate in real time through the user interface, review the automatic adjustment results, and perform necessary manual intervention.

[0072] In one embodiment of the present invention, staff can input specific instructions or data through a user interface to cover the automatically generated recommended infusion pump flow rate; an intuitive and easy-to-use user interface can be designed so that medical staff can easily input instructions or data to cover the automatically recommended infusion pump flow rate.

[0073] In one embodiment of the present invention, the infusion pump system further includes a safety module for monitoring abnormal situations during the infusion process and automatically adjusting or stopping the operation of the infusion pump when necessary. The safety module has a built-in anomaly detection algorithm that can analyze the patient's vital signs data and the working status of the infusion pump in real time. It sets safety thresholds for various physiological parameters and infusion pump operating indicators. Once the monitored data exceeds these thresholds, the system will automatically identify it as an abnormal situation and issue an alarm. The safety module continuously monitors the infusion process and tracks key parameters such as infusion rate, pressure, and air bubble detection in real time. When a minor abnormality is detected, the safety module can automatically adjust the infusion pump flow rate or other relevant parameters to attempt to restore the normal infusion state. When a serious abnormality is detected, such as blockage of the infusion tubing or a severe allergic reaction in the patient, the safety module will trigger an emergency stop function, immediately stopping the infusion pump and issuing an alarm.

[0074] In one embodiment of the present invention, the infusion pump system can adjust the infusion pump flow rate based on the patient's medication history and drug interactions; the system accesses the patient's medication history through an electronic health record (EHR) system, including previously used drugs, dosages, frequencies, and the patient's responses; the system accesses a drug interaction database, enabling it to query interactions between different drugs and the possible changes in effects; using the patient's medication history and drug interaction information, the system constructs a personalized infusion flow rate model to predict the optimal infusion rate.

[0075] In one embodiment of the present invention, the infusion pump system further includes a data storage module for storing the patient's infusion records and historical data for future analysis and reference. The system collects data from the information acquisition terminal, physiological parameter monitoring equipment, user interface operation, and safety module, including the patient's basic information, diagnosis results, drug information, vital sign data, infusion pump flow rate adjustment records, etc. The data storage module integrates the collected data to form a comprehensive infusion record, including but not limited to infusion time, drug dosage, flow rate adjustment, patient feedback, and medical staff intervention.

[0076] In one embodiment of the present invention, the infusion pump system further includes a communication module that allows multiple infusion pumps to exchange data and communicate with a central monitoring system for centralized management and control. A communication network is established, which can be based on a wired network, wireless network, or cellular network, to ensure a stable connection between the infusion pumps and the central monitoring system. The infusion pumps transmit information such as the patient's physiological parameters, infusion status, and flow rate adjustments to the central monitoring system in real time. The central monitoring system provides a centralized monitoring interface that displays the status and data of all connected infusion pumps, enabling medical staff to have a clear understanding of the entire infusion system. The central monitoring system has remote control capabilities, allowing medical staff to remotely adjust the settings of the infusion pumps or intervene when necessary.

[0077] The preferred embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, nor is it limited to the infusion pump flow rate control method based on a matching model. Devices and structures not described in detail herein should be understood as being implemented in a manner common to the art. Any person skilled in the art can make many possible variations and modifications to the technical solutions of the present invention, or modify them into equivalent embodiments, without departing from the scope of the present invention. This does not affect the essential content of the present invention. Therefore, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention are still within the protection scope of the present invention.

Claims

1. A method for controlling the flow rate of an infusion pump based on a matching model, characterized in that, include: The information collection terminal collects the doctor's diagnosis results, medication information, and patient information; the diagnosis results include at least the examination results and the doctor's confirmed diagnosis. The drug information includes at least the drug type and dosage; the patient information includes at least the patient's age, past medical history, and family history of hereditary diseases. The server builds a matching model based on the information collected by the information collection terminal. The matching model includes the diagnosis results, drug information, and patient information. The analysis module generates a recommended infusion pump flow rate based on the matching model established by the server and by retrieving relevant information stored in the server. The relevant information stored in the server includes infusion pump flow rates corresponding to different diagnostic results, drug information and patient conditions entered in advance by humans, and can also be generated based on big data and historical data analysis. Staff members should check the generated infusion pump flow rate or intervene manually. No manual intervention is required if staff members approve the infusion pump flow rate. Manual intervention is required if staff members do not approve the recommended infusion pump flow rate. The manual intervention method is to directly select or input the infusion pump flow rate value. After verifying that the infusion pump flow rate is correct or after manual intervention, a confirmation operation is performed. The analysis module compares the confirmed infusion pump flow rate with the maximum flow rate of the infusion tubing. If the confirmed infusion pump flow rate is less than or equal to the maximum flow rate of the infusion tubing, the infusion pump starts working. If the confirmed infusion pump flow rate is greater than the maximum flow rate of the infusion tubing, an alarm is triggered to remind staff to modify the infusion pump flow rate value or replace the infusion tubing. The method by which the analysis module calculates the maximum flow velocity in the infusion tubing includes: Based on the relationship between the flow of viscous fluid in an infusion tube and the actual flow of fluid in an infusion tube, a flow velocity model for the infusion tube is constructed: Rearrange the flow velocity model of the infusion tube and solve for the maximum flow velocity v of the infusion tube: Substituting the known values ​​of the fluid's dynamic viscosity μ, friction coefficient f, infusion tube diameter D, and fluid density ρ into the above equation, the maximum flow velocity v in the infusion tube can be calculated.

2. The infusion pump flow rate control method based on a matching model according to claim 1, characterized in that: The information acquisition terminal further includes at least one physiological parameter monitoring device for real-time monitoring of the patient's vital signs and transmitting the monitoring results to the server.

3. The infusion pump flow rate control method based on a matching model according to claim 2, characterized in that: The matching model established by the server also includes the patient's vital signs data, which is used to more accurately determine the infusion pump flow rate.

4. The infusion pump flow rate control method based on a matching model according to any one of claims 2-3, characterized in that: The analysis module further includes a machine learning algorithm for continuously optimizing and adjusting the infusion pump flow rate recommendation model.

5. The infusion pump flow rate control method based on a matching model according to claim 4, characterized in that: The analysis module can adjust the infusion pump flow rate based on the patient's real-time feedback.

6. The infusion pump flow rate control method based on a matching model according to claim 1, characterized in that: Staff can input specific commands or data through the user interface to override automatically generated infusion pump flow rate recommendations.

7. The infusion pump flow rate control method based on a matching model according to claim 4, characterized in that: The infusion pump also includes a safety module for monitoring abnormal situations during the infusion process and automatically adjusting or stopping the operation of the infusion pump when necessary.

8. The infusion pump flow rate control method based on a matching model according to claim 1, characterized in that: The infusion pump can adjust its flow rate based on the patient's medication history and drug interactions.

9. The infusion pump flow rate control method based on a matching model according to claim 1, characterized in that: The infusion pump also includes a data storage module for storing the patient's infusion records and historical data for future analysis and reference.

10. The infusion pump flow rate control method based on a matching model according to claim 1, characterized in that: The infusion pump also includes a communication module that allows multiple infusion pumps to exchange data and communicate with the central monitoring system to achieve centralized management and control.

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