Intelligent infusion system based on database dynamic feedback regulation and control and intelligent infusion control method

Abstract

The invention provides an intelligent infusion system and an intelligent liquid control method based on database dynamic feedback regulation and control, and relates to the technical field of medical equipment intelligent control. The system comprises an infusion terminal execution module, a multi-parameter monitoring module, a data transmission module, a central control server module and a dynamic database module; patient information, an infusion scheme, a threshold range and multi-dimensional data of historical records are stored through the dynamic database module, the central control server module calls the data and compares the data with real-time physiological parameters and infusion state parameters collected by the multi-parameter monitoring module for analysis, and the target infusion speed is calculated. Early warning is carried out according to the target infusion speed and the real-time monitoring parameters, accurate monitoring of the regulation and control parameters and the individual condition of the patient is ensured, the infusion speed is always in the optimal range adaptive to the physiological state of the patient, and the infusion adverse reaction caused by parameter errors and exceeding the physiological range is avoided.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology for medical devices, and in particular to an intelligent infusion system and intelligent infusion control method based on database dynamic feedback regulation. Background Technology

[0002] In clinical medical care, intravenous infusion is an important means of drug administration, nutritional support, and fluid replenishment. Its application covers multiple departments such as internal medicine, surgery, and emergency medicine. The traditional infusion process mainly relies on medical staff to manually adjust the drip rate knob of the infusion set and observe the patient's condition and the remaining amount of medicine through regular rounds. This mode is difficult to guarantee the real-time and continuous monitoring of infusion when there are many patients or when medical staff are busy. With the development of medical informatization and intelligence, rudimentary infusion pump devices have appeared on the market, which can achieve fixed-speed infusion. However, they still require manual preset parameters and lack the ability to dynamically respond to changes in the patient's physiological state and abnormalities in the infusion process, which cannot meet the refined and personalized needs of precision medicine for infusion control.

[0003] However, existing technologies lack dynamic control mechanisms supported by databases and mostly rely on single fixed parameter control. They cannot adjust infusion plans based on individual patient information such as age, condition, and allergy history, nor can they optimize current control strategies using historical infusion data. Furthermore, the linkage between monitoring and control is insufficient. They only have simple parameter monitoring functions, but the monitoring data is only used for local alarms and cannot be deeply analyzed and transformed into active control commands. This leads to reliance on manual intervention for abnormal handling. At the same time, infusion equipment mostly operates independently and cannot share data with hospital HIS systems and electronic medical record systems, which is not conducive to full traceability of the infusion process and medical quality control.

[0004] In summary, current infusion systems have significant shortcomings in personalized control and data-driven management, making it difficult to meet the complex and ever-changing infusion needs in clinical practice. Therefore, developing an intelligent infusion system based on dynamic feedback control from a database to achieve precise, automated, and information-based management of the infusion process has become an urgent technical problem to be solved in the field of medical equipment. Summary of the Invention

[0005] To address the technical problems existing in the prior art, the present invention provides the following technical solution:

[0006] On the one hand, an intelligent infusion system based on dynamic feedback regulation of a database is provided. This method is implemented by electronic devices. The system includes: an infusion terminal execution module, a multi-parameter monitoring module, a data transmission module, a central control server module, and a dynamic database module.

[0007] The infusion terminal execution module is used to receive infusion control commands sent by the central control server module, perform infusion speed adjustment and infusion start / stop operations, and provide feedback on the current infusion execution status information.

[0008] The multi-parameter monitoring module is used to collect patient physiological parameters, infusion tubing status parameters, and remaining drug volume parameters in real time during the infusion process, and convert the collected real-time parameters into digital signals.

[0009] The data transmission module adopts a wireless communication protocol to establish a data interaction channel between the infusion terminal execution module, the multi-parameter monitoring module and the central control server module, so as to realize real-time parameter uploading and control command downloading.

[0010] The central control server module is used to receive real-time parameters uploaded by the multi-parameter monitoring module, call the data in the dynamic database module for comparison and analysis, generate infusion control commands and send them to the infusion terminal execution module, and trigger abnormal warning signals at the same time.

[0011] The dynamic database module is used to store basic patient information, preset infusion plan data, historical infusion record data, real-time monitoring parameter threshold range data, and abnormal handling strategy data, and supports real-time data updates and queries.

[0012] Furthermore, the infusion terminal execution module includes a stepper motor drive unit, an infusion pump body, and a status detection sensor;

[0013] The stepper motor drive unit adjusts the rotation speed of the infusion pump body according to the instructions of the central control server module;

[0014] The status detection sensor is used to detect the operating status of the infusion pump body and feed it back to the central control server module.

[0015] Furthermore, the multi-parameter monitoring module includes a physiological parameter monitoring unit and an infusion status monitoring unit;

[0016] The physiological parameter monitoring unit includes a heart rate sensor, a blood pressure sensor, and a blood oxygen saturation sensor, used to collect the patient's vital signs data.

[0017] The infusion status monitoring unit includes a drip rate sensor, a pressure sensor, and a drug solution level sensor, which are used to collect equipment and drug solution status data during the infusion process.

[0018] Furthermore, the central control server module includes a data preprocessing unit, an intelligent decision-making unit, and an instruction issuing unit;

[0019] The data preprocessing unit is used to filter, denoise, and align timestamps on the received multi-source real-time monitoring data to form a unified patient state vector.

[0020] The intelligent decision-making unit is used to compare and analyze the processed real-time data with the thresholds, rules, and historical cases in the dynamic database module, and generate the target infusion rate based on the adaptive control formula. ,in, The initial baseline rate is retrieved from the dynamic database module based on patient information and drug knowledge base. , Current physiological parameter monitoring values With target value deviation, The rate of change of physiological parameter deviation, and The adaptive weighting coefficients are dynamically calculated by the intelligent decision-making unit by querying successful control records in similar scenarios in the historical case database;

[0021] The intelligent decision-making unit has a three-level early warning mechanism. Based on the degree to which real-time parameters exceed the threshold, it is divided into level one, level two, and level three early warnings. Different levels of early warning correspond to different processing strategies, and the processing strategies are stored in the strategy rule base of the dynamic database module.

[0022] The instruction issuing unit is used to transmit the instructions calculated by the intelligent decision-making unit. The Level 3 early warning was converted into a control command and issued.

[0023] Furthermore, the three-level early warning mechanism of the intelligent decision-making unit is divided according to the following rules:

[0024] Level 1 warning: When When triggered, the system maintains automatic control and displays prompt information on the human-machine interface;

[0025] Level 2 warning: When or When triggered, the system maintains automatic control but activates an audible and visual alarm to alert medical staff. and These are the thresholds for first-level and second-level deviations, respectively. and These are the minimum and maximum infusion rates, respectively.

[0026] Level 3 warning: When a Level 2 warning is triggered and any real-time parameter uploaded by the multi-parameter monitoring module exceeds the threshold range of the corresponding real-time monitoring parameter in the dynamic database module, a Level 3 warning is triggered to issue an audible and visual alarm and a remote alarm.

[0027] Furthermore, when the intelligent decision-making unit triggers a level-three warning, the system suspends the infusion and automatically executes predefined emergency operations in the strategy rule base, including: locking the infusion pump and sending emergency alarm information containing the patient ID, abnormality type, and parameters to the monitoring center and the mobile terminals of medical staff.

[0028] Furthermore, the dynamic database module specifically includes:

[0029] The patient information database is used to store patients' age, weight, allergy history, and diagnostic results.

[0030] A drug knowledge base is used to store information on the standard infusion rate range, maximum / minimum safe rate, drug compatibility, and common adverse reaction characteristics of different drugs.

[0031] The historical case library is used to store complete infusion process data after desensitization, including real-time parameter time-series records for each infusion, triggered events, and control strategies adopted.

[0032] The strategy rule base is used to store regulation rules and anomaly handling strategies generated based on clinical guidelines and historical case data mining. The rules include physiological parameter safety thresholds, parameter change rate warning thresholds, and corresponding treatment procedures.

[0033] On the other hand, a smart infusion control method based on database dynamic feedback regulation is provided. This method is applied to a smart infusion system based on database dynamic feedback regulation. The specific steps of this method are as follows:

[0034] S100, Protocol Loading and Initialization: The central control server module loads the corresponding preset infusion protocol data, real-time monitoring parameter threshold range data, and abnormal handling strategy data from the dynamic database module based on the input patient identity information.

[0035] S200, Multi-parameter real-time monitoring: The multi-parameter monitoring module continuously collects the patient's physiological parameters, infusion tubing status parameters, and remaining drug volume parameters, and uploads them to the central control server module through the data transmission module;

[0036] S300, Dynamic Decision Making and Command Generation: The central control server module compares and analyzes the received real-time parameters with the loaded threshold range, and generates infusion control commands containing infusion rate information according to the preset control algorithm.

[0037] S400, Command Issuance and Closed-Loop Execution: The central control server module sends infusion control commands to the infusion terminal execution module through the data transmission module. The infusion terminal execution module adjusts the infusion status accordingly and feeds back the execution status to the central control server module.

[0038] S500, Cyclic Monitoring and Anomaly Handling: Cyclic execution of S200 to S400, while the central control server module continuously monitors the system status according to the anomaly handling strategy loaded in S100, and triggers an anomaly warning once the warning conditions are met.

[0039] On the other hand, an electronic device is provided, the electronic device comprising: a processor and a memory;

[0040] The memory stores computer-readable instructions, which, when executed by the processor, implement an intelligent infusion system based on database dynamic feedback control as described above.

[0041] On the other hand, a computer-readable storage medium is provided, wherein at least one instruction is stored therein, the at least one instruction being loaded and executed by a processor to implement an intelligent infusion system based on database dynamic feedback control as described above.

[0042] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following:

[0043] I. This invention uses a dynamic database module to store multi-dimensional data such as patient information, infusion plans, threshold ranges, and historical records. The central control server module calls these data and compares and analyzes them with real-time physiological parameters and infusion status parameters collected by the multi-parameter monitoring module to calculate the target infusion rate. Based on the target infusion rate and real-time monitoring parameters, it issues early warnings to ensure accurate monitoring of the control parameters and the individual patient's condition, and to keep the infusion rate always within the optimal range that adapts to the patient's physiological state, avoiding adverse infusion reactions caused by parameter errors or exceeding the physiological range.

[0044] Second, this invention collects real-time data of the entire infusion process through a multi-parameter monitoring module, and uploads it to the central control server module via a data transmission module with encryption. The server module performs deviation analysis based on database thresholds. When a parameter exceeds the safe range, the intelligent decision-making unit triggers a tiered warning and invokes anomaly handling strategies. At the same time, the infusion terminal execution module receives instructions from the server to adjust the infusion status and feeds back the execution results to the server. This linkage mechanism enables the system to complete anomaly identification, warning, and handling without manual intervention, shortening anomaly response time, reducing the inspection pressure on medical staff, and ensuring the safety and continuity of the infusion process. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0046] Figure 1 This is a flowchart of an intelligent infusion system based on database dynamic feedback control provided in an embodiment of the present invention;

[0047] Figure 2 This is a schematic diagram of the control system of the intelligent infusion system based on database dynamic feedback regulation provided in an embodiment of the present invention;

[0048] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0049] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0050] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0051] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0052] In this embodiment of the invention, sometimes a subscript such as W1 may be mistakenly written as a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0053] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0054] Example 1

[0055] This embodiment provides an intelligent infusion system based on database dynamic feedback control. By constructing a closed-loop control system of "monitoring-analysis-decision-execution-feedback", it integrates five core modules: infusion terminal execution module, multi-parameter monitoring module, data transmission module, central control server module, and dynamic database module. It can dynamically adjust the infusion plan according to changes in the patient's physiological state, reduce manual intervention, improve the safety, accuracy and informatization level of infusion, realize intelligent control of the entire infusion process, and meet the refined and personalized infusion needs of clinical practice.

[0056] (1) Working principle and operation process of the infusion terminal execution module

[0057] The infusion terminal execution module receives infusion control commands from the central control server module, accurately executes infusion rate adjustment and infusion start / stop operations, and collects its own operating status information in real time and feeds it back to the central control server module, forming a closed-loop feedback at the execution level to ensure the consistency between infusion operation and control commands. This module is specifically composed of three parts: a stepper motor drive unit, an infusion pump body, and a status detection sensor. Each unit has a clear division of labor and works together to ensure the accuracy and reliability of infusion execution.

[0058] Stepper motor drive unit: Based on pulse signals, the stepper motor's rotation angle and speed are controlled, thereby adjusting the infusion rate of the infusion pump. This unit first receives control commands from the central control server module through the data transmission module. The commands contain motor speed parameters corresponding to the target infusion rate. The drive unit converts the target infusion rate into corresponding pulse signal parameters, which are indirectly related to the total infusion volume.

[0059] During operation, the stepper motor drive unit receives the target infusion rate update command from the central control server module in real time (when changes in the patient's physiological parameters cause the target rate to be adjusted), and dynamically adjusts the output pulse frequency: if the target rate increases, the drive unit increases the pulse frequency, which speeds up the stepper motor, increases the frequency at which the infusion pump squeezes the infusion tube, and increases the infusion rate; if the target rate decreases, the pulse frequency decreases, which slows down the motor speed and the infusion rate.

[0060] Status detection sensors: These sensors are used to collect real-time operating status data of the infusion pump body, ensuring the monitorability of the infusion process. They include a position sensor, a speed sensor, a pressure sensor (local), and a liquid level auxiliary sensor. The position sensor is installed at the pump head drive mechanism to detect the actual rotation position of the stepper motor, determining whether the infusion pump is in "standby," "running," or "paused" state, avoiding positional deviations caused by motor step loss. The speed sensor is connected to the stepper motor output shaft, collecting the actual motor speed in real time and converting the speed data into a digital signal, which is then fed back to the central control server module. This signal is compared with the target speed of the drive unit. If the deviation exceeds the allowable range (e.g., ±5%), a "speed deviation warning" is triggered, indicating possible mechanical jamming or drive failure. The local pressure sensor is installed near the infusion tube outlet to detect the real-time pressure of the medication output. If the pressure suddenly increases (e.g., due to infusion tube blockage) or suddenly decreases (e.g., due to infusion tube rupture or medication depletion), an abnormal pressure signal is immediately generated. The liquid level auxiliary sensor (if integrated) uses infrared or ultrasonic principles to assist in detecting the presence of medication in the infusion tube, preventing empty pump operation.

[0061] During overall operation, the workflow of the infusion terminal execution module is as follows: First, the central control server module issues an initial infusion control command (including the initial target infusion rate). The data transmission module decrypts the command and transmits it to the stepper motor drive unit. The drive unit converts the target rate into a pulse signal, controlling the stepper motor to drive the infusion pump body to start infusion. Simultaneously, the status detection sensor collects real-time status data such as motor speed, pump position, and outlet pressure. After converting the data into digital signals, it is uploaded to the central control server module through the data transmission module. The central control server module compares the actual status data with the command target data. If there is a deviation (such as the actual speed being lower than the target speed), the control command is adjusted and reissued to the drive unit until the actual status matches the target status. When a "pause" or "stop" command is received, or when the status detection sensor detects an anomaly, the drive unit immediately stops the motor, the infusion pump body stops infusion, and the abnormal status is fed back to the central control server module, awaiting further instructions (such as a restart command after troubleshooting).

[0062] (2) Working principle and operation process of multi-parameter monitoring module

[0063] The multi-parameter monitoring module comprehensively collects two types of key data during the infusion process: patient physiological parameters and infusion status parameters. It converts the collected analog signals into digital signals and uploads them to the central control server module through the data transmission module, providing data support for subsequent dynamic decision-making. This module is divided into a physiological parameter monitoring unit and an infusion status monitoring unit according to the different monitoring objects. The two types of units work independently and cooperate with each other to ensure the integrity and real-time nature of the collected data.

[0064] Physiological parameter monitoring unit: By collecting the patient's vital signs data in real time, it reflects the changes in the patient's physiological state during the infusion process. The core sensors include heart rate sensor, blood pressure sensor and blood oxygen saturation sensor. The three types of sensors monitor different dimensions of physiological indicators, which together constitute a comprehensive monitoring of the patient's physiological state.

[0065] During operation, the physiological parameter monitoring unit works as follows: First, medical staff select the corresponding sensor type and wearing position on the human-machine interface of the central control server module according to the patient's condition (such as age, weight, and diagnosis results), and load the normal threshold range of the patient's physiological parameters from the dynamic database. Then, after the sensor is worn, the unit performs an initial self-test to check whether the sensor is properly connected and whether the signal is stable. If the self-test passes, it begins to collect data in real time. During the collection process, the unit's built-in signal processing circuit filters and amplifies the raw signal, and then converts the analog signal into a digital signal through an analog-to-digital converter. Finally, the digital signal is encrypted by the data transmission module and uploaded to the central control server module. The upload cycle is synchronized with the sensor sampling cycle to ensure that the central control server module can obtain changes in the patient's physiological state in real time.

[0066] Infusion status monitoring unit: Through sensors installed in the infusion equipment and pipeline, it collects data on the equipment operation status and drug status in real time during the infusion process, reflecting whether the infusion is proceeding normally. It includes drip rate sensor, pressure sensor and drug level sensor. The three types of sensors monitor "infusion rate", "pipeline patency" and "remaining drug volume" respectively, which together constitute a comprehensive monitoring of the infusion process.

[0067] During operation, the multi-parameter monitoring module works as follows: After system startup, the physiological parameter monitoring unit and the infusion status monitoring unit initialize simultaneously, self-checking the sensor connection status and signal quality. If a sensor fault exists (such as signal interruption or data anomaly), a "sensor fault" signal is immediately generated and uploaded to the central control server module, triggering an "equipment fault warning." After the self-check passes, both units begin real-time data acquisition according to a preset sampling period. The acquired raw signals are processed (filtered, amplified, and converted from analog to digital) and converted into standardized digital signals. A timestamp is added to the digital signals to ensure data time consistency, and then the data is uploaded to the central control server module via the data transmission module. If data transmission is interrupted during the upload process, the module temporarily stores the data in a local cache and re-uploads the data after transmission resumes to avoid data loss. After receiving the data, the central control server module sends a "data reception confirmation" signal to the multi-parameter monitoring module. If the module does not receive the confirmation signal, it re-uploads the data to ensure the reliability of data transmission.

[0068] (3) Working principle and operation process of data transmission module

[0069] The data transmission module adopts a wireless communication protocol to establish a two-way data interaction channel between the infusion terminal execution module, the multi-parameter monitoring module, and the central control server module, realizing "real-time parameter uploading" and "control command downloading" while ensuring the security, real-time performance, and reliability of data transmission. Data uploading mainly includes the multi-parameter monitoring module uploading real-time parameters to the central control server module and the infusion terminal execution module uploading status data to the central control server module.

[0070] (4) Working principle and operation process of the central control server module

[0071] The central control server module receives real-time parameters uploaded by the multi-parameter monitoring module, compares and analyzes data from the dynamic database module, generates infusion control commands (such as target infusion rate) through intelligent algorithms, and sends them to the infusion terminal execution module. At the same time, it triggers graded early warning signals based on the deviation between real-time parameters and thresholds, realizing "data-driven dynamic decision-making". This module consists of three parts: a data preprocessing unit, an intelligent decision-making unit, and a command issuing unit. Each unit works together to ensure the accuracy, timeliness, and safety of the decision-making.

[0072] Data preprocessing unit: Standardizes multi-source real-time monitoring data (from physiological parameter monitoring unit and infusion status monitoring unit), eliminates data noise, unifies data format, and achieves data alignment, providing high-quality "data input" for intelligent decision-making unit and avoiding decision bias caused by raw data quality issues. The data preprocessing unit stores the integrated patient status vector in dynamic database module for easy subsequent query and retrospective analysis.

[0073] The intelligent decision-making unit compares and analyzes the patient state vector generated by the data preprocessing unit with the data (threshold range, historical cases, drug characteristics) in the dynamic database module. It calculates the target infusion rate using an adaptive control formula and triggers graded early warnings based on parameter deviations, achieving "personalized and dynamic infusion control decision-making." The target infusion rate is calculated as follows: ,in, The initial baseline rate is retrieved from the dynamic database module based on patient information and drug knowledge base. , Current physiological parameter monitoring values With target value deviation, The rate of change of physiological parameter deviation, and The adaptive weighting coefficients are dynamically calculated by the intelligent decision-making unit by querying successful control records in similar scenarios in the historical case database. The intelligent decision-making unit has a three-level early warning mechanism, categorized into Level 1, Level 2, and Level 3 early warnings based on the degree to which real-time parameters exceed thresholds. Different levels of early warning correspond to different handling strategies (stored in the strategy rule base of the dynamic database). Its core purpose is "tiered response and rapid handling" to avoid risks caused by untimely anomaly handling. The rules for the three-level early warning mechanism are as follows:

[0074] Level 1 warning: When When triggered, the system maintains automatic control and displays prompt information on the human-machine interface. The trigger time, trigger reason, handling measures, and control results of the first-level warning are recorded in the dynamic database module for easy subsequent traceability.

[0075] Level 2 warning: When or When triggered, the system maintains automatic control but activates an audible and visual alarm to alert medical staff. and These are the thresholds for first-level and second-level deviations, respectively. and These are the minimum and maximum infusion rates, respectively.

[0076] Level 3 warning: When a Level 2 warning is triggered and any real-time parameter uploaded by the multi-parameter monitoring module exceeds the threshold range of the corresponding real-time monitoring parameter in the dynamic database module, a Level 3 warning is triggered to issue an audible and visual alarm and a remote alarm.

[0077] (5) Working principle and operation process of dynamic database module

[0078] The dynamic database module stores basic patient information, preset infusion plan data, historical infusion record data, real-time monitoring parameter threshold range data, and anomaly handling strategy data. It supports real-time data updates and queries, providing comprehensive and accurate data support for the central control server module's decision-making. It also enables end-to-end data traceability of the infusion process. Based on different data types, this module is divided into four sub-databases: a patient information database, a drug knowledge base, a historical case database, and a strategy rule base. These sub-databases are interconnected and share data, forming a complete database system.

[0079] The patient information database is a sub-database that stores individual patient data. Its working principle is to obtain and store patients' basic and clinical information by connecting with the hospital's HIS system and electronic medical record system, providing patient-level data support for the development of personalized infusion plans and ensuring individualized infusion control.

[0080] The drug knowledge base is a sub-base that stores drug characteristic data. Its working principle is based on clinical guidelines, drug instructions, and pharmaceutical research literature to organize and store the characteristic parameters and usage rules of various infusion drugs, providing drug-level data support for the formulation and adjustment of infusion plans, and ensuring the safety and effectiveness of infusion regulation.

[0081] The historical case database stores and categorizes complete infusion process data after desensitization, providing experience references for intelligent decision-making in the central control server module, while also providing data support for clinical research and quality improvement, enabling continuous optimization of infusion protocols.

[0082] The strategy rule base is a sub-base that stores regulation rules and abnormal handling strategies. Its working principle is based on clinical guidelines and historical case data mining results to formulate and store various rules (such as physiological parameter safety thresholds and early warning triggering rules) and abnormal handling strategies (such as treatment procedures for different early warning levels) in the infusion process. This provides "rule-level" data support for the decision-making of the central control server module, ensuring the "standardization and safety" of infusion regulation.

[0083] In summary, the intelligent infusion system based on dynamic feedback control provided in this embodiment constructs a full-process control system of "data acquisition-preprocessing-decision-execution-feedback-optimization" through the collaborative work of the infusion terminal execution module, multi-parameter monitoring module, data transmission module, central control server module, and dynamic database module. This effectively solves the shortcomings of infusion systems relying on manual labor and existing infusion pumps lacking dynamic response and data-driven management. It enables the interoperability of infusion data and overall patient diagnosis and treatment data, providing more comprehensive support for multidisciplinary diagnosis and treatment decisions and promoting the deep integration of intelligent medical equipment and refined medical services.

[0084] Example 2

[0085] Based on Example 1, this example provides specific steps for the intelligent fluid control method based on database dynamic feedback regulation in performing dynamic feedback regulation of intelligent infusion, such as... Figure 1 As shown, the specific steps of this method are as follows:

[0086] Phase 1: System Initialization (S100)

[0087] Identity verification and data loading: Healthcare workers input or scan patient identity information.

[0088] Retrieve Personalized Plans: Based on the patient ID, the central control server automatically retrieves the patient's preset infusion plan, individualized safety parameter thresholds (such as target blood pressure, maximum / minimum allowable infusion rate, etc.), and abnormal handling strategies from the dynamic database of patient information and drug knowledge base.

[0089] System ready: The infusion terminal execution module (infusion pump) is initialized and awaits execution instructions.

[0090] Phase Two: Real-time Monitoring and Data Upload (S200)

[0091] Physiological parameter acquisition: The physiological parameter monitoring unit (such as blood pressure and blood oxygen saturation sensors) in the multi-parameter monitoring module continuously collects the patient's real-time vital signs data.

[0092] Infusion status acquisition: The infusion status monitoring unit (such as drip rate sensor and pressure sensor) in the same module continuously collects real-time data such as infusion rate, pipeline pressure, and remaining drug volume.

[0093] Encrypted data upload: All collected data is encrypted by the data transmission module and uploaded to the central control server module in real time.

[0094] Phase 3: Intelligent Decision Making and Command Generation (S300)

[0095] Data preprocessing: The data preprocessing unit of the central control server cleans, filters, and aligns the uploaded multi-source data to form a complete and reliable real-time status dataset.

[0096] Deviation calculation and analysis: The intelligent decision-making unit compares the processed real-time data (such as current blood pressure) with the target value loaded in the database to calculate the deviation value (ΔP) and its changing trend.

[0097] Dynamic decision-making:

[0098] Normal regulation: The intelligent decision-making unit calculates the target infusion rate most suitable for the current patient's condition based on a preset adaptive regulation algorithm, combined with the current deviation and rate of change.

[0099] Case study support: During the decision-making process, the system will query the historical case study library to find successful cases similar to the current situation, in order to optimize decision parameters.

[0100] Safety verification: The calculated target rate is verified against the absolute safety range of the drug in the drug knowledge base to ensure the safety of the instruction.

[0101] Tiered early warning judgment: The intelligent decision-making unit compares real-time data with multi-level thresholds in the database to determine whether an early warning is triggered.

[0102] No warning: If everything is normal, proceed directly to the instruction issuance step.

[0103] Level 1 warning: If the parameter deviation exceeds the first threshold, the system will maintain automatic adjustment and only prompt medical staff to pay attention on the interface.

[0104] Level 2 warning: If the parameter deviation exceeds a larger second threshold or the calculation rate exceeds the limit, the system will trigger an audible and visual alarm while maintaining control, reminding medical staff to intervene and conduct an examination.

[0105] Level 3 warning: If a serious abnormality occurs (such as pipeline blockage or sudden drop in blood pressure), the system will immediately trigger the highest level alarm.

[0106] Phase Four: Command Issuance and Execution (S400)

[0107] Command issuance: The command issuance unit will encrypt and issue the final determined target infusion rate or shutdown command to the infusion terminal execution module.

[0108] Precise execution: The stepper motor drive unit of the infusion terminal execution module receives instructions and precisely adjusts the speed of the infusion pump to change the infusion rate.

[0109] Status feedback: The status detection sensor feeds back the latest execution status of the infusion pump to the central control server in real time, forming an execution closed loop.

[0110] Phase 5: Cyclic Monitoring and Learning (S500)

[0111] Continuous loop: The system repeats steps 4-14 at a very high frequency to form a closed-loop control, continuously monitors, analyzes, and adjusts to ensure that the infusion process is always in an optimal or safe state.

[0112] Recording and Learning: The data from this successful control process (including real-time parameters, decision instructions, and final results) will be anonymized and stored in the historical case library as a new case model to enrich system knowledge and optimize future decisions.

[0113] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention, such as... Figure 3 As shown, the electronic device may include the above-mentioned Figure 1 The illustrated intelligent infusion system is based on database dynamic feedback control. Optionally, the electronic device 410 may include a first processor 2001.

[0114] Optionally, the electronic device 410 may also include a memory 2002 and a transceiver 2003.

[0115] The first processor 2001, memory 2002, and transceiver 2003 can be connected via a communication bus.

[0116] The following is combined with Figure 3 A detailed description of each component of electronic device 410 is provided below:

[0117] The first processor 2001 is the control center of the electronic device 410. It can be a single processor or a collective term for multiple processing elements. For example, the first processor 2001 can be one or more central processing units (CPUs), application-specific integrated circuits (ASICs), or one or more integrated circuits configured to implement embodiments of the present invention, such as one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs).

[0118] Optionally, the first processor 2001 can perform various functions of the electronic device 410 by running or executing software programs stored in the memory 2002 and calling data stored in the memory 2002.

[0119] In a specific implementation, as one example, the first processor 2001 may include one or more CPUs, for example... Figure 3 CPU0 and CPU1 are shown in the diagram.

[0120] In a specific implementation, as one example, the electronic device 410 may also include multiple processors, for example... Figure 3 The first processor 2001 and the second processor 2004 are shown in the diagram. Each of these processors can be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). Here, a processor can refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).

[0121] The memory 2002 is used to store the software program that executes the present invention, and is controlled by the first processor 2001 to execute it. The specific implementation method can be referred to the above method embodiment, and will not be repeated here.

[0122] Optionally, the memory 2002 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory 2002 may be integrated with the first processor 2001 or may exist independently and be accessed through the interface circuit of the electronic device 410. Figure 3 (Not shown in the image) is coupled to the first processor 2001, and this embodiment of the invention does not specifically limit this.

[0123] The transceiver 2003 is used to communicate with network devices or with terminal devices.

[0124] Alternatively, transceiver 2003 may include a receiver and a transmitter. Figure 3 (Not shown separately). The receiver is used to implement the receiving function, and the transmitter is used to implement the transmitting function.

[0125] Optionally, the transceiver 2003 can be integrated with the first processor 2001, or it can exist independently and be connected via the interface circuit of the electronic device 410. Figure 3 (Not shown in the image) is coupled to the first processor 2001, and this embodiment of the invention does not specifically limit this.

[0126] It should be noted that, Figure 3 The structure of the electronic device 410 shown does not constitute a limitation on the router. Actual knowledge structure identification devices may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0127] Furthermore, the technical effects of the electronic device 410 can be referred to the technical effects of the intelligent infusion system based on database dynamic feedback control described in the above method embodiments, and will not be repeated here.

[0128] It should be understood that the first processor 2001 in this embodiment of the invention may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0129] It should also be understood that the memory in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDRSDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DRRAM).

[0130] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0131] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An intelligent infusion system based on database dynamic feedback control, characterized in that, The system includes: an infusion terminal execution module, a multi-parameter monitoring module, a data transmission module, a central control server module, and a dynamic database module; The infusion terminal execution module is used to receive infusion control commands sent by the central control server module, perform infusion speed adjustment and infusion start / stop operations, and provide feedback on the current infusion execution status information. The multi-parameter monitoring module is used to collect patient physiological parameters, infusion tubing status parameters, and remaining drug volume parameters in real time during the infusion process, and convert the collected real-time parameters into digital signals. The data transmission module adopts a wireless communication protocol to establish a data interaction channel between the infusion terminal execution module, the multi-parameter monitoring module and the central control server module, so as to realize real-time parameter uploading and control command downloading. The central control server module is used to receive real-time parameters uploaded by the multi-parameter monitoring module, call the data in the dynamic database module for comparison and analysis, generate infusion control commands and send them to the infusion terminal execution module, and trigger abnormal warning signals at the same time. The dynamic database module is used to store basic patient information, preset infusion plan data, historical infusion record data, real-time monitoring parameter threshold range data, and abnormal handling strategy data, and supports real-time data updates and queries.

2. The intelligent infusion system based on database dynamic feedback control according to claim 1, characterized in that, The infusion terminal execution module includes a stepper motor drive unit, an infusion pump body, and a status detection sensor. The stepper motor drive unit adjusts the rotation speed of the infusion pump body according to the instructions of the central control server module; The status detection sensor is used to detect the operating status of the infusion pump body and feed it back to the central control server module.

3. The intelligent infusion system based on database dynamic feedback control according to claim 1, characterized in that, The multi-parameter monitoring module includes a physiological parameter monitoring unit and an infusion status monitoring unit; The physiological parameter monitoring unit includes a heart rate sensor, a blood pressure sensor, and a blood oxygen saturation sensor, used to collect the patient's vital signs data. The infusion status monitoring unit includes a drip rate sensor, a pressure sensor, and a drug solution level sensor, which are used to collect equipment and drug solution status data during the infusion process.

4. The intelligent infusion system based on database dynamic feedback control according to claim 1, characterized in that, The central control server module includes a data preprocessing unit, an intelligent decision-making unit, and an instruction issuing unit. The data preprocessing unit is used to filter, denoise, and align timestamps on the received multi-source real-time monitoring data to form a unified patient state vector. The intelligent decision-making unit is used to compare and analyze the processed real-time data with the thresholds, rules, and historical cases in the dynamic database module, and generate the target infusion rate based on the adaptive control formula. ,in, The initial baseline rate is retrieved from the dynamic database module based on patient information and drug knowledge base. , Current physiological parameter monitoring values With target value deviation, The rate of change of physiological parameter deviation, and These are adaptive weighting coefficients; The intelligent decision-making unit has a three-level early warning mechanism. Based on the degree to which real-time parameters exceed the threshold, it is divided into level one, level two, and level three early warnings. Different levels of early warning correspond to different processing strategies, and the processing strategies are stored in the strategy rule base of the dynamic database module. The instruction issuing unit is used to transmit the instructions calculated by the intelligent decision-making unit. The Level 3 early warning was converted into a control command and issued.

5. The intelligent infusion system based on database dynamic feedback control according to claim 4, characterized in that, The three-level early warning mechanism of the intelligent decision-making unit is divided according to the following rules: Level 1 warning: When When triggered, the system maintains automatic control and displays prompt information on the human-machine interface; Level 2 warning: When or When triggered, the system maintains automatic control but activates an audible and visual alarm to alert medical staff. and Here, represents the threshold values ​​for first-order and second-order deviations, and and represent the minimum and maximum values ​​of the infusion rate, respectively. Level 3 warning: When a Level 2 warning is triggered and any real-time parameter uploaded by the multi-parameter monitoring module exceeds the threshold range of the corresponding real-time monitoring parameter in the dynamic database module, a Level 3 warning is triggered to issue an audible and visual alarm and a remote alarm.

6. The intelligent infusion system based on database dynamic feedback control according to claim 5, characterized in that, When the intelligent decision-making unit triggers a level-three warning, the system suspends the infusion and automatically executes predefined emergency operations in the strategy rule base, including: locking the infusion pump and sending emergency alarm information containing the patient ID, abnormality type, and parameters to the monitoring center and medical staff's mobile terminals.

7. The intelligent infusion system based on database dynamic feedback control according to claim 1, characterized in that, The dynamic database module specifically includes: The patient information database is used to store patients' age, weight, allergy history, and diagnostic results. A drug knowledge base is used to store information on the standard infusion rate range, maximum / minimum safe rate, drug compatibility, and common adverse reaction characteristics of different drugs. The historical case library is used to store complete infusion process data after desensitization, including real-time parameter time-series records of each infusion, triggered events, and control strategies adopted. The strategy rule base is used to store regulation rules and anomaly handling strategies generated based on clinical guidelines and historical case data mining. The rules include physiological parameter safety thresholds, parameter change rate warning thresholds, and corresponding treatment procedures.

8. A smart infusion control method based on database dynamic feedback regulation, applicable to the smart infusion system based on database dynamic feedback regulation as described in any one of claims 1-7, characterized in that, The specific steps of this method are as follows: S100, Protocol Loading and Initialization: The central control server module loads the corresponding preset infusion protocol data, real-time monitoring parameter threshold range data, and abnormal handling strategy data from the dynamic database module based on the input patient identity information. S200, Multi-parameter real-time monitoring: The multi-parameter monitoring module continuously collects the patient's physiological parameters, infusion tubing status parameters, and remaining drug volume parameters, and uploads them to the central control server module through the data transmission module; S300, Dynamic Decision Making and Command Generation: The central control server module compares and analyzes the received real-time parameters with the loaded threshold range, and generates infusion control commands containing infusion rate information according to the preset control algorithm. S400, Command Issuance and Closed-Loop Execution: The central control server module sends infusion control commands to the infusion terminal execution module through the data transmission module. The infusion terminal execution module adjusts the infusion status accordingly and feeds back the execution status to the central control server module. S500, Cyclic Monitoring and Anomaly Handling: Cyclic execution of S200 to S400, while the central control server module continuously monitors the system status according to the anomaly handling strategy loaded in S100, and triggers an anomaly warning once the warning conditions are met.

9. An electronic device, characterized in that, The electronic device includes: a processor and a memory; The memory stores computer-readable instructions, which, when executed by the processor, implement the intelligent infusion system as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium contains program code, which can be called by a processor to execute the intelligent infusion system as described in any one of claims 1 to 7.

Images