An intelligent and precise bolus injection system for vasoactive drugs in cardiology department

Abstract

The application discloses a kind of intracardiac department vascular active drug intelligent precision bolus system, it is related to medical instrument technical field, including data acquisition unit, flow monitoring unit, pressure control unit, abnormal early warning unit, wireless communication unit and control decision unit;Flow monitoring unit is compensated to pump body characteristic, liquid viscosity and ambient temperature by micro flow sensor in combination with dynamic compensation algorithm;Pressure control unit adopts adaptive PID algorithm in combination with patient hemodynamic state dynamic setting target pressure range, realizes closed loop precision regulation and control;Abnormal early warning unit is based on multidimensional anomaly detection model identification pipeline blockage, needle falls off, drip and so on Abnormal and trigger three-level early warning;Wireless communication unit supports with the two-way data interaction of central monitoring system;Control decision unit adopts hierarchical architecture to carry out data fusion and intelligent decision-making.The system can control infusion precision error within 2%, realize the stable maintenance of pipeline pressure and the timely early warning response of exception, while supporting the centralized management and remote monitoring of multiple devices.

Description

Technical Field

[0001] This invention relates to the field of medical devices, specifically to an intelligent and precise injection system for vasoactive drugs in cardiology. Background Technology

[0002] In the field of intensive care, the continuous and precise infusion of vasoactive drugs is a key treatment for maintaining hemodynamic stability in patients. These drugs are extremely sensitive to dosage; even a small dose deviation can lead to drastic fluctuations in vital signs such as blood pressure and heart rate, and even cause serious cardiovascular complications. Therefore, infusion accuracy and safety are of paramount importance in cardiology intensive care. Intelligent precision infusion systems, as the core equipment for achieving safe infusion of vasoactive drugs, primarily function to automatically control the infusion rate according to a preset protocol and provide timely warnings in abnormal situations. Existing technologies have the following shortcomings: most infusion pumps use an open-loop drive mode, which cannot detect the actual flow rate in the tubing in real time, and can only drive according to preset parameters, resulting in a deviation between the actual infusion volume and the set value; alarm responses to abnormal situations such as tubing blockage and end of the pusher stroke are often delayed and the prompts are not prominent enough, making it difficult for medical staff to detect them in time, which can easily affect medication safety due to delayed treatment; in addition, existing equipment generally lacks closed-loop pressure monitoring functions, making it impossible to dynamically and accurately control tubing pressure, and it also lacks wireless data interaction capabilities, making it difficult to meet the needs of intensive care units for centralized remote management of multiple devices. These technical deficiencies are particularly prominent in the time-sensitive intensive care setting, severely restricting the safe and effective infusion of vasoactive drugs. Summary of the Invention

[0003] The purpose of this invention is to provide an intelligent and precise injection system for vasoactive drugs in cardiology, in order to solve the technical problems existing in the prior art, such as insufficient infusion accuracy, delayed abnormal alarm, lack of pressure closed-loop control, and inability to perform wireless data transmission.

[0004] To solve the above problems, the technical solution adopted by the present invention is as follows: A smart and precise injection system for vasoactive drugs in cardiology includes a data acquisition unit, a flow monitoring unit, a pressure control unit, an abnormality warning unit, a wireless communication unit, and a control decision unit. The data acquisition unit is used to acquire pressure signals, drive motor speed signals, drug level signals, and environmental parameter signals within the injection tubing. The data acquisition unit integrates a high-precision MEMS pressure sensor and a photoelectric level sensor. The sampling frequency of the MEMS pressure sensor is set to 100Hz, and the resolution of the photoelectric level sensor is set to 0.1mL. The flow monitoring unit is used to detect the actual flow rate in the injection pipeline in real time. The flow monitoring unit includes a microfluidic sensor and a dynamic compensation algorithm module. The microfluidic sensor is set at the outlet end of the injection pipeline and is used to directly measure the instantaneous flow rate of the liquid medicine. The dynamic compensation algorithm module performs compensation calculations based on the mechanical characteristic parameters of the injection pump, the viscosity parameters of the liquid medicine, and the ambient temperature parameters to eliminate flow deviations caused by differences in pump characteristics and liquid medicine characteristics. The output signal of the flow monitoring unit is connected to the control decision unit to provide real-time flow feedback data. The pressure control unit is used for closed-loop precise control of the pressure within the injection tubing. The pressure control unit includes an adaptive PID control algorithm module and a pressure target setting module. The pressure target setting module dynamically sets the target pressure range based on the patient's current hemodynamic state and the pharmacokinetic characteristics of the vasoactive drug being used. The adaptive PID control algorithm module automatically adjusts the speed of the drive motor based on the deviation between the real-time collected pressure signal and the target pressure range, ensuring that the tubing pressure is always maintained within the target range. The output signal of the pressure control unit is connected to the drive circuit of the drive motor, forming a closed-loop control circuit. The anomaly warning unit is used to provide timely warnings of abnormal situations during the injection process. The anomaly warning unit includes a multi-dimensional anomaly detection model and an early warning execution module. The multi-dimensional anomaly detection model receives output data from the flow monitoring unit and pressure control unit in real time and performs comprehensive analysis on injection pressure, flow deviation rate, remaining drug volume, and equipment operating status. The early warning execution module identifies anomaly types such as pipeline blockage, needle detachment, leakage, sudden pressure drop, and sudden pressure rise based on preset anomaly discrimination thresholds, and triggers corresponding levels of audible and visual alarm signals. The output signal of the anomaly warning unit is also connected to the wireless communication unit to send alarm information to the central monitoring system. The wireless communication unit is used to realize data interaction with external devices; the wireless communication unit adopts a medical-grade wireless communication module and supports a two-way data transmission protocol; the wireless communication unit sends the collected real-time flow, pressure and equipment status data to the central monitoring system, and receives parameter adjustment instructions and control commands from the central monitoring system; the wireless communication unit is also used to push alarm information generated by the abnormal warning unit to the mobile terminal devices of medical staff; The control decision unit is used to comprehensively analyze the input data of each unit and generate injection control commands. The control decision unit includes a data fusion module and a decision algorithm module. The data fusion module comprehensively processes the output data of the flow monitoring unit, pressure control unit, and abnormal warning unit. The decision algorithm module calculates the optimal injection control parameters based on the fused multidimensional data stream, using fuzzy logic algorithms and threshold determination strategies, and sends control commands to the drive motor. The control decision unit is also used to automatically execute preset safety intervention strategies when an abnormal warning signal is detected.

[0005] Furthermore, the dynamic compensation algorithm module in the flow monitoring unit adopts the following compensation strategy: establishing a mapping relationship model between the mechanical characteristic parameters of the injection pump and the flow deviation; correcting the flow change caused by viscosity according to the viscosity parameter of the drug solution; correcting the metering error caused by thermal expansion and contraction according to the ambient temperature parameter; and fusing the above corrections through a multiple linear regression algorithm to obtain the final compensation coefficient. The compensation accuracy target of the dynamic compensation algorithm module is to ensure that the system infusion accuracy error does not exceed 2%.

[0006] Furthermore, the adaptive PID control algorithm module in the pressure control unit adopts the following control strategy: based on the patient's hemodynamic state and drug characteristics, multiple sets of PID control parameters are preset; the response characteristics of the controlled object are monitored in real time, and the optimal PID parameter combination is dynamically selected; when the patient's state changes significantly, the PID parameters are automatically adjusted through a learning algorithm to adapt to the new control requirements; the target pressure range of the pressure control unit is set to within ±10% of the injection pressure value corresponding to the patient's target blood pressure.

[0007] Furthermore, the multi-dimensional anomaly detection model in the anomaly early warning unit adopts the following detection strategy: defining pipeline blockage as a combination of pressure continuously exceeding a set threshold and flow continuously falling below a set threshold; defining needle detachment as a combination of a sudden drop in pressure and a simultaneous sudden drop in flow; defining dripping as a combination of continuously low flow and pressure within the normal range; setting characteristic thresholds for each anomaly type and establishing a mapping relationship between anomaly type and early warning level; designing a three-level early warning mechanism, corresponding to early warnings requiring attention, alarms requiring processing, and emergency alarms requiring urgent intervention.

[0008] Furthermore, the wireless communication unit supports the following communication protocols: it supports data interface with the hospital information system to achieve automatic synchronization of patient information and medication orders; it supports a multi-device centralized management protocol with the central monitoring system to achieve unified monitoring and coordinated control of multiple injection devices; it supports point-to-point communication with mobile terminal devices to achieve real-time push of alarm information; and it adopts a data encryption transmission mechanism to ensure the security of patient privacy and medical data.

[0009] Furthermore, the control decision unit adopts a hierarchical control architecture, including a strategic layer, a tactical layer, and an operational layer. The strategic layer formulates infusion strategies and pressure control targets based on the patient's overall condition and long-term medication regimen. The tactical layer dynamically adjusts infusion parameters based on the patient's current real-time vital signs and medication response. The operational layer directly controls the rotational speed and injection volume of the drive motor to achieve precise drug infusion. The various levels of the control decision unit are coordinated through a state machine to ensure the timeliness and consistency of decisions.

[0010] Furthermore, the present invention also includes a parameter self-calibration module for performing self-checks and calibrations on the system before each injection. The parameter self-calibration module includes a flow calibration process and a pressure calibration process. The flow calibration process calibrates the microfluidic sensor using a standard metering pump to establish a correspondence between the sensor output and the actual flow rate. The pressure calibration process calibrates the pressure sensor using a standard pressure source to ensure the accuracy of pressure measurement. The calibration data is stored in the system's non-volatile memory and is automatically loaded each time the system is started.

[0011] Furthermore, the present invention also includes an emergency power storage module for maintaining the continuous operation of the system when the external power supply is interrupted; the emergency power storage module adopts a lithium battery pack with a capacity set to meet the power requirements for at least 4 hours of continuous charging; when the external power supply is interrupted, the system automatically switches to the emergency power storage module for power supply and sends a power failure alarm to the central monitoring system; when the power is below 20%, the system automatically reduces some non-critical functions to extend the running time.

[0012] Compared with the prior art, the beneficial effects of the present invention are: This invention sets up a flow monitoring unit to detect the actual flow in the injection pipeline in real time, and combines a dynamic compensation algorithm to comprehensively compensate for mechanical properties, drug viscosity and ambient temperature, thereby controlling the injection accuracy error within 2%, effectively solving the technical defect of the open-loop drive mode in the prior art that cannot accurately control the actual injection volume. This invention sets up a pressure control unit and uses an adaptive PID control algorithm to precisely regulate the pressure of the injection tubing in a closed loop. It dynamically sets a target pressure range that matches the patient's hemodynamic state and drug characteristics, and automatically adjusts the drive motor speed based on real-time feedback, so that the tubing pressure is always maintained within the target range, which significantly reduces the risk of complications caused by pressure fluctuations. This invention, by setting up a multi-dimensional anomaly detection model, comprehensively analyzes multi-dimensional parameters such as flow rate, pressure, and equipment status, and can accurately identify abnormal situations such as pipeline blockage, needle detachment, and leakage. It also achieves timely detection and rapid response to anomalies through a three-level early warning mechanism and wireless communication unit, effectively making up for the problem of delayed alarm response in the prior art. This invention, by setting up a medical-grade wireless communication module, supports two-way data interaction with the central monitoring system, realizing centralized management and remote monitoring of multiple injection devices, improving the overall informatization level and diagnostic efficiency of the intensive care unit, and providing a technical foundation for building a smart intensive care system. Attached Figure Description

[0013] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a schematic block diagram of the intelligent and precise injection system for vasoactive drugs in cardiology as described in this invention; Figure 2 This is a schematic diagram of the core principle framework of the pressure closed-loop precise control based on the adaptive PID control algorithm in this invention. Detailed Implementation Example 1

[0015] This invention relates to an intelligent and precise injection system for vasoactive drugs in cardiology, specifically to an infusion device and its control method for vasoactive drugs used in clinical cardiology. Please refer to the appendix. Figure 1 and attached Figure 2 The present invention will be described in detail below with reference to the specific embodiments.

[0016] According to a specific embodiment of the present invention, the overall architecture of the intelligent and precise injection system for vasoactive drugs in cardiology comprises eight core functional modules: a data acquisition unit, a flow monitoring unit, a pressure control unit, an anomaly warning unit, a wireless communication unit, a control decision unit, a parameter self-calibration module, and a battery emergency module. These functional modules interact with each other and transmit control signals via an internal bus, forming a complete closed-loop control system. The specific structure and working principle of each functional module are described in detail below.

[0017] 1. Data Acquisition Unit The data acquisition unit is the core sensing element of the entire intelligent injection system, responsible for collecting various parameter signals within the injection pipeline, providing fundamental data support for the system's intelligent decision-making and control. Please refer to the appendix. Figure 1 The data acquisition unit includes a high-precision MEMS pressure sensor, a photoelectric liquid level sensor, a multi-channel signal conditioning circuit, and an analog-to-digital conversion module.

[0018] A high-precision MEMS pressure sensor is positioned at a critical location in the injection tubing to acquire real-time liquid pressure signals within the tubing. This MEMS pressure sensor utilizes a medical-grade silicon piezoresistive sensing element, exhibiting excellent biocompatibility and chemical resistance, maintaining stable sensing performance in the specific chemical environment of vasoactive drugs. The MEMS pressure sensor's sampling frequency is set to 100Hz, meaning it acquires pressure data every 10 milliseconds, capturing instantaneous pressure changes during injection and providing a high-resolution pressure feedback signal to the pressure control unit. The sensor's measurement range is set to 0 to 300 mmHg, covering the entire pressure range potentially involved in the infusion of vasoactive drugs in cardiology, with a measurement accuracy better than ±0.5%FS.

[0019] A photoelectric liquid level sensor is positioned at an appropriate location within the medication container to monitor the remaining medication level. With a resolution of 0.1 mL, this sensor can accurately detect minute changes in the medication level, providing real-time data on the remaining medication volume to the anomaly warning unit. When the remaining medication level falls below a preset safety threshold, the system can issue an early warning, reminding medical staff to replace the medication promptly and preventing interruptions in the injection process due to depletion of the medication.

[0020] The multi-channel signal conditioning circuit is responsible for amplifying, filtering, and linearizing the raw signals output from the MEMS pressure sensor and photoelectric level sensor. The amplification circuit adopts an instrumentation amplifier architecture to amplify the weak sensor signal to the effective input range of the analog-to-digital converter module; the filtering circuit adopts a low-pass filter design with a cutoff frequency set to 50Hz to effectively suppress high-frequency noise interference; the linearization module compensates and corrects the nonlinear output of the sensor through a lookup table method or a polynomial fitting method.

[0021] The analog-to-digital converter (ADC) employs a multi-channel synchronous sampling architecture to convert the conditioned analog signal into a digital signal. The ADC has a resolution of 24 bits and an effective bit depth of at least 20 bits to ensure the high accuracy requirements for pressure and level measurements. The converted digital signal is transmitted via an internal bus to the data fusion module of the control decision unit for further processing.

[0022] The data acquisition unit also integrates environmental parameter sensors to collect environmental parameter signals such as ambient temperature, humidity, and atmospheric pressure. This environmental parameter data is transmitted to the dynamic compensation algorithm module of the flow monitoring unit for ambient temperature compensation correction of the flow measurement results. The ambient temperature sensor's measurement range is set to 0 to 50 degrees Celsius, with an accuracy better than ±0.5 degrees Celsius.

[0023] 2. Flow monitoring unit The flow monitoring unit is used to detect the actual flow rate in the injection line in real time and is a key feedback link for achieving accurate injection. Please refer to the appendix. Figure 1 The flow monitoring unit includes a microfluidic sensor, a dynamic compensation algorithm module, and a flow signal processing circuit.

[0024] The microfluidic sensor is positioned at the outlet end of the infusion line to directly measure the instantaneous flow rate of the drug solution. The microfluidic sensor employs a thermal microfluidic measurement principle, utilizing the quantitative relationship between the heat carried away by the fluid as it flows through a heating element and the flow rate. This measurement principle offers advantages such as fast response, high measurement accuracy, and no moving parts, making it suitable for high-precision measurement of minute fluid volumes. The microfluidic sensor's range is set to 0 to 50 ml / h, with a resolution of 0.01 ml / h, meeting the precise monitoring requirements for micro-infusion of vasoactive drugs. The microfluidic sensor's response time is set to within 100 milliseconds, enabling real-time reflection of instantaneous changes in flow rate.

[0025] The dynamic compensation algorithm module is the core processing unit of the flow monitoring unit. It is responsible for compensating and correcting the raw flow data obtained from the microfluidic sensor, eliminating measurement errors caused by various interference factors. This module performs comprehensive compensation calculations based on the mechanical characteristic parameters of the injection pump, the viscosity parameters of the liquid, and the ambient temperature parameters.

[0026] The dynamic compensation algorithm module employs the following specific compensation strategy: First, a mapping model is established between the mechanical characteristic parameters of the injection pump and the flow deviation. Different injection pumps exhibit differences in mechanical characteristics, including factors such as motor speed accuracy, gear transmission efficiency, and piston sealing. These factors can lead to deviations in the actual flow output under the same drive signal. The system pre-calibrates the mechanical characteristic curves of each injection pump, establishing a database of the correspondence between motor speed and theoretical flow rate. During actual operation, the theoretical flow rate value is obtained by looking up the table based on the actual speed signal of the drive motor, thereby eliminating the flow deviation introduced by differences in pump characteristics.

[0027] Secondly, the flow rate variation caused by viscosity is corrected based on the drug solution viscosity parameters. Vascular-active drugs have varying viscosities, and the actual flow rate differs significantly from the theoretical flow rate when infusing solutions of different viscosities using the same pump. The system has a built-in database of viscosity parameters for common vasoactive drugs. Medical staff input the type of drug being used through the human-machine interface, and the system automatically retrieves the corresponding viscosity parameters. Combined with the measured flow rate values ​​from the microfluidic sensor, a viscosity compensation algorithm is used to calculate the corrected actual flow rate. The compensation algorithm is based on the fluid dynamics principle of Poiseuille's law, considering factors such as pipe diameter, liquid viscosity, and pressure gradient, to establish a quantitative relationship model between viscosity and flow rate deviation rate.

[0028] Third, the system corrects for measurement errors caused by thermal expansion and contraction based on ambient temperature parameters. Changes in ambient temperature can cause slight variations in pipeline materials, drug density, and sensor characteristics. Although the impact is small on a single occasion, these variations can accumulate into considerable measurement errors over long-term micro-infusion. The system corrects the flow measurement results based on the actual temperature values ​​collected by the ambient temperature sensor using a temperature compensation algorithm. The compensation algorithm is based on the material's thermal expansion coefficient and the fluid state equation, establishing a correction coefficient table for temperature and measurement errors.

[0029] Finally, the three types of corrections are fused using a multiple linear regression algorithm to obtain the final compensation coefficients. The compensation accuracy target of the dynamic compensation algorithm module is to ensure that the system infusion accuracy error does not exceed 2%, that is, the relative error between the actual infusion volume and the target infusion volume is controlled within 2%. The update frequency of the compensation operation is set to 10Hz, synchronized with the update frequency of the pressure control loop.

[0030] The flow signal processing circuit further processes the compensated flow data output by the dynamic compensation algorithm module, including digital filtering, outlier removal, and flow accumulation calculation. Digital filtering employs a Kalman filter algorithm to effectively suppress random noise in the flow signal; the outlier removal module sets a reasonable physical confidence interval to automatically filter out outliers caused by transient sensor interference; and the flow accumulation calculation module integrates the instantaneous flow rate over time to obtain cumulative infusion data, providing medical staff with accurate records of total medication usage.

[0031] The output signal of the flow monitoring unit is connected to the control decision unit to provide real-time flow feedback data. The output data includes information such as the compensated instantaneous flow rate, cumulative infusion volume, flow deviation rate, and flow anomaly flag.

[0032] 3. Pressure control unit The pressure control unit is used for closed-loop precise regulation of the pressure within the injection tubing, and is a core control component ensuring safe infusion for patients. Please refer to the appendix. Figure 2 The pressure control unit includes an adaptive PID control algorithm module, a pressure target setting module, a pressure signal processing circuit, and a motor drive circuit.

[0033] The adaptive PID control algorithm module is the core control unit of the pressure control unit. It is responsible for automatically adjusting the speed of the drive motor based on the deviation between the real-time collected pressure signal and the target pressure range, ensuring that the pipeline pressure remains within the target range. This module employs an adaptive control strategy, dynamically adjusting control parameters according to changes in the characteristics of the controlled object to achieve optimal control performance.

[0034] The adaptive PID control algorithm module employs the following specific control strategies: First, multiple sets of PID control parameters are preset based on the patient's hemodynamic state and drug characteristics. Different patients exhibit varying sensitivities to vasoactive drugs, and the same patient's response to medication can change at different stages of their condition. The system includes pre-set PID parameters for various common clinical scenarios, including parameter templates corresponding to different conditions such as hypertensive emergencies, shock, and heart failure. Before initiating the injection, medical staff select the corresponding clinical scenario through the human-machine interface, and the system automatically loads the matching PID parameter set.

[0035] Secondly, the system monitors the response characteristics of the controlled object in real time and dynamically selects the optimal PID parameter combination. Through an online identification algorithm, the system estimates the transfer function parameters of the controlled object in real time, including object gain, time constant, and delay time. Based on the estimated object characteristic parameters, the algorithm dynamically selects the parameter combination closest to the current characteristics from a preset parameter set, achieving online optimization of the control parameters. The parameter selection algorithm uses a weighted Euclidean distance criterion to calculate the similarity between the current object characteristics and the object characteristic models corresponding to each preset parameter set, selecting the parameter combination with the highest similarity as the current control parameters.

[0036] Third, when the patient's condition changes significantly, the PID parameters are automatically adjusted through a learning algorithm to adapt to the new control requirements. The system employs an adaptive law based on gradient descent, dynamically adjusting the PID parameter values ​​according to control performance indicators such as overshoot, steady-state error, and settling time. The learning algorithm progressively optimizes the control parameters while ensuring system stability, enabling continuous improvement in control performance over time. Parameter adjustment uses a small-step strategy, limiting the magnitude of each adjustment to a preset range to avoid system oscillations caused by drastic changes in control parameters.

[0037] The pressure target setting module dynamically sets the target pressure range based on the patient's current hemodynamic status and the pharmacokinetic characteristics of the vasoactive drugs being used. This module receives real-time vital sign data from the data acquisition unit, including parameters such as blood pressure and heart rate, and automatically calculates the corresponding target injection pressure value based on the target blood pressure value set in the doctor's order. The target pressure range of the pressure control unit is set within ±10% of the injection pressure value corresponding to the patient's target blood pressure. For example, if the target blood pressure is 120 mmHg, the target pressure range is set to 108 to 132 mmHg. The target pressure range can be dynamically adjusted according to changes in the patient's condition. When the patient's blood pressure fluctuates significantly, the system automatically updates the target pressure range to ensure that the pressure control strategy matches the patient's actual needs.

[0038] The pressure signal processing circuit filters and processes the raw pressure data output by the data acquisition unit, including median filtering, moving average filtering, and boundary judgment. Median filtering effectively suppresses impulse noise in the pressure signal; moving average filtering smooths short-term fluctuations in the pressure signal; and the boundary judgment module detects whether the pressure exceeds the safe range, triggering an emergency handling procedure if it does.

[0039] The motor drive circuit drives the DC motor of the injection pump according to the control commands output by the adaptive PID control algorithm module. The motor drive circuit adopts an H-bridge power amplifier architecture, supporting forward and reverse rotation control and speed regulation. The drive circuit receives the speed setpoint from the control decision unit and adjusts the average motor voltage using pulse width modulation technology to achieve precise speed control. The motor drive circuit also integrates current detection and overcurrent protection functions; when the motor current exceeds the safety threshold, it automatically cuts off the drive signal and reports the fault to the control decision unit.

[0040] Please refer to the attached document. Figure 2 The core control equation of the adaptive PID control algorithm can be expressed as:

[0041] in, This represents the control quantity output by the controller, i.e., the speed setpoint of the drive motor; This indicates the pressure deviation at the current moment, which is the difference between the measured pressure and the midpoint of the target pressure range; , and These represent the proportional coefficient, integral coefficient, and derivative coefficient, respectively, which are dynamically adjusted according to an adaptive algorithm. The control quantity acts on the drive motor through the motor drive circuit, and the drive motor drives the piston or gear mechanism of the injection pump to achieve precise injection of the drug solution.

[0042] The output signal of the pressure control unit is connected to the drive circuit of the drive motor to form a closed-loop control circuit. The update frequency of the control circuit is set to 100Hz to match the pressure sampling frequency, ensuring timely control response.

[0043] 4. Anomaly Early Warning Unit The abnormality warning unit is used to provide timely warnings of abnormal situations during the injection process, and is an important protective measure to ensure patient safety. Please refer to the appendix. Figure 1 The anomaly warning unit includes a multi-dimensional anomaly detection model, a warning execution module, and an alarm drive circuit.

[0044] The multi-dimensional anomaly detection model is the core analysis unit of the anomaly early warning unit. It is responsible for receiving output data from the flow monitoring unit and pressure control unit in real time, and comprehensively analyzing injection pressure, flow deviation rate, remaining liquid volume, and equipment operating status. This model uses multi-dimensional feature extraction and pattern recognition technology to accurately identify various anomalies occurring during the injection process.

[0045] The multi-dimensional anomaly detection model employs the following specific detection strategies: First, it defines tubing blockage as a combination of pressure consistently exceeding a set threshold and flow consistently falling below a set threshold. When the injection tubing becomes blocked, tubing resistance increases sharply, flow significantly decreases under the same driving conditions, and pressure rises simultaneously. The system sets upper and lower thresholds for pressure and flow. When the combined condition of pressure continuously exceeding the upper threshold and flow continuously falling below the lower threshold is met, it is determined to be a tubing blockage anomaly. The judgment condition needs to last for a certain period of time, such as 5 seconds, to confirm the anomaly and avoid false alarms caused by brief interference. Second, it defines needle detachment as a combination of a sudden drop in pressure and a simultaneous sudden drop in flow. When the needle is detached from the blood vessel, the fluid directly enters the interstitial space or outside the body, causing an instantaneous drop in tubing pressure and a corresponding decrease in flow. The system calculates the rate of change of pressure and flow. When both show negative changes exceeding the threshold simultaneously, it is determined to be a needle detachment anomaly. The needle detachment judgment adopts a rapid response strategy, triggering an early warning immediately upon detection of the abnormal feature, without waiting for a certain duration. Third, it defines leakage as a combination of persistently low flow and pressure within the normal range. Drip refers to the slow seepage of medication from tubing or needle connections. This does not cause significant pressure changes, but results in the actual infused medication volume being less than the set value. The system sets a lower flow limit threshold; when the flow rate remains below this threshold while the pressure remains within the normal range, it is considered a drip abnormality. Fourth, characteristic thresholds are set for each type of abnormality, establishing a mapping relationship between abnormality type and warning level. The system has a built-in abnormality feature database containing characteristic descriptions and discrimination thresholds for various abnormalities. The discrimination thresholds can be adjusted according to the patient's specific situation; for example, for patients with hypotension, the lower flow limit threshold can be set even lower to accommodate lower physiological flow requirements.

[0046] The abnormal warning unit is designed with a three-level warning mechanism, corresponding to warnings requiring attention, alarms requiring action, and emergency alarms requiring immediate intervention. The first level of warning corresponds to the attention level, triggered when a minor abnormality is detected, such as the remaining medication level falling below 30%, with an alarm sound and interface display to alert medical staff. The second level of alarm corresponds to the action level, triggered when a moderate abnormality is detected, such as tubing blockage or leakage, with a strong alarm sound and a clear interface display, while simultaneously sending an alarm message to the central monitoring system via wireless communication. The third level of alarm corresponds to the emergency level, triggered when a severe abnormality is detected, such as needle dislodgement or a sudden drop in pressure, with a strong alarm sound and flashing light indicators, while simultaneously sending an emergency alarm message to the central monitoring system and mobile terminal devices, prompting medical staff to take immediate action.

[0047] The early warning execution module executes corresponding early warning actions based on the output of the multi-dimensional anomaly detection model. The early warning execution module includes alarm level determination logic, an alarm information generation module, and an alarm output control module. The alarm level determination logic determines which level of early warning to trigger based on the anomaly type and severity; the alarm information generation module generates alarm records containing information such as the anomaly type, occurrence time, and relevant parameter values; and the alarm output control module controls the execution of the alarm drive circuit and the wireless communication unit.

[0048] The alarm drive circuit is responsible for driving the audible and visual alarm device, including a speaker and indicator lights. The speaker outputs alarm sounds of different volumes and rhythms according to the alarm level; the indicator lights display light signals of different colors and flashing frequencies according to the alarm level. The first-level warning uses a soft warning sound and a green indicator light; the second-level alarm uses a louder alarm sound and a yellow indicator light; the third-level emergency alarm uses a strong alarm sound and a flashing red indicator light.

[0049] The output signal of the abnormality warning unit is also connected to the wireless communication unit to send alarm information to the central monitoring system. The alarm information is encapsulated in a standard medical device communication protocol format and includes fields such as device identifier, patient identifier, abnormality type, alarm level, occurrence time, and suggested handling measures.

[0050] 5. Wireless communication unit The wireless communication unit is used to enable data interaction with external devices and is a key module for achieving system networking and remote monitoring. Please refer to the appendix. Figure 1 The wireless communication unit includes a medical-grade wireless communication module, a data encryption module, a communication protocol stack, and an antenna system.

[0051] The medical-grade wireless communication module uses a wireless communication chip that complies with electromagnetic compatibility standards for medical devices, supporting low-power Bluetooth communication in the 2.4GHz band and medical-specific frequency band communication in the 868MHz band. This module possesses excellent anti-interference capabilities and low radiation characteristics, enabling stable operation in the complex electromagnetic environment of the intensive care unit. The wireless communication module's transmit power is set at 10 milliwatts, and its coverage distance meets the needs of centralized monitoring of multiple beds in the intensive care unit.

[0052] The wireless communication unit supports a two-way data transmission protocol, enabling real-time data interaction with the central monitoring system. The wireless communication unit transmits collected real-time flow, pressure, and equipment status data to the central monitoring system at a frequency of once every 5 seconds, ensuring that the monitoring end can promptly obtain the latest injection status data. Simultaneously, the wireless communication unit receives parameter adjustment instructions and control commands from the central monitoring system, including instructions for adjusting target flow, modifying target pressure range, and controlling injection start / stop. After verification, the received instructions are transmitted to the control decision unit for execution.

[0053] The wireless communication unit is also used to push alarm information generated by the abnormal warning unit to the mobile terminal devices of medical staff. When a second-level alarm or a third-level emergency alarm occurs, the system sends an alarm push message to the pre-bound mobile terminal device through the wireless communication unit. The mobile terminal device includes mobile computing devices such as smartphones and tablets, which are equipped with a dedicated monitoring application that can receive and display alarm information, and provide feedback interfaces for confirmation and processing.

[0054] The wireless communication unit supports the following communication protocols: First, it supports data interface with the hospital information system to achieve automatic synchronization of patient information and medication orders. The system communicates with the hospital information system through the HL7 standard interface to obtain data such as basic patient information and medication order content, reducing manual data entry work for medical staff. Second, it supports a multi-device centralized management protocol with the central monitoring system to achieve unified monitoring and coordinated control of multiple injection devices. The system adopts a device discovery protocol and a status reporting protocol, supporting centralized management of up to 32 injection devices by the central monitoring system. Third, it supports point-to-point communication with mobile terminal devices to achieve real-time push of alarm information. Point-to-point communication uses a simplified protocol stack to reduce communication latency and ensure the real-time nature of alarm information. Fourth, it adopts a data encryption transmission mechanism to ensure patient privacy and the security of medical data. The encryption algorithm adopts the AES-256 standard to encrypt transmitted data end-to-end, preventing data theft or tampering.

[0055] The antenna system employs a built-in antenna design, using a planar inverted-F antenna integrated within the device housing. The antenna system is optimized for the operating environment of medical devices, exhibiting omnidirectional radiation characteristics and stable impedance matching performance.

[0056] 6. Control Decision Unit The control and decision-making unit is used to comprehensively analyze the input data from each unit and generate injection control commands. It is the core scheduling and decision-making center of the entire intelligent injection system. Please refer to the appendix. Figure 1 The control and decision-making unit includes a data fusion module, a decision algorithm module, a status management module, and a security intervention module.

[0057] The data fusion module integrates the output data from the flow monitoring unit, pressure control unit, and anomaly early warning unit. It receives raw data from each functional module, performs data format unification, timestamp alignment, and data integrity verification. The module employs a multi-sensor data fusion algorithm to perform redundancy checks and consistency assessments on data from different sensors. When data inconsistencies or missing data are detected, the module uses default value substitution or predicted value imputation strategies to ensure data flow continuity. The fused integrated data is then transmitted to the decision algorithm module as input for decision analysis.

[0058] The decision-making algorithm module, based on the fused multidimensional data stream, uses fuzzy logic algorithms and threshold determination strategies to calculate the optimal injection control parameters. The fuzzy logic algorithm maps continuous variables such as flow rate deviation, pressure deviation, and remaining drug volume into discrete fuzzy linguistic variables, such as "too high," "normal," and "too low," and infers control decisions based on a pre-set fuzzy rule base. The threshold determination strategy sets hard limits on key parameters, forcibly executing safety intervention actions when parameters exceed the safety threshold. The decision-making algorithm module combines the advantages of both fuzzy logic and threshold determination strategies, enabling both smooth parameter adjustments and ensuring safe hard constraints.

[0059] The control decision-making unit adopts a hierarchical control architecture, comprising three levels: strategic, tactical, and operational. The strategic level formulates infusion strategies and pressure control targets based on the patient's overall condition and long-term medication regimen. It receives long-term medical orders from healthcare professionals via a human-machine interface, including target blood pressure range, medication type, and infusion duration, and formulates macro-level infusion strategies. The tactical level dynamically adjusts infusion parameters based on the patient's real-time vital signs and medication response. It analyzes flow and pressure data in real time and adjusts the infusion rate and target pressure range according to the patient's current physiological response. The operational level directly controls the drive motor's speed and injection volume to achieve precise drug infusion. It receives parameter targets from the tactical level and outputs motor drive signals through a closed-loop control algorithm.

[0060] The control decision-making unit coordinates its various levels through a state machine to ensure the timeliness and consistency of decisions. The state machine includes five main states: running, paused, calibration, alarm, and fault. The running state corresponds to the normal injection operation mode; the paused state corresponds to the medical staff pausing the injection; the calibration state corresponds to the parameter self-calibration module executing the calibration process; the alarm state corresponds to the response mode when an abnormality is detected; and the fault state corresponds to the protection mode when a hardware failure occurs. The state machine transitions between states based on input events and triggers corresponding processing actions.

[0061] The safety intervention module automatically executes preset safety intervention strategies upon detecting an abnormal warning signal. When the alarm flag output by the abnormal warning unit is set, the safety intervention module performs corresponding intervention actions based on the type and severity of the abnormality. For mild abnormalities, the safety intervention module performs parameter adjustment interventions, such as reducing the injection rate or adjusting the target pressure range; for moderate abnormalities, the safety intervention module performs injection suspension interventions, halting drug infusion and awaiting medical personnel intervention; for severe abnormalities, the safety intervention module performs emergency shutdown interventions, immediately stopping the injection and triggering an emergency alarm. The specific parameters of the safety intervention strategy can be configured according to clinical needs.

[0062] The output signals of the control decision unit include the drive motor speed setpoint, injection status indication, and alarm trigger signal. The drive motor speed setpoint is transmitted to the motor drive circuit of the pressure control unit via an internal bus; the injection status indication displays the current operating status through a human-machine interface; and the alarm trigger signal is transmitted to the early warning execution module of the abnormal early warning unit.

[0063] 7. Parameter self-calibration module This invention also includes a parameter self-calibration module for performing a self-check and calibration of the system before each injection, ensuring the accuracy of system measurement and control. Please refer to the appendix. Figure 1 The parameter self-calibration module includes a flow calibration process, a pressure calibration process, a calibration data management module, and a self-test diagnostic module.

[0064] The flow calibration process uses a standard metering pump to calibrate the microfluidic sensor, establishing a correspondence between the sensor output and the actual flow rate. During calibration, the system drives the push pump at a preset standard speed, simultaneously recording the actual output flow rate of the standard metering pump and the measured value of the microfluidic sensor. Using a multi-point calibration method, calibration data from at least five different flow points are collected, and the sensor characteristic curve equation is fitted. The calibration curve includes zero-point offset, sensitivity coefficient, and nonlinearity compensation parameters. Calibration data is stored in the system's non-volatile memory and automatically loaded upon each startup.

[0065] The pressure calibration process calibrates the pressure sensor using a standard pressure source to ensure the accuracy of pressure measurements. During calibration, the system connects to a standard pressure source to generate a known standard pressure value, while simultaneously recording the measured values ​​from the MEMS pressure sensor. A multi-point calibration method is used to collect calibration data from at least three standard pressure points, and the sensor characteristic curve equation is obtained by fitting the data. Calibration parameters include zero-point calibration values, sensitivity calibration coefficients, and temperature drift compensation coefficients. The pressure calibration data is also stored in non-volatile memory.

[0066] The calibration data management module manages calibration parameters and calibration history. It records the date and time of each calibration, the calibration results, and the information of the personnel performing the calibration, supporting the querying and tracing of calibration records. The module also monitors the calibration validity period and reminds medical staff to recalibrate before the calibration cycle expires. The default calibration cycle is set to 30 days.

[0067] The self-test diagnostic module automatically executes a self-test program each time the system starts, performing diagnostic tests on key functional modules. The self-test items include sensor function testing, drive circuit testing, communication function testing, and storage function testing. The self-test diagnostic module generates a self-test report, recording the pass / fail status of each test item. For items that fail, a fault flag is marked and a corresponding fault record is generated.

[0068] 8. Emergency Storage Module This invention also includes an emergency power storage module to maintain continuous system operation during external power outages, ensuring the continuity of drug infusion in intensive care settings. Please refer to the appendix. Figure 1 The emergency energy storage module includes a lithium battery pack, a power switching circuit, a power monitoring module, and a power management unit.

[0069] The emergency power storage module uses a medical-grade lithium battery pack as a backup power source. The lithium battery pack uses lithium iron phosphate cells, which feature high energy density, long cycle life, and good safety characteristics. The capacity of the lithium battery pack is designed to meet the power requirements for at least 4 hours of continuous drug administration. Based on typical vasoactive drug administration power, approximately 40 Wh of energy storage is required for 4 hours of continuous operation. The lithium battery pack is equipped with independent protection circuitry, including overcharge protection, over-discharge protection, overcurrent protection, and short-circuit protection.

[0070] The power switching circuit enables seamless switching between external power and the lithium battery pack. When the external power supply is normal, the power switching circuit converts the external power to the DC voltage required by the system while charging the lithium battery pack. When the external power supply is interrupted, the power switching circuit switches to the lithium battery pack for power within milliseconds, ensuring uninterrupted system operation. The power switching process has no perceptible impact on system operation and requires no restart or reinitialization.

[0071] The power monitoring module monitors the remaining power of the lithium battery pack in real time. Monitored parameters include battery voltage, battery current, cumulative discharge, and battery temperature. The module uses a Kalman filter algorithm to smooth the measured values ​​and estimate the current battery power and remaining usable time. The power estimation results are displayed through a human-machine interface and reported to the control decision unit.

[0072] The power management unit coordinates the operation strategy of the emergency power storage module. When external power is interrupted, the system automatically switches to the emergency power storage module and sends a power failure alarm to the central monitoring system, alerting medical staff to the abnormal external power supply. When the battery level drops below 20%, the system automatically reduces some non-critical functions to extend operating time. Function reduction strategies include reducing the data transmission frequency of wireless communication, turning off the display backlight, and turning off unnecessary indicator lights. The system prioritizes the continuous operation of the injection control function to ensure patient medication safety.

[0073] Based on the coordinated operation of the aforementioned functional modules, the intelligent and precise injection system for vasoactive drugs in cardiology of this invention can achieve high-precision control of vasoactive drug infusion. The system acquires pressure, flow rate, liquid level, and environmental parameters in real time through a data acquisition unit; dynamically compensates for the measured flow rate through a flow monitoring unit, controlling the infusion accuracy error within 2%; uses an adaptive PID algorithm in the pressure control unit to perform closed-loop regulation of the pipeline pressure, ensuring the pressure is always maintained within the target range; provides three-level early warning for abnormalities such as pipeline blockage, needle dislodgement, and leakage through an anomaly early warning unit; achieves two-way data interaction with the central monitoring system through a wireless communication unit; comprehensively analyzes the data from each unit and generates optimal control commands through a control decision unit; performs self-calibration before each use through a parameter self-calibration module; and maintains continuous operation when the external power supply is interrupted through a power storage emergency module. Example 2

[0074] Building upon Example 1, this embodiment of the invention provides an intelligent injection system optimized for specific clinical scenarios. This embodiment focuses on a specially optimized design for neonatal intensive care.

[0075] To address the specific needs of neonatal vasoactive drug infusion, this embodiment is optimized based on Embodiment 1 as follows: Regarding the data acquisition unit, the range of the MEMS pressure sensor was adjusted to 0 to 100 mmHg, better suited to the lower blood pressure range of newborns; simultaneously, the sampling frequency was increased to 200 Hz to capture faster hemodynamic changes in newborns. The resolution of the photoelectric liquid level sensor was improved to 0.05 mL, meeting the needs of precise medication measurement in newborns.

[0076] Regarding the flow monitoring unit, the range of the microfluidic sensor was adjusted to 0 to 10 ml / h, with a minimum resolution of 0.001 ml / h, meeting the high-precision requirements of neonatal micro-infusion. The dynamic compensation algorithm module incorporates a low-flow compensation algorithm tailored to the characteristics of neonatal medication, addressing the nonlinear characteristics of the microfluidic sensor in extremely low flow ranges.

[0077] Regarding the pressure control unit, the setting accuracy of the target pressure range has been improved to within ±5%, and a more refined pressure control strategy has been adopted to adapt to the fragile hemodynamic state of newborns. The parameter adjustment of the adaptive PID control algorithm adopts a more conservative strategy to avoid adverse effects on newborns caused by drastic changes in control parameters.

[0078] Regarding the abnormality warning unit, the discrimination threshold of the abnormality detection model was optimized for the characteristics of neonatal patients. The discrimination threshold for tubing blockage was lowered to adapt to the lower physiological parameter range of neonates; a more sensitive detection algorithm was used to detect needle dislodgement, because the risk of needle dislodgement is higher and more difficult to detect in neonates.

[0079] Regarding the wireless communication unit, support for a dedicated communication protocol with neonatal monitoring equipment has been added to achieve data synchronization with the neonatal monitor and acquire real-time vital signs data such as neonatal heart rate, respiration, and transcutaneous oxygen saturation, providing richer reference information for control decisions.

[0080] Regarding the emergency power storage module, the battery capacity has been adjusted to meet the power requirements for at least 8 hours of continuous injection, adapting to the possibility of prolonged power outages or transfers in the neonatal intensive care unit.

[0081] Through the above-mentioned optimized configuration, the intelligent injection system in this embodiment can better meet the special clinical needs of neonatal intensive care and provide a more accurate and safer solution for vasoactive drug infusion.

Claims

1. A smart and precise injection system for vasoactive drugs in cardiology, characterized in that, The system includes a data acquisition unit, a flow monitoring unit, a pressure control unit, an anomaly warning unit, a wireless communication unit, and a control decision unit. The data acquisition unit collects pressure signals, drive motor speed signals, drug level signals, and environmental parameter signals within the injection tubing, and integrates a high-precision MEMS pressure sensor and a photoelectric level sensor. The flow monitoring unit detects the actual flow rate in the injection tubing in real time. It includes a microfluidic sensor and a dynamic compensation algorithm module, which performs compensation calculations based on the mechanical characteristics of the injection pump, drug viscosity parameters, and ambient temperature parameters to eliminate flow deviations caused by differences in pump characteristics and drug properties. The pressure control unit performs closed-loop precise control of the pressure within the injection tubing. It includes an adaptive PID control algorithm module and a pressure target setting module, which dynamically sets the target pressure range based on the patient's hemodynamic state and the pharmacokinetic characteristics of the vasoactive drug used. It also automatically adjusts the drive motor speed based on the deviation between the real-time collected pressure signal and the target pressure range, ensuring the tubing pressure remains within the target range. The anomaly warning unit provides timely warnings of abnormal situations during the injection process, and includes multi-dimensional... The anomaly detection model and early warning execution module are used to receive the output data from the flow monitoring unit and pressure control unit in real time and comprehensively analyze the injection pressure, flow deviation rate, remaining drug volume, and equipment operating status. Based on preset anomaly discrimination thresholds, it identifies anomaly types such as tubing blockage, needle detachment, leakage, sudden pressure drop, and sudden pressure rise, and triggers corresponding audible and visual alarm signals. The wireless communication unit is used to realize data interaction with external devices. It adopts a medical-grade wireless communication module, supports a two-way data transmission protocol, and sends real-time flow, pressure, and equipment status data to the central monitoring system and receives parameter adjustment instructions and control commands. Simultaneously, it pushes alarm information to the mobile terminal devices of medical personnel. The control decision unit is used to comprehensively analyze the input data from each unit and generate injection control commands. It includes a data fusion module and a decision algorithm module, which comprehensively processes the output data from the flow monitoring unit, pressure control unit, and anomaly early warning unit. Based on the fused multidimensional data stream, it uses fuzzy logic algorithms and threshold judgment strategies to calculate the optimal injection control parameters and send control commands to the drive motor. Simultaneously, it automatically executes preset safety intervention strategies when an anomaly early warning signal is detected.

2. The intelligent and precise injection system for vasoactive drugs in cardiology according to claim 1, characterized in that, The dynamic compensation algorithm module adopts the following compensation strategy: establishing a mapping relationship model between the mechanical characteristic parameters of the injection pump and the flow deviation; correcting the flow change caused by viscosity according to the viscosity parameter of the drug solution; correcting the metering error caused by thermal expansion and contraction according to the ambient temperature parameter; and fusing the above corrections through a multiple linear regression algorithm to obtain the final compensation coefficient. The compensation accuracy target of the dynamic compensation algorithm module is to ensure that the system infusion accuracy error does not exceed 2%.

3. The intelligent and precise injection system for vasoactive drugs in cardiology according to claim 1, characterized in that, The sampling frequency of the MEMS pressure sensor is set to 100Hz, and the resolution of the photoelectric liquid level sensor is set to 0.1mL.

4. The intelligent and precise injection system for vasoactive drugs in cardiology according to claim 1, characterized in that, The adaptive PID control algorithm module adopts the following control strategy: multiple sets of PID control parameters are preset according to the patient's hemodynamic state and drug characteristics; the response characteristics of the controlled object are monitored in real time, and the optimal combination of PID parameters is dynamically selected; when the patient's state changes significantly, the PID parameters are automatically adjusted through a learning algorithm to adapt to the new control requirements; the target pressure range of the pressure control unit is set to within ±10% of the injection pressure value corresponding to the patient's target blood pressure.

5. The intelligent and precise injection system for vasoactive drugs in cardiology according to claim 1, characterized in that, The multi-dimensional anomaly detection model adopts the following detection strategy: defining pipeline blockage as a combination of pressure continuously exceeding a set threshold and flow continuously falling below a set threshold; defining needle detachment as a combination of a sudden drop in pressure and a sudden drop in flow simultaneously; defining dripping as a combination of a continuously low flow and pressure within the normal range; setting feature thresholds for each anomaly type and establishing a mapping relationship between anomaly type and warning level.

6. The intelligent and precise injection system for vasoactive drugs in cardiology according to claim 5, characterized in that, The early warning execution module is designed with a three-level early warning mechanism, corresponding to early warnings that require attention, alarms that require processing, and emergency alarms that require urgent intervention.

7. The intelligent and precise injection system for vasoactive drugs in cardiology according to claim 1, characterized in that, The wireless communication unit supports the following communication protocols: it supports data interface with the hospital information system to achieve automatic synchronization of patient information and medication orders; it supports a multi-device centralized management protocol with the central monitoring system to achieve unified monitoring and coordinated control of multiple injection devices; it supports point-to-point communication with mobile terminal devices to achieve real-time push of alarm information; and it adopts a data encryption transmission mechanism to ensure the security of patient privacy and medical data.

8. The intelligent and precise injection system for vasoactive drugs in cardiology according to claim 1, characterized in that, The control decision unit adopts a hierarchical control architecture, including a strategic layer, a tactical layer, and an operational layer. The strategic layer formulates infusion strategies and pressure control targets based on the patient's overall condition and long-term medication regimen. The tactical layer dynamically adjusts infusion parameters based on the patient's current real-time vital signs and medication response. The operational layer directly controls the rotational speed and injection volume of the drive motor to achieve precise drug infusion. The various levels of the control decision unit are coordinated through a state machine to ensure the timeliness and consistency of decisions.

9. The intelligent and precise injection system for vasoactive drugs in cardiology according to claim 1, characterized in that, It also includes a parameter self-calibration module, which is used to perform self-checks and calibrations on the system before each injection begins; the parameter self-calibration module includes a flow calibration process and a pressure calibration process; The flow calibration process calibrates the microflow sensor using a standard metering pump to establish the correspondence between the sensor output and the actual flow rate. The pressure calibration process calibrates the pressure sensor using a standard pressure source to ensure the accuracy of pressure measurements; calibration data is stored in the system's non-volatile memory and is automatically loaded each time the system is started.

10. The intelligent and precise injection system for vasoactive drugs in cardiology according to claim 1, characterized in that, It also includes an emergency power storage module to maintain the continuous operation of the system when the external power supply is interrupted; the emergency power storage module uses a lithium battery pack with a capacity set to meet the power requirements for at least 4 hours of continuous charging; when the external power supply is interrupted, the system automatically switches to the emergency power storage module for power supply and sends a power failure alarm to the central monitoring system; when the power is below 20%, the system automatically reduces some non-critical functions to extend the operating time.

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