Platelet aggregation inhibitor

Abstract

This invention provides a digital twin-based system and method for predicting the risk of cerebrovascular diseases in high-altitude environments, belonging to the field of cerebrovascular disease risk simulation and prediction technology. The system includes: an equipment control module, an oxygen control module, and an oxygen-pressure coupling control module. First, the oxygen concentration monitoring strategy of the oxygen regulation equipment is dynamically optimized based on concentration accuracy parameters and environmental impact parameters. Then, gas regulation dynamic factors are monitored in real time, and the equipment control strategy of the oxygen regulation equipment is dynamically adjusted based on these factors and concentration accuracy assessment values. Finally, the wind speed is dynamically adjusted according to the monitored gas injection status parameters, oxygen regulation is triggered based on oxygen equilibrium time and pressure equilibrium time, and cerebrovascular disease risk is predicted based on the adjusted oxygen regulation equipment and the hypobaric chamber. The high-fidelity high-altitude environment simulation based on digital twins significantly improves the accuracy of the cerebrovascular disease risk prediction model.

Description

Technical Field

[0001] This invention relates to the field of cerebrovascular disease risk simulation and prediction technology, and in particular to a cerebrovascular disease risk prediction system and method based on digital twins in high-altitude environments. Background Technology

[0002] Digital twin technology constructs virtual models to simulate an individual's physiological responses in a high-altitude environment. By combining environmental factors such as climate, air pressure, and oxygen concentration, it dynamically predicts cerebrovascular health status. The high-altitude environment cerebrovascular disease risk prediction system based on digital twins integrates digital twin technology with the characteristics of the high-altitude environment. It aims to predict and assess the risk of cerebrovascular diseases in residents or those adapted to high altitudes by real-time monitoring and analysis of individual health data and environmental changes.

[0003] Existing cerebrovascular disease risk prediction systems mainly integrate plateau environmental characteristics with individual health data. They utilize sensors and monitoring equipment to collect environmental parameters and individual physiological data in real time, process the data through data analysis models, and combine the impact of the plateau environment on the human body to assess the individual's cerebrovascular health risk under different environmental conditions.

[0004] For example, the invention patent announcement CN118711822B, concerning a method and system for predicting the risk of cardiovascular and cerebrovascular diseases, includes: based on existing clinical research and medical guidelines, performing text mining and key information extraction to identify risk factors for cardiovascular and cerebrovascular diseases, and constructing a relationship mapping table to obtain a risk factor database. This invention, through the use of recursive feature elimination and adaptive reinforcement learning, performs weighted calculation of risk factors in a weight adjustment model, and combines gradient boosting trees to classify risk levels.

[0005] For example, the patent application CN118969297A discloses a method, system, and related equipment for predicting the risk of cardiovascular and cerebrovascular diseases based on multimodal data. This includes: performing a 5th-order tensor product operation on the feature matrices corresponding to each modality of each sample data to obtain a higher-order tensor; processing the higher-order tensor through a low-rank tensor network to obtain a reconstructed low-rank tensor; labeling the low-rank tensor corresponding to each sample data with a risk label; training a classifier using the constructed dataset to obtain a target model; and predicting the cardiovascular and cerebrovascular disease risk of the patient under test using the target model.

[0006] However, the above-mentioned technologies still have at least the following problems:

[0007] In existing technologies, when using digital twins to simulate the risk of cerebrovascular diseases in high-altitude environments, it is necessary to use a hypobaric chamber and oxygen regulation equipment to simultaneously regulate air pressure and oxygen content to simulate the high-altitude environment. However, during the regulation process, since gas mixing and uniform distribution take a certain amount of time, the adjustment of oxygen concentration may lag behind the change in air pressure, resulting in asynchronous regulation of the two. The instantaneous state deviates from the real high-altitude environment, and there is a problem of low reliability of the high-altitude environment simulation based on digital twins. Summary of the Invention

[0008] To address the aforementioned issues, this invention provides a digital twin-based system and method for predicting the risk of cerebrovascular diseases in high-altitude environments. This solves the problem that in existing technologies, when using digital twins to simulate the risk of cerebrovascular diseases in high-altitude environments, it is necessary to use a hypobaric chamber and oxygen regulation equipment to simultaneously control air pressure and oxygen content to simulate the high-altitude environment. However, during the regulation process, because gas mixing and uniform distribution require a certain amount of time, the adjustment of oxygen concentration may lag behind changes in air pressure, leading to asynchronous regulation and instantaneous deviation from the real high-altitude environment. This results in low reliability of the high-altitude environment simulation constructed based on digital twins. This invention achieves a simulation that more closely approximates the real high-altitude environment, improving the reliability of the simulation results.

[0009] To achieve the above-mentioned objectives, the present invention provides the following technical solution:

[0010] On one hand, a digital twin-based system for predicting the risk of cerebrovascular diseases in high-altitude environments is provided, comprising: an equipment control module, an oxygen control module, an oxygen-pressure coupling control module, and a risk prediction database. The equipment control module is used to monitor concentration accuracy parameters and environmental impact parameters in real time to obtain a concentration accuracy assessment value, and to dynamically optimize the oxygen concentration monitoring strategy of the oxygen regulation equipment based on the concentration accuracy assessment value. The concentration accuracy assessment value is used to quantify the accuracy of the oxygen regulation equipment in measuring oxygen concentration. The oxygen control module is used to monitor dynamic gas regulation factors in real time, and to dynamically adjust the equipment control strategy of the oxygen regulation equipment based on the dynamic gas regulation factors and the concentration accuracy assessment value. The oxygen-pressure coupling control module is used to dynamically adjust the wind speed according to the monitored gas injection status parameters, trigger oxygen regulation based on oxygen equilibrium time and pressure equilibrium time, and predict the risk of cerebrovascular diseases based on the adjusted oxygen regulation equipment and the hypobaric chamber.

[0011] On the other hand, a method for predicting the risk of cerebrovascular diseases in high-altitude environments based on digital twins is also provided, including the following steps: real-time monitoring of concentration accuracy parameters and environmental impact parameters to obtain concentration accuracy assessment values, and dynamic optimization of the oxygen concentration monitoring strategy of the oxygen regulating equipment based on the concentration accuracy assessment values, wherein the concentration accuracy assessment values ​​are used to quantify the accuracy of the oxygen regulating equipment in measuring oxygen concentration; real-time monitoring of gas regulation dynamic factors, and dynamic adjustment of the equipment control strategy of the oxygen regulating equipment based on the gas regulation dynamic factors and the concentration accuracy assessment values; dynamic adjustment of wind speed according to the monitored gas injection state parameters, triggering oxygen regulation based on oxygen balance time and pressure balance time, and predicting the risk of cerebrovascular diseases based on the adjusted oxygen regulating equipment and the hypobaric chamber.

[0012] One or more technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages:

[0013] 1. This invention provides a digital twin-based high-altitude environment cerebrovascular disease risk prediction system, thereby achieving precise monitoring and regulation of oxygen concentration and air pressure changes in the high-altitude environment. It then achieves the goal of ensuring the accuracy and stability of oxygen concentration by dynamically optimizing the oxygen regulation equipment strategy, and can adjust the gas regulation and equipment control strategies in real time to ensure the reliability of the high-altitude environment constructed based on digital twin. At the same time, it can precisely regulate wind speed and oxygen balance through the oxygen-pressure coupling regulation module.

[0014] 2. This invention dynamically optimizes the oxygen concentration monitoring strategy of oxygen regulating equipment by using concentration accuracy assessment values. Based on the rate of change of air pressure and the rate of change of oxygen concentration, it dynamically adjusts the calibration and measurement frequency of the oxygen regulating equipment, thereby automatically optimizing the working state of the equipment within different concentration accuracy assessment value ranges. This further ensures that the equipment accurately controls the oxygen concentration under stable conditions, improves the accuracy of equipment measurements, and thus improves the accuracy of digital twin simulation of plateau environments.

[0015] 3. This invention obtains a control accuracy assessment value by quantitatively analyzing the dynamic factors and concentration accuracy assessment values ​​of gas regulation, and dynamically adjusts and precisely controls the oxygen regulation equipment based on the control accuracy assessment value. This enables appropriate adjustment measures to be taken under different conditions, ensuring the stability of oxygen supply and the safety of subjects during digital twin simulation, thereby achieving precise control of oxygen flow and optimizing the performance and reliability of the equipment.

[0016] 4. This invention dynamically adjusts the wind speed according to the gas injection status parameters and triggers oxygen regulation in advance by combining the difference between oxygen balance time and pressure balance time, thereby ensuring the balance of gas concentration, volume and pressure in the low-pressure chamber, optimizing gas stability during the gas injection process, and thus ensuring the stability of oxygen concentration and the balance of pressure, maintaining the synchronization of oxygen and pressure in the process of predicting and regulating the risk of cerebrovascular diseases. Attached Figure Description

[0017] 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.

[0018] Figure 1 A schematic diagram of the structure of a plateau environment cerebrovascular disease risk prediction system based on digital twin provided in an embodiment of the present invention;

[0019] Figure 2 The graph shows the change in the control accuracy assessment value of the cerebrovascular disease risk prediction system based on plateau environment provided in this embodiment of the invention.

[0020] Figure 3 A flowchart of a method for predicting the risk of cerebrovascular diseases in high-altitude environments based on digital twins, provided in an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0022] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms “first,” “second,” and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Similarly, the terms “an,” “a,” or “the,” and similar terms do not indicate a quantity limitation, but rather indicate the presence of at least one. The terms “comprising,” “including,” or “including,” and similar terms mean that the element or object preceding the word encompasses the element or object listed following the word and its equivalents, without excluding other elements or objects. The terms “connected,” “linked,” or “connected,” and similar terms are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect.

[0023] It should be noted that the terms "up", "down", "left", "right", "front", and "back" used in this invention are only used to indicate relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0024] This invention provides a digital twin-based system for predicting the risk of cerebrovascular diseases in high-altitude environments. By triggering oxygen regulation based on oxygen balance time and air pressure balance time, it achieves synchronous control of oxygen content and air pressure.

[0025] like Figure 1As shown in the diagram, this invention provides a schematic diagram of a digital twin-based risk prediction system for cerebrovascular diseases in high-altitude environments, including an equipment control module, an oxygen control module, an oxygen-pressure coupling control module, and a risk prediction database. The equipment control module is used to monitor concentration accuracy parameters and environmental impact parameters in real time to obtain a concentration accuracy assessment value, and to dynamically optimize the oxygen concentration monitoring strategy of the oxygen regulating equipment based on the concentration accuracy assessment value. The concentration accuracy assessment value is used to quantify the accuracy of the oxygen regulating equipment in measuring oxygen concentration. The oxygen control module is used to monitor gas regulation dynamic factors in real time, and to dynamically adjust the equipment control strategy of the oxygen regulating equipment based on the gas regulation dynamic factors and the concentration accuracy assessment value. The oxygen-pressure coupling control module... The system dynamically adjusts the wind speed based on monitored gas injection parameters, triggers oxygen regulation based on oxygen and pressure equilibrium times, and simulates a high-altitude environment using the adjusted oxygen regulation equipment and a hypobaric chamber. It then monitors multidimensional physiological data of the subjects (such as cerebral blood flow, blood oxygen saturation, and metabolic levels) combined with the subjects' basic health information (past medical history, gender, weight, etc.) to form a multidimensional feature vector. This multidimensional feature vector is used as input to a cerebrovascular disease risk prediction model (including logistic regression and neural network models) for model training. The model outputs a risk score representing the probability of a cerebrovascular event occurring in that environment, and provides health management recommendations based on the risk assessment results, achieving personalized cerebrovascular disease risk prediction.

[0026] In this embodiment, the present invention regulates the oxygen concentration within a low-pressure chamber by injecting oxygen and nitrogen through an oxygen regulation device, matching the low-oxygen conditions of the external high-altitude environment. The oxygen regulation device uses an internal oxygen concentration sensor to monitor the oxygen concentration in real time and automatically adjusts it based on prediction information provided by a digital twin model. The digital twin model simulates the impact of different oxygen concentrations on cerebrovascular health based on the effect of oxygen regulation, and predicts the risk of cerebrovascular diseases that may be triggered in the high-altitude environment, helping to determine whether further intervention is needed. This invention, through dynamic adjustment of the monitoring strategy, can reduce errors caused by the inherent precision limitations of the equipment, making oxygen concentration regulation more precise and avoiding lag that could affect the accuracy of the prediction results. The oxygen control module, through real-time monitoring and dynamic adjustment of the equipment's control strategy, can respond promptly to changes in gas concentration, avoiding oxygen regulation lag and thus ensuring more synchronized control of air pressure and oxygen. Real-time monitoring and adjustment of wind speed and oxygen regulation time avoids the problem of asynchronous air pressure and oxygen concentration regulation, thereby making the risk prediction of cerebrovascular diseases more accurate and ensuring real-time synchronization of air pressure and oxygen concentration, making the instantaneous state during the simulation process closer to the actual high-altitude environment.

[0027] In addition, the pre-set risk prediction database is used to store relevant data of the plateau environment cerebrovascular disease risk prediction system based on digital twins, including: reference equipment calibration frequency, allowable deviation equipment calibration frequency, critical measurement frequency, critical zero drift value, equipment calibration frequency influence factor, first threshold for concentration accuracy assessment and second threshold for concentration accuracy assessment, etc. The data in the risk prediction database can be directly queried through public databases such as the plateau climate monitoring data platform and the China Health Information Platform, or it can be obtained in cooperation with research institutions such as medical hospitals.

[0028] The deviation compliance calculation and processing methods involved in this invention are the same, all of which are methods for evaluating the degree of deviation between the measured value and the preset reference value, and combining the allowable error range to determine whether the current state meets the requirements.

[0029] Preferably, the environmental impact parameters include the temperature change amplitude, humidity value, and vibration frequency at each time monitoring point; the concentration accuracy parameters include the equipment calibration frequency, measurement frequency, and zero drift value; the steps for real-time monitoring of the concentration accuracy parameters and environmental impact parameters to obtain the concentration accuracy assessment value include: obtaining reference data for environmental impact parameters and reference data for concentration accuracy parameters from a preset risk prediction database; the environmental impact parameter reference data specifically includes: critical temperature change amplitude, reference humidity value, allowable deviation humidity value, and critical vibration frequency; the concentration accuracy parameter reference data specifically includes: reference equipment calibration frequency, allowable deviation equipment calibration frequency, critical measurement frequency, and critical zero drift value; calculating the approximation of the temperature change amplitude at each time monitoring point with the critical temperature change amplitude to obtain the temperature change amplitude influence parameter; calculating the deviation conformity of the humidity value at each time monitoring point with the reference humidity value and allowable deviation humidity value to obtain the humidity value influence parameter; and applying the temperature change amplitude influence factor and humidity value influence factor to the temperature... The parameters affecting the amplitude of change and the humidity are weighted and coupled, and the result of the coupling process is homogenized to obtain the environmental dynamic coupling parameter. The vibration frequency is weighted by calculating the approximation degree between the vibration frequency and the critical vibration frequency, and then weighted by the vibration frequency influence factor to obtain the vibration frequency influence parameter. The environmental dynamic coupling parameter is coupled with the vibration frequency influence parameter to obtain the environmental influence parameter. The allowable deviation equipment calibration frequency is weighted by calculating the deviation compliance between the equipment calibration frequency and the reference equipment calibration frequency to obtain the equipment calibration frequency influence parameter. The measured frequency and zero-point drift value are weighted by calculating the approximation degree between the measured frequency and the critical measured frequency and the critical zero-point drift value, respectively, to obtain the approximation degree calculation result. The concentration accuracy parameter influence factor is weighted and coupled by the concentration accuracy parameter influence factor, which includes the equipment calibration frequency influence factor, the measurement frequency influence factor, the zero-point drift value influence factor, and the environmental influence parameter influence factor.

[0030] The method for obtaining the concentration accuracy assessment value is as follows:

[0031]

[0032] In the formula, CA1 represents the concentration accuracy assessment value, α1 represents the equipment calibration frequency influence factor, α2 represents the measurement frequency influence factor, α3 represents the zero drift value influence factor, α4 represents the environmental influence parameter influence factor, CF1 represents the equipment calibration frequency, CF0 represents the reference equipment calibration frequency, CF2 represents the allowable deviation equipment calibration frequency, MF1 represents the measurement frequency, MF0 represents the critical measurement frequency, ZD1 represents the zero drift value, ZD0 represents the critical zero drift value, and EI represents the environmental influence parameter.

[0033] The environmental impact parameters are obtained in the following ways:

[0034]

[0035] In the formula, EI represents the environmental influence parameter, α5 represents the influence factor of temperature variation amplitude, α6 represents the influence factor of humidity value, α7 represents the influence factor of vibration frequency, and TA... 1i This represents the temperature change at the i-th time monitoring point relative to the previous time monitoring point, where TA is 1 when i is 1. 1i TA0 is 0, which represents the critical temperature variation range, HV. 1i HV1 represents the humidity value at the i-th time monitoring point, HV2 represents the reference humidity value, HV3 represents the allowable deviation humidity value, VG1 represents the vibration frequency, and VG0 represents the critical vibration frequency, where i is the time monitoring point number, i = 1, 2, 3, ..., N, and N is the total number of time monitoring points.

[0036] In this embodiment, the temperature change amplitude, humidity value, and vibration frequency can be obtained by directly measuring the center point of the hypobaric chamber using temperature, humidity, and vibration sensors. These three parameters are interrelated. For example, temperature changes can cause thermal expansion or contraction of materials such as metals and plastics in the equipment or sensors, potentially leading to minor changes in the internal structure of the equipment, affecting its stability, and possibly increasing vibration or sensitivity to vibration. High humidity can cause condensation on metal surfaces or water absorption and expansion of certain non-metallic materials, thus affecting the physical properties of the equipment. Humidity can also affect the electronic components of the sensors, leading to changes in vibration sensitivity. The environmental impact parameters obtained through comprehensive analysis can quantitatively assess the impact of the hypobaric chamber's internal environment on the measurement accuracy of the oxygen regulation equipment, and the measurement accuracy of the oxygen regulation equipment can also be optimized based on these environmental impact parameters.

[0037] The equipment calibration frequency can be directly viewed through the equipment update log, the measurement frequency is directly provided by the equipment functions, and the zero-point drift value can be obtained by placing the equipment in an oxygen environment of known concentration and observing the deviation between the equipment and the known concentration. These three factors are interrelated; for example, a higher equipment calibration frequency results in less sensor error, which may lead to a lower zero-point drift value. In addition, the zero-point drift value may also be affected by environmental parameters, such as temperature changes, which may cause sensor zero-point drift. The concentration accuracy assessment value reflects the measurement stability and precision of the oxygen regulation equipment and helps optimize equipment performance and reduce errors, thereby improving the reliability and accuracy of cerebrovascular disease risk assessment in simulated high-altitude environments.

[0038] Preferably, the step of dynamically optimizing the oxygen concentration monitoring strategy of the oxygen regulating equipment based on the concentration accuracy assessment value includes: obtaining a first threshold and a second threshold for concentration accuracy assessment from a preset risk prediction database; comparing the concentration accuracy assessment value with the first threshold and the second threshold respectively; if the concentration accuracy assessment value is less than the first threshold, forcibly shutting down the equipment and entering maintenance mode, and simultaneously reporting the anomaly to the management personnel; if the concentration accuracy assessment value is greater than or equal to the first threshold and less than the second threshold, performing zero-point calibration in real time, initiating multi-channel redundant measurement and correcting the oxygen concentration according to environmental influence parameters, and dynamically adjusting the equipment calibration frequency and measurement frequency according to the concentration accuracy assessment value, the rate of change of air pressure, and the rate of change of oxygen concentration; if the concentration accuracy assessment value is greater than or equal to the second threshold, performing zero-point calibration within a preset calibration interval, and maintaining the current calibration frequency and measurement frequency.

[0039] In this embodiment, the oxygen regulating equipment automatically performs comprehensive checks and repairs in maintenance mode. When software or hardware errors are detected, the anomaly is immediately reported to management personnel. Unlike "real-time zero-point calibration," periodic zero-point calibration does not rely on the instantaneous deviation of the measured value but is adjusted based on the equipment's periodic checks and maintenance. Periodic calibration can be performed once a day, once an hour, or once every half hour, etc. When correcting the oxygen concentration based on environmental impact parameters, the environmental impact parameters can be mapped to the oxygen concentration correction values ​​corresponding to each environmental impact parameter preset in the risk prediction database to obtain the corrected oxygen concentration value. The corrected oxygen concentration value is then summed with the original oxygen concentration value. Specifically, the risk prediction database establishes a one-to-one mapping relationship table between environmental impact parameters and oxygen concentration correction values. This table records each environmental impact parameter and its corresponding oxygen concentration correction value. These relationships can be one-to-one or many-to-one. When obtaining the oxygen concentration correction value, simply input the environmental impact parameter into the mapping relationship table, and the risk prediction database can quickly locate and return the corresponding oxygen concentration correction value. This invention divides three risk scenarios into two thresholds, enabling precise responses from "emergency shutdown" to "optimized fine-tuning," balancing safety and efficiency. It also maintains sensor accuracy through dynamic calibration, extends equipment maintenance cycles, and reduces operation and maintenance costs.

[0040] Preferably, the step of dynamically adjusting the equipment calibration frequency and measurement frequency based on the concentration accuracy assessment value, the rate of change of air pressure, and the rate of change of oxygen concentration includes: obtaining the equipment calibration frequency and measurement frequency range corresponding to each concentration accuracy assessment value range from a preset risk prediction database; comparing the concentration accuracy assessment value with each concentration accuracy assessment value range to obtain the concentration accuracy assessment value range, and then comparing the concentration accuracy assessment value range with the equipment calibration frequency and measurement frequency range corresponding to each concentration accuracy assessment value range to obtain the equipment calibration frequency and measurement frequency range corresponding to the concentration accuracy assessment value; obtaining the measurement frequency adjustment value based on the comprehensive processing of the rate of change of air pressure and the rate of change of oxygen concentration, coupling and adding the current measurement frequency with the measurement frequency adjustment value to obtain the adjusted measurement frequency; determining whether the adjusted measurement frequency is within the measurement frequency range, if so, marking the current measurement frequency as the adjusted measurement frequency; if not, and the adjusted measurement frequency is less than the minimum value of the measurement frequency range, marking the minimum value of the measurement frequency range as the adjusted measurement frequency; if not, and the adjusted measurement frequency is greater than the maximum value of the measurement frequency range, marking the maximum value of the measurement frequency range as the adjusted measurement frequency.

[0041] In this embodiment, the present invention ensures that the oxygen regulating device is always in the optimal measurement state by dynamically adjusting the calibration frequency and measurement frequency of the device based on real-time data, thereby improving measurement accuracy and device reliability. By combining dynamic adjustment with the rate of change of air pressure and oxygen concentration, the system can automatically optimize the calibration frequency and measurement frequency according to environmental conditions, avoiding unnecessary measurement cycles while ensuring the real-time nature and accuracy of the data. By limiting the range of calibration frequency and measurement frequency, the system avoids measurement frequencies that are too high or too low, thereby avoiding unnecessary damage to the device or inaccurate results and ensuring the safety of device operation.

[0042] Preferably, the step of obtaining the measurement frequency adjustment value by comprehensively processing the air pressure change rate and the oxygen concentration change rate includes: obtaining the reference air pressure change rate, the reference oxygen concentration change rate, the unit air pressure change rate, and the unit oxygen concentration change rate from a preset risk prediction database; when the air pressure change rate is greater than the reference air pressure change rate, the difference between the air pressure change rate and the reference air pressure change rate is marked as the deviation air pressure change rate, and the air pressure adjustment unit is obtained based on the deviation air pressure change rate and the unit air pressure change rate; otherwise, no additional processing is performed, and the air pressure adjustment unit represents the truncated division relationship between the deviation air pressure change rate and the unit air pressure change rate; when the oxygen concentration change rate is greater than the reference oxygen concentration change rate, the difference between the oxygen concentration change rate and the reference oxygen concentration change rate is marked as the deviation oxygen concentration change rate, and the oxygen adjustment unit is obtained based on the deviation oxygen concentration change rate and the unit oxygen concentration change rate; otherwise, no additional processing is performed, and the oxygen adjustment unit represents the truncated division relationship between the deviation oxygen concentration change rate and the unit oxygen concentration change rate; and coupling the air pressure adjustment unit and the oxygen adjustment unit to obtain the measurement frequency adjustment value.

[0043] In this embodiment, the pressure regulation unit can be obtained by dividing the rate of change of deviation pressure by the rate of change of unit pressure and taking the integer part. Similarly, the oxygen regulation unit can be obtained by dividing the rate of change of deviation oxygen concentration by the rate of change of unit oxygen concentration and taking the integer part. The rate of change of unit pressure and the rate of change of unit oxygen concentration represent the response rate of pressure and oxygen concentration changes, i.e., the correction amount required per unit change. The pressure regulation unit and the oxygen regulation unit represent the integer multiple relationship between the difference in pressure and oxygen concentration changes and the rate of change of unit, indicating the degree to which the measurement frequency needs adjustment. This invention, by dynamically adjusting the measurement frequency based on the rates of change of pressure and oxygen concentration, ensures that the equipment can still provide accurate measurement data even under conditions of significant environmental changes. Simultaneously, through intelligent adjustment, it can adapt to changes in pressure and oxygen concentration, avoiding measurement errors caused by external environmental fluctuations. Precise control of the measurement and calibration frequency ranges effectively prevents equipment malfunctions caused by improper operation. Especially when environmental changes are significant, it avoids the equipment operating at inappropriate frequencies, thereby ensuring the long-term safe operation of the equipment.

[0044] Preferably, the step of dynamically adjusting the equipment control strategy of the oxygen regulating device based on the gas regulation dynamic factor and the concentration accuracy assessment value includes: quantifying the regulation accuracy of the oxygen regulating device according to the gas regulation dynamic factor and the concentration accuracy assessment value to obtain the control accuracy assessment value; comparing the control accuracy assessment value with the preset control accuracy assessment first threshold and control accuracy assessment second threshold in the risk prediction database respectively; if the control accuracy assessment value is less than the control accuracy assessment first threshold, then suspending the air pressure regulation, locking the current chamber pressure, switching to a constant oxygen flow mode to ensure the safety of the subject, and identifying the faulty unit; if the control accuracy assessment value is greater than or equal to the control accuracy assessment first threshold and less than the control accuracy assessment second threshold, then activating the detection step signal to dynamically adjust the equipment parameters, and simultaneously activating the turbulence mode at the oxygen injection point; if the control accuracy assessment value is greater than or equal to the control accuracy assessment second threshold, then loading the preset high-altitude simulation equipment parameters, and simultaneously maintaining the laminar flow mode.

[0045] In this embodiment, the device parameters include proportional gain, integral time, and derivative time. The proportional gain is adjusted as follows: In the formula, K p1 K represents the current proportional gain. p0 E1 represents the original proportional gain, α is the adjustment coefficient (controlling the adjustment range of the proportional gain, directly affecting the oxygen regulation response speed of the equipment; in current usage scenarios, the proportional gain adjustment range is 1 to 1.5 times the default value, such as α being 0.5), E2 represents the second threshold for control accuracy assessment, E represents the current control accuracy assessment value, and E1 represents the first threshold for control accuracy assessment; the adjustment method for integral time is as follows: In the formula, T1 represents the current integration time, T0 represents the original integration time, and β is an adjustment coefficient (to control the intensity of the integral action and eliminate steady-state error; in current application scenarios, the integration time adjustment range is 0.7 to 1 times the default value, such as β being 0.3, to avoid excessively weakening the integration time); the adjustment method for the derivative time is as follows: In the formula, T d1 Let T represent the time of the present differential. d0The original integral time is represented by γ, which is an adjustment coefficient (controlling the damping effect of the derivative action to suppress overshoot; in current applications, the derivative time is limited to 1 to 1.2 times the default value, e.g., γ is 0.2). Laminar flow mode is a state of gas flow where gas molecules flow along parallel paths at a stable and orderly speed, ensuring a stable and uniform airflow, making oxygen supply more precise and stable, suitable for environments with strict oxygen concentration requirements. Turbulent flow mode is an irregular and disordered state of gas flow with large velocity variations, generating eddies, which helps increase the mixing of gas flow and can improve the mixing efficiency of oxygen with other gases. This invention makes precise adjustments based on gas regulation dynamic factors and concentration accuracy assessment values. When the control accuracy is insufficient, it can automatically switch to a safer mode to ensure the safety of the subject. By dynamically adjusting equipment parameters and activating turbulence mode based on assessment values, it can respond more quickly under various dynamic changes, ensuring oxygen regulation accuracy, thereby improving the overall efficiency and reliability of the equipment.

[0046] Preferably, the gas regulation dynamic factors include the rate of change of gas pressure, the rate of change of oxygen concentration, and the gas mixing efficiency. The step of quantifying the regulation accuracy of the oxygen regulating equipment based on the gas regulation dynamic factors and the concentration accuracy assessment value to obtain the control accuracy assessment value includes: obtaining reference data of the gas regulation dynamic factors and the critical concentration accuracy assessment value from a preset risk prediction database. Specifically, the reference data of the gas regulation dynamic factors includes: the critical rate of change of gas pressure, the critical rate of change of oxygen concentration, and the critical gas mixing efficiency; calculating the approximation of the rate of change of gas pressure and the rate of change of oxygen concentration to the critical rate of change of gas pressure and the critical rate of change of oxygen concentration, respectively; and using the influence factors of the rate of change of gas pressure and the rate of change of oxygen concentration. The influence factors are weighted and coupled with the results of the proportion convergence calculation, and the results are then inversely proportional to obtain the change rate influence parameter. The gas mixing efficiency and concentration accuracy assessment values ​​are respectively compared with the critical gas mixing efficiency and critical concentration accuracy assessment values ​​to obtain the proportion convergence calculation. The results are then weighted with the gas mixing efficiency influence factor and the concentration accuracy influence factor to obtain the dynamic control performance index. The change rate influence parameter and the dynamic control performance index are coupled to obtain the control accuracy assessment value. The control accuracy assessment value represents the quantitative data of the degree of influence of the gas pressure change rate, oxygen concentration change rate and gas mixing efficiency on the control accuracy of oxygen regulation equipment.

[0047] The control accuracy assessment value is obtained in the following way:

[0048]

[0049] In the formula, CA represents the control accuracy assessment value, β1 represents the pressure change rate influence factor, β2 represents the oxygen concentration change rate influence factor, β3 represents the gas mixing efficiency influence factor, β7 represents the concentration accuracy influence factor, GP1 represents the pressure change rate, GP0 represents the critical pressure change rate, OC1 represents the oxygen concentration change rate, OC0 represents the critical oxygen concentration change rate, ME1 represents the gas mixing efficiency, ME0 represents the critical gas mixing efficiency, CA1 represents the concentration accuracy assessment value, and CA0 represents the critical concentration accuracy assessment value.

[0050] In this embodiment, the rate of change of air pressure is the ratio of the change in air pressure in the low-pressure chamber to the current monitoring time period, which can be monitored and calculated in real time by an air pressure sensor; the rate of change of oxygen concentration represents the ratio of the change in oxygen concentration in the low-pressure chamber to the current monitoring time period, which can be directly monitored using oxygen regulating equipment; the gas mixing efficiency represents the uniformity of gas mixing in the low-pressure chamber, which can be obtained by collecting oxygen concentration data at various locations in the low-pressure chamber, calculating the standard deviation of oxygen concentration, and using the gas mixing efficiency calculation formula, which is: In the formula, ME1 represents the gas mixing efficiency, σ represents the standard deviation of oxygen concentration, and σ max This represents the preset maximum permissible standard deviation. These three factors are interconnected; for example, changes in air pressure in high-altitude areas directly affect oxygen dissolution and concentration. When air pressure changes significantly, the rate of change in oxygen concentration typically increases. Higher gas mixing efficiency results in a more stable rate of change in oxygen concentration. The comprehensive analysis yields a control accuracy assessment value that evaluates the control performance of oxygen regulation equipment, enabling precise control of the oxygen regulation system and ensuring a stable and safe oxygen supply in simulated high-altitude environments.

[0051] The factors influencing the rate of change of air pressure, the rate of change of oxygen concentration, and the gas mixing efficiency were set to 0.2, 0.5, and 0.1, respectively. The air pressure change rate was set to 10 hPa / s, the critical air pressure change rate to 0, the oxygen concentration change rate to 100 ppm / s, the critical oxygen concentration change rate to 0, the critical gas mixing efficiency to 95%, and the concentration accuracy assessment value and critical concentration accuracy assessment value to 1. As the gas mixing efficiency continuously increases, the control accuracy assessment value was calculated. Table 1 shows the control accuracy assessment value data for the cerebrovascular disease risk prediction system based on the plateau environment.

[0052] Table 1. Data on the control accuracy evaluation of the cerebrovascular disease risk prediction system based on plateau environment.

[0053] serial number <![CDATA[ME1%]]> CA 1 90 0.619 2 92 0.630 3 94 0.640 4 96 0.651 5 98 0.661

[0054] like Figure 2 The figure shown is a graph illustrating the variation of the control accuracy assessment value of the cerebrovascular disease risk prediction system based on a plateau environment provided in an embodiment of the present invention. (See Table 1 and...) Figure 2 It can be seen that when the factors affecting the rate of change of air pressure, the rate of change of oxygen concentration, the gas mixing efficiency, the concentration accuracy, the rate of change of air pressure, the rate of change of critical air pressure, the rate of change of oxygen concentration, the rate of change of critical oxygen concentration, the critical gas mixing efficiency, the concentration accuracy assessment value, and the critical concentration accuracy assessment value remain unchanged, the control accuracy assessment value also increases continuously as the gas mixing efficiency increases.

[0055] Preferably, the gas includes oxygen and nitrogen; the step of dynamically adjusting the wind speed based on the monitored gas injection state parameters, and triggering oxygen adjustment based on oxygen equilibrium time and pressure equilibrium time, includes: obtaining gas injection state parameters based on the gas injection state parameters; comparing the gas injection state parameters with preset gas injection state thresholds in the risk prediction database; if the gas injection state parameters are greater than or equal to the gas injection state thresholds and the gas type is oxygen, then marking the difference between the gas injection state parameters and the gas injection state thresholds as deviation gas injection state parameters; comparing the deviation gas injection state parameters with the preset wind speed adjustment ratios corresponding to each deviation gas injection state parameter in the risk prediction database to obtain the wind speed adjustment ratio corresponding to the deviation gas injection state parameters; and increasing the wind speed according to the wind speed adjustment ratio. Simultaneously balance the air pressure; if the gas injection status parameter is greater than or equal to the gas injection status threshold and the gas type is nitrogen, monitor the oxygen concentration in real time and balance the air pressure, start oxygen compensation injection according to the oxygen concentration and trigger the nitrogen over-limit alarm; if the gas injection status parameter is less than the gas injection status threshold and the gas type is oxygen, determine whether the current wind speed is the preset minimum wind speed limit. If so, no additional processing is performed. Otherwise, gradually reduce the wind speed (e.g., reduce the preset wind speed by one level per second) until the minimum wind speed limit is reached; if the gas injection status parameter is less than the gas injection status threshold and the gas type is nitrogen, close the ventilation opening; trigger oxygen adjustment in advance according to the difference between the oxygen balance time and the air pressure balance time. Specifically, adjust oxygen first, and then adjust the air pressure after the difference time has elapsed.

[0056] In this embodiment, when it is necessary to increase the oxygen concentration, oxygen is injected using an oxygen regulating device; when it is necessary to decrease the oxygen concentration, nitrogen is injected using the same device. Simultaneously, the gases are rapidly mixed, and the exhaust valve is opened to maintain pressure balance. By dynamically adjusting the wind speed based on changes in gas injection parameters, the system ensures that both oxygen and pressure balance are maintained while avoiding unnecessary energy consumption due to excessively high or low wind speeds. The system can automatically adjust the wind speed based on real-time monitored gas injection parameters, ensuring that the oxygen regulating device can respond quickly to changes under different conditions, maintaining oxygen concentration and pressure balance. Especially when oxygen and nitrogen injection are unbalanced, it promptly replenishes oxygen or triggers an alarm, effectively preventing gas over- or under-supplied conditions. Depending on the gas type, the system can flexibly adjust its response strategy, improving system flexibility and responsiveness.

[0057] Preferably, the gas injection state parameters include the injected gas concentration, chamber volume, and pressure difference. The steps for obtaining the gas injection state parameters based on the gas injection state parameters include: obtaining reference data for the gas injection state parameters from a preset risk prediction database, specifically including: reference injected gas concentration, allowable deviation injected gas concentration, critical chamber volume, and critical pressure difference; performing a deviation compliance calculation on the allowable deviation injected gas concentration with the injected gas concentration and the reference injected gas concentration to obtain the injected gas concentration influence parameter; performing a proportion convergence calculation on the chamber volume and critical pressure difference with the critical chamber volume and pressure difference, respectively; and then coupling the injected gas concentration influence parameter and the proportion convergence calculation results with weights through the gas injection state parameter influence factors to obtain the gas injection state parameters. The gas injection state parameter influence factors include a chamber volume influence factor, a pressure difference influence factor, and an injected gas concentration influence factor. The gas injection state parameters represent the quantitative data of the degree of influence of the injected gas concentration, chamber volume, and pressure difference on the gas stability within the chamber.

[0058] The gas injection state parameters are obtained as follows:

[0059]

[0060] In the formula, GI represents the gas injection state parameter, β4 represents the injection gas concentration influence factor, β5 represents the cabin volume influence factor, β6 represents the pressure range influence factor, IC1 represents the injection gas concentration, IC0 represents the reference injection gas concentration, IC2 represents the allowable deviation injection gas concentration, CV1 represents the cabin volume, CV0 represents the critical cabin volume, PR1 represents the pressure range, and PR0 represents the critical pressure range.

[0061] In this embodiment, since the oxygen regulating equipment controls the gas concentration by injecting oxygen or nitrogen, the injected gas concentration can be directly obtained from the gas control function of the oxygen regulating equipment; the chamber volume can be obtained directly from the geometric dimensions of the chamber (length, width, and height) or through measuring devices such as a 3D scanner; the pressure difference refers to the difference between the maximum and minimum pressure values ​​within the chamber, which can be measured by a pressure sensor or barometer. These three parameters are interrelated. For example, if the injected oxygen quantity is too large, the gas concentration will increase, potentially leading to an increase in chamber pressure and a large pressure difference; if the injected gas quantity is too small, the gas concentration will decrease, and the pressure may also decrease, thus affecting the system's balance; with a constant chamber volume, if the injected gas concentration is too high or too low, the pressure will change, resulting in an increased pressure difference. The gas injection state parameters obtained through comprehensive analysis can provide a basis for the adjustment of the oxygen regulating equipment, precisely adjusting the gas injection quantity and regulating the airflow to maintain the stable and safe operation of the system.

[0062] A digital twin-based method for predicting the risk of cerebrovascular diseases in high-altitude environments includes the following steps: real-time monitoring of concentration accuracy parameters and environmental impact parameters to obtain concentration accuracy assessment values, and dynamic optimization of the oxygen concentration monitoring strategy of the oxygen regulation equipment based on the concentration accuracy assessment values, wherein the concentration accuracy assessment values ​​are used to quantify the accuracy of the oxygen regulation equipment in measuring oxygen concentration; real-time monitoring of gas regulation dynamic factors, and dynamic adjustment of the equipment control strategy of the oxygen regulation equipment based on the gas regulation dynamic factors and the concentration accuracy assessment values; dynamic adjustment of wind speed according to the monitored gas injection status parameters, triggering oxygen regulation based on oxygen equilibrium time and pressure equilibrium time, and prediction of cerebrovascular disease risk based on the adjusted oxygen regulation equipment and the hypobaric chamber.

[0063] The following points need to be explained:

[0064] (1) The accompanying drawings of the embodiments of the present invention only involve the structures involved in the embodiments of the present invention. Other structures can refer to the general design.

[0065] (2) For clarity, the thickness of layers or regions is enlarged or reduced in the drawings used to describe embodiments of the present invention; that is, these drawings are not drawn to actual scale. It is understood that when an element such as a layer, film, region, or substrate is referred to as being “above” or “below” another element, the element may be “directly” located “above” or “below” the other element, or there may be intermediate elements.

[0066] (3) Where there is no conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other to obtain new embodiments.

[0067] The above are merely specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. The scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A digital twin-based system for predicting the risk of cerebrovascular diseases in high-altitude environments, characterized in that, include: Equipment control module, oxygen control module, oxygen pressure coupling control module, and risk prediction database; The equipment control module is used to monitor concentration accuracy parameters and environmental impact parameters in real time to obtain concentration accuracy assessment values, and to dynamically optimize the oxygen concentration monitoring strategy of the oxygen regulating equipment based on the concentration accuracy assessment values. The concentration accuracy assessment values ​​are used to quantify the accuracy of the oxygen regulating equipment when measuring oxygen concentration. The steps for dynamically optimizing the oxygen concentration monitoring strategy of the oxygen regulating equipment based on the concentration accuracy assessment value include: Obtain the first threshold and the second threshold for concentration accuracy assessment from the preset risk prediction database; The concentration accuracy assessment value is compared with the first threshold and the second threshold of concentration accuracy assessment respectively. If the concentration accuracy assessment value is less than the first threshold of concentration accuracy assessment, the machine is forced to stop and enter maintenance mode, and the abnormality is reported to the management personnel. If the concentration accuracy assessment value is greater than or equal to the first threshold of concentration accuracy assessment and less than the second threshold of concentration accuracy assessment, then zero-point calibration is performed in real time, multi-channel redundant measurement is started, and the oxygen concentration is corrected according to the environmental influence parameters. The equipment calibration frequency and measurement frequency are dynamically adjusted according to the concentration accuracy assessment value, the rate of change of air pressure and the rate of change of oxygen concentration. If the concentration accuracy assessment value is greater than or equal to the second threshold for concentration accuracy assessment, zero-point calibration is performed within the preset calibration interval; The oxygen control module is used to monitor the dynamic factors of gas regulation in real time, and dynamically adjust the equipment control strategy of the oxygen regulation equipment based on the dynamic factors of gas regulation and the concentration accuracy assessment value. The steps for dynamically adjusting the equipment control strategy of the oxygen regulation equipment based on the gas regulation dynamic factor and the concentration accuracy assessment value include: The control accuracy assessment value is obtained by quantifying the regulation accuracy of the oxygen regulation equipment based on the gas regulation dynamic factor and the concentration accuracy assessment value. The control accuracy assessment value is compared with the preset control accuracy assessment first threshold and control accuracy assessment second threshold in the risk prediction database. If the control accuracy assessment value is less than the control accuracy assessment first threshold, the air pressure regulation is paused, the current chamber pressure is locked, and the constant oxygen flow mode is switched to ensure the safety of the subject and the faulty unit is identified. If the control accuracy assessment value is greater than or equal to the first control accuracy assessment threshold and less than the second control accuracy assessment threshold, then the detection step signal is activated to dynamically adjust the equipment parameters, and at the same time, the turbulence mode is activated at the oxygen injection point. If the control accuracy assessment value is greater than or equal to the second threshold of control accuracy assessment, then the preset high-altitude simulation equipment parameters are loaded while maintaining laminar flow mode. The oxygen-pressure coupling control module is used to dynamically adjust the wind speed according to the monitored gas injection status parameters, trigger oxygen regulation based on oxygen balance time and pressure balance time, and predict the risk of cerebrovascular diseases based on the adjusted oxygen regulation equipment and the hypobaric chamber.

2. The cerebrovascular disease risk prediction system based on digital twin in high-altitude environments according to claim 1, characterized in that, The environmental impact parameters include the temperature change range, humidity value, and vibration frequency at each time monitoring point; The concentration accuracy parameters include the equipment calibration frequency, measurement frequency, and zero-point drift value; The steps for obtaining a concentration accuracy assessment value by real-time monitoring of concentration accuracy parameters and environmental impact parameters include: The environmental impact parameter reference data and concentration accuracy parameter reference data are obtained from the preset risk prediction database. The environmental impact parameter reference data specifically includes: critical temperature variation range, reference humidity value, allowable deviation humidity value, and critical vibration frequency. The concentration accuracy parameter reference data specifically includes: reference equipment calibration frequency, allowable deviation equipment calibration frequency, critical measurement frequency, and critical zero drift value. The approximation degree of the temperature change amplitude at each time monitoring point is calculated by comparing it with the critical temperature change amplitude to obtain the parameter of temperature change amplitude influence. The humidity values ​​at each time monitoring point are compared with the reference humidity value and the allowable deviation humidity value to calculate the degree of conformity and obtain the humidity value influence parameter. After weighting the parameters affecting temperature variation amplitude and humidity value respectively by the temperature variation amplitude influence factor and humidity value influence factor, the coupling process is performed, and the result of the coupling process is homogenized to obtain the environmental dynamic coupling parameters. After calculating the approximation degree between the vibration frequency and the critical vibration frequency, the vibration frequency influence parameter is obtained by weighting it through the vibration frequency influence factor. The environmental impact parameters are obtained by coupling the environmental dynamic coupling parameters with the vibration frequency influence parameters. The deviation compliance of the allowable deviation equipment calibration frequency with the equipment calibration frequency and the reference equipment calibration frequency is calculated to obtain the equipment calibration frequency influence parameter. The measurement frequency and zero drift value are respectively compared with the critical measurement frequency and critical zero drift value to calculate the approximation degree, and the approximation degree calculation result is obtained. By weighting and coupling the influence parameters of equipment calibration frequency, proportion convergence, and environmental impact after inverse proportional calculation using the concentration accuracy parameter influence factors, a concentration accuracy assessment value is obtained. The concentration accuracy parameter influence factors include the equipment calibration frequency influence factor, measurement frequency influence factor, zero drift value influence factor, and environmental impact parameter influence factor.

3. The cerebrovascular disease risk prediction system based on digital twin in high-altitude environments according to claim 1, characterized in that, The steps of dynamically adjusting the equipment calibration frequency and measurement frequency based on the concentration accuracy assessment value, the rate of change of air pressure, and the rate of change of oxygen concentration include: Obtain the equipment calibration frequency and measurement frequency range corresponding to the accuracy assessment value range of each concentration from the preset risk prediction database; The concentration accuracy assessment value is compared with the range of each concentration accuracy assessment value to obtain the concentration accuracy assessment value range. Then, the concentration accuracy assessment value range is compared with the equipment calibration frequency and measurement frequency range corresponding to each concentration accuracy assessment value range to obtain the equipment calibration frequency and measurement frequency range corresponding to the concentration accuracy assessment value. The measurement frequency adjustment value is obtained by comprehensively processing the rate of change of air pressure and the rate of change of oxygen concentration. The current measurement frequency is coupled with the measurement frequency adjustment value to obtain the adjusted measurement frequency. Determine whether the adjusted measurement frequency is within the measurement frequency range. If so, mark the current measurement frequency as the adjusted measurement frequency. If not and the adjusted measurement frequency is less than the minimum value of the measurement frequency range, then mark the minimum value of the measurement frequency range as the adjusted measurement frequency. If not, and the adjusted measurement frequency is greater than the maximum value of the measurement frequency range, then the maximum value of the measurement frequency range is marked as the adjusted measurement frequency.

4. The plateau environment cerebrovascular disease risk prediction system based on digital twins according to claim 3, characterized in that, The step of obtaining the measurement frequency adjustment value by comprehensively processing the rate of change of air pressure and the rate of change of oxygen concentration includes: Obtain the reference air pressure change rate, reference oxygen concentration change rate, unit air pressure change rate, and unit oxygen concentration change rate from the preset risk prediction database. When the rate of change of air pressure is greater than the rate of change of reference air pressure, the difference between the rate of change of air pressure and the rate of change of reference air pressure is marked as the deviation rate of change of air pressure, and the air pressure adjustment unit is obtained based on the deviation rate of change of air pressure and the unit rate of change of air pressure. Otherwise, no additional processing is performed. The air pressure adjustment unit represents the cut-off division relationship between the deviation rate of change of air pressure and the unit rate of change of air pressure. When the rate of change of oxygen concentration is greater than the rate of change of reference oxygen concentration, the difference between the rate of change of oxygen concentration and the rate of change of reference oxygen concentration is marked as the deviation rate of change of oxygen concentration. The oxygen adjustment unit is obtained based on the deviation rate of change of oxygen concentration and the unit rate of change of oxygen concentration. Otherwise, no additional processing is performed. The oxygen adjustment unit represents the truncated division relationship between the deviation rate of change of oxygen concentration and the unit rate of change of oxygen concentration. The pressure regulation unit and the oxygen regulation unit are coupled to obtain the measurement frequency regulation value.

5. The cerebrovascular disease risk prediction system based on digital twin in high-altitude environments according to claim 1, characterized in that, The gas regulation dynamic factors include the rate of change of gas pressure, the rate of change of oxygen concentration, and the gas mixing efficiency; The steps to quantify the control accuracy assessment value of oxygen regulating equipment based on gas regulation dynamic factors and concentration accuracy assessment values ​​include: The reference data of gas regulation dynamic factors and the accuracy assessment value of critical concentration are obtained from the preset risk prediction database. The reference data of gas regulation dynamic factors specifically include: the rate of change of critical gas pressure, the rate of change of critical oxygen concentration and the critical gas mixing efficiency. The rate of change of air pressure and the rate of change of oxygen concentration are respectively calculated by the proportion of the rate of change of critical air pressure and the rate of change of critical oxygen concentration. The results of the proportion of the rate of change of air pressure and the rate of change of oxygen concentration are weighted and coupled by the influence factors of the rate of change of air pressure and the rate of change of oxygen concentration. The result of the processing is then inversely proportional to obtain the parameter of the rate of change. The gas mixing efficiency and concentration accuracy assessment values ​​are compared with the critical gas mixing efficiency and critical concentration accuracy assessment values ​​to calculate the degree of approximation. The results are then weighted by the gas mixing efficiency influence factor and the concentration accuracy influence factor to obtain the dynamic control performance index. The control accuracy evaluation value is obtained by coupling the change rate influence parameter and the dynamic control performance index. The control accuracy evaluation value represents the quantitative data of the degree of influence of the gas pressure change rate, oxygen concentration change rate and gas mixing efficiency on the control accuracy of oxygen regulation equipment.

6. The plateau environment cerebrovascular disease risk prediction system based on digital twins according to claim 1, characterized in that, The gas includes oxygen and nitrogen; The step of dynamically adjusting the wind speed based on monitored gas injection status parameters and triggering oxygen regulation based on oxygen equilibrium time and gas pressure equilibrium time includes: Obtain the gas injection state parameters based on the gas injection state parameters; The gas injection state parameter is compared with the preset gas injection state threshold in the risk prediction database. If the gas injection state parameter is greater than or equal to the gas injection state threshold and the gas type is oxygen, the difference between the gas injection state parameter and the gas injection state threshold is marked as the deviation gas injection state parameter. The deviation gas injection state parameter is compared with the wind speed adjustment ratio corresponding to each deviation gas injection state parameter preset in the risk prediction database to obtain the wind speed adjustment ratio corresponding to the deviation gas injection state parameter. The wind speed is increased according to the wind speed adjustment ratio while balancing the air pressure. If the gas injection status parameter is greater than or equal to the gas injection status threshold and the gas type is nitrogen, the oxygen concentration is monitored in real time while the gas pressure is balanced. Based on the oxygen concentration, oxygen compensation injection is initiated and a nitrogen over-limit alarm is triggered. If the gas injection state parameter is less than the gas injection state threshold and the gas type is oxygen, determine whether the current wind speed is the preset minimum wind speed limit. If it is, no additional processing is performed; otherwise, gradually reduce the wind speed until the minimum wind speed limit is reached. If the gas injection status parameter is less than the gas injection status threshold and the gas type is nitrogen, then close the vent. Oxygen regulation is triggered based on the difference between oxygen equilibrium time and pressure equilibrium time.

7. The plateau environment cerebrovascular disease risk prediction system based on digital twins according to claim 6, characterized in that, The gas injection status parameters include the injected gas concentration, chamber volume, and pressure difference. The step of obtaining the gas injection state parameters based on the gas injection state parameters includes: Reference data of gas injection status parameters are obtained from a pre-set risk prediction database, including: reference injection gas concentration, allowable deviation injection gas concentration, critical chamber volume, and critical pressure range. The deviation compliance of the allowable deviation injection gas concentration with the injection gas concentration and the reference injection gas concentration is calculated to obtain the parameter of the influence of injection gas concentration. The proportion of the chamber volume and critical pressure difference to the critical chamber volume and pressure difference is calculated. Then, the results of the proportion calculation are coupled by weighting the injection gas concentration influence parameter and the proportion of proportion through the gas injection state parameter influence factor to obtain the gas injection state parameter. The gas injection state parameter influence factor includes the chamber volume influence factor, the pressure difference influence factor and the injection gas concentration influence factor. The gas injection state parameter represents the quantitative data of the degree of influence of the injection gas concentration, chamber volume and pressure difference on the gas stability in the chamber.

8. A method for predicting the risk of cerebrovascular diseases in high-altitude environments based on digital twins, said method being based on the system of any one of claims 1-7, characterized in that, The method includes the following steps: Real-time monitoring of concentration accuracy parameters and environmental impact parameters is used to obtain concentration accuracy assessment values. Based on the concentration accuracy assessment values, the oxygen concentration monitoring strategy of the oxygen regulating equipment is dynamically optimized. The concentration accuracy assessment values ​​are used to quantify the accuracy of the oxygen regulating equipment when measuring oxygen concentration. Real-time monitoring of gas regulation dynamic factors, and dynamic adjustment of the equipment control strategy of oxygen regulation equipment based on gas regulation dynamic factors and concentration accuracy assessment values; The wind speed is dynamically adjusted based on the monitored gas injection status parameters. Oxygen regulation is triggered based on oxygen balance time and air pressure balance time. Cerebrovascular disease risk is predicted based on the adjusted oxygen regulation equipment and the hypobaric chamber.

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