A stroke risk warning method and system based on digital twins

Abstract

The present invention provides a stroke risk warning method and system based on digital twins, relating to the technical field of stroke risk warning. The method comprises the following steps: acquisition assessment; acquisition update delay assessment; acquisition update integrity assessment; and stroke risk prediction. The present invention analyzes acquisition control data and determines whether to perform acquisition update delay assessment and acquisition update integrity assessment. If acquisition update delay assessment is performed, it determines whether to perform acquisition update delay optimization. If acquisition update integrity assessment is performed, it determines whether to perform acquisition update integrity optimization. Finally, the stroke risk prediction level is obtained, thereby achieving the effect of improving the accuracy of stroke risk warning data and solving the problem of low accuracy of stroke risk warning data in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of stroke risk warning technology, and in particular to a stroke risk warning method and system based on digital twins. Background Art

[0002] Digital twin technology is an emerging digital technology that creates virtual mirrors of physical objects, enabling real-time interaction and mapping between the physical and digital worlds. In the medical field, digital twin technology can be applied to patient physiological status monitoring, disease prediction, and management. By collecting patients' clinical data and physiological indicators and building a digital twin model of the patient, doctors can gain real-time insights into their health status and conduct accurate disease prediction and management. Stroke is a serious cerebrovascular disease characterized by high morbidity, disability, and mortality. Currently, early warning of stroke relies primarily on clinical symptoms, imaging examinations, and biochemical markers.

[0003] Existing methods are based on patient physiological data, input into the corresponding digital twin model, and simulate the patient's physiological state based on the output results of the digital twin model.

[0004] However, in the process of implementing the technical solutions of the embodiments of the present invention, the present invention found that the above technology has at least the following technical problems:

[0005] In the existing technology, as the physiological status (blood pressure, heart rate data) of cerebrovascular patients changes, the digital twin model needs to be updated frequently. High-frequency data acquisition may lead to inaccurate charge and discharge pressure control of the blood pressure monitor, and there are delays in data update and synchronization, resulting in low accuracy of stroke risk warning data. Summary of the Invention

[0006] The present invention provides a stroke risk warning method based on digital twins. The method obtains an acquisition evaluation value by analyzing the acquired acquisition control data and determines whether to perform acquisition update delay evaluation and acquisition update integrity evaluation. If an acquisition update delay evaluation is performed, a data update delay analysis is performed based on the acquired acquisition update delay data to determine whether to perform acquisition update delay optimization. If an acquisition update integrity evaluation is performed, a data update integrity analysis is performed based on the acquired acquisition update integrity data to determine whether to perform acquisition update integrity optimization, thereby improving the accuracy of stroke risk warning data.

[0007] In order to solve the above-mentioned purpose of the invention, the technical solution provided by the present invention is as follows:

[0008] A stroke risk warning method based on digital twins comprises the following steps: analyzing acquired acquisition control data to obtain an acquisition evaluation value, and determining whether to perform acquisition update delay evaluation and acquisition update integrity evaluation; if an acquisition update delay evaluation is performed, performing data update delay analysis based on the acquired acquisition update delay data, and determining whether to perform acquisition update delay optimization; if an acquisition update integrity evaluation is performed, performing data update integrity analysis based on the acquired acquisition update integrity data, and determining whether to perform acquisition update integrity optimization; inputting stroke risk prediction data corresponding to the obtained qualified acquisition evaluation value into the constructed digital twin model to obtain a stroke risk prediction level, and performing a stroke risk warning based on the stroke risk prediction level, wherein the stroke risk prediction level represents a result output based on the digital twin model, and the qualified acquisition evaluation value represents an acquisition evaluation value that meets a preset acquisition control interval.

[0009] Optionally, the acquisition control data is used to reflect the influence of the acquisition control parameters on the acquisition control of blood pressure related data within a preset time period, specifically including the gas inflow-pressure influence value, the gas inflow-number influence value, the gas outflow-pressure influence value and the gas outflow-number influence value; the acquisition control data is obtained by processing based on the acquisition control parameters and the preset acquisition control parameters obtained from the database; the acquisition control parameters include the maximum gas inflow rate, the maximum inflation pressure value, the maximum inflation number value, the maximum gas outflow rate, the maximum deflation pressure value and the maximum deflation number value; the preset acquisition control parameters include the preset maximum inflow rate, the preset maximum inflation pressure, the preset maximum inflation number, the preset maximum outflow rate, the preset maximum deflation pressure and the preset maximum deflation number; the acquisition update delay data is used to reflect the influence of the acquisition update delay parameters on the synchronization of blood pressure related data updates within a preset time period, specifically including the response and number evaluation value, the response and interval evaluation value, the update and number evaluation value and the update and interval evaluation value; the acquisition update delay The data is obtained by processing based on the acquisition update delay parameters and the preset acquisition update delay parameters obtained from the database; the acquisition update delay parameters include the maximum response delay time, the maximum number of inflation and deflation times, the maximum inflation interval time and the maximum update delay time; the preset acquisition update delay parameters include the preset maximum response delay time, the preset maximum number of inflation and deflation times, the preset maximum inflation interval time and the preset maximum update delay time; the acquisition update integrity data is used to reflect the influence of the acquisition update integrity parameters on the integrity of blood pressure-related data acquisition within a preset time period, specifically including the acquisition completeness and number evaluation value, the acquisition completeness and interval evaluation value and the acquisition completeness and noise evaluation value; the acquisition update integrity data is obtained by processing based on the acquisition update integrity parameters and the preset acquisition update integrity parameters obtained from the database; the acquisition update integrity parameters include the maximum amount of collected blood pressure data and the collection blood pressure noise ratio; the preset acquisition update integrity parameters include the preset maximum amount of collected blood pressure data and the preset maximum amount of blood pressure acquisition noise ratio.

[0010] Optionally, the specific process of obtaining the acquisition evaluation value from the acquisition control data obtained by the analysis is as follows: performing a first inflow operation on the obtained gas inflow first processing value to obtain a gas inflow-pressure influence value, the gas inflow-pressure influence value represents quantitative data on the degree of influence of the maximum gas inflow rate and the maximum inflation pressure value on the acquisition control of blood pressure related data, the gas inflow first processing value includes the maximum gas inflow rate, the maximum inflation pressure value, the preset inflation pressure weight value, the preset maximum inflow rate and the preset maximum inflation pressure; performing a second inflow operation on the obtained gas inflow second processing value to obtain a gas inflow-number influence value, the gas inflow-number influence value represents quantitative data on the degree of influence of the maximum gas inflow rate and the maximum inflation number value on the acquisition control of blood pressure related data, the gas inflow second processing value includes the maximum gas inflow rate, the maximum inflation number value, the preset inflation number weight value, the preset maximum inflow rate and the preset maximum inflation number; performing a first outflow operation on the obtained gas outflow first processing value to obtain Gas outflow-pressure influence value, the gas outflow-pressure influence value represents the quantitative data of the influence degree of the maximum gas outflow rate and the maximum deflation pressure value on the acquisition and control of blood pressure-related data, the first gas outflow processing value includes the maximum gas outflow rate, the maximum deflation pressure value, the preset deflation pressure weight value, the preset maximum outflow rate and the preset maximum deflation pressure; the second gas outflow processing value obtained is subjected to a second outflow operation to obtain a gas outflow-number influence value, the gas outflow-number influence value represents the quantitative data of the influence degree of the maximum gas outflow rate and the maximum deflation number value on the acquisition and control of blood pressure-related data, the second gas outflow processing value includes the maximum gas outflow rate, the maximum deflation number value, the preset deflation number weight value, the preset maximum outflow rate and the preset maximum deflation number; the obtained acquisition control data and the preset acquisition control weight group obtained from the database are multiplied to obtain an acquisition evaluation value; the acquisition evaluation value is used to evaluate the blood pressure-related data acquisition and control situation during blood pressure monitoring based on digital twins.

[0011] Optionally, the specific process of determining whether to perform acquisition update delay evaluation and acquisition update integrity evaluation is as follows: determine whether the acquired acquisition evaluation value is within a preset acquisition control interval, and the preset acquisition control interval is the interval range corresponding to the preset acquisition control maximum value and the preset acquisition control minimum value; when the acquisition evaluation value is within the preset acquisition control interval, mark the numerical value corresponding to the corresponding acquisition evaluation value as a qualified acquisition evaluation value; when the acquisition evaluation value is greater than the preset acquisition control maximum value, perform acquisition update delay evaluation; when the acquisition evaluation value is less than the preset acquisition control minimum value, perform acquisition update integrity evaluation.

[0012] Optionally, the specific process of performing data update delay analysis based on the acquired acquisition update delay data is as follows: a blood pressure acquisition update delay value is obtained by multiplying the acquisition update delay data and the preset acquisition update delay weight group obtained from the database; the blood pressure acquisition update delay value is used to reflect the blood pressure-related data update delay situation in the acquisition update delay evaluation; the preset acquisition update delay weight group includes a response first weight value, a response second weight value, an update first weight value and an update second weight value; the response and number evaluation value is obtained by performing a first response delay operation on the response delay first processing value, and the response and number evaluation value represents quantitative data on the degree of influence of the maximum number of inflation and deflation times and the maximum value of the response delay duration on the blood pressure-related data update delay, and the first response delay processing value includes the maximum response delay duration, the maximum number of inflation and deflation times, the preset response and inflation and deflation weight, the preset maximum response delay duration and the preset maximum number of inflation and deflation times; the response and interval evaluation value is obtained by performing a second response delay operation on the response delay second processing value, and the response and interval evaluation value represents the maximum inflation interval duration and the maximum response delay duration. The same quantitative data on the degree of influence on the update delay of blood pressure related data; the second processing value of the response delay includes the maximum response delay duration, the maximum inflation interval duration, the preset response and interval weight, the preset maximum response delay duration and the preset maximum inflation interval; the update and number evaluation value is obtained by performing a first update delay operation on the first processing value of the update delay, and the update and number evaluation value represents the quantitative data on the degree of influence of the maximum inflation and deflation times and the maximum update delay duration on the update delay of the blood pressure related data, the first processing value of the update delay includes the maximum update delay duration, the maximum inflation and deflation times, the preset update and inflation and deflation weight, the preset maximum update delay duration and the preset maximum inflation and deflation times; the update and interval evaluation value is obtained by performing a second update delay operation on the second processing value of the update delay, and the update and interval evaluation value represents the quantitative data on the degree of influence of the maximum inflation interval duration and the maximum update delay duration on the update delay of the blood pressure related data, the second processing value of the update delay includes the maximum update delay duration, the maximum inflation interval duration, the preset update and interval weight, the preset maximum update delay duration and the preset maximum inflation interval.

[0013] Optionally, the specific process of determining whether to perform collection update delay optimization is as follows: determine whether the monitored blood pressure collection update delay value is not higher than a preset collection update delay threshold; if so, do not perform collection update delay optimization, otherwise send a prompt to the preset personnel to perform collection update delay optimization; when the blood pressure collection update delay value is still higher than the preset collection update delay threshold after collection update delay optimization, send an alarm prompt to the preset personnel; the collection update delay optimization includes reducing the collection frequency and prompting to release the pressure; reducing the collection frequency means that the preset personnel reduces the collection frequency of blood pressure-related data step by step by a preset multiple; prompting to release the pressure means sending a prompt to the preset personnel to adjust the number of times the blood pressure monitor releases the pressure.

[0014] Optionally, the specific process of performing data update integrity analysis based on the acquired collection and update integrity data is as follows: obtaining a complete and inflation and deflation data group, a complete and interval data group, and a complete and noise ratio data group; obtaining an acquisition completeness and number evaluation value by performing complete and inflation and deflation operations on the complete and inflation and deflation data group, the acquisition completeness and number evaluation value represents quantitative data on the degree of influence of the maximum amount of collected blood pressure data and the maximum number of inflation and deflation times on the integrity of the blood pressure-related data update, the complete and inflation and deflation data group includes the maximum amount of collected blood pressure data, the maximum number of inflation and deflation times, a preset complete and inflation and deflation weight value, a preset maximum amount of collected blood pressure data, and a preset maximum number of inflation and deflation times; obtaining an acquisition completeness and interval evaluation value by performing complete and interval operations on the complete and interval data group, the acquisition completeness and interval evaluation value represents the degree of influence of the maximum amount of collected blood pressure data and the maximum inflation interval time on the integrity of the blood pressure-related data update. Data, the complete and interval data group includes the maximum amount of collected blood pressure data, the maximum inflation interval time, the preset complete and interval weight value, the preset maximum amount of collected blood pressure data and the preset maximum inflation interval; the collection complete and noise evaluation value is obtained by performing complete and noise ratio operation on the complete and noise ratio data group, and the collection complete and noise evaluation value represents the quantitative data of the degree of influence of the maximum amount of collected blood pressure data and the collected blood pressure noise ratio on the integrity of the blood pressure-related data update, the complete and noise ratio data group includes the maximum amount of collected blood pressure data, the collected blood pressure noise ratio, the preset complete and noise ratio weight value, the preset maximum amount of collected blood pressure data and the preset maximum value of the blood pressure collection noise ratio; the collection update complete value is obtained by performing a product operation on the collection update integrity data and the preset collection update integrity weight group obtained from the database; the collection update complete value is used to reflect the blood pressure-related data update integrity status during the collection update integrity evaluation process.

[0015] Optionally, the specific process of determining whether to perform collection and update integrity optimization is as follows: determining whether the monitored collection and update integrity value is not lower than a preset collection and update integrity threshold obtained from the database; if so, not performing collection and update integrity optimization, otherwise sending a prompt to the preset personnel to perform collection and update integrity optimization; when the collection and update integrity value is still lower than the preset collection and update integrity threshold after collection and update integrity optimization, sending an alarm prompt to the preset personnel; the collection and update integrity optimization includes increasing the collection frequency and prompting for charging; increasing the collection frequency means that the preset personnel increases the collection frequency of blood pressure-related data step by step by a preset multiple; the prompting for charging means sending a prompt to the preset personnel to adjust the charging times of the blood pressure monitor.

[0016] Optionally, the specific process of performing stroke risk warning based on the stroke risk prediction level is as follows: inputting the stroke risk prediction data and the preset stroke risk prediction level into the constructed digital twin model for training to obtain the stroke risk prediction model; inputting the stroke risk prediction data obtained in real time into the stroke risk prediction model to obtain the stroke risk prediction level; when the stroke risk prediction model outputs a first-level warning, sending a first-level warning prompt to the preset personnel; when the stroke risk prediction model outputs a second-level warning, sending a second-level warning prompt to the preset personnel; the stroke risk prediction level includes a first-level warning and a second-level warning; the stroke risk prediction data includes a qualified collection assessment value and blood pressure-related data corresponding to the qualified collection assessment value.

[0017] An embodiment of the present invention provides a stroke risk warning system based on digital twins, including an acquisition evaluation module, an acquisition update delay evaluation module, an acquisition update integrity evaluation module and a stroke risk prediction level module: wherein the acquisition evaluation module is used to analyze the acquired acquisition control data to obtain an acquisition evaluation value, and determine whether to perform acquisition update delay evaluation and acquisition update integrity evaluation; the acquisition update delay evaluation module is used to perform data update delay analysis based on the acquired acquisition update delay data if an acquisition update delay evaluation is performed, and determine whether to perform acquisition update delay optimization; the acquisition update integrity evaluation module is used to perform data update integrity analysis based on the acquired acquisition update integrity data if an acquisition update integrity evaluation is performed, and determine whether to perform acquisition update integrity optimization; the stroke risk prediction level module is used to input the stroke risk prediction data corresponding to the obtained qualified acquisition evaluation value into the constructed digital twin model to obtain a stroke risk prediction level, and perform a stroke risk warning based on the stroke risk prediction level, wherein the stroke risk prediction level represents a result output based on the digital twin model, and the qualified acquisition evaluation value represents an acquisition evaluation value that meets a preset acquisition control interval.

[0018] One or more technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages:

[0019] In the above scheme, the acquisition evaluation value is obtained by analyzing the acquisition control data and judging whether to perform acquisition update delay evaluation and acquisition update integrity evaluation. If acquisition update delay evaluation is performed, data update delay analysis is performed and judging whether to perform acquisition update delay optimization. If acquisition update integrity evaluation is performed, data update integrity analysis is performed and judging whether to perform acquisition update integrity optimization. Finally, the stroke risk prediction level is obtained based on the qualified acquisition evaluation value, thereby improving the reliability of the stroke risk prediction level output by the digital twin model, and further improving the accuracy of the stroke risk warning data.

[0020] The acquisition evaluation value is obtained by multiplying the obtained acquisition control data and the preset acquisition control weight group, and then the blood pressure acquisition update delay value is obtained by multiplying the acquisition update delay data and the preset acquisition update delay weight group. Finally, the acquisition update integrity data and the preset acquisition update integrity weight group are multiplied to obtain the acquisition update integrity value, thereby improving the reliability of obtaining data related to stroke risk prediction, and thus improving the timeliness of obtaining data related to stroke risk prediction.

[0021] By inputting stroke risk prediction data and preset stroke risk prediction levels into the constructed digital twin model for training to obtain a stroke risk prediction model, and then inputting the real-time acquired stroke risk prediction data into the stroke risk prediction model to obtain the stroke risk prediction level, the timeliness of the stroke risk level warning based on the digital twin model is improved, and then the reliability of the stroke risk level warning based on the digital twin model is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 A flowchart of a stroke risk warning method based on digital twins provided in an embodiment of the present invention;

[0024] Figure 2 A schematic diagram of the structure of a digital twin-based stroke risk warning system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0025] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the described embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] Unless otherwise defined, the technical or scientific terms used in the present invention shall have the usual meaning understood by persons of ordinary skill in the field to which the present invention belongs. The words "first", "second" and similar terms used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. Similarly, words such as "one", "an" or "the" do not indicate a quantity limitation, but rather indicate the presence of at least one. Words such as "include" or "comprise" mean that the elements or objects preceding the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Words such as "connect" or "connected" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect.

[0027] It should be noted that the terms "up", "down", "left", "right", "front" and "back" used in the present invention are only used to indicate relative position relationships. When the absolute position of the object being described changes, the relative position relationship may also change accordingly.

[0028] The present invention provides a stroke risk warning method based on digital twins. The method obtains an acquisition evaluation value by analyzing acquisition control data and determines whether to perform acquisition update delay evaluation and acquisition update integrity evaluation. If an acquisition update delay evaluation is performed, a data update delay analysis is performed and it is determined whether to perform acquisition update delay optimization. If an acquisition update integrity evaluation is performed, a data update integrity analysis is performed and it is determined whether to perform acquisition update integrity optimization. Finally, a stroke risk prediction level is obtained based on the qualified acquisition evaluation value, thereby achieving the effect of improving the accuracy of stroke risk warning data.

[0029] like Figure 1 As shown, a flowchart of a stroke risk warning method based on digital twins provided by an embodiment of the present invention is provided. The stroke risk warning method based on digital twins includes the following steps:

[0030] Collection evaluation: Analyze the acquired collection control data to obtain the collection evaluation value and determine whether to perform collection update delay evaluation and collection update integrity evaluation;

[0031] Collection update delay evaluation: If collection update delay evaluation is performed, data update delay analysis is performed based on the acquired collection update delay data to determine whether collection update delay optimization is performed;

[0032] Collection and update integrity assessment: If collection and update integrity assessment is performed, data update integrity analysis is performed based on the acquired collection and update integrity data to determine whether collection and update integrity optimization is required.

[0033] Stroke risk prediction: The stroke risk prediction data corresponding to the qualified collection assessment value is input into the constructed digital twin model to obtain the stroke risk prediction level, and a stroke risk warning is performed based on the stroke risk prediction level. The stroke risk prediction level represents the result based on the output of the digital twin model, and the qualified collection assessment value represents the collection assessment value that meets the preset collection control interval.

[0034] It should be added that the acquisition control data is used to reflect the influence of the acquisition control parameters on the acquisition control of blood pressure-related data within a preset time period, specifically including the gas inflow-pressure influence value, the gas inflow-number influence value, the gas outflow-pressure influence value and the gas outflow-number influence value; the acquisition control data is obtained based on the acquisition control parameters and the preset acquisition control parameters obtained from the database; the acquisition control parameters include the maximum gas inflow rate, the maximum inflation pressure value, the maximum inflation number value, the maximum gas outflow rate, the maximum deflation pressure value and the maximum deflation number value; the preset acquisition control parameters include the preset maximum inflow rate, the preset maximum inflation pressure, the preset maximum inflation number, the preset maximum outflow rate, the preset maximum deflation pressure and the preset maximum deflation number.

[0035] Among them, the gas inflow rate of the preset position point of the blood pressure monitor airbag within the preset time period is monitored and obtained by the pressure sensor and the flow sensor, and its maximum value, that is, the maximum gas inflow rate, is counted; the pressure at the preset position point inside the cuff of the blood pressure monitor during the inflation process within the preset time period is monitored by the pressure sensor, and its maximum value, that is, the maximum inflation pressure value, is counted; the number of inflations within the preset time period is monitored by the built-in counter of the blood pressure monitor, and its maximum value, that is, the maximum inflation number value, is counted; the gas outflow rate of the preset position point of the blood pressure monitor airbag within the preset time period is monitored and analyzed by the pressure sensor and the flow sensor, and its maximum value, that is, the maximum gas outflow rate, is counted; the pressure at the preset position point inside the cuff of the blood pressure monitor during the deflation process within the preset time period is monitored by the pressure sensor, and its maximum value, that is, the maximum deflation pressure value, is counted; the number of deflations within the preset time period is monitored by the built-in counter of the blood pressure monitor, and its maximum value, that is, the maximum deflation number value, is counted.

[0036] The aforementioned database is a database for storing various set data in a digital twin-based stroke risk warning method provided by an embodiment of the present invention. The database includes but is not limited to a preset maximum inflow rate, a preset maximum inflation pressure, a preset maximum number of inflations, and the like. The various values ​​are directly set by technicians. For example, the preset maximum inflow rate is represented by the maximum value of the gas inflow rate monitored during the historical time period in the database, the preset maximum inflation pressure is represented by the maximum value of the inflation gas pressure during the historical time period in the database, the preset maximum number of inflations is represented by the maximum value of the inflation times during the historical time period in the database, the preset maximum outflow rate is represented by the maximum value of the gas outflow rate monitored during the historical time period in the database, the preset maximum deflation pressure is represented by the maximum value of the deflation gas pressure during the historical time period in the database, and the preset maximum deflation times is represented by the maximum value of the deflation times during the historical time period in the database. The units of the maximum gas inflow rate, the maximum gas outflow rate, the preset maximum inflow rate, and the preset maximum outflow rate are all meters per second, the units of the maximum inflation pressure, the maximum deflation pressure, the preset maximum inflation pressure, and the preset maximum deflation pressure are all Pascals, and the units of the maximum number of inflations, the maximum number of deflations, the preset maximum number of inflations, and the preset maximum number of deflations are all times.

[0037] The acquisition update delay data is used to reflect the impact of the acquisition update delay parameters on the synchronization of blood pressure-related data updates within a preset time period, specifically including the response and number evaluation value, the response and interval evaluation value, the update and number evaluation value, and the update and interval evaluation value; the acquisition update delay data is obtained based on the acquisition update delay parameters and the preset acquisition update delay parameters obtained from the database; the acquisition update delay parameters include the maximum response delay time, the maximum inflation and deflation times, the maximum inflation interval time, and the maximum update delay time; the preset acquisition update delay parameters include the preset maximum response delay time, the preset maximum inflation and deflation times, the preset maximum inflation interval time, and the preset maximum update delay time.

[0038] Among them, the blood pressure monitor, timer, and signal generator are used to analyze and obtain the maximum absolute value of the difference between the response time of the blood pressure monitor and the preset response time within the preset time period, that is, the maximum response delay time; the built-in counter of the blood pressure monitor is used to monitor the sum of the number of inflation and deflation times within the preset time period and count its maximum value, that is, the maximum inflation and deflation times; the blood pressure monitor and timer are used to monitor the inflation interval time within the preset time period and count its maximum value, that is, the maximum inflation interval time; the blood pressure monitor, timer, and signal generator are used to analyze and obtain the maximum absolute value of the difference between the update time of the blood pressure monitor and the preset update time within the preset time period, that is, the maximum update delay time.

[0039] The preset maximum response delay is represented by the maximum response delay of blood pressure monitors during the historical time period in the database. The preset maximum number of inflation and deflation times is represented by the maximum total number of inflations and deflations during the historical time period in the database. The preset maximum inflation interval is represented by the maximum inflation interval during the historical time period in the database. The preset maximum update delay is represented by the maximum update delay of blood pressure monitors during the historical time period in the database. The maximum response delay, maximum update delay, maximum inflation interval, preset maximum response delay, preset maximum inflation interval, and preset maximum update delay are all expressed in seconds. The maximum number of inflations and deflations and the preset maximum number of inflations and deflations are expressed in times.

[0040] The collection update integrity data is used to reflect the impact of the collection update integrity parameters on the collection integrity of blood pressure-related data within a preset time period, specifically including the collection completeness and number evaluation value, the collection completeness and interval evaluation value, and the collection completeness and noise evaluation value; the collection update integrity data is obtained based on the collection update integrity parameters and the preset collection update integrity parameters obtained from the database; the collection update integrity parameters include the maximum amount of collected blood pressure data and the collection blood pressure noise ratio; the preset collection update integrity parameters include the preset maximum amount of collected blood pressure data and the preset maximum value of the blood pressure collection noise ratio.

[0041] Among them, the amount of data corresponding to the blood pressure related data (such as systolic pressure, diastolic pressure, etc.) within a preset time period is obtained by the built-in memory of the blood pressure monitor and its maximum value is counted, that is, the maximum blood pressure data amount is collected; the ratio of the noise power and signal power corresponding to the blood pressure related data within the preset time period is analyzed and obtained by the blood pressure monitor and signal analysis software (such as MATrix LABoratory) and its maximum value is counted, that is, the blood pressure noise ratio is collected.

[0042] The preset maximum blood pressure data volume is represented by the maximum amount of blood pressure data collected during the historical time period in the database. The preset maximum blood pressure data noise ratio is represented by the maximum amount of blood pressure data collected during the historical time period in the database. Both the maximum amount of blood pressure data collected and the preset maximum amount of blood pressure data collected are expressed in bits.

[0043] In this embodiment, by monitoring acquisition control data, acquisition update delay data, acquisition update integrity data and physiological data such as heart rate, blood pressure, blood oxygen saturation, etc., the digital twin model can output the corresponding stroke risk prediction level. When the monitored acquisition evaluation value is not within the preset acquisition control interval, it is necessary to determine whether to perform acquisition update delay optimization and acquisition update integrity optimization based on the acquired blood pressure acquisition update delay value and acquisition update integrity value; when the monitored acquisition evaluation value is within the preset acquisition control interval, the blood pressure acquisition update delay value is not higher than the preset acquisition update delay threshold, and the acquisition update integrity value is not lower than the preset acquisition update integrity threshold, the corresponding stroke risk prediction data (blood pressure, heart rate, blood lipids, etc.) is input into the constructed digital twin model (existing) for training to obtain a stroke risk prediction model, and the real-time stroke risk prediction data is input into the stroke risk prediction model to output the stroke risk prediction level; there is an interactive relationship between the acquisition evaluation value, the acquisition update integrity value and the blood pressure acquisition update delay value, which jointly affect the process and results of stroke risk prediction; through the method of the present invention, the effect of improving the accuracy of stroke risk warning data can be achieved.

[0044] It should be added that the blood pressure monitor in the embodiment of the present invention is an ambulatory blood pressure monitor, which is suitable for performing brain damage and promoting the damage repair process through RIC (Remote Ischemic Conditioning) technology. The limb blood pressure cuff provided by the blood pressure monitor can be repeatedly inflated and deflated to repeatedly and briefly block and restore blood flow to non-vital organs or tissues such as limbs, thereby stimulating the body's endogenous protection mechanism, improving the ischemia and hypoxia tolerance of remote organs, and providing the brain with ischemic tolerance and effective protection against subsequent fatal ischemia.

[0045] The specific process of analyzing the acquired acquisition control data to obtain the acquisition evaluation value is as follows: the first inflow operation processing is performed on the obtained gas inflow first processing value to obtain the gas inflow-pressure impact value, that is, The first inflow operation processing represents multiplying the result of the ratio operation of the maximum gas inflow rate and the preset maximum inflow rate, the result of the ratio operation of the maximum inflation pressure value and the preset maximum inflation pressure, and the preset inflation pressure weight value. The first gas inflow processing value includes the maximum gas inflow rate, the maximum inflation pressure value, the preset inflation pressure weight value, the preset maximum inflow rate and the preset maximum inflation pressure. The maximum gas inflow rate and the maximum inflation pressure value are in direct proportion. The maximum gas inflow rate represents the maximum value of the rate at which gas flows into the airbag within the preset time period. The second inflow operation processing is performed on the obtained gas inflow second processing value to obtain the gas inflow-number influence value, that is, The second inflow operation processing represents multiplying the result of the ratio operation of the maximum gas inflow rate and the preset maximum inflow rate, the result of the ratio operation of the maximum inflation number value and the preset maximum inflation number value, and the preset inflation number weight value. The second processed value of gas inflow includes the maximum gas inflow rate, the maximum inflation number value, the preset inflation number weight value, the preset maximum inflow rate and the preset maximum inflation number, and the maximum gas inflow rate and the maximum inflation number value are in direct proportion. The first outflow operation processing is performed on the obtained gas outflow first processed value to obtain the gas outflow-pressure influence value, that is, The first outflow operation processing represents multiplying the result of the ratio operation of the maximum gas outflow rate and the preset maximum outflow rate, the result of the ratio operation of the maximum deflation pressure value and the preset maximum deflation pressure, and the preset deflation pressure weight value. The first gas outflow processing value includes the maximum gas outflow rate, the maximum deflation pressure value, the preset deflation pressure weight value, the preset maximum outflow rate and the preset maximum deflation pressure. The maximum gas outflow rate and the maximum deflation pressure value are in direct proportion. The second outflow operation processing is performed on the obtained gas outflow second processing value to obtain the gas outflow-number influence value, that is, The second outflow operation processing represents multiplying the result of the ratio operation of the maximum gas outflow rate and the preset maximum outflow rate, the result of the ratio operation of the maximum deflation times and the preset maximum deflation times with the preset deflation times weight value, and the gas outflow second processing value includes the maximum gas outflow rate, the maximum deflation times, the preset deflation times weight value, the preset maximum outflow rate and the preset maximum deflation times, and the maximum gas outflow rate and the maximum deflation times are in direct proportion; the acquisition control data obtained and the preset acquisition control weight group obtained from the database are multiplied to obtain the acquisition evaluation value; the acquisition evaluation value is used to evaluate the blood pressure monitoring process based on digital twins The blood pressure related data collection and control situation during the process; the gas inflow-pressure impact value represents the quantitative data of the influence of the maximum gas inflow rate and the maximum inflation pressure value on the blood pressure related data collection and control, the gas inflow-times impact value represents the quantitative data of the influence of the maximum gas inflow rate and the maximum inflation times value on the blood pressure related data collection and control, the gas outflow-pressure impact value represents the quantitative data of the influence of the maximum gas outflow rate and the maximum deflation pressure value on the blood pressure related data collection and control, the gas outflow-times impact value represents the quantitative data of the influence of the maximum gas outflow rate and the maximum deflation times value on the blood pressure related data collection and control.

[0046] The acquisition control data is inversely proportional to the acquisition evaluation value;

[0047] The collection evaluation value is obtained by the following method:

[0048]

[0049] Where, Indicates the collection evaluation value in the u1-th preset time period, u1=1,2,...,g1, u1 represents the number of the preset time period, g1 represents the total number of preset time periods, Indicates the gas inflow-pressure impact value in the u1th preset time period, Indicates the gas inflow-number impact value within the u1th preset time period, Indicates the gas outflow-pressure impact value in the u1th preset time period, It represents the gas outflow-number impact value in the u1-th preset time period, P1 represents the preset gas inflow first weight, P2 represents the preset gas inflow second weight, P3 represents the preset gas outflow first weight, and P4 represents the preset gas outflow second weight.

[0050] Indicates the maximum gas inflow rate within the u1th preset time period, Indicates the maximum inflation pressure value within the u1th preset time period, Indicates the maximum number of inflation times within the u1th preset time period, Indicates the maximum gas outflow rate within the u1th preset time period, Indicates the maximum deflation pressure value within the u1th preset time period, Indicates the maximum number of deflation times within the u1th preset time period. Indicates the preset maximum inflow rate. Indicates the preset maximum inflation pressure. Indicates the preset maximum number of inflation times. Indicates the preset maximum outflow rate. Indicates the preset maximum deflation pressure. Indicates the preset maximum deflation times, W 1 Indicates the preset inflation pressure weight value, W 2 Indicates the preset inflation times weight value, W 3 Indicates the preset deflation pressure weight value, W 4 It represents the preset deflation times weight value, and e represents a natural constant.

[0051] In this embodiment, a set of mapping groups is obtained from a database. Within this mapping group, a mapping set is defined that reflects the mapping relationship between acquisition control data and corresponding preset acquisition control weight groups. Real-time acquisition control data is input into the mapping group to obtain a corresponding preset acquisition control weight group. The mapping relationships within this mapping set can be one-to-one or many-to-one. For example, in this embodiment, the weights range from 0 to 1. The preset acquisition control weight group includes a preset gas inflow first weight, a preset gas inflow second weight, a preset gas outflow first weight, and a preset gas outflow second weight, and is used to reflect the impact of the acquisition control data on the acquisition evaluation value.

[0052] It should be added that, in this embodiment, a mapping set is set in advance to reflect the mapping relationship between the preset inflation pressure weight value, preset inflation number weight value, preset deflation pressure weight value and preset deflation number weight value corresponding to the acquisition control input data; by inputting the real-time acquisition control input data into the mapping set, the corresponding preset inflation pressure weight value, preset inflation number weight value, preset deflation pressure weight value and preset deflation number weight value can be obtained; the mapping relationship in the mapping set can be a one-to-one correspondence or a many-to-one relationship; for example, in this embodiment, the value range of the weight is 0-1; the acquisition control input data includes the maximum gas inflow rate and the maximum inflation pressure value, the maximum gas inflow rate and the maximum inflation number value, the maximum gas outflow rate and the maximum deflation pressure value, and the maximum gas outflow rate and the maximum inflation pressure value.

[0053] The algorithm of this embodiment combines the acquisition control data analysis to obtain the acquisition evaluation value. The larger the gas inflow-pressure impact value, the greater the impact of the gas inflow rate and inflation pressure on the acquisition and control of blood pressure-related data, resulting in a decrease in the acquisition evaluation value; the larger the gas inflow-number impact value, the greater the impact of the gas inflow rate and inflation number on the acquisition and control of blood pressure-related data, resulting in a decrease in the acquisition evaluation value; the larger the gas outflow-pressure impact value, the greater the impact of the gas outflow rate and deflation number on the acquisition and control of blood pressure-related data, resulting in a decrease in the acquisition evaluation value; the larger the gas outflow-number impact value, the greater the impact of the gas outflow rate and deflation number on the acquisition and control of blood pressure-related data, resulting in a decrease in the acquisition evaluation value. In summary, the acquisition control data and the acquisition evaluation value are inversely proportional.

[0054] The collected control data in the algorithm of this embodiment does not exist independently, and the variables are interrelated, which requires comprehensive analysis. When the maximum value of the gas inflow rate increases, the inflation speed increases, which may cause the maximum inflation pressure value to rise; the faster the gas outflow rate, the more drastic the pressure change, which may cause the maximum deflation pressure value to drop; the maximum deflation pressure value is also affected by the maximum deflation times. The larger the maximum deflation times, the greater the pressure increase, which may lead to an increase in the deflation pressure, and then the maximum deflation pressure value increases; the maximum inflation pressure value is affected by the maximum inflation times. The larger the maximum inflation times, the greater the maximum inflation times, which may lead to a greater maximum inflation pressure value, which may have a negative impact on the stability and accuracy of blood pressure monitoring. By analyzing the comprehensive impact between parameters, an accurate assessment of the blood pressure-related data acquisition and control situation in the blood pressure monitoring process based on digital twins is achieved, thereby improving the accuracy of stroke risk warning data.

[0055] Among them, the specific process of judging whether to perform acquisition update delay evaluation and acquisition update integrity evaluation is as follows: judge whether the acquired acquisition evaluation value is within the preset acquisition control interval, and the preset acquisition control interval is the interval range corresponding to the preset acquisition control maximum value and the preset acquisition control minimum value; when the acquisition evaluation value is within the preset acquisition control interval, mark the numerical value corresponding to the corresponding acquisition evaluation value as a qualified acquisition evaluation value; a qualified acquisition evaluation value represents an acquisition evaluation value within the preset acquisition control interval; when the acquisition evaluation value is greater than the preset acquisition control maximum value, it indicates that the change in the acquisition frequency of blood pressure-related data has an impact on the stroke acquisition update, and an acquisition update delay evaluation is performed; when the acquisition evaluation value is less than the preset acquisition control minimum value, it indicates that the change in the acquisition frequency of blood pressure-related data has an impact on the stroke acquisition integrity, and an acquisition update integrity evaluation is performed.

[0056] It should be added that the specific process of determining whether to perform collection update delay optimization is as follows: determine whether the monitored blood pressure collection update delay value is not higher than the preset collection update delay threshold; if so, do not perform collection update delay optimization, otherwise send a prompt to the preset personnel to perform collection update delay optimization; when the blood pressure collection update delay value is still higher than the preset collection update delay threshold after collection update delay optimization, send an alarm prompt to the preset personnel; collection update delay optimization includes reducing the collection frequency and prompting to release the pressure; reducing the collection frequency means that the preset personnel reduces the collection frequency of blood pressure-related data step by step by a preset multiple; prompting to release the pressure means sending a prompt to the preset personnel to adjust the number of times the blood pressure monitor releases the pressure.

[0057] The specific process of determining whether to perform collection update integrity optimization is as follows: determine whether the monitored collection update integrity value is not lower than the preset collection update integrity threshold obtained from the database; if so, do not perform collection update integrity optimization, otherwise send a prompt to the preset personnel to perform collection update integrity optimization; when the collection update integrity value is still lower than the preset collection update integrity threshold after collection update integrity optimization, send an alarm prompt to the preset personnel; collection update integrity optimization includes increasing the collection frequency and prompting for charging; increasing the collection frequency means that the preset personnel increases the collection frequency of blood pressure-related data step by step by a preset multiple; prompting for charging means sending a prompt to the preset personnel to adjust the charging times of the blood pressure monitor.

[0058] In this embodiment, the preset acquisition control maximum value is represented by the maximum value of the acquisition evaluation value of the historical time period in the database, the preset acquisition control minimum value is represented by the minimum value of the acquisition evaluation value of the historical time period in the database, the preset acquisition update delay threshold is represented by the average value of the blood pressure acquisition update delay value of the historical time period in the database, and the preset acquisition update complete threshold is represented by the average value of the acquisition update complete value of the historical time period in the database.

[0059] When the monitored blood pressure collection update delay value is higher than the preset collection update delay threshold, collection update delay optimization is required, that is, by pre-setting personnel to gradually reduce the collection frequency by a preset multiple, and gradually reduce the number of pressure releases of the blood pressure monitor by a preset multiple to achieve improved data processing speed and reduced delays (update delay and response delay); when the monitored collection update completeness value is lower than the preset collection update completeness threshold, collection update integrity optimization is required, that is, by pre-setting personnel to gradually increase the collection frequency by a preset multiple, and gradually reduce the number of pressure injections of the blood pressure monitor by a preset multiple to increase the number of blood pressure data collections and obtain more comprehensive data samples, thereby improving the accuracy of stroke risk warning data.

[0060] Among them, the specific process of performing data update delay analysis based on the acquired acquisition update delay data is as follows: the blood pressure acquisition update delay value is obtained by performing a product operation on the acquisition update delay data and the preset acquisition update delay weight group obtained from the database; the blood pressure acquisition update delay value is used to reflect the update delay of the blood pressure-related data in the acquisition update delay evaluation; the preset acquisition update delay weight group includes a response first weight value, a response second weight value, an update first weight value and an update second weight value; the acquisition update delay data is directly proportional to the blood pressure acquisition update delay value; the response and number evaluation value is obtained by performing a first response delay operation on the response delay first processing value, that is, The first response delay operation processing represents the result of the ratio operation of the maximum number of inflation and deflation times and the preset maximum number of inflation and deflation times, the result of the ratio operation of the maximum response delay time and the preset maximum response delay time, and the product operation of the preset response and inflation and deflation weight. The first processing value of the response delay includes the maximum response delay time, the maximum number of inflation and deflation times, the preset response and inflation and deflation weight, the maximum value of the preset response delay time and the maximum value of the preset inflation and deflation times. The maximum response delay time is directly proportional to the maximum number of inflation and deflation times. The maximum response delay time represents the maximum absolute value of the difference between the response time of the blood pressure monitor within the preset time period and the preset response time obtained from the database. The maximum number of inflation and deflation times represents the maximum value of the sum of the inflation and deflation times monitored by the blood pressure monitor within the preset time period. The response and interval evaluation value is obtained by performing the second response delay operation processing on the second processing value of the response delay, that is, The second response delay operation processing represents the product operation of the result of the ratio operation of the maximum value of the inflation interval and the preset maximum value of the inflation interval, the result of the ratio operation of the maximum value of the response delay and the preset maximum value of the response delay, and the preset response and interval weight; the second processing value of the response delay includes the maximum value of the response delay, the maximum value of the inflation interval, the preset response and interval weight, the preset maximum value of the response delay and the preset maximum value of the inflation interval, and the maximum value of the response delay is directly proportional to the maximum value of the inflation interval; the update and number evaluation value is obtained by performing the first update delay operation on the first processing value of the update delay, that is The first update delay operation processing represents the result of the ratio operation of the maximum number of inflation and deflation times and the preset maximum number of inflation and deflation times, the result of the ratio operation of the maximum update delay time and the preset maximum update delay time, and the product operation of the preset update and inflation and deflation weights. The first processing value of the update delay includes the maximum update delay time, the maximum number of inflation and deflation times, the preset update and inflation and deflation weights, the maximum preset update delay time and the maximum preset number of inflation and deflation times. The maximum update delay time is directly proportional to the maximum number of inflation and deflation times. The maximum update delay time represents the maximum absolute value of the difference between the update time of the blood pressure monitor and the preset update time obtained from the database within the preset time period; the update and interval evaluation value is obtained by performing the second update delay operation processing on the second processing value of the update delay, that is, The second update delay operation processing represents the result of the ratio operation of the maximum inflation interval time and the preset inflation interval time, the result of the ratio operation of the maximum update delay time and the preset update delay time, and the product operation of the preset update and interval weight. The second processing value of the update delay includes the maximum update delay time, the maximum inflation interval time, the preset update and interval weight, the preset maximum update delay time and the preset maximum inflation interval time. The maximum update delay time is directly proportional to the maximum inflation interval time; the response and number evaluation value represents the quantitative data of the influence of the maximum inflation and deflation times and the maximum response delay time on the update delay of blood pressure related data, the response and interval evaluation value represents the quantitative data of the influence of the maximum inflation interval time and the maximum response delay time on the update delay of blood pressure related data, the update and number evaluation value represents the quantitative data of the influence of the maximum inflation and deflation times and the maximum update delay time on the update delay of blood pressure related data, and the update and interval evaluation value represents the quantitative data of the influence of the maximum inflation interval time and the maximum update delay time on the update delay of blood pressure related data.

[0061] The blood pressure acquisition update delay value is obtained by the following method:

[0062]

[0063] Where, represents the blood pressure collection update delay value in the a1th delayed evaluation time period, a1=1,2,...,b1, a1 represents the number of the delayed evaluation time period, b1 represents the total number of delayed evaluation time periods, and the delayed evaluation time period represents the preset time period in the analysis process based on the acquired collection update delay data. Indicates the response and number evaluation values ​​in the a1th delayed evaluation period, represents the response and interval evaluation value in the a1th delayed evaluation period, Indicates the update and number evaluation values ​​in the a1th delayed evaluation period, represents the update and interval evaluation value in the a1th delayed evaluation time period, K1 represents the response to the first weight value, K2 represents the response to the second weight value, K3 represents the update of the first weight value, and K4 represents the update of the second weight value.

[0064] Indicates the maximum response delay duration in the a1th delay evaluation period. Indicates the maximum number of inflation and deflation times in the a1th delayed evaluation period, Indicates the maximum duration of the inflation interval in the a1th delayed evaluation period, Indicates the maximum update delay duration in the a1th delay evaluation period. Indicates the maximum preset response delay time. Indicates the preset maximum number of inflation and deflation times. Indicates the preset maximum value of the inflation interval. represents the maximum value of the preset update delay, h1 represents the preset response and inflation and deflation weight, h2 represents the preset response and interval weight, h3 represents the preset update and inflation and deflation weight, h4 represents the preset update and interval weight, and e represents a natural constant.

[0065] In this embodiment, a group of mapping groups is obtained from the database, and a mapping set is set in the mapping group, which can be used to reflect the mapping relationship between the acquisition and update delay data and the corresponding preset acquisition and update delay weight group; the corresponding preset acquisition and update delay weight group is obtained by inputting the real-time acquisition and update delay data into the mapping group; the mapping relationship in the mapping set can be a one-to-one correspondence or a many-to-one relationship; for example, in this embodiment, the weight value range is 0-1.

[0066] It should be added that, in this embodiment, a mapping set is set in advance to reflect the mapping relationship between the preset response and inflation and deflation weights, preset response and interval weights, preset updates and inflation and deflation weights, and preset updates and interval weights corresponding to the update delay input data; by inputting the real-time update delay input data into the mapping set, the corresponding preset response and inflation and deflation weights, preset response and interval weights, preset updates and inflation and deflation weights, and preset updates and interval weights can be obtained; the mapping relationship in the mapping set can be a one-to-one correspondence or a many-to-one relationship; for example, in this embodiment, the value range of the weight is 0-1; the update delay input data includes the maximum number of inflation and deflation times and the maximum response delay time, the maximum inflation interval time and the maximum response delay time, the maximum update delay time and the maximum number of inflation and deflation times, and the maximum update delay time and the maximum inflation interval time.

[0067] The algorithm of this embodiment combines the collection and update delay data analysis to obtain the blood pressure collection and update delay value. The larger the response and number evaluation value, the greater the impact of the response delay time and the number of inflation and deflation times on the blood pressure-related data update delay, resulting in a larger blood pressure collection and update delay value; the larger the response and interval evaluation value, the greater the impact of the response delay time and the inflation interval time on the blood pressure-related data update delay, resulting in a larger blood pressure collection and update delay value; the larger the update and number evaluation value, the greater the impact of the update delay time and the number of inflation and deflation times on the blood pressure-related data update delay, resulting in a larger blood pressure collection and update delay value; the larger the update and interval evaluation value, the greater the impact of the update delay time and the inflation interval time on the blood pressure-related data update delay, resulting in a larger blood pressure collection and update delay value. In summary, the collection and update delay data is directly proportional to the blood pressure collection and update delay value.

[0068] In the algorithm of this embodiment, the acquisition and update delay data do not exist independently. The variables are interrelated and require comprehensive analysis. When the maximum value of the number of inflation and deflation times is larger, it means that the monitoring reaction speed is more likely to slow down, which may lead to a delay in the monitoring response, thereby increasing the maximum value of the response delay time; a longer inflation interval may also lead to reduced monitoring efficiency, because the monitoring cycle will become longer, which may increase the possibility of response delay, resulting in an increase in the maximum value of the response delay time; a shorter inflation interval may lead to more frequent inflation and deflation operations, thereby increasing the number of inflation and deflation times, resulting in an increase in the maximum value of the inflation and deflation times; as the number of inflation and deflation times increases, it may take longer to update blood pressure-related data, resulting in an increase in the maximum value of the update delay time; by analyzing the comprehensive influence between the parameters, an accurate assessment of the update delay of blood pressure-related data in the acquisition and update delay assessment is achieved, thereby achieving the effect of improving the accuracy of stroke risk warning data.

[0069] The specific process of performing data update integrity analysis based on the acquired collection update integrity data is as follows: obtain the complete and inflation and deflation data group, the complete and interval data group, and the complete and noise ratio data group; obtain the collection completeness and number evaluation value by performing complete and inflation and deflation operations on the complete and inflation and deflation data group, that is, The complete and inflation and deflation operation processing represents the result of performing a ratio operation on the maximum amount of collected blood pressure data and the preset maximum amount of collected blood pressure data, the result of performing a ratio operation on the maximum number of inflation and deflation times and the preset maximum number of inflation and deflation times, and the product operation on the preset complete and inflation and deflation weight value. The complete and inflation and deflation data group includes the maximum amount of collected blood pressure data, the maximum number of inflation and deflation times, the preset complete and inflation and deflation weight value, the preset maximum amount of collected blood pressure data, and the preset maximum number of inflation and deflation times. The maximum amount of collected blood pressure data represents the maximum amount of data corresponding to the blood pressure-related data within the preset time period. The collection complete and interval evaluation value is obtained by performing a complete and interval operation processing on the complete and interval data group, that is, The complete and interval operation processing means performing a product operation on the result of performing a ratio operation on the maximum amount of collected blood pressure data and the preset maximum amount of collected blood pressure data, the result of performing a ratio operation on the maximum amount of inflation interval and the preset maximum amount of inflation interval, and the preset complete and interval weight value. The complete and interval data group includes the maximum amount of collected blood pressure data, the maximum amount of inflation interval, the preset complete and interval weight value, the preset maximum amount of collected blood pressure data, and the preset maximum amount of inflation interval; the collection complete and noise evaluation value is obtained by performing a complete and noise ratio operation on the complete and noise ratio data group, that is, The completeness and noise ratio calculation processing means performing a product operation on the result of performing a ratio operation on the maximum amount of collected blood pressure data and the preset maximum amount of collected blood pressure data, the result of performing a ratio operation on the preset completeness and noise ratio weight value and the collected blood pressure noise ratio, and the preset completeness and noise ratio weight value. The completeness and noise ratio data group includes the maximum amount of collected blood pressure data, the collected blood pressure noise ratio, the preset completeness and noise ratio weight value, the preset maximum amount of collected blood pressure data, and the preset maximum value of the blood pressure collection noise ratio; the collection update completeness value is obtained by performing a product operation on the collection update completeness data and the preset collection update completeness weight group obtained from the database; the collection update completeness value is used to reflect the update completeness of blood pressure-related data during the collection update integrity assessment process; the collection update completeness The value is directly proportional to the collection and update integrity data; the maximum amount of collected blood pressure data is directly proportional to the maximum number of inflation and deflation times; the maximum amount of collected blood pressure data is directly proportional to the maximum inflation interval time; the maximum amount of collected blood pressure data is inversely proportional to the collection blood pressure noise ratio. The collection completeness and number evaluation value represents the quantitative data on the degree of influence of the maximum amount of collected blood pressure data and the maximum number of inflation and deflation times on the integrity of blood pressure-related data updates. The collection completeness and interval evaluation value represents the quantitative data on the degree of influence of the maximum amount of collected blood pressure data and the maximum inflation interval time on the integrity of blood pressure-related data updates. The collection completeness and noise evaluation value represents the quantitative data on the degree of influence of the maximum amount of collected blood pressure data and the maximum inflation interval time on the integrity of blood pressure-related data updates.

[0070] The collection update complete value is obtained by the following method:

[0071]

[0072] Where, Indicates the collection and update integrity value of the n1th collection and update integrity assessment period. The collection and update integrity assessment period is a preset time period during the analysis of the acquired collection and update integrity data. Indicates the collection completeness and number evaluation value in the n1th collection update integrity evaluation period. Indicates the collection integrity and interval evaluation value in the n1th collection update integrity evaluation period. It represents the collection integrity and noise evaluation value in the n1th collection update integrity evaluation time period, D1 represents the preset collection integrity first weight value, D2 represents the preset collection integrity second weight value, and D3 represents the preset collection integrity third weight value.

[0073] Indicates the maximum amount of blood pressure data collected during the n1th collection update integrity assessment period. Indicates the maximum number of inflation and deflation times in the n1th acquisition update integrity assessment time period. Indicates the maximum duration of the inflation interval in the n1th acquisition update integrity assessment time period. represents the noise ratio of the collected blood pressure in the n1th collection update integrity assessment period, Indicates the preset maximum number of inflation and deflation times. Indicates the preset maximum value of the inflation interval. Indicates the preset maximum amount of blood pressure data collected. represents the preset maximum value of the blood pressure acquisition noise ratio, X1 represents the preset complete and inflation and deflation weight values, X2 represents the preset complete and interval weight values, X3 represents the preset complete and noise ratio weight values, and e represents a natural constant.

[0074] In this embodiment, a mapping group is obtained from a database. Within this mapping group, a mapping set is defined that reflects the mapping relationship between collection and update integrity data and corresponding preset collection and update integrity weight groups. Real-time collection and update integrity data is input into the mapping group to obtain a corresponding preset collection and update integrity weight group. The mapping relationships within this mapping set can be one-to-one or many-to-one. For example, in this embodiment, the weights range from 0 to 1. The preset collection and update integrity weight group includes a preset collection integrity first weight value, a preset collection integrity second weight value, and a preset collection integrity third weight value, which reflect the degree of influence of the collection and update integrity data on the collection and update integrity value.

[0075] It should be added that, in this embodiment, a mapping set is set in advance to reflect the mapping relationship between the updated integrity input data and the corresponding preset integrity and inflation and deflation weight values, preset integrity and interval weight values, and preset integrity and noise ratio weight values; by inputting the real-time updated integrity input data into the mapping set, the corresponding preset integrity and inflation and deflation weight values, preset integrity and interval weight values, and preset integrity and noise ratio weight values ​​can be obtained; the mapping relationship in the mapping set can be a one-to-one correspondence or a many-to-one relationship; for example, in this embodiment, the value range of the weight is 0-1; the updated integrity input data includes the maximum amount of collected blood pressure data and the maximum number of inflation and deflation times, the maximum amount of collected blood pressure data and the maximum inflation interval time, and the maximum amount of collected blood pressure data and the collected blood pressure noise ratio.

[0076] The algorithm of this embodiment combines the collection and update integrity data analysis to obtain the collection and update completeness value. The larger the collection completeness and number evaluation value, the greater the impact of the amount of blood pressure data collected and the number of inflation and deflation times on the integrity of the blood pressure-related data update, resulting in an increase in the collection and update completeness value; the larger the collection completeness and interval evaluation value, the greater the impact of the amount of blood pressure data collected and the inflation interval duration on the integrity of the blood pressure-related data update, resulting in an increase in the collection and update completeness value; the larger the collection completeness and noise evaluation value, the greater the impact of the amount of blood pressure data collected and the blood pressure noise ratio on the integrity of the blood pressure-related data update, resulting in an increase in the collection and update completeness value. In summary, the collection and update integrity data is directly proportional to the collection and update completeness value.

[0077] In the algorithm of this embodiment, the collected and updated integrity data does not exist independently. The variables are interrelated and require comprehensive analysis. When the amount of collected blood pressure data increases, it means that more blood pressure information can be obtained, which helps to improve the accuracy and completeness of blood pressure monitoring. The larger the amount of collected blood pressure data, the longer the update time may be, and even more noise may be introduced, resulting in an increase in the noise ratio of the collected blood pressure. The more times of inflation and deflation, the more noise interference may be increased, thereby affecting the quality of data collection. The longer the inflation interval, the less data integrity and monitoring continuity may be, resulting in stronger noise interference, which increases the noise ratio of the collected blood pressure. By analyzing the comprehensive influence between the parameters, an accurate assessment of the update integrity of blood pressure-related data during the collection and update integrity assessment is achieved, thereby improving the accuracy of stroke risk warning data.

[0078] Among them, the specific process of stroke risk warning based on the stroke risk prediction level is as follows: the stroke risk prediction data and the preset stroke risk prediction level are input into the constructed digital twin model for training to obtain the stroke risk prediction model; the real-time acquired stroke risk prediction data is input into the stroke risk prediction model to obtain the stroke risk prediction level; when the stroke risk prediction model outputs a first-level warning, it indicates that the stroke risk level is high, and a first-level warning prompt is sent to the preset personnel; when the stroke risk prediction model outputs a second-level warning, it indicates that the stroke risk level is low, and a second-level warning prompt is sent to the preset personnel; the stroke risk prediction level includes a first-level warning and a second-level warning; the stroke risk prediction data includes a qualified collection assessment value and blood pressure-related data corresponding to the qualified collection assessment value.

[0079] In this embodiment, the acquired stroke risk prediction data and the preset stroke risk prediction level are input into the existing digital twin model for training to obtain a trained digital twin model, i.e., a stroke risk prediction model. Then, the acquired real-time stroke risk prediction data is input into the stroke risk prediction model to output a stroke risk prediction level. If a first-level warning is output, indicating that the stroke risk level is high, a first-level warning prompt is sent to the preset personnel. If a second-level warning is output, indicating that the stroke risk level is relatively low (first-level warning), a second-level warning prompt is sent to the preset personnel. After receiving the warning prompt, the preset personnel can take preset measures to realize real-time monitoring of stroke risk protection to avoid inaccurate prediction results due to data quality issues, thereby achieving the effect of improving the accuracy of stroke risk warning data.

[0080] like Figure 2 The figure shows a schematic diagram of the structure of a digital twin-based stroke risk warning system provided by an embodiment of the present invention. The embodiment of the present invention provides a digital twin-based stroke risk warning system, including an acquisition evaluation module, an acquisition update delay evaluation module, an acquisition update integrity evaluation module, and a stroke risk prediction level module: wherein the acquisition evaluation module is used to analyze the acquired acquisition control data to obtain an acquisition evaluation value and determine whether to perform acquisition update delay evaluation and acquisition update integrity evaluation; the acquisition update delay evaluation module is used to perform data update delay analysis based on the acquired acquisition update delay data if acquisition update delay evaluation is performed, and determine whether to perform acquisition update delay optimization; the acquisition update integrity evaluation module is used to perform data update integrity analysis based on the acquired acquisition update integrity data if acquisition update integrity evaluation is performed, and determine whether to perform acquisition update integrity optimization; the stroke risk prediction level module is used to input the stroke risk prediction data corresponding to the obtained qualified acquisition evaluation value into the constructed digital twin model to obtain a stroke risk prediction level, and perform a stroke risk warning based on the stroke risk prediction level. The stroke risk prediction level represents the result output based on the digital twin model, and the qualified acquisition evaluation value represents the acquisition evaluation value that meets the preset acquisition control interval.

[0081] In this embodiment, the acquisition evaluation value monitored by the acquisition evaluation module is used to determine whether to perform acquisition update delay evaluation and acquisition update integrity evaluation. When the acquisition evaluation value is within the preset acquisition control range, the acquisition update delay evaluation and acquisition update integrity evaluation are not performed; the acquisition update delay evaluation module and the acquisition update integrity evaluation module are used to perform acquisition update delay evaluation and acquisition update integrity evaluation respectively. When the blood pressure acquisition update delay value monitored by the acquisition update delay evaluation module and the acquisition update integrity evaluation module is not higher than the preset acquisition update delay threshold and the acquisition update integrity value is not lower than the preset acquisition update integrity threshold, the acquisition update delay optimization and acquisition update integrity optimization can be stopped; the acquisition update delay evaluation module can obtain the stroke risk prediction level based on the obtained stroke risk prediction data, thereby improving the accuracy of stroke risk monitoring, and further achieving the effect of improving the accuracy of stroke risk warning data.

[0082] There are a few points to note:

[0083] (1) The drawings of the embodiments of the present invention only relate to the structures related to the embodiments of the present invention. Other structures may refer to conventional designs.

[0084] (2) For the sake of clarity, the thickness of layers or regions in the drawings used to describe the embodiments of the present invention are exaggerated or reduced, that is, these drawings are not drawn to scale. It is understood that when an element such as a layer, film, region, or substrate is referred to as being "on" or "under" another element, the element may be "directly" "on" or "under" the other element or intervening elements may be present.

[0085] (3) In the absence of conflict, the embodiments of the present invention and the features therein may be combined with each other to form new embodiments.

[0086] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. The protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A stroke risk warning method based on digital twins, characterized in that: The following steps are involved: Analyze the acquired collection control data to obtain the collection evaluation value, and determine whether to perform collection update delay evaluation and collection update integrity evaluation; The acquisition control data is used to reflect the influence of the acquisition control parameters on the acquisition control of blood pressure related data within a preset time period, specifically including the gas inflow-pressure influence value, the gas inflow-frequency influence value, the gas outflow-pressure influence value and the gas outflow-frequency influence value; If the collection update delay evaluation is performed, the data update delay analysis is performed based on the acquired collection update delay data to determine whether the collection update delay optimization is performed; The acquisition and update delay data is used to reflect the impact of the acquisition and update delay parameters on the synchronization of blood pressure-related data updates within a preset time period, specifically including response and number evaluation values, response and interval evaluation values, update and number evaluation values, and update and interval evaluation values; The blood pressure collection update delay value is obtained by multiplying the collection update delay data and the preset collection update delay weight group obtained from the database; The specific process of determining whether to perform acquisition update delay optimization is as follows: Determine whether the monitored blood pressure collection update delay value is not higher than the preset collection update delay threshold; if so, do not optimize the collection update delay; otherwise, send a reminder to the preset personnel to optimize the collection update delay; When the blood pressure collection update delay value is still higher than the preset collection update delay threshold after the collection update delay optimization is performed, an alarm prompt is sent to the preset personnel; the collection update delay optimization includes reducing the collection frequency and prompting to release blood pressure; reducing the collection frequency means that the preset personnel gradually reduces the collection frequency of blood pressure-related data by a preset multiple; prompting to release blood pressure means sending a prompt to the preset personnel to adjust the number of blood pressure releases of the blood pressure monitor; If a collection and update integrity assessment is performed, a data update integrity analysis is performed based on the acquired collection and update integrity data to determine whether collection and update integrity optimization is performed; The acquisition and update integrity data is used to reflect the impact of the acquisition and update integrity parameters on the integrity of blood pressure-related data acquisition within a preset time period, specifically including the acquisition integrity and number evaluation value, the acquisition integrity and interval evaluation value, and the acquisition integrity and noise evaluation value; Obtaining a collection and update integrity value by multiplying the collection and update integrity data and a preset collection and update integrity weight group obtained from a database; The specific process of determining whether to perform collection and update integrity optimization is as follows: Determine whether the monitored collection and update completeness value is not lower than a preset collection and update completeness threshold obtained from the database; if so, do not perform collection and update completeness optimization; otherwise, send a prompt to a preset person to perform collection and update completeness optimization; when the collection and update completeness value is still lower than the preset collection and update completeness threshold after the collection and update completeness optimization, send an alarm prompt to the preset person; the collection and update completeness optimization includes increasing the collection frequency and prompting recharging; increasing the collection frequency means that the preset person increases the collection frequency of blood pressure-related data step by step by a preset multiple; prompting recharging means sending a prompt to the preset person to adjust the recharging times of the blood pressure monitor; The stroke risk prediction data corresponding to the obtained qualified acquisition evaluation value is input into the constructed digital twin model to obtain the stroke risk prediction level, and a stroke risk warning is performed based on the stroke risk prediction level. The stroke risk prediction level represents the result based on the output of the digital twin model, and the qualified acquisition evaluation value represents the acquisition evaluation value that meets the preset acquisition control interval.

2. The stroke risk early warning method based on digital twins according to claim 1 is characterized in that: The acquisition control data is obtained by processing based on the acquisition control parameters and the preset acquisition control parameters obtained from the database; The acquisition control parameters include the maximum gas inflow rate, the maximum inflation pressure, the maximum inflation times, the maximum gas outflow rate, the maximum deflation pressure and the maximum deflation times; The preset acquisition control parameters include a preset maximum inflow rate, a preset maximum inflation pressure, a preset maximum number of inflations, a preset maximum outflow rate, a preset maximum deflation pressure, and a preset maximum number of deflations; The acquisition and update delay data is obtained by processing based on the acquisition and update delay parameter and the preset acquisition and update delay parameter obtained from the database; The acquisition update delay parameters include the maximum response delay time, the maximum number of inflation and deflation times, the maximum inflation interval time and the maximum update delay time; The preset acquisition update delay parameters include a preset maximum response delay time, a preset maximum number of inflation and deflation times, a preset maximum inflation interval, and a preset maximum update delay time; The acquisition and update integrity data is obtained by processing based on the acquisition and update integrity parameter and the preset acquisition and update integrity parameter obtained from the database; The acquisition and update integrity parameters include the maximum amount of collected blood pressure data and the collected blood pressure noise ratio; The preset acquisition update integrity parameters include a preset maximum value of the amount of collected blood pressure data and a preset maximum value of the blood pressure acquisition noise ratio.

3. The digital twin-based stroke risk warning method according to claim 2, characterized in that: The specific process of analyzing the acquired acquisition control data to obtain the acquisition evaluation value is as follows: performing a first inflow operation on the obtained first processed gas inflow value to obtain a gas inflow-pressure influence value, the gas inflow-pressure influence value representing quantitative data of the degree of influence of the maximum gas inflow rate and the maximum inflation pressure value on the acquisition and control of blood pressure-related data, the first processed gas inflow value including the maximum gas inflow rate, the maximum inflation pressure value, a preset inflation pressure weight value, a preset maximum inflow rate, and a preset maximum inflation pressure; performing a second inflow operation on the obtained second processed gas inflow value to obtain a gas inflow-number impact value, the gas inflow-number impact value representing quantitative data of the degree of influence of the maximum gas inflow rate and the maximum number of inflations on the acquisition and control of blood pressure-related data, the second processed gas inflow value including the maximum gas inflow rate, the maximum number of inflations, a preset inflation number weight value, a preset maximum inflow rate, and a preset maximum number of inflations; performing a first outflow calculation on the obtained first processed gas outflow value to obtain a gas outflow-pressure influence value, the gas outflow-pressure influence value representing quantitative data of the degree of influence of the maximum gas outflow rate and the maximum deflation pressure value on the acquisition and control of blood pressure-related data, the first processed gas outflow value including the maximum gas outflow rate, the maximum deflation pressure value, a preset deflation pressure weight value, a preset maximum outflow rate, and a preset maximum deflation pressure; performing a second outflow operation on the obtained second processed gas outflow value to obtain a gas outflow-number impact value, wherein the gas outflow-number impact value represents quantified data of the degree of influence of the maximum gas outflow rate and the maximum deflation number value on the collection and control of blood pressure-related data, and the second processed gas outflow value includes the maximum gas outflow rate, the maximum deflation number value, a preset deflation number weight value, a preset maximum outflow rate, and a preset maximum deflation number; Performing a product operation on the acquired acquisition control data and the preset acquisition control weight group obtained from the database to obtain an acquisition evaluation value; The acquisition evaluation value is used to evaluate the blood pressure-related data acquisition control situation during the blood pressure monitoring process based on digital twins.

4. The digital twin-based stroke risk warning method according to claim 3, characterized in that: The specific process of determining whether to perform collection and update delay assessment and collection and update integrity assessment is as follows: Determine whether the acquired acquisition evaluation value is within a preset acquisition control interval, where the preset acquisition control interval is an interval range corresponding to a preset acquisition control maximum value and a preset acquisition control minimum value; When the acquisition evaluation value is within the preset acquisition control interval, the corresponding value of the acquisition evaluation value is marked as a qualified acquisition evaluation value; When the acquisition evaluation value is greater than the preset acquisition control maximum value, the acquisition update delay evaluation is performed; When the collection evaluation value is less than the preset collection control minimum value, a collection update integrity assessment is performed.

5. The digital twin-based stroke risk warning method according to claim 2, characterized in that: The specific process of performing data update delay analysis based on the acquired collection update delay data is as follows: The blood pressure collection update delay value is used to reflect the blood pressure related data update delay in the collection update delay assessment; The preset acquisition update delay weight group includes responding to the first weight value, responding to the second weight value, updating the first weight value and updating the second weight value; The response and number evaluation value is obtained by performing a first response delay operation on the first response delay processing value, and the response and number evaluation value represents quantitative data of the degree of influence of the maximum number of inflation and deflation times and the maximum response delay duration on the update delay of the blood pressure-related data. The first response delay processing value includes the maximum response delay duration, the maximum number of inflation and deflation times, the preset response and inflation and deflation weights, the preset maximum response delay duration, and the preset maximum number of inflation and deflation times; The response and interval evaluation value is obtained by performing a second response delay operation on the second processed response delay value, and the response and interval evaluation value represents quantitative data of the degree of influence of the maximum inflation interval duration and the maximum response delay duration on the delay in updating the blood pressure-related data; the second processed response delay value includes the maximum response delay duration, the maximum inflation interval duration, a preset response and interval weight, a preset maximum response delay duration, and a preset maximum inflation interval duration; The update and number evaluation value is obtained by performing a first update delay operation on the first update delay processing value, and the update and number evaluation value represents quantitative data of the degree of influence of the maximum number of inflation and deflation times and the maximum update delay time on the update delay of the blood pressure-related data. The first update delay processing value includes the maximum update delay time, the maximum number of inflation and deflation times, the preset update and inflation and deflation weights, the preset maximum update delay time, and the preset maximum number of inflation and deflation times; The update and interval evaluation value is obtained by performing a second update delay operation on the second processing value of the update delay. The update and interval evaluation value represents quantitative data on the degree of influence of the maximum inflation interval duration and the maximum update delay duration on the update delay of blood pressure-related data. The second processing value of the update delay includes the maximum update delay duration, the maximum inflation interval duration, the preset update and interval weight, the preset maximum update delay duration and the preset maximum inflation interval.

6. The digital twin-based stroke risk warning method according to claim 2, characterized in that: The specific process of performing data update integrity analysis based on the acquired collection and update integrity data is as follows: Acquire a complete and inflation / deflation data set, a complete and interval data set, and a complete and noise ratio data set; The complete and inflation and deflation data set is processed by performing complete and inflation and deflation operations to obtain a collection completeness and number evaluation value, wherein the collection completeness and number evaluation value represents quantitative data on the degree of influence of the maximum amount of collected blood pressure data and the maximum number of inflation and deflation times on the integrity of the blood pressure-related data update, and the complete and inflation and deflation data set includes the maximum amount of collected blood pressure data, the maximum number of inflation and deflation times, a preset complete and inflation and deflation weight value, a preset maximum amount of collected blood pressure data, and a preset maximum number of inflation and deflation times; A collection completeness and interval evaluation value is obtained by performing completeness and interval calculation processing on the completeness and interval data group, wherein the collection completeness and interval evaluation value represents quantitative data on the degree of influence of the maximum amount of collected blood pressure data and the maximum inflation interval duration on the integrity of the blood pressure-related data update, and the completeness and interval data group includes the maximum amount of collected blood pressure data, the maximum inflation interval duration, a preset completeness and interval weight value, a preset maximum amount of collected blood pressure data, and a preset maximum inflation interval; A collection integrity and noise evaluation value is obtained by performing a integrity and noise ratio operation on the integrity and noise ratio data set, wherein the collection integrity and noise evaluation value represents quantitative data on the degree of influence of the maximum amount of collected blood pressure data and the collected blood pressure noise ratio on the integrity of the blood pressure-related data update, and the integrity and noise ratio data set includes the maximum amount of collected blood pressure data, the collected blood pressure noise ratio, a preset integrity and noise ratio weight value, a preset maximum amount of collected blood pressure data, and a preset maximum blood pressure collection noise ratio; The acquisition and update completeness value is used to reflect the update completeness of blood pressure related data during the acquisition and update completeness assessment process.

7. The stroke risk warning method based on digital twins according to claim 1 is characterized in that: The specific process of performing stroke risk warning based on the stroke risk prediction level is as follows: Inputting stroke risk prediction data and preset stroke risk prediction levels into the constructed digital twin model for training to obtain a stroke risk prediction model; Inputting the real-time acquired stroke risk prediction data into the stroke risk prediction model to obtain the stroke risk prediction level; When the stroke risk prediction model outputs a first-level warning, a first-level warning prompt is sent to the preset personnel; When the stroke risk prediction model outputs a secondary warning, a secondary warning prompt is sent to the preset personnel; The stroke risk prediction levels include level one warning and level two warning; The stroke risk prediction data includes qualified collection assessment values ​​and blood pressure related data corresponding to the qualified collection assessment values.

8. A stroke risk warning system based on digital twins, used to implement the method according to any one of claims 1 to 7, characterized in that: It includes acquisition assessment module, acquisition update delay assessment module, acquisition update integrity assessment module and stroke risk prediction module: The acquisition evaluation module is used to analyze the acquired acquisition control data to obtain an acquisition evaluation value and determine whether to perform acquisition update delay evaluation and acquisition update integrity evaluation; The acquisition update delay evaluation module is used to perform data update delay analysis based on the acquired acquisition update delay data if acquisition update delay evaluation is performed, and determine whether to perform acquisition update delay optimization; The acquisition and update integrity assessment module is used to perform data update integrity analysis based on the acquired acquisition and update integrity data if acquisition and update integrity assessment is performed, and determine whether to perform acquisition and update integrity optimization; The stroke risk prediction module is used to input the stroke risk prediction data corresponding to the obtained qualified acquisition evaluation value into the constructed digital twin model to obtain the stroke risk prediction level, and perform stroke risk warning based on the stroke risk prediction level. The stroke risk prediction level represents the result output based on the digital twin model, and the qualified acquisition evaluation value represents the acquisition evaluation value that meets the preset acquisition control interval.

Images