Cerebral stroke risk early warning method and system based on digital twinning

Abstract

The invention provides a cerebral apoplexy risk early warning method and system based on digital twinning, and relates to the technical field of cerebral apoplexy risk early warning. The method comprises the following steps: acquiring and evaluating; acquiring update delay evaluation; acquiring and updating integrity evaluation; and cerebral apoplexy risk prediction. The method comprises the following steps: analyzing acquisition control data, judging whether to carry out acquisition update delay evaluation and acquisition update integrity evaluation, if the acquisition update delay evaluation is carried out, judging whether to carry out acquisition update delay optimization, and if the acquisition update integrity evaluation is carried out, judging whether to carry out acquisition update integrity optimization. And finally, obtaining the cerebral apoplexy risk prediction level, thereby achieving the effect of improving the accuracy of the cerebral apoplexy risk early warning data, and solving the problem that the accuracy of the cerebral apoplexy risk early warning data is not high in the prior art.

Description

Technical Field

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

[0002] Digital twin technology is an emerging digital technology that realizes real-time interaction and mapping between the physical world and the digital world by constructing a virtual mirror of an entity object. In the medical field, digital twin technology can be applied to aspects such as monitoring the physiological state of patients, disease prediction and management. By collecting clinical data, physiological indicators, etc. of patients and constructing a digital twin model of the patient, doctors can understand the patient's health status in real time and perform accurate disease prediction and management. Stroke is a serious cerebrovascular disease characterized by high incidence, high disability rate and high mortality rate. At present, the warning of stroke mainly relies on the clinical symptoms of patients, imaging examinations and biochemical indicators, etc.

[0003] The existing method is based on the physiological data of patients, inputs the corresponding digital twin model, and simulates the physiological state of patients based on the output results of the digital twin model.

[0004] However, in the process of implementing the technical solution of the present invention in the embodiments of the present invention, it is found that the above technologies have at least the following technical problems:

[0005] In the prior art, due to the change of the physiological state (blood pressure, heart rate data) of cerebrovascular patients, the digital twin model needs to be updated frequently. High-frequency data acquisition may lead to inaccurate control of the charging and discharging pressure of the blood pressure monitor, and there is a delay in data update and synchronization, resulting in the problem of low accuracy of stroke risk warning data. Summary of the Invention

[0006] The present invention provides a stroke risk warning method based on digital twin. By analyzing the obtained acquisition control data to obtain an acquisition evaluation value and determining whether to perform acquisition update delay evaluation and acquisition update integrity evaluation, if the acquisition update delay evaluation is performed, data update delay analysis is performed according to the obtained acquisition update delay data to determine whether to perform acquisition update delay optimization, if the acquisition update integrity evaluation is performed, data update integrity analysis is performed according to the obtained acquisition update integrity data to determine whether to perform acquisition update integrity optimization, thereby improving the accuracy of stroke risk warning data.

[0007] To achieve the above invention purpose, the technical solutions provided by the present invention are as follows:

[0008] A stroke risk early warning method based on digital twin, comprising the following steps: analyzing the acquired acquisition control data to obtain an acquisition evaluation value, and judging whether to perform acquisition update delay evaluation and acquisition update integrity evaluation; if performing acquisition update delay evaluation, performing data update delay analysis according to the acquired acquisition update delay data, and judging whether to perform acquisition update delay optimization; if performing acquisition update integrity evaluation, performing data update integrity analysis according to the acquired acquisition update integrity data, and judging whether to perform acquisition update integrity optimization; inputting 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 performing stroke risk early warning based on the stroke risk prediction level, where 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.

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

[0010] Optionally, the specific process of obtaining the acquisition evaluation value from the acquired acquisition control data is as follows: perform a first inflow operation on the obtained first gas inflow value to obtain a gas inflow-pressure influence value, where the gas inflow-pressure influence value represents the quantification data of the combined influence of the maximum gas inflow rate and the maximum inflation pressure value on the acquisition control of blood pressure-related data. The first gas inflow value includes 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; perform a second inflow operation on the obtained second gas inflow value to obtain a gas inflow-number influence value, where the gas inflow-number influence value represents the quantification data of the combined influence of the maximum gas inflow rate and the maximum inflation number value on the acquisition control of blood pressure-related data. The second gas inflow value includes the maximum gas inflow rate, the maximum inflation number value, a preset inflation number weight value, a preset maximum inflow rate, and a preset maximum inflation number; perform a first outflow operation on the obtained first gas outflow value to obtain a gas outflow-pressure influence value, where the gas outflow-pressure influence value represents the quantification data of the combined influence of the maximum gas outflow rate and the maximum deflation pressure value on the acquisition control of blood pressure-related data. The first gas outflow value includes 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; perform a second outflow operation on the obtained second gas outflow value to obtain a gas outflow-number influence value, where the gas outflow-number influence value represents the quantification data of the combined influence of the maximum gas outflow rate and the maximum deflation number value on the acquisition control of blood pressure-related data. The second 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; perform a product operation on the obtained acquisition control data and the preset acquisition control right recombination obtained from the database to obtain an acquisition evaluation value; the acquisition evaluation value is used to evaluate the acquisition control situation of blood pressure-related data during blood pressure monitoring based on digital twin.

[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 obtained acquisition evaluation value is within a preset acquisition control range, where the preset acquisition control range is the 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 range, mark the corresponding value of the acquisition evaluation value as a qualified acquisition evaluation value; when the acquisition evaluation value is greater than the preset acquisition control maximum value, perform an acquisition update delay evaluation; when the acquisition evaluation value is less than the preset acquisition control minimum value, perform an acquisition update integrity evaluation.

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

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

[0014] Optionally, the specific process of performing data update integrity analysis based on the obtained acquisition update integrity data is as follows: Obtain a complete and inflation / deflation data group, a complete and interval data group, and a complete and noise ratio data group; obtain an acquisition integrity and number evaluation value by performing a complete and inflation / deflation operation on the complete and inflation / deflation data group, where the acquisition integrity and number evaluation value represents the quantification data of the influence degree of the maximum blood pressure data acquisition amount and the maximum inflation / deflation times on the data update integrity of blood pressure-related data, and the complete and inflation / deflation data group includes the maximum blood pressure data acquisition amount, the maximum inflation / deflation times, a preset complete and inflation / deflation weight value, a preset maximum blood pressure data acquisition amount, and a preset maximum inflation / deflation times; obtain an acquisition integrity and interval evaluation value by performing a complete and interval operation on the complete and interval data group, where the acquisition integrity and interval evaluation value represents the quantification data of the influence degree of the maximum blood pressure data acquisition amount and the maximum inflation interval duration on the data update integrity of blood pressure-related data, and the complete and interval data group includes the maximum blood pressure data acquisition amount, the maximum inflation interval duration, a preset complete and interval weight value, a preset maximum blood pressure data acquisition amount, and a preset maximum inflation interval; obtain an acquisition integrity and noise evaluation value by performing a complete and noise ratio operation on the complete and noise ratio data group, where the acquisition integrity and noise evaluation value represents the quantification data of the influence degree of the maximum blood pressure data acquisition amount and the blood pressure acquisition noise ratio on the data update integrity of blood pressure-related data, and the complete and noise ratio data group includes the maximum blood pressure data acquisition amount, the blood pressure acquisition noise ratio, a preset complete and noise ratio weight value, a preset maximum blood pressure data acquisition amount, and a preset maximum blood pressure acquisition noise ratio; obtain an acquisition update integrity value by performing a product operation on the acquisition update integrity data and a preset acquisition update integrity weight group obtained from the database; the acquisition update integrity value is used to reflect the data update integrity situation of blood pressure-related data during the acquisition update integrity evaluation process.

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

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

[0017] The embodiment of the present invention provides a stroke risk early 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: Among them, the acquisition evaluation module is used to analyze the obtained 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, if performing acquisition update delay evaluation, perform data update delay analysis based on the obtained acquisition update delay data, and determine whether to perform acquisition update delay optimization; the acquisition update integrity evaluation module is used to, if performing acquisition update integrity evaluation, perform data update integrity analysis based on the obtained acquisition update integrity data, 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 the stroke risk prediction level, and perform stroke risk early 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.

[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 solution, by analyzing the acquisition control data to obtain an acquisition evaluation value and determining whether to perform an acquisition update delay evaluation and an acquisition update integrity evaluation. If an acquisition update delay evaluation is performed, data update delay analysis is carried out and it is determined whether to perform acquisition update delay optimization. If an acquisition update integrity evaluation is performed, data update integrity analysis is carried out and it is determined whether to perform acquisition update integrity optimization. Finally, based on the qualified acquisition evaluation value, the stroke risk prediction level is obtained, 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] By performing a product operation on the obtained acquisition control data and the preset acquisition control right recombination to obtain an acquisition evaluation value, then performing a product operation on the acquisition update delay data and the preset acquisition update delay right recombination to obtain the blood pressure acquisition update delay value, and finally performing a product operation on the acquisition update integrity data and the preset acquisition update integrity right recombination to obtain the acquisition update complete value, the reliability of obtaining data related to stroke risk prediction is improved, and further the timeliness of obtaining data related to stroke risk prediction is improved.

[0021] By 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, and then inputting the real-time obtained 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 further 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 will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0023] Figure 1 It is a flowchart of the method for stroke risk warning based on digital twin provided in the embodiments of the present invention;

[0024] Figure 2 It is a schematic structural diagram of the system for stroke risk warning based on digital twin provided in the embodiments of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0025] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the described embodiments of the present invention without creative efforts shall fall within the scope of protection of the present invention.

[0026] Unless otherwise defined, the technical terms or scientific terms used in the present invention shall have the ordinary meanings understood by those of ordinary skill in the art to which the present invention pertains. The terms "first", "second", and similar terms used in the present invention do not denote any order, quantity, or importance, but are only used to distinguish different components. Similarly, the terms "a", "an", or "the" and similar terms do not denote a quantity limitation, but mean that there is at least one. The terms "comprising", "including", or similar terms are intended to mean that the elements or items appearing before the term cover the elements or items listed after the term and their equivalents, without excluding other elements or items. The terms "connected" or "coupled" and similar terms 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 "upper", "lower", "left", "right", "front", "rear", etc. used in the present invention are only used to represent relative positional relationships. When the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0028] The present invention provides a method for stroke risk early warning based on digital twin. By analyzing the acquired control data, an acquisition evaluation value is obtained, and it is judged whether to perform acquisition update delay evaluation and acquisition update integrity evaluation. If the acquisition update delay evaluation is performed, data update delay analysis is carried out and it is judged whether to perform acquisition update delay optimization. If the acquisition update integrity evaluation is performed, data update integrity analysis is carried out and it is judged whether to perform acquisition update integrity optimization. Finally, the stroke risk prediction level is obtained based on the qualified acquisition evaluation value, achieving the effect of improving the accuracy of stroke risk early warning data.

[0029] As Figure 1 shown, it is a flowchart of a method for stroke risk early warning based on digital twin provided by an embodiment of the present invention. A method for stroke risk early warning based on digital twin includes the following steps:

[0030] Acquisition evaluation: Analyze the acquired control data to obtain an acquisition evaluation value, and judge whether to perform acquisition update delay evaluation and acquisition update integrity evaluation;

[0031] Collection update delay evaluation: If collection update delay evaluation is performed, data update delay analysis is carried out based on the obtained collection update delay data to determine whether to optimize the collection update delay;

[0032] Collection update integrity evaluation: If collection update integrity evaluation is performed, data update integrity analysis is carried out based on the obtained collection update integrity data to determine whether to optimize the collection update integrity;

[0033] Stroke risk prediction: The stroke risk prediction data corresponding to the obtained qualified collection evaluation values is input into the constructed digital twin model to obtain the stroke risk prediction level. Based on the stroke risk prediction level, stroke risk early warning is carried out. The stroke risk prediction level represents the result output based on the digital twin model, and the qualified collection evaluation value represents the collection evaluation value that meets the preset collection control interval.

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

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

[0036] The aforementioned database is a database for storing various types of set data in a stroke risk warning method based on digital twin 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 inflation times, etc. Various values therein are directly set by technicians. For example, the preset maximum inflow rate is represented by the maximum value of the monitored gas inflow rate in the historical time period in the database, the preset maximum inflation pressure is represented by the maximum value of the inflation gas pressure in the historical time period in the database, the preset maximum inflation times is represented by the maximum value of the inflation times in the historical time period in the database, the preset maximum outflow rate is represented by the maximum value of the monitored gas outflow rate in the historical time period in the database, the preset maximum deflation pressure is represented by the maximum value of the deflation gas pressure in the historical time period in the database, and the preset maximum deflation times is represented by the maximum value of the deflation times in 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 value, the maximum deflation pressure value, the preset maximum inflation pressure, and the preset maximum deflation pressure are all pascals. The units of the maximum inflation times value, the maximum deflation times value, the preset maximum inflation times, and the preset maximum deflation times are all times.

[0037] Collect update delay data to reflect the influence of the collection update delay parameter on the update synchronization of blood pressure-related data within a preset time period, specifically including the response and times evaluation value, the response and interval evaluation value, the update and times evaluation value, and the update and interval evaluation value. The collection update delay data is obtained by processing based on the collection update delay parameter and the preset collection update delay parameter obtained from the database. The collection update delay parameter includes the maximum response delay duration, the maximum inflation and deflation times, the maximum inflation interval duration, and the maximum update delay duration. The preset collection update delay parameter includes the preset maximum response delay duration, the preset maximum inflation and deflation times, the preset maximum inflation interval, and the preset maximum update delay duration.

[0038] Among them, the maximum value of the absolute value of the difference between the response duration of the blood pressure monitor and the preset response duration within a preset time period is obtained through analysis by the blood pressure monitor, timer, and signal generator, which is the maximum response delay duration. The sum of the inflation and deflation times within a preset time period is monitored by the built-in counter of the blood pressure monitor and its maximum value is statistically calculated, which is the maximum inflation and deflation times. The maximum value of the inflation interval duration within a preset time period is monitored by the blood pressure monitor and timer and statistically calculated, which is the maximum inflation interval duration. The maximum value of the absolute value of the difference between the blood pressure monitor update duration and the preset update duration within a preset time period is obtained through analysis by the blood pressure monitor, timer, and signal generator, which is the maximum update delay duration.

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

[0040] Collecting update integrity data is used to reflect the influence of the collecting update integrity parameters on the collecting integrity of blood pressure-related data within a preset time period, specifically including the collecting integrity and frequency evaluation value, the collecting integrity and interval evaluation value, and the collecting integrity and noise evaluation value. The collecting update integrity data is obtained by processing based on the collecting update integrity parameters and the preset collecting update integrity parameters retrieved from the database. The collecting update integrity parameters include the maximum value of the collected blood pressure data volume and the collecting blood pressure noise ratio. The preset collecting update integrity parameters include the preset maximum value of the collected blood pressure data volume and the maximum value of the preset blood pressure collecting noise ratio.

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

[0042] The preset maximum value of the collected blood pressure data volume is represented by the maximum value of the collected blood pressure data volume in the historical time period in the database. The maximum value of the preset blood pressure collecting noise ratio is represented by the maximum value of the blood pressure collecting noise ratio in the historical time period in the database. The units of the maximum value of the collected blood pressure data volume and the preset maximum value of the collected blood pressure data volume are both bits.

[0043] In this embodiment, by monitoring and collecting control data, collection update delay data, collection 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 collection evaluation value is not within the preset collection control range, it is necessary to determine whether to perform collection update delay optimization and collection update integrity optimization based on the obtained blood pressure collection update delay value and collection update complete value; when the monitored collection evaluation value is within the preset collection control range, the blood pressure collection update delay value is not higher than the preset collection update delay threshold, and the collection update complete value is not lower than the preset collection update complete threshold, the corresponding stroke risk prediction data (blood pressure, heart rate, blood lipid, 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 interaction relationship among the collection evaluation value, the collection update complete value, and the blood pressure collection 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 a dynamic blood pressure monitor, which is suitable for brain injury and promoting the injury repair process through RIC (Remote Ischemic Conditioning) technology. It can repeatedly inflate and deflate the limb blood pressure cuff provided by the blood pressure monitor to perform repeated and short-term blood flow interruption and restoration on non-vital organs or tissues such as the limb, stimulate the body's endogenous protection mechanism, improve the ischemia and hypoxia tolerance of distant organs, and provide ischemic tolerance for the brain and effective protection against subsequent fatal ischemia.

[0045] Among them, the specific process of obtaining the collection evaluation value by analyzing the collected control data is as follows: perform a first inflow operation process on the obtained first gas inflow value to obtain a gas inflow-pressure influence value, that is The first inflow operation process represents the result of multiplying the ratio operation result of the maximum gas inflow rate and the preset maximum inflow rate, the ratio operation result of the maximum inflation pressure value and the preset maximum inflation pressure, and the preset inflation pressure weight value. The first gas inflow 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 a direct proportion relationship. The maximum gas inflow rate represents the maximum rate of gas inflow into the airbag within a preset time period; perform a second inflow operation process on the obtained second gas inflow value to obtain a gas inflow-number influence value, that is The second inflow operation process represents the product operation of the ratio operation result of the maximum gas inflow rate and the preset maximum inflow rate, the ratio operation result of the maximum inflation times value and the preset maximum inflation times, and the preset inflation times weight value. The gas inflow second processing value includes the maximum gas inflow rate, the maximum inflation times value, the preset inflation times weight value, the preset maximum inflow rate, and the preset maximum inflation times. The maximum gas inflow rate and the maximum inflation times value are in a direct proportional relationship. The first outflow operation process is performed on the obtained gas outflow first processing value to obtain the gas outflow-pressure influence value, that is The first outflow operation process represents the product operation of the ratio operation result of the maximum gas outflow rate and the preset maximum outflow rate, the ratio operation result of the maximum deflation pressure value and the preset maximum deflation pressure, and the preset deflation pressure weight value. The gas outflow first 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 a direct proportional relationship. The second outflow operation process is performed on the obtained gas outflow second processing value to obtain the gas outflow-times influence value, that is The second outflow operation process represents the product operation of the ratio operation result of the maximum gas outflow rate and the preset maximum outflow rate, the ratio operation result of the maximum deflation times value and the preset maximum deflation times, and the preset deflation times weight value. The gas outflow second processing value includes the maximum gas outflow rate, the maximum deflation times value, the preset deflation times weight value, the preset maximum outflow rate, and the preset maximum deflation times. The maximum gas outflow rate and the maximum deflation times value are in a direct proportional relationship. The product operation is performed on the obtained acquisition control data and the preset acquisition control right reorganization obtained from the database to obtain the acquisition evaluation value. The acquisition evaluation value is used to evaluate the acquisition control situation of blood pressure-related data during the blood pressure monitoring based on digital twins. The gas inflow-pressure influence value represents the quantification data of the influence degree of the maximum gas inflow rate and the maximum inflation pressure value on the acquisition control of blood pressure-related data. The gas inflow-times influence value represents the quantification data of the influence degree of the maximum gas inflow rate and the maximum inflation times value on the acquisition control of blood pressure-related data. The gas outflow-pressure influence value represents the quantification data of the influence degree of the maximum gas outflow rate and the maximum deflation pressure value on the acquisition control of blood pressure-related data. The gas outflow-times influence value represents the quantification data of the influence degree of the maximum gas outflow rate and the maximum deflation times value on the acquisition control of blood pressure-related data.

[0046] The acquisition control data and the acquisition evaluation value are in an inverse proportional relationship;

[0047] Among them, the acquisition evaluation value is obtained by the following method:

[0048]

[0049] In the formula, represents the acquisition evaluation value in the u1-th preset time period, where u1 = 1, 2,..., g1, u1 represents the number of the preset time period, and g1 represents the total number of preset time periods. represents the gas inflow-pressure influence value in the u1-th preset time period. represents the gas inflow-number of times influence value in the u1-th preset time period. represents the gas outflow-pressure influence value in the u1-th preset time period. represents the gas outflow-number of times influence value in the u1-th preset time period. P1 represents the first weight of the preset gas inflow, P2 represents the second weight of the preset gas inflow, P3 represents the first weight of the preset gas outflow, and P4 represents the second weight of the preset gas outflow.

[0050] represents the maximum gas inflow rate value in the u1-th preset time period. represents the maximum inflation pressure value in the u1-th preset time period. represents the maximum inflation number of times value in the u1-th preset time period. represents the maximum gas outflow rate value in the u1-th preset time period. represents the maximum deflation pressure value in the u1-th preset time period. represents the maximum deflation number of times value in the u1-th preset time period. represents the preset maximum inflow rate. represents the preset maximum inflation pressure. represents the preset maximum inflation number of times. represents the preset maximum outflow rate. represents the preset maximum deflation pressure. represents the preset maximum deflation number of times, W 1 represents the preset inflation pressure weight value, W 2 represents the preset inflation number of times weight value, W 3 represents the preset deflation pressure weight value, W 4 represents the preset deflation number of times weight value, and e represents the natural constant.

[0051] In this embodiment, a set of mapping groups is obtained from the database. A mapping set is set in the mapping group, which can be used to reflect the mapping relationship between the acquisition control data and the corresponding preset acquisition control right recombination; by inputting the real-time acquisition control data into the mapping group, the corresponding preset acquisition control right recombination is obtained; the mapping relationship in the mapping set can be a one-to-one or many-to-one relationship; for example, in this embodiment, the value range of the weight is 0-1. The preset acquisition control right recombination 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, which are used to reflect the influence of the acquisition control data on the acquisition evaluation value.

[0052] It should be added that in this embodiment, a mapping set for reflecting the mapping relationship between the acquisition control input data and the corresponding preset inflation pressure weight value, preset inflation times weight value, preset deflation pressure weight value, and preset deflation times weight value is set in advance; by inputting the real-time acquisition control input data into the mapping set, the corresponding preset inflation pressure weight value, preset inflation times weight value, preset deflation pressure weight value, and preset deflation times weight value can be obtained; the mapping relationship in the mapping set can be a one-to-one or 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 times 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 greater the gas inflow-pressure influence value, it means that the gas inflow rate and the inflation pressure have a greater influence on the acquisition control of blood pressure-related data, resulting in a decrease in the acquisition evaluation value; the greater the gas inflow-times influence value, it means that the gas inflow rate and the inflation times have a greater influence on the acquisition control of blood pressure-related data, resulting in a decrease in the acquisition evaluation value; the greater the gas outflow-pressure influence value, it means that the gas outflow rate and the deflation times have a greater influence on the acquisition control of blood pressure-related data, resulting in a decrease in the acquisition evaluation value; the greater the gas outflow-times influence value, it means that the gas outflow rate and the deflation times have a greater influence on the acquisition 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 in an inverse relationship.

[0054] In the algorithm of this embodiment, the acquisition control data does not exist independently, and there is a mutual correlation between independent variables, which requires comprehensive analysis. When the maximum value of the gas inflow rate increases, the inflation speed accelerates, which may lead to an increase in the maximum inflation pressure value; the faster the gas outflow rate, the more drastic the pressure change, which may lead to a decrease in the maximum deflation pressure value; the maximum deflation pressure value is also affected by the maximum number of deflation times. The larger the maximum number of deflation times value, the greater the deflation pressure may be, and then the maximum deflation pressure value increases; the maximum inflation pressure value is affected by the maximum number of inflation times. The larger the maximum number of inflation times value, the greater the maximum inflation pressure value may be, which may have a negative impact on the stability and accuracy of blood pressure monitoring. By analyzing the comprehensive influence between parameters, the accurate evaluation of the acquisition control situation of blood pressure-related data in the blood pressure monitoring process based on digital twins is realized, and then the accuracy of stroke risk warning data is improved.

[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 obtained 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 value corresponding to the acquisition evaluation value as a qualified acquisition evaluation value; the qualified acquisition evaluation value represents the 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 affects the acquisition update of stroke, and perform acquisition update delay evaluation; 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 affects the acquisition integrity of stroke, and perform acquisition update integrity evaluation.

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

[0057] The specific process for determining whether to perform acquisition update integrity optimization is as follows: Determine whether the monitored acquisition update integrity value is not lower than the preset acquisition update integrity threshold obtained from the database; if so, do not perform acquisition update integrity optimization, otherwise send a prompt to the preset personnel for acquisition update integrity optimization; when the acquisition update integrity value is still lower than the preset acquisition update integrity threshold after performing acquisition update integrity optimization, send an alarm prompt to the preset personnel; Acquisition update integrity optimization includes increasing the acquisition frequency and prompting for pressurization; Increasing the acquisition frequency means that the preset personnel gradually increase the acquisition frequency of blood pressure-related data by a preset multiple; Prompting for pressurization means sending a prompt to the preset personnel to adjust the number of pressurizations of the blood pressure monitor.

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

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

[0060] Among them, the specific process for performing data update delay analysis based on the obtained acquisition update delay data is as follows: Obtain the blood pressure acquisition update delay value through a multiplication 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 situation of 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 through a first response delay operation on the response delay first processing value, that is The first response delay operation processing represents the result of multiplying the ratio of the maximum number of charging and discharging cycles and the preset maximum number of charging and discharging cycles, the ratio of the maximum response delay duration and the preset maximum response delay duration by the preset response-to-charging / discharging weight. The first response delay processing value includes the maximum response delay duration, the maximum number of charging and discharging cycles, the preset response-to-charging / discharging weight, the preset maximum response delay duration, and the preset maximum number of charging and discharging cycles. The maximum response delay duration is directly proportional to the maximum number of charging and discharging cycles. The maximum response delay duration represents the maximum absolute value of the difference between the response duration of the blood pressure monitor within a preset time period and the preset response duration obtained from the database. The maximum number of charging and discharging cycles represents the maximum sum of the number of inflation and deflation cycles monitored by the blood pressure monitor within a preset time period. The response-to-interval evaluation value is obtained by performing a second response delay operation processing on the second response delay processing value, that is The second response delay operation processing represents the result of multiplying the ratio of the maximum inflation interval duration and the preset maximum inflation interval, the ratio of the maximum response delay duration and the preset maximum response delay duration by the preset response-to-interval weight. The second response delay processing value includes the maximum response delay duration, the maximum inflation interval duration, the preset response-to-interval weight, the preset maximum response delay duration, and the preset maximum inflation interval. The maximum response delay duration is directly proportional to the maximum inflation interval duration. The update-to-cycle evaluation value is obtained by performing a first update delay operation processing on the first update delay processing value, that is The first update delay operation processing represents the result of multiplying the ratio of the maximum number of charging and discharging cycles and the preset maximum number of charging and discharging cycles, the ratio of the maximum update delay duration and the preset maximum update delay duration, and the preset update-to-charging / discharging weight. The first update delay processing value includes the maximum update delay duration, the maximum number of charging and discharging cycles, the preset update-to-charging / discharging weight, the preset maximum update delay duration, and the preset maximum number of charging and discharging cycles. The maximum update delay duration is directly proportional to the maximum number of charging and discharging cycles. The maximum update delay duration represents the maximum absolute value of the difference between the update duration of the blood pressure monitor within a preset time period and the preset update duration obtained from the database. The update-to-interval evaluation value is obtained by performing a second update delay operation processing on the second update delay processing value, that is The second update delay operation processing represents the result of the ratio operation between the maximum inflation interval duration and the preset maximum inflation interval, the result of the ratio operation between the maximum update delay duration and the preset maximum update delay duration, and the product operation with the preset update and interval weight. The update delay second processing value 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. The maximum update delay duration is directly proportional to the maximum inflation interval duration; the response and count evaluation value represents the quantization data of the influence degree of the maximum inflation and deflation count and the maximum response delay duration on the update delay of blood pressure-related data. The response and interval evaluation value represents the quantization data of the influence degree of the maximum inflation interval duration and the maximum response delay duration on the update delay of blood pressure-related data. The update and count evaluation value represents the quantization data of the influence degree of the maximum inflation and deflation count and the maximum update delay duration on the update delay of blood pressure-related data. The update and interval evaluation value represents the quantization data of the influence degree of the maximum inflation interval duration and the maximum update delay duration on the update delay of blood pressure-related data.

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

[0062]

[0063] In the formula, represents the blood pressure acquisition update delay value in the a1-th delay evaluation time period, where a1 = 1, 2,..., b1, a1 represents the number of the delay evaluation time period, and b1 represents the total number of the delay evaluation time periods. The delay evaluation time period represents a preset time period in the analysis process based on the acquired acquisition update delay data. represents the response and count evaluation value in the a1-th delay evaluation time period. represents the response and interval evaluation value in the a1-th delay evaluation time period. represents the update and count evaluation value in the a1-th delay evaluation time period. represents the update and interval evaluation value in the a1-th delay evaluation time period. K1 represents the first response weight value, K2 represents the second response weight value, K3 represents the first update weight value, and K4 represents the second update weight value.

[0064] represents the maximum response delay duration in the a1-th delay evaluation time period. represents the maximum inflation and deflation count in the a1-th delay evaluation time period. represents the maximum inflation interval duration in the a1-th delay evaluation time period. represents the maximum update delay duration in the a1-th delay evaluation time period. represents the maximum value of the preset response delay duration represents the maximum value of the preset number of charge and discharge cycles represents the maximum value of the preset inflation interval represents the maximum value of the preset update delay duration, h1 represents the preset response and charge-discharge weight, h2 represents the preset response and interval weight, h3 represents the preset update and charge-discharge weight, h4 represents the preset update and interval weight, and e represents the natural constant

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

[0066] It should be added that in this embodiment, a mapping set for reflecting the mapping relationship between the update delay input data and the corresponding preset response and charge-discharge weight, preset response and interval weight, preset update and charge-discharge weight, and preset update and interval weight is set in advance; by inputting the real-time update delay input data into the mapping set, the corresponding preset response and charge-discharge weight, preset response and interval weight, preset update and charge-discharge weight, and preset update and interval weight can be obtained; the mapping relationship in this mapping set can be a one-to-one or 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 value of the number of charge and discharge cycles and the maximum value of the response delay duration, the maximum value of the inflation interval duration and the maximum value of the response delay duration, the maximum value of the update delay duration and the maximum value of the number of charge and discharge cycles, and the maximum value of the update delay duration and the maximum value of the inflation interval duration

[0067] The algorithm of this embodiment combines the analysis of the collected update delay data to obtain the blood pressure collection update delay value. The larger the response and number evaluation value, the greater the impact of the response delay duration and the number of charge and discharge cycles on the update delay of blood pressure-related data, resulting in a larger blood pressure collection update delay value; the larger the response and interval evaluation value, the greater the impact of the response delay duration and the inflation interval duration on the update delay of blood pressure-related data, resulting in a larger blood pressure collection update delay value; the larger the update and number evaluation value, the greater the impact of the update delay duration and the number of charge and discharge cycles on the update delay of blood pressure-related data, resulting in a larger blood pressure collection update delay value; the larger the update and interval evaluation value, the greater the impact of the update delay duration and the inflation interval duration on the update delay of blood pressure-related data, resulting in a larger blood pressure collection update delay value. In summary, there is a proportional relationship between the collected update delay data and the blood pressure collection update delay value

[0068] In the algorithm of this embodiment, the collected update delay data does not exist independently, and there is a mutual correlation between the independent variables, which requires comprehensive analysis. When the maximum value of the number of charging and discharging cycles is larger, it means that the possibility of the monitored reaction speed slowing down is greater, which may lead to the delay of the monitoring response, and then increase the maximum value of the response delay duration; the longer the inflation interval may also lead to the reduction of the monitoring efficiency, because the monitoring period will become longer, which may increase the possibility of response delay and lead to the increase of the maximum value of the response delay duration; the shorter the inflation interval may lead to more frequent charging and discharging operations, thus increasing the number of charging and discharging cycles and resulting in the increase of the maximum value of the number of charging and discharging cycles; the increase of the number of charging and discharging cycles may require a longer time to update the blood pressure-related data, thus leading to the increase of the maximum value of the update delay duration; by analyzing the comprehensive influence among the parameters, the accurate evaluation of the update delay of the blood pressure-related data in the acquisition update delay evaluation is realized, and then the effect of improving the accuracy of the stroke risk warning data is achieved.

[0069] Among them, the specific process of data update integrity analysis according to the obtained acquisition update integrity data is as follows: obtain the complete and charging / discharging data group, the complete and interval data group, and the complete and noise ratio data group; through the complete and charging / discharging operation processing on the complete and charging / discharging data group, obtain the acquisition integrity and number evaluation value, that is The complete and charging / discharging operation processing represents the result of the ratio operation of the maximum value of the collected blood pressure data volume and the preset maximum value of the collected blood pressure data volume, the result of the ratio operation of the maximum value of the number of charging and discharging cycles and the preset maximum value of the number of charging and discharging cycles, and the product operation with the preset complete and charging / discharging weight value. The complete and charging / discharging data group includes the maximum value of the collected blood pressure data volume, the maximum value of the number of charging and discharging cycles, the preset complete and charging / discharging weight value, the preset maximum value of the collected blood pressure data volume, and the preset maximum value of the number of charging and discharging cycles. The maximum value of the collected blood pressure data volume represents the maximum value of the data volume corresponding to the blood pressure-related data within the preset time period; through the complete and interval operation processing on the complete and interval data group, obtain the acquisition integrity and interval evaluation value, that is The complete and interval operation processing represents the result of the ratio operation of the maximum value of the collected blood pressure data volume and the preset maximum value of the collected blood pressure data volume, the result of the ratio operation of the maximum value of the inflation interval duration and the preset maximum value of the inflation interval, and the product operation with the preset complete and interval weight value. The complete and interval data group includes the maximum value of the collected blood pressure data volume, the maximum value of the inflation interval duration, the preset complete and interval weight value, the preset maximum value of the collected blood pressure data volume, and the preset maximum value of the inflation interval; through the complete and noise ratio operation processing on the complete and noise ratio data group, obtain the acquisition integrity and noise evaluation value, that is The full-to-noise ratio operation process represents the result of performing a ratio operation on the maximum value of the collected blood pressure data volume and the preset maximum value of the collected blood pressure data volume, the result of performing a ratio operation on the preset full-to-noise ratio weight value and the collected blood pressure noise ratio, and the product operation of the preset full-to-noise ratio weight value. The full-to-noise ratio data group includes the maximum value of the collected blood pressure data volume, the collected blood pressure noise ratio, the preset full-to-noise ratio weight value, the preset maximum value of the collected blood pressure data volume, and the preset maximum value of the blood pressure collection noise ratio. The collected update complete value is obtained by performing a product operation on the collected update integrity data and the preset collected update integrity weight group obtained from the database. The collected update complete value is used to reflect the update integrity of blood pressure-related data during the process of collecting update integrity evaluation. The collected update complete value is directly proportional to the collected update integrity data. The maximum value of the collected blood pressure data volume is directly proportional to the maximum value of the inflation and deflation times. The maximum value of the collected blood pressure data volume is directly proportional to the maximum value of the inflation interval duration. The maximum value of the collected blood pressure data volume is inversely proportional to the collected blood pressure noise ratio. The collected complete and count evaluation value represents the quantitative data of the influence degree of the maximum value of the collected blood pressure data volume and the maximum value of the inflation and deflation times on the update integrity of blood pressure-related data. The collected complete and interval evaluation value represents the quantitative data of the influence degree of the maximum value of the collected blood pressure data volume and the maximum value of the inflation interval duration on the update integrity of blood pressure-related data. The collected complete and noise evaluation value represents the quantitative data of the influence degree of the maximum value of the collected blood pressure data volume and the collected blood pressure noise ratio on the update integrity of blood pressure-related data.

[0070] Among them, the collected update complete value is obtained by the following method:

[0071]

[0072] In the formula, represents the collected update complete value in the n1th collected update integrity evaluation time period. The collected update integrity evaluation time period is a preset time period during the analysis process based on the obtained collected update integrity data. represents the collected complete and count evaluation value in the n1th collected update integrity evaluation time period. represents the collected complete and interval evaluation value in the n1th collected update integrity evaluation time period. represents the collected complete and noise evaluation value in the n1th collected update integrity evaluation time period. D1 represents the preset first weight value for collection completeness, D2 represents the preset second weight value for collection completeness, and D3 represents the preset third weight value for collection completeness.

[0073] represents the maximum value of the collected blood pressure data volume in the n1th collected update integrity evaluation time period. represents the maximum value of the inflation and deflation times in the n1th collected update integrity evaluation time period. represents the maximum inflation interval duration in the n1-th acquisition update integrity evaluation time period, represents the acquisition blood pressure noise ratio in the n1-th acquisition update integrity evaluation time period, represents the maximum value of the preset inflation and deflation times, represents the maximum value of the preset inflation interval, represents the maximum value of the preset acquisition blood pressure data volume, represents the maximum value of the preset blood pressure acquisition noise ratio, X1 represents the preset integrity and inflation-deflation weight value, X2 represents the preset integrity and interval weight value, X3 represents the preset integrity and noise ratio weight value, and e represents the natural constant.

[0074] In this embodiment, a set of mapping groups is obtained from the database. A mapping set is set in this mapping group, which can be used to reflect the mapping relationship between the acquisition update integrity data and the corresponding preset acquisition update integrity weight group; by inputting the real-time acquisition update integrity data into the mapping group, the corresponding preset acquisition update integrity weight group is obtained; the mapping relationship in this mapping set can be a one-to-one or many-to-one relationship; for example, in this embodiment, the value range of the weight is 0-1. The preset acquisition update integrity weight group includes a preset acquisition integrity first weight value, a preset acquisition integrity second weight value, and a preset acquisition integrity third weight value, which are used to reflect the influence degree of the acquisition update integrity data on the acquisition update integrity value.

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

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

[0077] In the algorithm of this embodiment, the acquisition update integrity data does not exist independently, and there is a mutual correlation between the independent variables, which requires comprehensive analysis. When the blood pressure data acquisition volume increases, it means that more blood pressure information can be obtained, which helps to improve the accuracy and integrity of blood pressure monitoring. The larger the blood pressure data acquisition volume, it may also lead to an increase in the update time, and even may introduce more noise, resulting in an increase in the blood pressure acquisition noise ratio; the more the number of inflation and deflation cycles, the more likely it is to increase noise interference, thereby affecting the acquisition quality of data; the longer the inflation interval, the more likely it is to lead to a decrease in the integrity of data and the continuity of monitoring, and further lead to stronger noise interference, resulting in an increase in the blood pressure acquisition noise ratio; by analyzing the comprehensive influence between parameters, the accurate evaluation of the update integrity of blood pressure-related data in the process of acquisition update integrity evaluation is realized, and further the improvement of the accuracy of stroke risk warning data is realized.

[0078] Among them, the specific process of stroke risk warning based on the stroke risk prediction level is as follows: input 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; input the real-time obtained 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, it indicates a high stroke risk, and send a first-level warning prompt to the preset personnel; when the stroke risk prediction model outputs a second-level warning, it indicates a low stroke risk, and send 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 acquisition evaluation value and the blood pressure-related data corresponding to the qualified acquisition evaluation value.

[0079] In this embodiment, the obtained stroke risk prediction data and the preset stroke risk prediction level are input into the constructed existing digital twin model for training to obtain the trained digital twin model, that is, the stroke risk prediction model. Then, by inputting the obtained real-time stroke risk prediction data into the stroke risk prediction model, the stroke risk prediction level can be output. If a first-level warning is output, it indicates a high stroke risk level, and a first-level warning prompt is sent to the preset personnel. If a second-level warning is output, it indicates a relatively low stroke risk level (compared with the first-level warning), and a second-level warning prompt is sent to the preset personnel. After receiving the warning prompt, the preset personnel can take preset measures, thereby realizing real-time monitoring of stroke risk protection, avoiding inaccurate prediction results caused by data quality problems, and further achieving the effect of improving the accuracy of stroke risk warning data.

[0080] As Figure 2 shown, it is a schematic structural diagram of the stroke risk warning system based on digital twin provided by the embodiment of the present invention. The embodiment of the present invention provides a stroke risk warning system based on digital twin, including a collection evaluation module, a collection update delay evaluation module, a collection update integrity evaluation module, and a stroke risk prediction level module. Among them, the collection evaluation module is used to analyze the obtained collection control data to obtain a collection evaluation value, and judge whether to perform collection update delay evaluation and collection update integrity evaluation; the collection update delay evaluation module is used to, if the collection update delay evaluation is performed, perform data update delay analysis according to the obtained collection update delay data, and judge whether to perform collection update delay optimization; the collection update integrity evaluation module is used to, if the collection update integrity evaluation is performed, perform data update integrity analysis according to the obtained collection update integrity data, and judge whether to perform collection update integrity optimization; the stroke risk prediction level module is used to input the stroke risk prediction data corresponding to the obtained qualified collection 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 collection evaluation value represents the collection evaluation value that meets the preset collection control interval.

[0081] In this embodiment, based on the acquisition evaluation value monitored by the acquisition evaluation module, it is determined whether to perform acquisition update delay evaluation and acquisition update integrity evaluation. When the acquisition evaluation value is within the preset acquisition control range, no acquisition update delay evaluation and acquisition update integrity evaluation are performed; the acquisition update delay evaluation module and the acquisition update integrity evaluation module are respectively used to perform acquisition update delay evaluation and acquisition update integrity evaluation. 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 complete value is not lower than the preset acquisition update complete threshold, the acquisition update delay optimization and the 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 monitoring accuracy of the stroke risk, and further achieving the effect of improving the accuracy of the stroke risk warning data.

[0082] The following points need to be explained:

[0083] (1) The accompanying drawings of the embodiments of the present invention only relate to the structures involved in the embodiments of the present invention, and other structures can refer to the general design.

[0084] (2) For clarity, in the accompanying drawings used to describe the embodiments of the present invention, the thickness of the layer or region is enlarged or reduced, that is, these drawings are not drawn according to the actual scale. It can be 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 can be "directly" on or under the other element or there can be an intermediate element.

[0085] (3) Without conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other to obtain new embodiments.

[0086] The above is only the specific implementation manner 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 subject to 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; 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 to perform collection update delay optimization; If the collection and update integrity assessment is performed, the data update integrity analysis is performed based on the acquired collection and update integrity data to determine whether to perform collection and update integrity optimization; 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, characterized in 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 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 value of gas inflow rate, the maximum inflation pressure value, the maximum inflation times value, the maximum value of gas outflow rate, the maximum deflation pressure value and the maximum deflation times value; The preset acquisition control parameters include a preset maximum inflow rate, a preset maximum inflation pressure, a preset maximum inflation number, a preset maximum outflow rate, a preset maximum deflation pressure and a preset maximum deflation number; The acquisition update delay data is used to reflect the influence of the acquisition update delay parameter on the synchronization of blood pressure related data update 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 by processing based on the acquisition update delay parameter and the preset acquisition 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 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; 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 value of the acquired blood pressure data volume and the acquired 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 stroke risk early warning method based on digital twins according to claim 2 is 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 gas inflow first processing value to obtain a gas inflow-pressure influence value, wherein the gas inflow-pressure influence value represents quantitative data of the influence degree of the maximum gas inflow rate and the maximum inflation pressure value on the blood pressure related data acquisition control, and 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, wherein the gas inflow-number influence value represents quantitative data of the degree of influence of the maximum gas inflow rate and the maximum inflation number value on the blood pressure related data acquisition control, and 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 processing on the obtained gas outflow first processed value to obtain a gas outflow-pressure influence value, wherein the gas outflow-pressure influence value represents quantitative data of the influence degree of the maximum gas outflow rate and the maximum deflation pressure value on the blood pressure related data acquisition control, and the gas outflow first processed 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; Performing a second outflow operation on the obtained gas outflow second processed value to obtain a gas outflow-number influence value, wherein the gas outflow-number influence value represents quantitative data of the degree of influence of the maximum gas outflow rate and the maximum deflation number value on the blood pressure related data acquisition control, and the gas outflow second processed 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; 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 stroke risk early warning method based on digital twins according to claim 3 is characterized in that: The specific process of determining whether to perform collection update delay assessment and collection 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 collection evaluation value is within the preset collection control interval, the numerical value corresponding to the corresponding collection evaluation value is marked as a qualified collection evaluation value; When the collection evaluation value is greater than the preset collection control maximum value, the collection 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 stroke risk early warning method based on digital twins according to claim 2 is 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 obtained by multiplying the collection update delay data and the preset collection update delay weight group obtained from the database; 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 response delay first processing value, and the response and number evaluation value represents quantitative data of the degree of influence of the maximum value of the number of inflation and deflation times and the maximum value of the response delay duration on the update delay of the blood pressure related data, and the response delay first processing value includes the maximum value of the response delay duration, the maximum value of the number of inflation and deflation times, the preset response and inflation and deflation weights, the preset maximum value of the response delay duration, and the preset maximum value of the 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 quantitative data of the degree of influence of the maximum value of the inflation interval duration and the maximum value of the response delay duration on the delay in updating the blood pressure related data; the response delay second processing value includes the maximum value of the response delay duration, the maximum value of the inflation interval duration, the preset response and interval weight, the preset maximum value of the response delay duration and the preset maximum value of the inflation interval; The update and number evaluation value is obtained by performing a first update delay operation on the update delay first processing value, and the update and number evaluation value represents quantitative data of the influence of the maximum value of the number of inflation and deflation times and the maximum value of the update delay duration on the update delay of the blood pressure related data, and the update delay first processing value includes the maximum value of the update delay duration, the maximum value of the number of inflation and deflation times, the preset update and inflation and deflation weights, the preset maximum value of the update delay duration, and the preset maximum value of the number of inflation and deflation times; The update and interval evaluation value is obtained by performing a second update delay operation on the update delay second processing value. 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 update delay second processing value 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 stroke risk early warning method based on digital twins according to claim 5 is characterized in 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 a preset collection update delay threshold; If yes, do not perform collection update delay optimization, otherwise send a reminder 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 the collection update delay optimization, an alarm is sent to the preset personnel; The collection update delay optimization includes reducing the collection frequency and prompting pressure relief; The lowering of the collection frequency means that the preset personnel gradually lower the collection frequency of blood pressure related data by a preset multiple; The reminder to release blood pressure means sending a reminder to a preset person to adjust the number of pressure releases of the blood pressure monitor.

7. The stroke risk early warning method based on digital twins according to claim 2 is 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 collection completeness and number of times evaluation value is obtained by performing completeness and inflation and deflation operation processing on the complete and inflation and deflation data group, wherein the collection completeness and number of times evaluation value represents the quantitative data of the influence of the maximum amount of collected blood pressure data and the maximum number of inflation and deflation times on the integrity of the update of blood pressure related data, and 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 completeness 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 complete and interval data group is processed by complete and interval calculation to obtain a collection complete and interval evaluation value, wherein the collection complete and interval evaluation value represents quantitative data of the influence of the maximum amount of collected blood pressure data and the maximum value of the inflation interval duration on the integrity of the blood pressure related data update, and the complete and interval data group includes the maximum amount of collected blood pressure data, the maximum value of the inflation interval duration, a preset complete and interval weight value, a preset maximum amount of collected blood pressure data, and a preset maximum value of the inflation interval; The acquisition integrity and noise evaluation value is obtained by performing integrity and noise ratio calculation processing on the integrity and noise ratio data group, wherein the acquisition integrity and noise evaluation value represents 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, and the complete and noise ratio data group includes the maximum amount of collected blood pressure data, the collected blood pressure noise ratio, a preset complete and noise ratio weight value, a preset maximum amount of collected blood pressure data, and a preset maximum blood pressure collection noise ratio; The collection and update integrity value is obtained by multiplying the collection and update integrity data and the preset collection and update integrity weight group obtained from the database; The collection and update completeness value is used to reflect the update completeness of blood pressure related data during the collection and update completeness assessment process.

8. The digital twin-based stroke risk warning method according to claim 7, characterized in that: The specific process of determining whether to perform collection update integrity optimization is as follows: Determine whether the monitored collection update complete value is not less than a preset collection update complete threshold obtained from the database; If yes, do not perform collection update integrity optimization, otherwise send a reminder to the preset personnel to perform collection 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, an alarm is sent to the preset personnel; The collection update integrity optimization includes increasing the collection frequency and prompting for charging; The increasing collection frequency means that the preset personnel gradually increase the collection frequency of blood pressure related data by a preset multiple; The charging reminder means sending a reminder to a preset person to adjust the charging times of the blood pressure monitor.

9. The stroke risk early warning method based on digital twins according to claim 1, characterized in that: The specific process of performing stroke risk warning based on 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 a stroke risk prediction model; Inputting the stroke risk prediction data acquired 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, a first-level warning prompt is sent to the preset personnel; When the stroke risk prediction model outputs a second-level warning, a second-level warning prompt is sent to the preset personnel; The stroke risk prediction levels include primary warning and secondary warning; The stroke risk prediction data includes qualified collection assessment values ​​and blood pressure related data corresponding to the qualified collection assessment values.

10. A stroke risk warning system based on digital twins, 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 an acquisition update delay evaluation and an 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 the 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 the 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 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.

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