CN110710960B - Arterial blood vessel age estimation method and device - Google Patents
Arterial blood vessel age estimation method and device Download PDFInfo
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Abstract
The application is suitable for cardiovascular disease prevention technical field, provides a blood vessel age reckoning method, including obtaining the basic data that wait to detect the user, the basic data includes: the actual physiological age, gender, and actual arteriosclerosis index of the user; determining the age bracket to which the user to be detected belongs according to the actual physiological age of the user to be detected; acquiring an ASI average value and an ASI standard deviation value corresponding to the age bracket and the gender from a pre-established clinical database according to the age bracket to which the user to be detected belongs and the gender; calculating to obtain an ASI standard score according to the actual arteriosclerosis index ASI, the obtained ASI average value and the ASI standard deviation value; and calculating to obtain the initial age of the artery of the user to be detected according to the ASI standard score, the actual physiological age of the user to be detected and the age bracket of the user to be detected.
Description
Technical Field
The application belongs to the technical field of cardiovascular disease prevention, and particularly relates to an arterial blood vessel age calculation method and device.
Background
Cardiovascular diseases (CVD) have the characteristics of high morbidity, high disability rate and the like, and are continuously the first cause of death of residents in China since 1990. Therefore, the method has important clinical significance for screening asymptomatic CVD high-risk groups and performing primary prevention. Arteriosclerosis and changes in arterial lumen elasticity play an important role in the development of CVD and are a prerequisite for the development of cardiovascular disease. Thus, monitoring of vascular sclerosis and alterations in elasticity is more predictive of the occurrence of cardiovascular events.
The judgment criteria for the elasticity and age of the artery mainly include the following three types: framingham score, pulse wave velocity, and carotid intimal-media thickness. The Fremingham score can well reflect the condition of arterial aging grade and give the risk of cardiovascular and cerebrovascular diseases within ten years. However, the method does not provide the corresponding vascular age, and compared with the vascular age, the vascular age is more intuitive, so that the psychological feeling caused by the method can urge the patient to adopt a more reasonable life style; in addition, the implementation of the technology can only be carried out in hospitals, and many patients rarely go to the hospitals for examination without diseases, thereby greatly reducing the effect of preventing cardiovascular diseases.
Therefore, an arterial blood vessel age estimation method is urgently needed so as to predict the risk degree of heart disease, cerebral apoplexy, diabetes and the like.
Disclosure of Invention
The embodiment of the application provides an artery blood vessel age estimation method and device, and aims to solve the problem that the blood vessel age cannot be accurately estimated in the traditional technical scheme.
The embodiment of the application is realized in such a way that a method for estimating the age of a blood vessel comprises a method for estimating the age of an artery blood vessel, and comprises the following steps:
acquiring basic data of a user to be detected, wherein the basic data comprises: the actual physiological age, gender, and actual arteriosclerosis index of the user;
determining the age bracket of the user to be detected according to the actual physiological age of the user to be detected; acquiring an ASI average value and an ASI standard deviation value corresponding to the age bracket and the gender from a pre-established clinical database according to the age bracket to which the user to be detected belongs and the gender;
calculating to obtain an ASI standard score according to the actual arteriosclerosis index, the obtained ASI average value and the obtained ASI standard deviation value;
and calculating to obtain the initial age of the artery of the user to be detected according to the ASI standard score, the actual physiological age of the user to be detected and the age bracket to which the user to be detected belongs.
In a second aspect, an embodiment of the present application further provides an arterial blood vessel age estimation device, including:
the first acquisition module is used for acquiring basic data of a user to be detected, and the basic data comprises: the actual physiological age, gender and actual arteriosclerosis index ASI of the user;
the age group determining module is used for determining the age group of the user to be detected according to the actual physiological age of the user to be detected;
the second acquisition module is used for acquiring an ASI average value and an ASI standard deviation value corresponding to the age group and the gender from a pre-established clinical database according to the age group and the gender to which the user to be detected belongs;
the first calculation module is used for calculating to obtain an ASI standard score according to the actual arteriosclerosis index, the obtained ASI average value and the obtained ASI standard deviation value;
and the second calculation module is used for calculating and obtaining the initial age of the artery of the user to be detected according to the ASI standard score, the actual physiological age of the user to be detected and the age group of the user to be detected.
In a third aspect, an embodiment of the present application further provides a terminal device, including the apparatus in the second aspect, a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the blood vessel age estimation method in any one of the first aspects when executing the computer program.
In a fourth aspect, the present application further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the method for estimating the age of a blood vessel according to any one of the first aspect is implemented.
According to the embodiment of the application, the standard score is calculated by utilizing a big database, the age, the sex and the actual arteriosclerosis index of a user, and the age of a blood vessel is further calculated according to the ASI standard score, so that the risk degree of heart disease, cerebral apoplexy, diabetes and the like is predicted; and further correcting the estimated age of the blood vessel according to whether the tested person smokes and drinks, and at least one factor of systolic pressure, diastolic pressure, pulse pressure, heart rate and age, or/and correcting the actual arteriosclerosis index and then further estimating the age of the blood vessel, so that the estimation accuracy is improved, and a reference basis is provided for disease diagnosis more effectively.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic diagram of an arterial blood vessel age estimation method according to an embodiment of the present disclosure;
FIG. 2 is a diagram of a pulse waveform of a user according to an embodiment of the present disclosure;
FIG. 3 is a diagram of a pulse waveform of a low heart rate user according to an embodiment of the present disclosure;
FIG. 4 is a diagram of a pulse waveform of a user with heart rate variability according to an embodiment of the present disclosure;
fig. 5 is a schematic view of an arterial blood vessel age estimation device according to an embodiment of the present disclosure;
fig. 6 is a schematic view of an arterial blood vessel age estimation device according to an embodiment of the present disclosure;
fig. 7 is a schematic diagram of a terminal device according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
In order to explain the technical solution described in the present application, the following description will be given by way of specific examples.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the present application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in the specification of the present application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
The first embodiment is as follows:
referring to fig. 1, the arterial blood vessel age estimation provided in the first embodiment of the present application is described as follows, and the arterial blood vessel age estimation in the first embodiment of the present application includes:
the arteriosclerosis index (ASI for short) reflects the degree of arteriosclerosis, and the smaller the numerical value is, the lighter the degree of arteriosclerosis is, and the lower the risk of causing cardiovascular and cerebrovascular diseases is; if the arteriosclerosis index is 4 or more, it is considered that arteriosclerosis has occurred, and the larger the value is, the more severe the degree of arteriosclerosis is, and the higher the risk of cardiovascular and cerebrovascular diseases is. The actual method for measuring the arteriosclerosis index is not specifically limited in the application, and the measurement can be carried out by adopting the existing mature technology.
Modern people live more and more tired, eat more and more unhealthy, move less and less, and unconsciously accelerate the blockage of blood vessels, so that the blood vessels can step into the old in advance. The actual physiological and vascular ages of humans may vary widely, with a 30 year old human having blood vessels that are 60 years old. Higher vessel age reflects higher arterial stiffness and greater risk of cardiovascular and cerebrovascular disease.
102, determining the age bracket of the user to be detected according to the actual physiological age of the user to be detected;
the age group can determine the age span according to actual conditions, can be refined to each month of each age, and can also comprise a longer age span, such as 1-10 years. For example, the age groups are divided into 10 years, 20 years, 30 years, 40 years, 50 years, 60 years, 70 years, 80 years, 90 years and 100 years in 10 years, the actual physiological age of the user to be detected is 7 years and belongs to the 10 years age group, and the actual physiological age of the user to be detected is 35 years and belongs to the 40 years age group. To be closer to the actual situation, the age groups may be more refined, for example, the age groups may be divided by 5 years, or the age groups may be divided by 1 year.
103, acquiring an ASI average value and an ASI standard deviation value corresponding to the age bracket and the gender from a pre-established clinical database according to the age bracket to which the user to be detected belongs and the gender;
when the clinical database is established in advance, more user samples are required to be contained, and the user can reflect different conditions as much as possible, such as different health degrees, different professions, different regions, different family histories and the like, so that the sample data has representativeness. The arteriosclerosis indexes ASI of each user in the sample are measured one by one, and the average Mean and Standard Deviation SD (Standard development) of the arteriosclerosis indexes ASI corresponding to users of different ages and different sexes are calculated. Age group, gender, corresponding ASI mean and ASI standard deviation values are calculated and stored in a clinical database.
104, calculating to obtain an ASI standard score according to the actual arteriosclerosis index of the user to be detected, the obtained ASI average value and the obtained ASI standard deviation value;
wherein the ASI standard score is calculated specifically as:
ASI standard score = (actual arteriosclerosis index-ASI mean)/ASI standard deviation value;
or ASI standard score = ((Log (actual arteriosclerosis index-X, Y) × 100) -ASI mean)/ASI standard deviation value.
Wherein X, Y is a fixed parameter value, the preferable X value range is 15-40, and the Y value range is 3-8.
Preferably, the ASI standard score calculated may be stored for later use.
And 105, calculating to obtain the initial age of the artery of the user to be detected according to the ASI standard score, the actual physiological age of the user to be detected and the age bracket of the user to be detected.
Preferably, the calculation of the initial age of the artery of the user to be detected specifically includes:
the initial age of the arterial vessel = actual physiological age + age group/(N × ASI standard score), N ranges from 8 to 12, and preferably N is 10.
Preferably, the initial age of the artery blood vessel can be displayed to a user through a display, or can be sent to the user or a medical unit through a network, a mobile phone and the like, so that the user can know the health condition, and a doctor can decide a treatment mode or store the treatment mode for later use.
Further, in order to improve the estimation accuracy of the blood vessel age, further correction is needed for some special cases. After step 105, further comprising:
and step 106, correcting the initial age of the arterial blood vessel by adopting a comprehensive correction coefficient K to obtain the final age of the arterial blood vessel, wherein the final age = K = K multiplied by the initial age of the arterial blood vessel, and the comprehensive correction coefficient K is related to at least one factor of whether a user smokes and drinks, systolic pressure, diastolic pressure, pulse pressure, heart rate and age. Specifically, the estimated arterial blood vessel age is positively correlated with the heart rate of the subject, and the larger the heart rate of the subject is, the larger the initial arterial blood vessel age is. Conversely, the smaller the heart rate, the lower the initial age of the resulting arterial vessel.
Specifically, ASI is related to whether the subject smokes or drinks. If the testee smokes and drinks frequently in the last few days of the test, the measured ASI value is higher. Smoking is also one of the risk factors for endothelial damage, leading to a reduction in the amount of NO released from the endothelium. No matter whether the blood pressure is normal or not, the compliance of the artery of the smoking group is obviously reduced compared with that of the non-smoking group, and is obviously related with the annual number of smoking. Prolonged lack of exercise also reduces arterial tone, and exercise can increase arterial compliance with increased oxygen consumption. The long-term high-salt diet also has injury effect on vessel wall. In daily life, people with high stress and high mental stress may have reduced elasticity of arteries compared with other normal people. In addition to environmental factors, genetic factors may play a role in the reduction of arterial tone.
Arterial vessel prediction age is generally higher in hypertensive patients with high systolic blood pressure than in normotensive patients. This is because when the systolic pressure is high, the pulse wave breaks the cuff and the pressure is relatively early, so that the pressure reflection wave comes in advance, which increases the systolic pressure and thus increases the initial age of the arterial vessel.
When the diastolic pressure is low, the time for the arterial blood flow to be patent is delayed backwards and the elasticity of the artery becomes weaker. This causes the diastolic pressure to decrease, thereby increasing the initial age of the arterial vessel.
The pulse pressure is the late stage of arteriosclerosis, and when the pulse pressure increases, the elasticity of the artery decreases, the pulse wave velocity is small, and the blood flow impulse becomes small. At the same time, the systolic pressure becomes larger and the diastolic pressure becomes smaller, thereby increasing the initial age of the arterial vessel.
With age, pulse pressure increases and high pulse pressure difference is considered to be an important risk factor for cardiovascular events, mainly due to the decreased compliance of the aorta with age. As the age increases, ASI tends to increase, and the incidence of arteriosclerosis varies significantly among age groups.
At least one of whether the user smokes and drinks, the systolic pressure, the diastolic pressure, the pulse pressure, the heart rate, the age and the like of the user can be selected as a correction factor according to actual conditions; and grouping the selected correction factors, wherein each group corresponds to one correction coefficient, and the comprehensive correction coefficient K is equal to the product of all grouped correction coefficients. Where each packet may contain one or more factors. It is understood that the number of the correction factors can be only 1, the number of the groups can be determined according to the requirement, and the number of the factors in each group can be determined according to the requirement.
Taking the example that each group only contains one correction factor, when only the systolic pressure factor is selected for correction, the comprehensive correction coefficient K = K2; or when two factors of systolic pressure and diastolic pressure are selected for correction, the comprehensive correction coefficient K = K2 multiplied by K3; or when five factors of systolic pressure, diastolic pressure, pulse pressure, heart rate and age are selected for correction, the comprehensive correction coefficient K = K2 × K3 × K4 × K5 × K6, and so on, and is not described herein again;
taking the example that each group contains different correction factors, for example, considering whether smoking and drinking, systolic pressure, diastolic pressure, pulse pressure, heart rate, age 6 factors, the groups are three: determining a correction coefficient K1 according to whether the user smokes and drinks as a first group; determining a correction coefficient K2 according to the systolic pressure, the diastolic pressure and the pulse pressure of the user as a second sub-group; and determining a correction coefficient K3 according to the third group of the heart rate and the age of the user, wherein the comprehensive correction coefficient K = K1 × K2 × K3.
Taking the example that each group contains different correction factors, when considering 5 factors of systolic pressure, diastolic pressure, pulse pressure, heart rate and age, the groups are divided into two groups: determining a correction coefficient K2 according to the heart rate, the systolic pressure, the diastolic pressure and the pulse pressure of a user as a first group; the correction factor K3 is determined from the age of the user as a second group, and the overall correction factor K = K2 × K3.
It is understood that the influence factors can be freely combined in grouping, and specific transformation is not illustrated here.
Preferably, for a user with a heart rate of more than 120 times/minute, the value range of the correction coefficient K5 is 1.0-1.1.
Preferably, the correction coefficient K2 ranges from 1.2 to 1.4 for patients with a systolic blood pressure of 140mmHg or higher.
Preferably, the correction coefficient K3 ranges from 0.8 to 1.0 for users with diastolic blood pressure lower than 80 mmHg.
Preferably, the correction coefficient K4 ranges from 1.0 to 1.1 for a user with a pulse pressure higher than 60 mmHg.
Preferably, the correction coefficient K6 ranges from 1.0 to 1.1 for users over 60 years old.
In step 104, the actual arteriosclerosis index measuring method for the user to be detected specifically comprises the following steps:
the oscillography is to identify the small pulses from arm to cuff, differentiate them and perform multiple treatments to form an envelope representing the peak value of the pulses, so as to obtain the blood pressure value. As shown in fig. 2, a mountain-shaped graph is a graph of pulse wave pressure of a user monitored by an oscillometric method, an arc line is a cuff pressure curve, a first point and a last point where a straight line corresponding to 80% of a maximum peak value of a pulse wave intersects with the pulse wave are selected, a cuff pressure curve pressure value corresponding to the first point is taken as P1, a cuff pressure curve pressure value corresponding to the last point is taken as P2, an actual arteriosclerosis index = mx (P1-P2) of the user, a value range of M is 8-12, and preferably N is 10.
In order to calculate the ASI standard score more accurately, the ASI standard score may be calculated after correcting the actual calculation process of the arteriosclerosis index. For example, in the case of a low heart rate, the pressure curve drops faster between two waves due to less effective waveform, but 80% of the maximum peak is selected, and then the point closest to 80% of the maximum peak is found in the peak array, which is likely to cause poor detection when the peak points of two adjacent waves are close. To this end, the system will process as follows: when finding the peak point on the left of the maximum peak value, if 80% of the amplitude of the maximum peak value point is right between two waves with similar peak values, taking the pulse wave of the rear peak value A point, and multiplying the corresponding cuff pressure P1 by a correction coefficient J1 which is more than 1 to correct; when finding the peak value right of the maximum peak value, the pulse wave of the next peak value D point is also taken, and the corresponding cuff pressure P2 is multiplied by a correction coefficient J2 which is larger than 1 for correction. Due to the arrangement ofIn the process of gas, the gas generally begins to bleed faster, so K31 is available>K31'. For example, one tester data collected by the arteriosclerosis and vascular age measuring device is shown in fig. 3, the tester is a 76-year-old female, and the heart rate is only 43 times/min. As can be seen from fig. 3, the abscissa represents the number of sampling points, and the ordinate represents the pulse wave pressure value of the user, which is the case where the corresponding pressure values of the front and rear pulse waves need to be corrected. The detection system can take the point A and the point D to respectively correct the pressure value and the correction coefficient K ＇ = × J1 × J2, and the corrected arteriosclerosis index of the user = M × (P1-P2) × J1 × J2.
The correction of the actual calculation of the arteriosclerosis index can also be the case: when the systolic pressure is higher, brachial arteries are not completely blocked, a larger oscillatory wave appears in the initial deflation stage, the first point and the last point where a straight line corresponding to 80% of the maximum peak value of the pulse wave intersects with the pulse wave are not directly selected, but the first point and the last point where a straight line corresponding to 80% +/-5% of the maximum peak value of the pulse wave intersects with the pulse wave are selected, and then the actual arteriosclerosis index of the user is calculated as described above.
The actual calculation of the arteriosclerosis index may be corrected as follows: when heart rate variation occurs, as shown in fig. 4, it is easy to generate error by performing conventional calculation according to the oscillometric principle, because the heart rate variation causes the waveform to be very disordered and the waveform regularity is poor, as shown in fig. 5, the actual arteriosclerosis index of the user is calculated according to pulse wave compensation and sequence exchange.
Furthermore, the technical scheme of correcting the actual arteriosclerosis index calculation process can be combined with the technical scheme of correcting by adopting the comprehensive correction coefficient K, namely correcting the actual arteriosclerosis index calculation of the user firstly and then correcting by adopting the comprehensive correction coefficient K.
Example two:
in a second embodiment of the present application, there is provided an arterial blood vessel age estimation device, which is shown only in the relevant portions of the present application for convenience of explanation, and with reference to fig. 6, the arterial blood vessel age estimation device includes:
a first obtaining module 601, configured to obtain basic data of a user to be detected, where the basic data includes: the actual physiological age, gender and actual arteriosclerosis index ASI of the user;
an age group determining module 602, configured to determine, according to the actual physiological age of the user to be detected, an age group to which the user to be detected belongs;
a second obtaining module 603, configured to obtain, according to the age group and the gender of the user to be detected, an ASI average value and an ASI standard deviation value corresponding to the age group and the gender from a pre-established clinical database;
a first calculating module 604, configured to calculate an ASI standard score according to the actual arteriosclerosis index, the obtained ASI average value, and the obtained ASI standard deviation value;
the second calculating module 605 is configured to calculate and obtain an initial age of an artery of the user to be detected according to the ASI standard score, the actual physiological age of the user to be detected, and the age group to which the user to be detected belongs.
Optionally, the first calculating module 604 is specifically configured to:
ASI standard score = (actual arteriosclerosis index-SI mean)/ASI standard deviation value; or ASI standard score = ((Log (actual arteriosclerosis index-X, Y) × 100) -ASI mean)/ASI standard deviation value, X and Y are fixed parameter values.
Optionally, the second calculating module 605 is specifically configured to:
the initial age of the arterial vessel = actual physiological age + age group/(N × ASI standard score), and N ranges from 8 to 12.
Optionally, the arterial blood vessel age estimation device further includes:
and the first correction module is used for correcting the initial age of the artery blood vessel by adopting a comprehensive correction coefficient K to obtain the final age of the artery blood vessel, wherein the final age of the artery blood vessel = K multiplied by the initial age of the artery blood vessel, and the comprehensive correction coefficient K is related to at least one factor of smoking and drinking of a user, systolic pressure, diastolic pressure, pulse pressure, heart rate and age of the user.
Optionally, the first modification module is specifically configured to:
selecting whether the user smokes and drinks, and the systolic pressure, diastolic pressure, pulse pressure, heart rate and age of the user as correction factors;
and grouping the selected correction factors, wherein each group corresponds to one correction coefficient, and the comprehensive correction coefficient K is equal to the product of all grouped correction coefficients.
Optionally, the arterial blood vessel age estimator further comprises:
and the second correction module is used for calculating the ASI standard score after correcting the actual arteriosclerosis index.
Optionally, the actual arteriosclerosis index = M × (P1-P2), the value range of M is 8 to 12, P1 is a cuff pressure curve pressure value corresponding to a first point where a straight line corresponding to 80% of the maximum peak value of the pulse wave intersects the pulse wave, and P2 is a cuff pressure curve pressure value corresponding to a last point where a straight line corresponding to 80% of the maximum peak value of the pulse wave intersects the pulse wave.
Example three:
fig. 7 is a schematic diagram of a terminal device provided in the third embodiment of the present application. As shown in fig. 7, the terminal device 7 of this embodiment includes: a processor 70, a memory 71 and a computer program 72 stored in said memory 71 and executable on said processor 70. The processor 70, when executing the computer program 72, implements the steps in the above-described embodiment of the arterial blood vessel age estimation method, such as steps S101 to S105 shown in fig. 1. Alternatively, the processor 70, when executing the computer program 72, implements the functions of each module/unit in the above-mentioned device embodiments, such as the functions of the modules 601 to 605 shown in fig. 6.
Illustratively, the computer program 72 may be partitioned into one or more modules/units that are stored in the memory 71 and executed by the processor 70 to accomplish the present application. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program 72 in the terminal device 7. For example, the computer program 72 may be divided into a position information module, a distance sorting module, an obstacle detection module, a re-detection module, and an electromagnetic interference module, each of which has the following specific functions:
the terminal device 7 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The terminal device may include, but is not limited to, a processor 70, a memory 71. It will be appreciated by those skilled in the art that fig. 7 is merely an example of a terminal device 7 and does not constitute a limitation of the terminal device 7 and may comprise more or less components than shown, or some components may be combined, or different components, for example the terminal device may further comprise input output devices, network access devices, buses, etc.
The Processor 70 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 71 may be an internal storage unit of the terminal device 7, such as a hard disk or a memory of the terminal device 7. The memory 71 may also be an external storage device of the terminal device 7, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the terminal device 7. Further, the memory 71 may also include both an internal storage unit and an external storage device of the terminal device 7. The memory 71 is used for storing the computer program and other programs and data required by the terminal device. The memory 71 may also be used to temporarily store data that has been output or is to be output.
In a fourth aspect, the present application further provides a computer-readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the computer program implements the steps that can be implemented in the foregoing method embodiments.
In a fifth aspect, the present application provides a computer program product, which when executed on a mobile terminal, enables the mobile terminal to implement the steps in the foregoing method embodiments.
The beneficial effects of the embodiment of the application are as follows:
(1) Calculating a standard score by using a big database, the age, the sex and the actual arteriosclerosis index of the user, and further calculating the age of a blood vessel according to the ASI standard score so as to predict the risk degree of heart disease, cerebral apoplexy, diabetes and the like;
(2) According to whether the testee smokes and drinks, at least one factor of systolic pressure, diastolic pressure, pulse pressure, heart rate and age is used for correcting the initial age of the arterial blood vessel, or/and the actual arteriosclerosis index of the user is corrected, and then the age of the blood vessel is further calculated, so that the calculation accuracy is improved, and a reference basis is provided for disease diagnosis more effectively.
It should be noted that, for the information interaction, execution process, and other contents between the above-mentioned devices/units, the specific functions and technical effects thereof are based on the same concept as those of the embodiment of the method of the present application, and specific reference may be made to the part of the embodiment of the method, which is not described herein again.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium and can implement the steps of the embodiments of the methods described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing apparatus/terminal apparatus, a recording medium, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), an electrical carrier signal, a telecommunications signal, and a software distribution medium. Such as a usb-disk, a removable hard disk, a magnetic or optical disk, etc. In certain jurisdictions, computer-readable media may not be an electrical carrier signal or a telecommunications signal in accordance with legislative and patent practice. In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment. Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.
Claims (5)
1. An arterial blood vessel age estimation device, comprising:
the first acquisition module is used for acquiring basic data of a user to be detected, and the basic data comprises: the actual physiological age, sex and actual arteriosclerosis index ASI of the user;
the age group determining module is used for determining the age group to which the user to be detected belongs according to the actual physiological age of the user to be detected, and the age group is an age span determined according to the actual situation;
the second acquisition module is used for acquiring an ASI average value and an ASI standard deviation value corresponding to the age group and the gender from a pre-established clinical database according to the age group and the gender of the user to be detected; wherein the ASI standard score obtained by calculation is as follows:
ASI standard score = (actual arteriosclerosis index-SI mean)/ASI standard deviation value;
the first calculation module is used for calculating to obtain an ASI standard score according to the actual arteriosclerosis index, the obtained ASI average value and the obtained ASI standard deviation value;
the second calculation module is used for calculating and obtaining the initial age of the artery of the user to be detected according to the ASI standard score, the actual physiological age of the user to be detected and the age group of the user to be detected; wherein the initial age of the artery of the user to be detected obtained by calculation is as follows:
the initial age of the arterial vessel = actual physiological age + age group/(N × ASI standard score), and the value range of N is 8-12;
and the correction module is used for correcting the initial age of the artery blood vessel by adopting a comprehensive correction coefficient K to obtain the final age of the artery blood vessel, wherein the final age of the artery blood vessel = K multiplied by the initial age of the artery blood vessel, and the comprehensive correction coefficient K is related to at least one factor of whether the user smokes and drinks, the systolic pressure, the diastolic pressure, the pulse pressure, the heart rate and the age of the user.
2. The arterial vessel age estimator according to claim 1, wherein the correlation of the integrated correction factor K with at least one of whether the user smokes and drinks, the systolic pressure, the diastolic pressure, the pulse pressure, the heart rate, and the age of the user comprises:
selecting whether the user smokes and drinks, and the systolic pressure, diastolic pressure, pulse pressure, heart rate and age of the user as correction factors;
and grouping the selected correction factors, wherein each group corresponds to one correction coefficient, and the comprehensive correction coefficient K is equal to the product of all grouped correction coefficients.
3. The arterial vessel age estimator according to any of claims 1 to 2, further comprising:
calculating the ASI standard score after correcting the actual arteriosclerosis index.
4. The arterial blood vessel age estimation device according to claim 3, wherein the actual arteriosclerosis index = M x (P1-P2), M ranges from 8 to 12, P1 is a cuff pressure curve pressure value corresponding to a first point where a straight line corresponding to 80% of a maximum peak value of a pulse wave intersects the pulse wave, and P2 is a cuff pressure curve pressure value corresponding to a last point where a straight line corresponding to 80% of the maximum peak value of the pulse wave intersects the pulse wave.
5. A terminal device comprising the apparatus of claim 1, a memory, a processor, and a computer program stored in the memory and executable on the processor.
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| CN114431847A (en) * | 2020-11-06 | 2022-05-06 | 爱奥乐医疗器械(深圳)有限公司 | Arteriosclerosis detection method, device, system and computer program |
| CN112582067A (en) * | 2020-12-21 | 2021-03-30 | 安徽华米智能科技有限公司 | Age estimation model training and age estimation method and device based on big data |
| US20220336104A1 (en) * | 2021-04-16 | 2022-10-20 | Withings | Devices, Systems and Processes to Compute A Vascular Health Related Score |
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