CN107491628A - Personalized user health risk coefficient analysis system and method - Google Patents
Personalized user health risk coefficient analysis system and method Download PDFInfo
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Abstract
The invention discloses a kind of personalized user health risk network analysis system, data module, collection user data module, platform user data module, data normalization processing module, storage user data module are uploaded including user, for being stored in the user data after the processing of professional etiquette generalized；Consumer's risk model, for by constantly being adjusted to user data, continuing to optimize and calculating analysis so as to which user health risk be identified；Risk factor module is generated, for carrying out calculating the final health risk coefficient for drawing user according to all customer data and consumer's risk model.Using above-mentioned technical proposal, by obtaining all static and dynamic datas of user and constantly updating and improve the data of each side, the risk model of user can more accurately be obtained, new health risk coefficient is constantly calculated, so as to draw more accurate health risk assessment result, relatively reliable accurate Risk-warning is provided the user.
Description
Technical field
The present invention relates to internet field of medical technology, refers specifically to a kind of personalized user health risk network analysis system and method.
Background technology
As the deterioration of people's living environment, the frequency more and more higher of the life major disease of ordinary people, age increasingly rejuvenation, people increasingly want to a reliable system and their physical risk state are monitored, alerted.Secondly as all trades and professions interconnect the development of networking, smart machine is increasingly popularized, and we can obtain the wider data of user, and then monitoring more in all directions is carried out to user's body, and then more rationally, the health risk of more punctual identification user.
Relatively more similar risk recognition system currently on the market, the main static data for being all based on user, for example age of user, sex, job overall and gene, system obtain these substantial amounts of data, the health risk assessment then drawn to carrying out data analysis.
There is a bigger defect in such a scheme, be exactly that user's caused data in usually living do not include carry out health risk assessment, such as user movement data, physical examination data, sick state, and then cause health risk assessment deviation to be present.
Therefore the present invention needs to provide a kind of personalized user health risk network analysis system and method, mainly include user's static data（Age of user, sex, job overall, gene）Caused data, which are uniformly included, in usually being lived with user shares assessment, so as to draw the health risk assessment result more prepared.
The content of the invention
Present invention aims at solve above-mentioned the deficiencies in the prior art, there is provided a kind of personalized user health risk network analysis system and method, the system is by the static data of user（Age of user, sex, job overall, gene）Caused data, which are uniformly included, in usually being lived with user shares assessment, so as to draw the health risk assessment result more prepared.
In order to solve the above-mentioned technical problem, the technical scheme is that：
A kind of personalized user health risk network analysis system, including：
User uploads data module, for the health data by upload user,
User data module is gathered, for gathering user's weight, blood pressure, heart rate, blood fat and the exercise data of user；
Platform user data module, for the user's exercise data for obtaining the static basis data of user, the detailed physical examination data that system is docked with medical center, system are docked with sport health APP；
Data normalization processing module, the data whole for obtaining user, the processing that data are standardized；
User data module is stored, for being stored in the user data after the processing of professional etiquette generalized；
Consumer's risk model, for by constantly being adjusted to user data, continuing to optimize and calculating analysis so as to which user health risk be identified；
Risk factor module is generated, for carrying out calculating the final health risk coefficient for drawing user according to all customer data and consumer's risk model.
Preferably, the user, which uploads the health data that data cell uploads, includes physical examination data and sick state.
Preferably, the exercise data of the collection user data cell collection includes motion duration, move distance, motion consumption.
Preferably, the static basis data of the platform user data cell storage include age, sex, job overall, gene.
Present invention also offers a kind of personalized user health risk systematic analytic method, step includes：
S1, the health data by platform upload user, and user's weight, blood pressure, heart rate, blood fat and the exercise data of user are gathered, while obtain the static basis data of user, user's exercise data that the detailed physical examination data that system is docked with medical center, system are docked with sport health APP；
S2, obtain the whole data of user, the processing to be standardized to data；
S3, the user data being stored in after the processing of professional etiquette generalized；
S4, by constantly being adjusted to user data, continue to optimize and calculate analysis so as to which user health risk be identified；
S5, according to all customer data and consumer's risk model calculate the health risk coefficient for finally drawing user.
Preferably, the step S4 includes：
Step S4-1, by substantial amounts of user data computing, so as to obtain new consumer's risk model；
Step S4-2, health risk coefficient calculating is carried out to user by the new consumer's risk model after continuous renewal.
The present invention has the characteristics of following and beneficial effect：
Using above-mentioned technical proposal, by obtaining all static and dynamic datas of user and constantly updating and improve the data of each side, the risk model of user can more accurately be obtained, new health risk coefficient is constantly calculated, so as to draw more accurate health risk assessment result, relatively reliable accurate Risk-warning is provided the user.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, the required accompanying drawing used in embodiment or description of the prior art will be briefly described below, apparently, drawings in the following description are only some embodiments of the present invention, for those of ordinary skill in the art, without having to pay creative labor, other accompanying drawings can also be obtained according to these accompanying drawings.
Fig. 1 is principle of the invention flow chart；
Fig. 2 is consumer's risk model flow figure in Fig. 1.
Embodiment
The embodiment of the present invention is described further below in conjunction with the accompanying drawings.Herein it should be noted that being used to help understand the present invention for the explanation of these embodiments, but do not form limitation of the invention.It is mutually combined in addition, as long as technical characteristic involved in each embodiment of invention described below does not form conflict can each other.
The invention provides present invention also offers a kind of personalized user health risk systematic analytic method, as shown in figure 1, step includes：
S1, the health data by platform upload user, and user's weight, blood pressure, heart rate, blood fat and the exercise data of user are gathered, while obtain the static basis data of user, user's exercise data that the detailed physical examination data that system is docked with medical center, system are docked with sport health APP；
S2, obtain the whole data of user, the processing to be standardized to data；
S3, the user data being stored in after the processing of professional etiquette generalized；
S4, by constantly being adjusted to user data, continue to optimize and calculate analysis so as to which user health risk be identified；
S5, according to all customer data and consumer's risk model calculate the health risk coefficient for finally drawing user.
In wherein step S1, user, which uploads the health data that data cell uploads, includes physical examination data and sick state；Gathering the exercise data of user data cell collection includes motion duration, move distance, motion consumption；The static basis data of platform user data cell storage include age, sex, job overall, gene.
It should be understood that all personal basic document information and health data of user are obtained in step S1.Personal basic document mainly has address name, sex, age, date of birth, occupation etc..Health data mainly has passing medical history, blood pressure, height, body weight, height and weight index
(BMI), stature, eating habit, health etc..Wherein as blood pressure, height, body weight these data are mainly measured by some portable body examination instruments by user oneself or medical worker, and you are updated to newest numerical value.Passing medical history, eating habit are then filled in by user when registering or filled in by medical worker after body is checked out as user.The projects such as health, stature after body examination Data Analysis Services of the analysis module according to user mainly by voluntarily drawing.Further, it is also possible to be equipped with different motion monitoring instruments for user, the daily exercise situation of user is recorded.By obtaining newest most comprehensive data, so as to draw more accurate, more comprehensive health risk assessment result, relatively reliable accurate Risk-warning is provided the user.
As shown in Fig. 2 step S4 includes：
Step S4-1, by substantial amounts of user data computing, so as to obtain new consumer's risk model；
Step S4-2, health risk coefficient calculating is carried out to user by the new consumer's risk model after continuous renewal.
By obtaining newest most comprehensive data, constantly the health risk coefficient of adjustment user calculates relatively reliable, more accurately.
In the method for the present invention, consumer's risk model：The identification of user health risk factor is a kind of function, wherein, above-mentioned risk model is calculated using following logical function：
Y=alpha+beta 1Y1+ β 2Y2+ ...+β nYn, wherein α is constant, and the β 2 ... of β 1 are coefficients, and Y1, Y2 are variables, and Y is result of calculation, α, β 1, β 2 ... Y1, Y2 can obtain from above-mentioned relevant parameter.
Present invention also offers a kind of personalized user health risk network analysis system, including：
User uploads data module, and for the health data by upload user, user, which uploads the health data that data cell uploads, includes physical examination data and sick state.
User data module is gathered, for gathering user's weight, blood pressure, heart rate, blood fat and the exercise data of user, the exercise data of collection user data cell collection includes motion duration, move distance, motion consumption.
Platform user data module, for the user's exercise data for obtaining the static basis data of user, the detailed physical examination data that system is docked with medical center, system are docked with sport health APP；The static basis data of platform user data cell storage include age, sex, job overall, gene.
Data normalization processing module, the data whole for obtaining user, the processing that data are standardized；
User data module is stored, for being stored in the user data after the processing of professional etiquette generalized；
Consumer's risk model, for by constantly being adjusted to user data, continuing to optimize and calculating analysis so as to which user health risk be identified；
Risk factor module is generated, for carrying out calculating the final health risk coefficient for drawing user according to all customer data and consumer's risk model, coefficient is bigger, and it is bigger that user gives birth to weight strong wind danger.
Using above-mentioned technical proposal, by obtaining a large amount of comprehensive dynamics of user and static data, so as to be calculated newest, most accurate health risk coefficient.
It should be understood that all personal basic document information and health data of data module, collection user data module and platform user data module acquisition user are uploaded by user.Personal basic document mainly has address name, sex, age, date of birth, occupation, personality etc..Health data mainly has passing medical history, blood pressure, height, body weight, height and weight index
(BMI), stature, eating habit, health etc..Wherein as blood pressure, height, body weight these data are mainly measured by some portable body examination instruments by user oneself or medical worker, and you are updated to newest numerical value.Passing medical history, eating habit are then filled in by user when registering or filled in by medical worker after body is checked out as user, are obtained so as to be docked in medical center.The projects such as health, stature after body examination Data Analysis Services of the analysis module according to user mainly by voluntarily drawing.In addition, user is equipped with different motion monitoring instruments, the daily exercise situation of user, user's exercise data that system is docked with sport health APP are recorded.By obtaining newest most comprehensive data, so as to draw more accurate, more comprehensive health risk assessment result, relatively reliable accurate Risk-warning is provided the user.
Embodiments of the present invention are explained in detail above in association with accompanying drawing, but the invention is not restricted to described embodiment.For a person skilled in the art, in the case where not departing from the principle of the invention and spirit, a variety of change, modification, replacement and modification is carried out to these embodiments, still fallen within protection scope of the present invention.
Claims (9)
- A kind of 1. personalized user health risk network analysis system, it is characterised in that including：User uploads data module, for the health data by upload user,User data module is gathered, for gathering user's weight, blood pressure, heart rate, blood fat and the exercise data of user；Platform user data module, for the user's exercise data for obtaining the static basis data of user, the detailed physical examination data that system is docked with medical center, system are docked with sport health APP；Data normalization processing module, the data whole for obtaining user, the processing that data are standardized；User data module is stored, for being stored in the user data after the processing of professional etiquette generalized；Consumer's risk model, for by constantly being adjusted to user data, continuing to optimize and calculating analysis so as to which user health risk be identified；Risk factor module is generated, for carrying out calculating the final health risk coefficient for drawing user according to all customer data and consumer's risk model.
- 2. personalized user health risk network analysis system according to claim 1, it is characterised in that the user, which uploads the health data that data cell uploads, includes physical examination data and sick state.
- 3. personalized user health risk network analysis system according to claim 1, it is characterised in that the exercise data of the collection user data cell collection includes motion duration, move distance, motion consumption.
- 4. personalized user health risk network analysis system according to claim 1, it is characterised in that the static basis data of the platform user data cell storage include age, sex, job overall, gene.
- 5. a kind of personalized user health risk systematic analytic method, it is characterised in that step includes：S1, the health data by platform upload user, and user's weight, blood pressure, heart rate, blood fat and the exercise data of user are gathered, while obtain the static basis data of user, user's exercise data that the detailed physical examination data that system is docked with medical center, system are docked with sport health APP；S2, obtain the whole data of user, the processing to be standardized to data；S3, the user data being stored in after the processing of professional etiquette generalized；S4, by constantly being adjusted to user data, continue to optimize and calculate analysis so as to which user health risk be identified；S5, according to all customer data and consumer's risk model calculate the health risk coefficient for finally drawing user.
- 6. according to claim 5 personalized user health risk systematic analytic method, it is characterised in that the step S4 includes：Step S4-1, by substantial amounts of user data computing, so as to obtain new consumer's risk model；Step S4-2, health risk coefficient calculating is carried out to user by the new consumer's risk model after continuous renewal.
- 7. personalized user health risk systematic analytic method according to claim 5, it is characterised in that the user, which uploads the health data that data cell uploads, includes physical examination data and sick state.
- 8. personalized user health risk systematic analytic method according to claim 5, it is characterised in that the exercise data of the collection user data cell collection includes motion duration, move distance, motion consumption.
- 9. personalized user health risk systematic analytic method according to claim 5, it is characterised in that the static basis data of the platform user data cell storage include age, sex, job overall, gene.
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| CN108595953A (en) * | 2018-04-04 | 2018-09-28 | 厦门雷德蒙软件开发有限公司 | Method for carrying out risk assessment on mobile phone application |
| CN109671502A (en) * | 2018-12-18 | 2019-04-23 | 北京妙医佳信息技术有限公司 | Object portrait update method and device |
| CN109671503A (en) * | 2018-12-18 | 2019-04-23 | 北京妙医佳信息技术有限公司 | Healthy scheme evaluation method and device |
| CN112509699A (en) * | 2020-12-28 | 2021-03-16 | 医渡云（北京）技术有限公司 | Health identification code generation method and device, storage medium and electronic equipment |
| CN114022293A (en) * | 2021-10-29 | 2022-02-08 | 松下电气设备(中国)有限公司 | Health assessment data generation and management device |
| CN119700014A (en) * | 2023-09-27 | 2025-03-28 | 中国人民解放军海军军医大学第一附属医院 | A smart clothing for monitoring the health of a single soldier |
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Application publication date: 20171219 |