CN117373604A - Method, system and medium for quickly looking up health report - Google Patents
Method, system and medium for quickly looking up health report Download PDFInfo
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- 230000036541 health Effects 0.000 title claims abstract description 264
- 238000000034 method Methods 0.000 title claims abstract description 57
- 239000013566 allergen Substances 0.000 claims abstract description 55
- 238000012544 monitoring process Methods 0.000 claims abstract description 45
- 238000007781 pre-processing Methods 0.000 claims abstract description 12
- 230000008569 process Effects 0.000 claims abstract description 9
- 239000008280 blood Substances 0.000 claims description 26
- 210000004369 blood Anatomy 0.000 claims description 26
- 238000012549 training Methods 0.000 claims description 24
- 230000003862 health status Effects 0.000 claims description 20
- 238000012795 verification Methods 0.000 claims description 20
- 230000036760 body temperature Effects 0.000 claims description 18
- 230000036039 immunity Effects 0.000 claims description 18
- 230000037396 body weight Effects 0.000 claims description 14
- 230000002068 genetic effect Effects 0.000 claims description 14
- 238000012552 review Methods 0.000 claims description 14
- 230000036387 respiratory rate Effects 0.000 claims description 10
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 8
- 230000036772 blood pressure Effects 0.000 claims description 8
- 229910052760 oxygen Inorganic materials 0.000 claims description 8
- 239000001301 oxygen Substances 0.000 claims description 8
- 238000012545 processing Methods 0.000 claims description 7
- 230000006855 networking Effects 0.000 claims description 6
- 230000002159 abnormal effect Effects 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 4
- 230000010485 coping Effects 0.000 claims description 4
- WQZGKKKJIJFFOK-GASJEMHNSA-N Glucose Natural products OC[C@H]1OC(O)[C@H](O)[C@@H](O)[C@@H]1O WQZGKKKJIJFFOK-GASJEMHNSA-N 0.000 claims description 2
- 239000008103 glucose Substances 0.000 claims description 2
- 238000001514 detection method Methods 0.000 abstract description 6
- 238000004458 analytical method Methods 0.000 description 8
- 230000006872 improvement Effects 0.000 description 8
- 230000036391 respiratory frequency Effects 0.000 description 8
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- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H15/00—ICT specially adapted for medical reports, e.g. generation or transmission thereof
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- G06F18/24—Classification techniques
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
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Abstract
The embodiment of the application provides a method, a system and a medium for quickly looking up a health report, wherein the method comprises the following steps: acquiring allergen information through historical big data, inputting the allergen information into a standard health model, and outputting the standard health information; collecting physiological signals of a user, and preprocessing the physiological signals to obtain health state monitoring information of the user; comparing the user health state monitoring information with the standard health information to obtain a deviation rate; judging whether the deviation rate is larger than or equal to a preset deviation rate threshold value; if the health risk information is greater than or equal to the health risk information, generating health risk information; if the health report is smaller than the preset threshold, generating a health report, and transmitting the health report in a preset mode; the user allergen is analyzed to intelligently generate the user standard health information, so that errors caused in the monitoring state detection process of the user can be effectively avoided, the interference of the allergen information is avoided in advance, the generation rate of the health report is improved, and the quick look-up of the health report is realized.
Description
Technical Field
The application relates to the field of health report generation and query, in particular to a method, a system and a medium for quickly looking up a health report.
Background
The intelligent wearing equipment is a general name for carrying out intelligent design and developing wearable equipment to daily wearing by applying a wearing technology, such as a watch, a bracelet, glasses, clothes and the like, can record action data in all weather, calculate fat burning conditions, enable a user to comprehensively know exercise data and master physical health conditions, the existing intelligent wearing equipment displays single health conditions in the process of carrying out health monitoring on the user, cannot form comprehensive health reports, cannot comprehensively analyze self physical conditions in the process of carrying out health monitoring, has poor monitoring effect, and aims at the problems, so that an effective technical solution is needed.
Disclosure of Invention
The embodiment of the application aims to provide a method, a system and a medium for quickly checking a health report, which can intelligently generate user standard health information by analyzing user allergens, can effectively avoid errors caused by a user in the monitoring state detection process, avoid the interference of the allergen information in advance, improve the generation rate of the health report and realize the quick checking of the health report.
The embodiment of the application also provides a method for quickly looking up the health report, which comprises the following steps:
acquiring allergen information through historical big data, inputting the allergen information into a standard health model, and outputting the standard health information;
collecting physiological signals of a user, and preprocessing the physiological signals to obtain health state monitoring information of the user;
comparing the user health state monitoring information with the standard health information to obtain a deviation rate;
judging whether the deviation rate is larger than or equal to a preset deviation rate threshold value;
if the health risk information is greater than or equal to the health risk information, generating health risk information;
if the data is smaller than the preset threshold, a health report is generated, and the health report is transmitted according to a preset mode.
Optionally, in the method for quickly looking up a health report according to the embodiment of the present application, allergen information is obtained through historical big data, and the allergen information is input into a standard health model and output standard health information, specifically:
acquiring user identity information, and acquiring user history visit information in a networking manner according to the user identity information;
recording the genetic medical history of the user through a questionnaire, and analyzing according to the genetic medical history of the user and the historical treatment information of the user to obtain the allergen information of the user;
classifying the user allergen information to generate a training set and a verification set;
training the standard health model through the training set, and performing parameter verification adjustment on the standard health model through the verification set;
and acquiring standard health information through the adjusted standard health model.
Optionally, in the method for quickly looking up a health report according to the embodiment of the present application, a physiological signal of a user is collected, and the physiological signal is preprocessed to obtain health status monitoring information of the user, which specifically includes:
collecting physiological signals of a user, extracting signal characteristics, and comparing the signal characteristics with preset characteristics to obtain characteristic deviation rate;
judging whether the characteristic deviation rate is larger than a preset characteristic deviation rate threshold value or not;
if the signal characteristics are larger than the signal characteristics, carrying out average value processing on the signal characteristics;
if the signal characteristics are smaller than the threshold value, fitting the signal characteristics to generate a physiological signal curve graph of the user.
Optionally, in the method for rapid review of health reports according to the embodiments of the present application, the physiological signal of the user includes one or a combination of two or more of heart rate data, blood pressure data, blood oxygen data, sleep data, blood glucose, body weight, body temperature, respiratory rate, and immunity.
Optionally, in the method for quickly looking up a health report according to the embodiment of the present application, after collecting a physiological signal of a user and preprocessing the physiological signal to obtain health status monitoring information of the user, the method further includes:
acquiring a user real-time physiological signal, and comparing the user real-time physiological signal with the recorded information of the latest visit record to obtain difference information;
calculating the deviation of the real-time physiological signals according to the difference information, and updating the record information of the user treatment record;
analyzing the health state of the user according to the updated record information;
and when the health state of the user is abnormal, correcting the health state monitoring information of the user.
Optionally, in the method for quickly looking up a health report according to the embodiment of the present application, if the health risk information is greater than or equal to the health risk information, after generating the health risk information, the method further includes:
acquiring health risk information, and performing characteristic threshold calculation on the health risk information to obtain a risk upper limit value;
grading the health risk information to obtain a plurality of risk grades, and generating a plurality of risk grade ranges;
comparing the risk upper limit value with a plurality of risk level ranges;
judging the risk level of the health risk information according to the upper risk limit value;
and generating corresponding risk prompt information and coping strategies according to the risk level of the health risk information.
In a second aspect, embodiments of the present application provide a rapid review health reporting system, the system comprising: the system comprises a memory and a processor, wherein the memory comprises a program of a quick-looking-up health report method, and the program of the quick-looking-up health report method realizes the following steps when being executed by the processor:
acquiring allergen information through historical big data, inputting the allergen information into a standard health model, and outputting the standard health information;
collecting physiological signals of a user, and preprocessing the physiological signals to obtain health state monitoring information of the user;
comparing the user health state monitoring information with the standard health information to obtain a deviation rate;
judging whether the deviation rate is larger than or equal to a preset deviation rate threshold value;
if the health risk information is greater than or equal to the health risk information, generating health risk information;
if the data is smaller than the preset threshold, a health report is generated, and the health report is transmitted according to a preset mode.
Optionally, in the rapid review health report system described in the embodiments of the present application, allergen information is obtained through historical big data, and the allergen information is input into a standard health model and output standard health information, specifically:
acquiring user identity information, and acquiring user history visit information in a networking manner according to the user identity information;
recording the genetic medical history of the user through a questionnaire, and analyzing according to the genetic medical history of the user and the historical treatment information of the user to obtain the allergen information of the user;
classifying the user allergen information to generate a training set and a verification set;
training the standard health model through the training set, and performing parameter verification adjustment on the standard health model through the verification set;
and acquiring standard health information through the adjusted standard health model.
Optionally, in the rapid review health report system described in the embodiments of the present application, a physiological signal of a user is collected, and the physiological signal is preprocessed to obtain health status monitoring information of the user, which specifically includes:
collecting physiological signals of a user, extracting signal characteristics, and comparing the signal characteristics with preset characteristics to obtain characteristic deviation rate;
judging whether the characteristic deviation rate is larger than a preset characteristic deviation rate threshold value or not;
if the signal characteristics are larger than the signal characteristics, carrying out average value processing on the signal characteristics;
if the signal characteristics are smaller than the threshold value, fitting the signal characteristics to generate a physiological signal curve graph of the user.
In a third aspect, embodiments of the present application further provide a computer readable storage medium, where a fast look-up health reporting method program is included, where the fast look-up health reporting method program, when executed by a processor, implements the steps of the fast look-up health reporting method as described in any one of the above.
As can be seen from the above, the method, the system and the medium for quickly looking up the health report provided by the embodiments of the present application acquire allergen information through historical big data, input the allergen information into a standard health model, and output standard health information; collecting physiological signals of a user, and preprocessing the physiological signals to obtain health state monitoring information of the user; comparing the user health state monitoring information with the standard health information to obtain a deviation rate; judging whether the deviation rate is larger than or equal to a preset deviation rate threshold value; if the health risk information is greater than or equal to the health risk information, generating health risk information; if the health report is smaller than the preset threshold, generating a health report, and transmitting the health report in a preset mode; by analyzing the user allergen to intelligently generate the user standard health information, errors caused in the monitoring state detection process of the user can be effectively avoided, the interference of the allergen information is avoided in advance, the generation rate of the health report is improved, and the technology for quickly checking the health report is realized.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, the claims, and the drawings, as well as the objects and advantages of the application may be realized and obtained by means of the instrumentalities particularly pointed out in the written description, claims, and drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a method for quickly looking up a health report according to an embodiment of the present application;
FIG. 2 is a standard health model training flowchart of a method for quickly looking up a health report according to an embodiment of the present application;
fig. 3 is a signal feature fitting flowchart of a method for quickly looking up a health report according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of a rapid review health report system according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. The components of the embodiments of the present application, which are generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, as provided in the accompanying drawings, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, are intended to be within the scope of the present application.
It should be noted that like reference numerals and letters refer to like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only to distinguish the description, and are not to be construed as indicating or implying relative importance.
Referring to fig. 1, fig. 1 is a flowchart of a method for quickly looking up a health report according to some embodiments of the present application. The method for quickly checking the health report is used in the terminal equipment and comprises the following steps:
s101, acquiring allergen information through historical big data, inputting the allergen information into a standard health model, and outputting the standard health information;
s102, collecting physiological signals of a user, and preprocessing the physiological signals to obtain health state monitoring information of the user;
s103, comparing the user health state monitoring information with standard health information to obtain a deviation rate;
s104, judging whether the deviation rate is larger than or equal to a preset deviation rate threshold value;
s105, if the health risk information is greater than or equal to the health risk information, generating health risk information;
if the data is smaller than the preset threshold, a health report is generated, and the health report is transmitted according to a preset mode.
It is to be noted that, through obtaining the user allergen, signal interference when reducing the allergen to user health status analysis improves and judges the accuracy, through carrying out filtering, smoothing to the physiological information, guarantee that the physiological signal can maximize the health status of display user, thereby when analyzing and calculating user health status detection information, the accuracy is higher, when user health status monitoring information appears great deviation, it shows that user health status appears great fluctuation this moment, health status appears the risk, realize the risk and carry out the early warning, in addition, user health status fluctuation is less, carry out real-time output with the health report, health report generation efficiency is improved.
Referring to fig. 2, fig. 2 is a standard health model training flowchart of a quick look health reporting method in some embodiments of the present application. According to the embodiment of the invention, the allergen information is acquired through the historical big data, is input into the standard health model, and is output, specifically:
s201, acquiring user identity information, and acquiring user history visit information in a networking manner according to the user identity information;
s202, recording the genetic medical history of the user through a questionnaire, and analyzing according to the genetic medical history of the user and the historical treatment information of the user to obtain the allergen information of the user;
s203, classifying the user allergen information to generate a training set and a verification set;
s204, training the standard health model through a training set, and performing parameter verification adjustment on the standard health model through a verification set;
s205, standard health information is acquired through the adjusted standard health model.
It should be noted that, analysis is performed on the user allergen through the genetic medical history of the user and the historical treatment information of the user, so that multi-source analysis is realized, the analysis result is closer to the actual value, in addition, in the training process of the model, the parameter verification after the model training is realized through classifying the user allergen information, when the parameter has larger deviation, the model parameter is corrected, the output result of the standard health model is ensured to be more accurate, and the model has stronger learning ability.
Referring to fig. 3, fig. 3 is a signal feature fitting flowchart of a method for quickly looking up a health report in some embodiments of the present application. According to the embodiment of the invention, the physiological signals of the user are collected and preprocessed to obtain the health state monitoring information of the user, and the method specifically comprises the following steps:
s301, collecting physiological signals of a user, extracting signal characteristics, and comparing the signal characteristics with preset characteristics to obtain a characteristic deviation rate;
s302, judging whether the characteristic deviation rate is larger than a preset characteristic deviation rate threshold value;
s303, if the signal characteristics are larger than the preset threshold value, carrying out mean value processing on the signal characteristics;
and S304, if the signal characteristics are smaller than the threshold value, fitting the signal characteristics to generate a physiological signal curve graph of the user.
The physiological signals of the user are extracted by the features, the signal features are analyzed, the deviation of the signal features is judged, the signal features are optimized, the signal features are ensured to be in a preferable feature range, and the physiological signals of the user more accurately reflect the health state of the user.
According to an embodiment of the invention, the physiological signal of the user comprises one or a combination of more than two of heart rate data, blood pressure data, blood oxygen data, sleep data, blood sugar, body weight, body temperature, respiratory rate, immunity.
According to the embodiment of the invention, the physiological signals of the user are collected and preprocessed, and after the health state monitoring information of the user is obtained, the method further comprises the following steps:
acquiring a user real-time physiological signal, and comparing the user real-time physiological signal with the recorded information of the latest visit record to obtain difference information;
calculating the deviation of the real-time physiological signals according to the difference information, and updating the record information of the user treatment record;
analyzing the health state of the user according to the updated record information;
and when the health state of the user is abnormal, correcting the health state monitoring information of the user.
By analyzing the real-time physiological signals of the user, when the real-time physiological signals of the user greatly influence the health monitoring information of the user, the information of the user treatment record is updated, so that the next calling is ensured, the data analysis error is smaller, and the accuracy of monitoring the health state of the user is improved.
According to an embodiment of the present invention, if the health risk information is greater than or equal to the health risk information, the method further includes:
acquiring health risk information, and performing characteristic threshold calculation on the health risk information to obtain a risk upper limit value;
grading the health risk information to obtain a plurality of risk grades, and generating a plurality of risk grade ranges;
comparing the risk upper limit value with a plurality of risk level ranges;
judging the risk level of the health risk information according to the upper risk limit value;
and generating corresponding risk prompt information and coping strategies according to the risk level of the health risk information.
It should be noted that the heart rate risk is classified into three levels of high, medium and low, and the user can view the data, risk prompt, cause and improvement opinion of the heart rate; blood pressure risk is classified into three classes of high/medium/low, and the user can view blood pressure data, risk prompts, causes and improvement comments.
Sleep risks are classified into three grades of high, medium and low, and a user can check sleep data, risk prompts, causes and improvement comments; blood oxygen risk is classified into three classes of high/medium/low, and users can view blood oxygen data, risk prompts, causes and improvement comments.
In addition, health data such as blood sugar, body weight, body temperature, respiratory frequency, immunity and the like are also managed in a grading manner, and different solutions are provided for different grades.
According to an embodiment of the present invention, further comprising:
obtaining blood sugar, body weight, body temperature, respiratory rate and immunity data of different time nodes;
analyzing blood sugar, weight, body temperature, respiratory rate and immunity data of adjacent time nodes to generate corresponding offset values;
generating weight coefficients of blood sugar, body weight, body temperature, respiratory frequency and immunity data according to the offset value;
the blood sugar, the weight, the body temperature, the respiratory rate and the immunity data are weighted according to the weight coefficient to generate risk classification;
according to the risk classification, adjusting different weight coefficients of blood sugar, body weight, body temperature, respiratory frequency and immunity data;
and optimizing the health report according to the adjusted blood sugar, body weight, body temperature, respiratory frequency and immunity data.
It should be noted that, by performing optimization adjustment of different weights on the reaction states and the reaction indexes of different health data, the user health data of the health report reaction is more close to the actual data, and the accuracy of the health report is improved.
Referring to fig. 4, fig. 4 is a schematic structural diagram of a rapid review health report system according to some embodiments of the present application. In a second aspect, embodiments of the present application provide a rapid review health reporting system 4, comprising: the memory 41 and the processor 42, the memory 41 includes a program for fast looking up the health report method, and the program for fast looking up the health report method when executed by the processor realizes the following steps:
acquiring allergen information through historical big data, inputting the allergen information into a standard health model, and outputting the standard health information;
collecting physiological signals of a user, and preprocessing the physiological signals to obtain health state monitoring information of the user;
comparing the user health state monitoring information with the standard health information to obtain a deviation rate;
judging whether the deviation rate is larger than or equal to a preset deviation rate threshold value;
if the health risk information is greater than or equal to the health risk information, generating health risk information;
if the data is smaller than the preset threshold, a health report is generated, and the health report is transmitted according to a preset mode.
It is to be noted that, through obtaining the user allergen, signal interference when reducing the allergen to user health status analysis improves and judges the accuracy, through carrying out filtering, smoothing to the physiological information, guarantee that the physiological signal can maximize the health status of display user, thereby when analyzing and calculating user health status detection information, the accuracy is higher, when user health status monitoring information appears great deviation, it shows that user health status appears great fluctuation this moment, health status appears the risk, realize the risk and carry out the early warning, in addition, user health status fluctuation is less, carry out real-time output with the health report, health report generation efficiency is improved.
According to the embodiment of the invention, the allergen information is acquired through the historical big data, is input into the standard health model, and is output, specifically:
acquiring user identity information, and acquiring user history visit information in a networking manner according to the user identity information;
recording the genetic medical history of the user through a questionnaire, and analyzing according to the genetic medical history of the user and the historical treatment information of the user to obtain the allergen information of the user;
classifying the user allergen information to generate a training set and a verification set;
training the standard health model through the training set, and performing parameter verification adjustment on the standard health model through the verification set;
and acquiring standard health information through the adjusted standard health model.
It should be noted that, analysis is performed on the user allergen through the genetic medical history of the user and the historical treatment information of the user, so that multi-source analysis is realized, the analysis result is closer to the actual value, in addition, in the training process of the model, the parameter verification after the model training is realized through classifying the user allergen information, when the parameter has larger deviation, the model parameter is corrected, the output result of the standard health model is ensured to be more accurate, and the model has stronger learning ability.
According to the embodiment of the invention, the physiological signals of the user are collected and preprocessed to obtain the health state monitoring information of the user, and the method specifically comprises the following steps:
collecting physiological signals of a user, extracting signal characteristics, and comparing the signal characteristics with preset characteristics to obtain characteristic deviation rate;
judging whether the characteristic deviation rate is larger than a preset characteristic deviation rate threshold value or not;
if the signal characteristics are larger than the signal characteristics, carrying out average value processing on the signal characteristics;
if the signal characteristics are smaller than the threshold value, fitting the signal characteristics to generate a physiological signal curve graph of the user.
The physiological signals of the user are extracted by the features, the signal features are analyzed, the deviation of the signal features is judged, the signal features are optimized, the signal features are ensured to be in a preferable feature range, and the physiological signals of the user more accurately reflect the health state of the user.
According to an embodiment of the invention, the physiological signal of the user comprises one or a combination of more than two of heart rate data, blood pressure data, blood oxygen data, sleep data, blood sugar, body weight, body temperature, respiratory rate, immunity.
According to the embodiment of the invention, the physiological signals of the user are collected and preprocessed, and after the health state monitoring information of the user is obtained, the method further comprises the following steps:
acquiring a user real-time physiological signal, and comparing the user real-time physiological signal with the recorded information of the latest visit record to obtain difference information;
calculating the deviation of the real-time physiological signals according to the difference information, and updating the record information of the user treatment record;
analyzing the health state of the user according to the updated record information;
and when the health state of the user is abnormal, correcting the health state monitoring information of the user.
By analyzing the real-time physiological signals of the user, when the real-time physiological signals of the user greatly influence the health monitoring information of the user, the information of the user treatment record is updated, so that the next calling is ensured, the data analysis error is smaller, and the accuracy of monitoring the health state of the user is improved.
According to an embodiment of the present invention, if the health risk information is greater than or equal to the health risk information, the method further includes:
acquiring health risk information, and performing characteristic threshold calculation on the health risk information to obtain a risk upper limit value;
grading the health risk information to obtain a plurality of risk grades, and generating a plurality of risk grade ranges;
comparing the risk upper limit value with a plurality of risk level ranges;
judging the risk level of the health risk information according to the upper risk limit value;
and generating corresponding risk prompt information and coping strategies according to the risk level of the health risk information.
It should be noted that the heart rate risk is classified into three levels of high, medium and low, and the user can view the data, risk prompt, cause and improvement opinion of the heart rate; blood pressure risk is classified into three classes of high/medium/low, and the user can view blood pressure data, risk prompts, causes and improvement comments.
Sleep risks are classified into three grades of high, medium and low, and a user can check sleep data, risk prompts, causes and improvement comments; blood oxygen risk is classified into three classes of high/medium/low, and users can view blood oxygen data, risk prompts, causes and improvement comments.
In addition, health data such as blood sugar, body weight, body temperature, respiratory frequency, immunity and the like are also managed in a grading manner, and different solutions are provided for different grades.
According to an embodiment of the present invention, further comprising:
obtaining blood sugar, body weight, body temperature, respiratory rate and immunity data of different time nodes;
analyzing blood sugar, weight, body temperature, respiratory rate and immunity data of adjacent time nodes to generate corresponding offset values;
generating weight coefficients of blood sugar, body weight, body temperature, respiratory frequency and immunity data according to the offset value;
the blood sugar, the weight, the body temperature, the respiratory rate and the immunity data are weighted according to the weight coefficient to generate risk classification;
according to the risk classification, adjusting different weight coefficients of blood sugar, body weight, body temperature, respiratory frequency and immunity data;
and optimizing the health report according to the adjusted blood sugar, body weight, body temperature, respiratory frequency and immunity data.
It should be noted that, by performing optimization adjustment of different weights on the reaction states and the reaction indexes of different health data, the user health data of the health report reaction is more close to the actual data, and the accuracy of the health report is improved.
A third aspect of the present invention provides a computer readable storage medium having embodied therein a fast look-up health reporting method program which, when executed by a processor, implements the steps of a fast look-up health reporting method as described in any one of the above.
According to the method, the system and the medium for quickly looking up the health report, the allergen information is acquired through the historical big data, and is input into the standard health model and output into the standard health information; collecting physiological signals of a user, and preprocessing the physiological signals to obtain health state monitoring information of the user; comparing the user health state monitoring information with the standard health information to obtain a deviation rate; judging whether the deviation rate is larger than or equal to a preset deviation rate threshold value; if the health risk information is greater than or equal to the health risk information, generating health risk information; if the health report is smaller than the preset threshold, generating a health report, and transmitting the health report in a preset mode; by analyzing the user allergen to intelligently generate the user standard health information, errors caused in the monitoring state detection process of the user can be effectively avoided, the interference of the allergen information is avoided in advance, the generation rate of the health report is improved, and the technology for quickly checking the health report is realized.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above described device embodiments are only illustrative, e.g. the division of units is only one logical function division, and there may be other divisions in actual implementation, such as: multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. In addition, the various components shown or discussed may be coupled or directly coupled or communicatively coupled to each other via some interface, whether indirectly coupled or communicatively coupled to devices or units, whether electrically, mechanically, or otherwise.
The units described above as separate components may or may not be physically separate, and components shown as units may or may not be physical units; can be located in one place or distributed to a plurality of network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present invention may be integrated in one processing unit, or each unit may be separately used as one unit, or two or more units may be integrated in one unit; the integrated units may be implemented in hardware or in hardware plus software functional units.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware related to program instructions, and the foregoing program may be stored in a readable storage medium, where the program, when executed, performs steps including the above method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk or an optical disk, or the like, which can store program codes.
Alternatively, the above-described integrated units of the present invention may be stored in a readable storage medium if implemented in the form of software functional modules and sold or used as separate products. Based on such understanding, the technical solution of the embodiments of the present invention may be embodied in essence or a part contributing to the prior art in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, ROM, RAM, magnetic or optical disk, or other medium capable of storing program code.
Claims (10)
1. A method for quickly reviewing a health report, comprising:
acquiring allergen information through historical big data, inputting the allergen information into a standard health model, and outputting the standard health information;
collecting physiological signals of a user, and preprocessing the physiological signals to obtain health state monitoring information of the user;
comparing the user health state monitoring information with the standard health information to obtain a deviation rate;
judging whether the deviation rate is larger than or equal to a preset deviation rate threshold value;
if the health risk information is greater than or equal to the health risk information, generating health risk information;
if the data is smaller than the preset threshold, a health report is generated, and the health report is transmitted according to a preset mode.
2. The rapid review health reporting method of claim 1, wherein the allergen information is obtained through historical big data, and the allergen information is input into a standard health model and output standard health information, specifically:
acquiring user identity information, and acquiring user history visit information in a networking manner according to the user identity information;
recording the genetic medical history of the user through a questionnaire, and analyzing according to the genetic medical history of the user and the historical treatment information of the user to obtain the allergen information of the user;
classifying the user allergen information to generate a training set and a verification set;
training the standard health model through the training set, and performing parameter verification adjustment on the standard health model through the verification set;
and acquiring standard health information through the adjusted standard health model.
3. The method for quickly looking up a health report according to claim 2, wherein the steps of collecting physiological signals of the user and preprocessing the physiological signals to obtain health status monitoring information of the user comprise:
collecting physiological signals of a user, extracting signal characteristics, and comparing the signal characteristics with preset characteristics to obtain characteristic deviation rate;
judging whether the characteristic deviation rate is larger than a preset characteristic deviation rate threshold value or not;
if the signal characteristics are larger than the signal characteristics, carrying out average value processing on the signal characteristics;
if the signal characteristics are smaller than the threshold value, fitting the signal characteristics to generate a physiological signal curve graph of the user.
4. The rapid review health report method of claim 3, wherein the user physiological signal comprises one or a combination of two or more of heart rate data, blood pressure data, blood oxygen data, sleep data, blood glucose, body weight, body temperature, respiratory rate, immunity.
5. The method for rapid review of health reporting as defined in claim 4, wherein after collecting the physiological signals of the user and preprocessing the physiological signals to obtain the health status monitoring information of the user, further comprising:
acquiring a user real-time physiological signal, and comparing the user real-time physiological signal with the recorded information of the latest visit record to obtain difference information;
calculating the deviation of the real-time physiological signals according to the difference information, and updating the record information of the user treatment record;
analyzing the health state of the user according to the updated record information;
and when the health state of the user is abnormal, correcting the health state monitoring information of the user.
6. The rapid review health report method of claim 5, wherein if the generated health risk information is greater than or equal to the generated health risk information, further comprising:
acquiring health risk information, and performing characteristic threshold calculation on the health risk information to obtain a risk upper limit value;
grading the health risk information to obtain a plurality of risk grades, and generating a plurality of risk grade ranges;
comparing the risk upper limit value with a plurality of risk level ranges;
judging the risk level of the health risk information according to the upper risk limit value;
and generating corresponding risk prompt information and coping strategies according to the risk level of the health risk information.
7. A rapid review health reporting system, the system comprising: the system comprises a memory and a processor, wherein the memory comprises a program of a quick-looking-up health report method, and the program of the quick-looking-up health report method realizes the following steps when being executed by the processor:
acquiring allergen information through historical big data, inputting the allergen information into a standard health model, and outputting the standard health information;
collecting physiological signals of a user, and preprocessing the physiological signals to obtain health state monitoring information of the user;
comparing the user health state monitoring information with the standard health information to obtain a deviation rate;
judging whether the deviation rate is larger than or equal to a preset deviation rate threshold value;
if the health risk information is greater than or equal to the health risk information, generating health risk information;
if the data is smaller than the preset threshold, a health report is generated, and the health report is transmitted according to a preset mode.
8. The rapid review health reporting system of claim 7, wherein the allergen information is obtained from historical big data, and the allergen information is input into a standard health model and output standard health information, specifically:
acquiring user identity information, and acquiring user history visit information in a networking manner according to the user identity information;
recording the genetic medical history of the user through a questionnaire, and analyzing according to the genetic medical history of the user and the historical treatment information of the user to obtain the allergen information of the user;
classifying the user allergen information to generate a training set and a verification set;
training the standard health model through the training set, and performing parameter verification adjustment on the standard health model through the verification set;
and acquiring standard health information through the adjusted standard health model.
9. The rapid review health reporting system of claim 8, wherein the system collects physiological signals of the user and pre-processes the physiological signals to obtain user health status monitoring information, comprising:
collecting physiological signals of a user, extracting signal characteristics, and comparing the signal characteristics with preset characteristics to obtain characteristic deviation rate;
judging whether the characteristic deviation rate is larger than a preset characteristic deviation rate threshold value or not;
if the signal characteristics are larger than the signal characteristics, carrying out average value processing on the signal characteristics;
if the signal characteristics are smaller than the threshold value, fitting the signal characteristics to generate a physiological signal curve graph of the user.
10. A computer readable storage medium, characterized in that the computer readable storage medium comprises a fast look-up health reporting method program, which, when executed by a processor, implements the steps of the fast look-up health reporting method according to any one of claims 1 to 6.
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