CN117594181A - Method and system for generating health report based on data detection - Google Patents
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- 230000036541 health Effects 0.000 title claims abstract description 222
- 238000001514 detection method Methods 0.000 title claims abstract description 32
- 238000000034 method Methods 0.000 title claims abstract description 21
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 37
- 239000008280 blood Substances 0.000 claims description 37
- 210000004369 blood Anatomy 0.000 claims description 37
- 229910052760 oxygen Inorganic materials 0.000 claims description 37
- 239000001301 oxygen Substances 0.000 claims description 37
- 230000036760 body temperature Effects 0.000 claims description 27
- 238000007405 data analysis Methods 0.000 claims description 17
- 230000002526 effect on cardiovascular system Effects 0.000 claims description 15
- 230000002159 abnormal effect Effects 0.000 claims description 14
- 238000004458 analytical method Methods 0.000 claims description 14
- 230000000747 cardiac effect Effects 0.000 claims description 14
- 210000000748 cardiovascular system Anatomy 0.000 claims description 9
- 230000007958 sleep Effects 0.000 claims description 8
- 230000009286 beneficial effect Effects 0.000 abstract description 2
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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
- G16H15/00—ICT specially adapted for medical reports, e.g. generation or transmission thereof
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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 invention discloses a method and a system for generating a health report based on data detection, comprising the following steps: s1: configuring a preset data range and a health scheme, and collecting and uploading user data; s2: obtaining health conditions based on the user data and the preset data range; s3: obtaining a health score based on the user data and the health condition; s4: matching a health regimen based on the health condition and the health score; s5: a health report is generated based on the user data, the health condition, the health score and the health plan, and the user performs corresponding adjustment according to the health report. The invention has the beneficial effects that: the health condition of the specific user can be detected and scored based on the specific user, so that the health scheme is matched and the health report is generated, and the user behavior is convenient to adjust.
Description
Technical Field
The invention relates to the technical field of health data detection, in particular to a method and a system for generating a health report based on data detection.
Background
With the development of artificial intelligence technology, the field of health management is also coming into the new opportunity. By utilizing data detection and analysis, the health data of the user can be comprehensively and accurately estimated and disease risk predicted. And further, the user can be better helped to manage health and provide matching suggestions.
In the prior art, user data is generally collected through a sensor, so that a user knows various data values, can not comprehensively analyze and judge whether the user needs to perform health adjustment based on the data values, and has the problems that the health condition of the user can not be detected and scored based on a specific user, and then a health scheme is matched and a health report is generated.
For example, the invention disclosed in chinese patent literature as "health detection device", having publication number CN111714127a and application date of 2020, 6 and 9, includes a weight measuring unit, a servo unit, a carrier unit, and an antenna unit, wherein the servo unit is connected to the carrier unit, and the antenna unit is disposed on the carrier unit; the weight measuring assembly is used for bearing a human body, collecting the weight value of the human body and sending the weight value of the human body to the antenna assembly; the servo component is used for driving the bearing part to rotate around the human body and sending position information to the antenna component, and the position information is used for representing the rotation angle of the bearing part; the antenna component is used for receiving the weight value of the human body and the position information, transmitting electromagnetic waves to the human body when the weight value of the human body meets a first preset condition, receiving electromagnetic waves reflected by the human body, wherein the electromagnetic waves reflected by the human body and the weight value of the human body are used for the external computing equipment to calculate the human body health index, and the electromagnetic waves are millimeter waves or terahertz waves, so that the operation of health detection on the human body can be simplified. But there is a problem in that it is impossible to detect and score the health condition of a specific user based on the user, thereby matching the health scheme and generating a health report.
Disclosure of Invention
Aiming at the defects that the prior art can not detect and score the health condition of a specific user so as to match a health scheme and generate a health report, the application provides a health report generation method and system based on data detection, which can detect and score the health condition of the specific user so as to match the health scheme and generate the health report, so that the user behavior can be conveniently adjusted.
The following is a technical scheme of the invention, a health report generating method based on data detection, comprising the following steps:
s1: configuring a preset data range and a health scheme, and collecting and uploading user data;
s2: obtaining health conditions based on the user data and the preset data range;
s3: obtaining a health score based on the user data and the health condition;
s4: matching a health regimen based on the health condition and the health score;
s5: a health report is generated based on the user data, the health condition, the health score and the health plan, and the user performs corresponding adjustment according to the health report.
Preferably, in S1, the user data includes heart rate, blood oxygen, body temperature, step count, and sleep information.
Preferably, in S2, the heart rate is within a preset data range, and the heart rate is normal, otherwise, the heart rate is abnormal; blood oxygen is within a preset data range, and is normal, otherwise, the blood oxygen is abnormal; the body temperature is within the preset data range, and the body temperature is normal, otherwise, the body temperature is abnormal; the number of steps exceeds a step number threshold, and the number of steps reaches the standard, otherwise, the number of steps does not reach the standard.
Preferably, in S3, the health score comprises a stress score, a heart rate score, and a cardiovascular score.
Preferably, the pressure index is calculated based on heart rate, expressed as follows:
in the above formula, c is a pressure index, b is a heart rate, a is a cardiac cycle, n is the number of detected heart rates, and sigma is a standard deviation of the cardiac cycle;
and matching the pressure scores according to the pressure intervals in which the pressure indexes are located.
Preferably, the heart rate score is calculated based on the heart rate and a constant, expressed as follows:
S heart rate of heart ＝k·μ
In the above formula, mu is the standard deviation of heart rate, b is the heart rate, n is the number of times of heart rate detection, k is a constant, S Heart rate of heart Scoring heart rate;
based on gender and age matching constant k.
Preferably, the cardiovascular score is calculated based on the health condition, expressed as follows:
in the above, Q Cardiovascular system For cardiovascular scoring, l is the number of heart rate events, m is the number of heart rate events detected, q 1 Constant value of heart rate, q 2 Is a score constant for heart rate anomalies.
Preferably, in S4, the health regimen includes regimen conditions and regimen content;
the health condition and the health score are matched with the program condition, the health program is determined based on the program condition, and the program content is acquired based on the health program.
A data detection based health report generation system comprising:
the data acquisition module is used for acquiring user data;
the data uploading module is used for uploading user data and is connected with the data acquisition module and the server;
the parameter configuration module is used for configuring a preset data range and is connected with the server;
the data analysis module is used for obtaining health conditions based on user data and a preset data range and is connected with the data acquisition module and the parameter configuration module;
the comprehensive analysis module obtains health scores based on the user data and the health conditions and is connected with the data acquisition module and the data analysis module;
the scheme matching module is used for matching the health scheme based on the health condition and the health score and connecting the data analysis module and the comprehensive analysis module;
and the report generation module is used for generating a health report based on the user data, the health condition, the health score and the health scheme and uploading the health report, and is connected with the scheme matching module and the server.
Preferably, the data acquisition module comprises a photo-volume sensor, a temperature sensor, an accelerometer and a gyroscope.
The invention has the beneficial effects that:
1. the user data such as heart rate, blood oxygen, body temperature, step number, sleep information and the like can be monitored so as to enable the user to know the self condition;
2. the user data can be judged whether to be in the preset data range or not by customizing the preset data range, so that the health condition of a specific user can be obtained, and the accuracy of the health condition is improved;
3. when the user does not set the preset data range, judging through the standard data range, and improving the universality of the watch system;
4. the health score can be obtained according to the user data and the health condition, so that the user can know the health condition of the user more, and the health proposal can be obtained by matching the health proposal based on the health condition and the health score, thereby being convenient for the user to adjust the work and rest according to the health proposal;
5. a health report can be generated based on user data, health conditions, health scores and health schemes, so that a user can know the conditions of the user in detail.
Drawings
FIG. 1 is a schematic diagram of a data detection based health report generation system of the present invention;
FIG. 2 is a flow chart of a method of generating a health report based on data detection of the present invention;
in the figure:
1-a data acquisition module; 2-a data uploading module; 3-a parameter configuration module; 4-a data analysis module; 5-a comprehensive analysis module; 6-a scheme matching module; 7-a report generation module; 8-server.
Detailed Description
In order to make the technical problems solved by the present invention, the technical solutions adopted and the technical effects achieved more clear, the technical solutions of the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings, and it is obvious that the described embodiments are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the description of the present invention, unless explicitly stated and limited otherwise, the terms "connected," "connected," and "fixed" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communicated with the inside of two elements or the interaction relationship of the two elements. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
In the present invention, unless expressly stated or limited otherwise, a first feature "above" or "below" a second feature may include both the first and second features being in direct contact, as well as the first and second features not being in direct contact but being in contact with each other through additional features therebetween. Moreover, a first feature being "above," "over" and "on" a second feature includes the first feature being directly above and obliquely above the second feature, or simply indicating that the first feature is higher in level than the second feature. The first feature being "under", "below" and "beneath" the second feature includes the first feature being directly under and obliquely below the second feature, or simply means that the first feature is less level than the second feature.
Example 1
As shown in fig. 1, a data detection-based health report generation system includes:
the data acquisition module 1 is used for acquiring user data and is connected with the data uploading module 2, the data analysis module 4 and the comprehensive analysis module 5;
a data uploading module 2 for uploading user data to a server 8, connecting the data acquisition module 1 and the server 8,
the parameter configuration module 3 is used for self-defining and configuring a preset data range and is connected with the data analysis module 4 and the server 8;
the data analysis module 4 is used for obtaining health conditions based on user data and a preset data range and is connected with the data acquisition module 1, the parameter configuration module 3, the comprehensive analysis module 5 and the scheme matching module 6;
the comprehensive analysis module 5 obtains health scores based on the user data and the health conditions and is connected with the data acquisition module 1, the data analysis module 4 and the scheme matching module 6;
the scheme matching module 6 is used for matching the health scheme based on the health condition and the health score and is connected with the data analysis module 4, the comprehensive analysis module 5 and the report generation module 7;
a report generation module 7 for generating and uploading a health report based on the user data, the health status, the health score and the health plan, and connecting the plan matching module 6 and the server 8;
and the data acquisition module 1 is used for acquiring user data. The user data comprise heart rate, blood oxygen, body temperature, step number, sleep information and other data, wherein the heart rate is monitored through a heart rate sensor, the blood oxygen is monitored through a blood oxygen sensor, or the heart rate and the blood oxygen are monitored through a photoelectric volume sensor, the body temperature is monitored through a temperature sensor, the arm movement of a user is detected through an accelerometer and a gyroscope, then the data analysis and the processing are carried out through an algorithm, the step number of the movement is finally calculated, the accelerometer can measure acceleration caused by gravity acceleration and arm vibration, and the gyroscope can measure the angular velocity of the arm. Through analysis and processing of the data, the watch senses the motion state of the body when the user walks or runs, and judges the type of motion (such as walking, running and the like) and the specific step number through an algorithm. Under the sleep state, the intelligent watch can continuously monitor the parameters, and processes and analyzes the collected data through a built-in sleep algorithm, so that different sleep stages are identified, and sleep information including sleep time, awake time, shallow sleep time, deep sleep time and the like is obtained.
The data uploading module 2 is configured to upload user data to the server 8. The data uploading module 2 is connected with the data acquisition module 1, user data is acquired from the data acquisition module 1, the data uploading module 2 is in communication connection with the server 8, and the user data is uploaded to the server 8.
And the parameter configuration module 3 is used for self-defining and configuring a preset data range. The parameter configuration module 3 configures a preset data range, and judges whether the user data is normal by comparing the user data with the preset data range, wherein the preset data range comprises information such as a heart rate range, a blood oxygen range, a body temperature range, a step number threshold value and the like. Because the physical condition of each user has a difference, the health condition of the user can be more met by configuring the preset data range. When the user does not configure the preset data range of the parameter configuration module 3, the value of the preset data range in the parameter configuration module 3 is the standard data range, so that the universality of the system is improved. In addition, the parameter configuration module 3 configures user basic information such as age, sex, and the like.
And the data analysis module 4 is used for obtaining the health condition by comparing the user data with a preset data range. The data analysis module 4 acquires user data and a preset data range, compares the heart rate with the heart rate range, if the heart rate is in the heart rate range, the heart rate is normal, otherwise, the heart rate is abnormal; comparing the blood oxygen with the blood oxygen range, if the blood oxygen is in the blood oxygen range, the blood oxygen is normal, otherwise, the blood oxygen is abnormal; comparing the body temperature with the body temperature range, if the body temperature is in the body temperature range, the body temperature is normal, otherwise, the body temperature is abnormal; judging whether the step number exceeds a step number threshold, if so, the step number reaches the standard, otherwise, the step number does not reach the standard.
And the comprehensive analysis module 5 obtains health scores based on the user data. The comprehensive analysis module 5 obtains user data, analyzes the user data to obtain health scores, and the health scores comprise pressure scores, heart rate scores, cardiovascular scores and the like.
Calculating a stress index c based on the heart rate, and matching a stress score S according to a stress interval in which the stress index c is located Pressure of . And calculating a stress index according to the fluctuation between heart rates, and evaluating the stress score based on the stress interval in which the stress index is located. Specifically, a continuous n detected heart rate b is obtained, a cardiac cycle a is calculated according to the heart rate b, and an average value of the cardiac cycle a is calculatedAnd standard deviation sigma of cardiac cycle, according to average +.>And the standard deviation sigma of the cardiac cycle.
And calculating a heart rate score based on the heart rate, and further judging whether heart rate abnormality exists. Specifically, a heart rate standard deviation μ is calculated based on the heart rate b, a heart rate score S is calculated based on the gender and age matching constant k, and the heart rate standard deviation μ and constant k Heart rate of heart And then according to the heart rate score S Heart rate of heart And evaluating whether heart rate abnormality exists.
Calculating a cardiovascular score Q based on heart rate normalcy or heart rate abnormalities in health conditions Cardiovascular system . Specifically, heart rate results of continuous m detection are obtained, and the number of normal heart rate times l and the number of abnormal heart rate times m-l are counted, so that a cardiovascular score Q is calculated Cardiovascular system 。
When heart rate abnormality is detected more than 3 times in continuous m times of heart rate detection, cardiovascular score Q Cardiovascular system A score of 0, and early warning is required. In addition, the above scheme is also applicable to blood oxygen evaluation to obtain blood oxygen score Q Blood oxygen And will not be described in detail herein.
The regimen matching module 6 matches a health regimen based on the health condition and the health score. The server 8 is configured with a health scheme, wherein the health scheme comprises scheme conditions and scheme contents, the scheme conditions are health conditions and health scores, the corresponding scheme contents are obtained through the scheme conditions, the scheme contents are health suggestions aiming at the scheme conditions, and the health suggestions comprise life habits, diet structures, exercise plans and the like so as to promote health management of users.
The report generation module 7 generates a health report based on the user data, the health status, the health score and the health plan, and uploads the health report to the server 8. The report generating module 7 acquires user data, health conditions, health scores and health schemes, the report generating module 7 configures a preset template, the preset template fixedly displays field names such as heart rate, blood oxygen and the like, field values corresponding to the field names are supplemented through the acquired data, and after all the field values are circularly supplemented, the preset template is saved into a PDF type health report.
The system also comprises a storage module, wherein the storage module is used for storing user data, health conditions, health scores, health schemes, health reports and the like.
Example two
As shown in fig. 2, the method for generating the health report based on the data detection comprises the following steps:
s1: configuring a preset data range and a health scheme, and collecting and uploading user data;
s2: obtaining health conditions based on the user data and the preset data range;
s3: obtaining a health score based on the user data and the health condition;
s4: matching a health regimen based on the health condition and the health score;
s5: a health report is generated based on the user data, the health condition, the health score and the health plan, and the user performs corresponding adjustment according to the health report.
In step S1, a preset data range and a health scheme are configured, and user data is collected and uploaded. Specifically, preset data are configured, and the preset data range comprises information such as a heart rate range, a blood oxygen range, a body temperature range, a step number threshold value and the like. Because the physical condition of each user has a difference, the health condition of the user can be more met by configuring the preset data range. When the user does not configure the preset data range of the parameter configuration module 3, the value of the preset data range in the parameter configuration module 3 is the standard data range, so that the universality of the system is improved. In addition, the parameter configuration module 3 configures user basic information such as age, sex, and the like.
The server 8 configures a health plan including plan conditions and plan content, the plan conditions being health conditions and health scores.
The heart rate is monitored through the heart rate sensor, the blood oxygen is monitored through the blood oxygen sensor, or the heart rate and the blood oxygen are monitored through the photoelectric volume sensor, the body temperature is monitored through the temperature sensor, the arm motion of a user is detected through the accelerometer and the gyroscope, then the data analysis and the processing are carried out through the algorithm, the number of steps of the motion is finally calculated, when the user walks or runs, the watch can sense the motion state of the body, and the type of the motion and the specific number of steps are judged through the algorithm.
In step S2, the health condition is obtained based on the user data and the preset data range. Specifically, the data analysis module 4 acquires user data and a preset data range, compares the heart rate with the heart rate range, if the heart rate is in the heart rate range, the heart rate is normal, otherwise, the heart rate is abnormal; comparing the blood oxygen with the blood oxygen range, if the blood oxygen is in the blood oxygen range, the blood oxygen is normal, otherwise, the blood oxygen is abnormal; comparing the body temperature with the body temperature range, if the body temperature is in the body temperature range, the body temperature is normal, otherwise, the body temperature is abnormal; judging whether the step number exceeds a step number threshold, if so, the step number reaches the standard, otherwise, the step number does not reach the standard.
In step S3, a health score is obtained based on the user data and the health status. The comprehensive analysis module 5 obtains user data, analyzes the user data to obtain health scores, and the health scores comprise pressure scores, heart rate scores, cardiovascular scores and the like.
Calculating a stress index c based on the heart rate, and matching a stress score S according to a stress interval in which the stress index c is located Pressure of . And calculating a stress index according to the fluctuation between heart rates, and evaluating the stress score based on the stress interval in which the stress index is located. In particular, obtainTaking the heart rate b detected by continuous n, calculating a cardiac cycle a according to the heart rate b, and calculating the average value of the cardiac cycle aAnd standard deviation sigma of cardiac cycle, according to average +.>And calculating a pressure index c by using the standard deviation sigma of the cardiac cycle, wherein the expression is as follows:
in the above formula, c is a pressure index, b is a heart rate, a is a cardiac cycle, n is the number of detected heart rates, and σ is a standard deviation of the cardiac cycle.
Each pressure interval corresponds to a pressure score, the pressure interval where the pressure index c is located is analyzed, and then the pressure score S is obtained according to the pressure interval Pressure of As shown in table 1.
Table 1 pressure scoring table.
| Pressure interval | Pressure score S Pressure of |
| [c 1 ,c 2 ) | s 1 |
| [c 2 ,c 3 ) | s 2 |
| [c 3 ,c 4 ) | s 3 |
| ... | ... |
And calculating a heart rate score based on the heart rate, and further judging whether heart rate abnormality exists. Specifically, a heart rate standard deviation μ is calculated based on the heart rate b, a heart rate score S is calculated based on the gender and age matching constant k, and the heart rate standard deviation μ and constant k Heart rate of heart And further, whether the heart rate abnormality exists or not is evaluated according to the heart rate score, wherein the expression is as follows:
S heart rate of heart ＝k·μ
In the above formula, mu is the standard deviation of heart rate, b is the heart rate, n is the number of times of heart rate detection, k is a constant, S Heart rate of heart The heart rate is scored.
The gender and age of the user are obtained based on the gender and age matching constant k as shown in table 2.
Table 2 constant tables for gender and age.
Calculating a cardiovascular score Q based on heart rate normalcy or heart rate abnormalities in health conditions Cardiovascular system . Specifically, heart rate results of continuous m detection are obtained, and the number of normal heart rate times l and the number of abnormal heart rate times m-l are counted, so that a cardiovascular score Q is calculated Cardiovascular system The expression is as follows:
in the above, Q Cardiovascular system For cardiovascular scoring, l is the number of heart rate events, m is the number of heart rate events detected, q 1 Constant value of heart rate, q 2 Is a score constant for heart rate anomalies.
When heart rate abnormality is detected more than 3 times in continuous m times of heart rate detection, cardiovascular score Q Cardiovascular system A score of 0, and early warning is required. In addition, the above scheme is also applicable to blood oxygen evaluation to obtain blood oxygen score Q Blood oxygen And will not be described in detail herein.
In step S4, a health regimen is matched based on the health condition and the health score. Specifically, the solution conditions are health conditions and health scores, corresponding solution contents are obtained through the solution conditions, the solution contents are health suggestions aiming at the solution conditions, and the health suggestions comprise life habits, dietary structures, exercise plans and the like so as to promote health management of users.
In step S5, a health report is generated based on the user data, the health status, the health score and the health plan, and the user performs corresponding adjustment according to the health report. Specifically, the report generating module 7 acquires user data, health status, health score and health plan, the report generating module 7 configures a preset template, the preset template fixedly displays field names such as heart rate, blood oxygen and the like, and supplements field values corresponding to the field names through the acquired data, and after all the field values are circularly supplemented, the preset template is saved into a PDF type health report. The user refers to the health report, and the living habit, the diet structure, the exercise planning and the like are adjusted according to the health report so as to promote the health management of the user and improve the health level of the user.
The user data such as heart rate, blood oxygen, body temperature, step number, sleep information and the like can be monitored so as to enable the user to know the self condition; the user data can be judged whether to be in the preset data range or not by customizing the preset data range, so that the health condition of a specific user can be obtained, and the accuracy of the health condition is improved; when the user does not set the preset data range, judging through the standard data range, and improving the universality of the system; the health score can be obtained according to the user data and the health condition, so that the user can know the health condition of the user; the health scheme can be matched based on the health condition and the health score, so that health suggestions are obtained, and a user can conveniently adjust the work and rest according to the health suggestions; a health report can be generated based on user data, health conditions, health scores and health schemes, so that a user can know the conditions of the user in detail. The data acquisition module 1 of the present system is suitable for mobile devices (e.g. smart watches, cell phones, etc.) or other related devices.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. The method for generating the health report based on the data detection is characterized by comprising the following steps of:
s1: configuring a preset data range and a health scheme, and collecting and uploading user data;
s2: obtaining health conditions based on the user data and the preset data range;
s3: obtaining a health score based on the user data and the health condition;
s4: matching a health regimen based on the health condition and the health score;
s5: a health report is generated based on the user data, the health condition, the health score and the health plan, and the user performs corresponding adjustment according to the health report.
2. The method of claim 1, wherein in S1, the user data includes heart rate, blood oxygen, body temperature, number of steps, and sleep information.
3. The method for generating a health report based on data detection according to claim 2, wherein in S2, the heart rate is within a preset data range, and the heart rate is normal, otherwise, the heart rate is abnormal; blood oxygen is within a preset data range, and is normal, otherwise, the blood oxygen is abnormal; the body temperature is within the preset data range, and the body temperature is normal, otherwise, the body temperature is abnormal; the number of steps exceeds a step number threshold, and the number of steps reaches the standard, otherwise, the number of steps does not reach the standard.
4. A method of generating a health report based on data detection according to claim 1 or 3, wherein in S3 the health score comprises a stress score, a heart rate score and a cardiovascular score.
5. The data detection-based health report generation method of claim 4, wherein the pressure index is calculated based on heart rate, expressed as follows:
in the above formula, c is a pressure index, b is a heart rate, a is a cardiac cycle, n is the number of detected heart rates, and sigma is a standard deviation of the cardiac cycle;
and matching the pressure scores according to the pressure intervals in which the pressure indexes are located.
6. The data detection-based health report generation method of claim 4, wherein the heart rate score is calculated based on the heart rate and a constant, expressed as follows:
S heart rate of heart ＝k·μ
In the above formula, mu is the standard deviation of heart rate, b is the heart rate, n is the number of times of heart rate detection, k is a constant, S Heart rate of heart Scoring heart rate;
based on gender and age matching constant k.
7. The data detection-based health report generation method of claim 4, wherein the cardiovascular score is calculated based on the health condition, expressed as follows:
in the above, Q Cardiovascular system For cardiovascular scoring, l is the number of heart rate events, m is the number of heart rate events detected, q 1 Constant value of heart rate, q 2 Is a score constant for heart rate anomalies.
8. The method for generating a health report based on data detection according to claim 4, wherein in S4, the health plan includes plan conditions and plan contents;
the health condition and the health score are matched with the program condition, the health program is determined based on the program condition, and the program content is acquired based on the health program.
9. A data detection based health report generation system adapted to the data detection based health report generation method of any one of claims 1 to 8, comprising:
the data acquisition module is used for acquiring user data;
the data uploading module is used for uploading user data and is connected with the data acquisition module and the server;
the parameter configuration module is used for configuring a preset data range and is connected with the server;
the data analysis module is used for obtaining health conditions based on user data and a preset data range and is connected with the data acquisition module and the parameter configuration module;
the comprehensive analysis module obtains health scores based on the user data and the health conditions and is connected with the data acquisition module and the data analysis module;
the scheme matching module is used for matching the health scheme based on the health condition and the health score and connecting the data analysis module and the comprehensive analysis module;
and the report generation module is used for generating a health report based on the user data, the health condition, the health score and the health scheme and uploading the health report, and is connected with the scheme matching module and the server.
10. The data detection based health report generating system of claim 9, wherein the data acquisition module comprises a photo-volume sensor, a temperature sensor, an accelerometer, and a gyroscope.
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