CN112151171A - Physique test method based on identity recognition - Google Patents
Physique test method based on identity recognition Download PDFInfo
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Abstract
The invention belongs to the technical field of physique test, and discloses a physique test method based on identity recognition, wherein the physique test system based on identity recognition comprises: the system comprises an identity information acquisition module, an identity recognition module, a health data acquisition module, a bone recognition module, a main control module, a data recognition module, a physique test module, a bone grading module, a prediction module, a comprehensive grading module, an inquiry module, a cloud storage module and a display module. The data identification module is used for setting a storage area of the health detection data for each user, so that the source of the health detection data can be conveniently identified, and the health change condition of the user in a period of time can be tracked and detected; meanwhile, biological data of a target person is acquired through a prediction module, a sleep state of the target person is always determined based on the acquired biological data, and a change in physical condition of the target person can be accurately predicted based on the determined sleep state.
Description
Technical Field
The invention belongs to the technical field of physique test, and particularly relates to a physique test method based on identity recognition.
Background
Constitutions, which are formed by innate inheritance and acquired acquisition, are relatively stable characteristics inherent to human individuals in morphological structure and functional activities, and are related to psychological traits. The differences in individual constitutions are manifested by some differences in the response and adaptation to external stimuli under physiological conditions, and susceptibility to some pathogenic factors and predispositions to disease development during the onset of disease. Therefore, the study on the constitution is helpful for analyzing the occurrence and the evolution of diseases and provides a basis for diagnosing and treating the diseases. However, the existing physical fitness test method based on identity recognition cannot accurately identify the health data source; meanwhile, the physical condition cannot be accurately predicted.
In summary, the problems of the prior art are as follows: the existing physique test method cannot quickly, safely and comprehensively test the physique of a user; the existing physique test method based on identity recognition cannot accurately recognize the health data source; meanwhile, the physical condition cannot be accurately predicted; human skeletal data cannot be evaluated.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a physique test method based on identity recognition.
The invention is realized in this way, a physique test system based on identity recognition, which includes:
the system comprises an identity information acquisition module, an identity recognition module, a health data acquisition module, a bone recognition module, a main control module, a data recognition module, a physique test module, a bone grading module, a prediction module, a comprehensive grading module, an inquiry module, a cloud storage module and a display module;
the identity information acquisition module is connected with the main control module and is used for acquiring user identity information data by using identity information acquisition equipment;
the identity recognition module is connected with the main control module and is used for matching and recognizing the collected user identity information data and the user identity information in the user information database;
the health data acquisition module is connected with the main control module and is used for acquiring user health data through the health detection equipment;
the skeleton recognition module is connected with the main control module and used for recognizing the skeleton structure of the user through the Kinect camera;
the main control module is connected with the identity information acquisition module, the identity recognition module, the health data acquisition module, the bone recognition module, the data recognition module, the physique test module, the bone grading module, the prediction module, the comprehensive grading module, the query module, the cloud storage module and the display module and is used for controlling each module to normally work through the host;
the data identification module is connected with the main control module and used for identifying the health data source through an identification program;
the physique test module is connected with the main control module and used for testing the physique of the user through the test equipment and outputting a physique test result;
the skeleton scoring module is connected with the main control module and used for comparing the skeleton structure data of the user with the standard skeleton data and outputting a skeleton score;
the prediction module is connected with the main control module and used for predicting the physical condition of the user through a prediction program;
the comprehensive evaluation module is connected with the main control module and used for outputting a user physical fitness comprehensive evaluation score based on the physical fitness test result, the skeletal evaluation and the physical body prediction result;
the query module is connected with the main control module and used for inputting user identity information data through input equipment, and querying user related health data and identification results, physique test results, bone structure data, bone score record, prediction results and physique comprehensive evaluation scores;
the cloud storage module is connected with the main control module and used for carrying out cloud storage on the user identity information, the health data, the bone data, the standard bone data, the bone score, the physique test result, the prediction result and the user physique comprehensive evaluation score through a cloud server and generating a user information database;
and the display module is connected with the main control module and used for displaying the user identity information, the health data, the bone data, the standard bone data, the bone score, the physique test result, the prediction result and the user physique comprehensive evaluation score through a display.
The invention also aims to provide a constitution testing method based on identity recognition, which comprises the following steps:
acquiring user identity information data by using identity information acquisition equipment; matching and identifying the collected user identity information data with the user identity information in the user information database; if the matching is successful, outputting the relevant user information stored in the user information database; if the matching is not successful, automatically inputting user information, and turning to the step two to perform the physical fitness test;
acquiring user health data through health detection equipment; carrying out user skeleton structure identification through a Kinect camera; identifying the health data source through an identification program;
step three, testing the physique of the user through the testing equipment, and outputting a physique testing result; comparing the user skeleton structure data with the standard skeleton data, and outputting a skeleton score; predicting the physical condition of the user through a prediction program;
outputting a user physique comprehensive evaluation score based on the obtained user health data, physique test result, skeleton score and body prediction result;
and fifthly, displaying the collected user identity information, the health data, the bone data, the standard bone data, the bone score, the physique test result, the prediction result and the user physique comprehensive evaluation score through a display.
Further, in step two, the data identification method is as follows:
1) receiving first identity authentication information input by a first user through an identification program; judging whether the first identity authentication information is stored in a preset authentication information base or not;
2) if not, acquiring a first identification mark corresponding to the first identity authentication information, and correspondingly storing the first identity authentication information and the first identification mark through the authentication information base;
3) dividing a first storage area corresponding to the first identification mark from a preset storage, and correspondingly storing the first identification mark and a storage address of the first storage area through a preset mapping table;
4) when the first user uses a health detection device connected in advance to carry out health detection, receiving health detection data sent by the health detection device;
5) storing the health detection data in the first memory area.
Further, the data identification method further comprises the following steps:
if the first identity authentication information is stored in a preset authentication information base, acquiring a first identification mark corresponding to the first identity authentication information through the authentication information base; determining a first storage area corresponding to the first identification mark through the mapping table; performing said 4); receiving a health data management instruction and at least one identity authentication information input by a second user; determining the management authority of the second user according to the at least one identity authentication information; displaying a health data management interface corresponding to the management authority; receiving newly-added identity authentication information input by the second user according to the health data management interface; determining a second identification mark of the second user according to the at least one identity authentication information; and storing the newly-added identity authentication information to the authentication information base according to the second identification mark.
Further, in step three, the prediction method is as follows:
first, acquiring biological data of a target person, body motion data of motion of a body of the target person, by a medical detection apparatus, in the determination, the sleep state is always determined based on the body motion data;
secondly, the sleep state of the target person is always determined based on the acquired biological data,
finally, based on the determined sleep state, a change in the physical condition of the target person is predicted.
Further, in the prediction, when the physical motion data is lower than a predetermined value for a predetermined period, deterioration of the physical condition of the target person is predicted.
Further, the predicting predicts deterioration of the physical condition of the target person based on a frequency with which the target person wakes up at night;
predicting deterioration of the physical condition of the target person when the frequency of the wake-up of the target person at night is equal to or more than a predetermined number of times in the prediction;
the deterioration of the physical condition of the target person includes the onset of dementia peripheral symptoms,
in the prediction, the onset of dementia peripheral symptoms of the target person is predicted based on at least one of the frequency of nighttime awakening of the target person and the frequency of afternoon nap or early evening nap of the target person.
Further, the fitness test method based on identity recognition further comprises the following steps:
(1) the user identity information data can be input through the input equipment, and the relevant health data and the identification result, the physique test result, the bone structure data, the bone score record, the prediction result and the physique comprehensive assessment score of the user are inquired;
(2) and cloud storage is carried out on the user identity information, the health data, the bone data, the standard bone data, the bone score, the constitution test result, the prediction result and the user constitution comprehensive evaluation score through a cloud server, and a user information database is generated.
Another object of the present invention is to provide a computer program for implementing the method for fitness test based on identification.
The invention also aims to provide an information data processing terminal for implementing the identity recognition-based physique test method.
The invention has the advantages and positive effects that: the invention can not only test the physique of the user from multiple aspects of physique, skeleton and health data, but also output the comprehensive evaluation score of the user and predict the physical condition of the user. Meanwhile, the invention can carry out quick information data query by matching the identity information, thereby not only improving the query efficiency, but also ensuring the safety of the user data. The data identification module is used for setting a storage area of the health detection data for each user, so that the source of the health detection data can be conveniently identified, and the health change condition of the user in a period of time can be tracked and detected; meanwhile, biological data of a target person is acquired through a prediction module, a sleep state of the target person is always determined based on the acquired biological data, and a change in physical condition of the target person can be accurately predicted based on the determined sleep state.
Drawings
Fig. 1 is a schematic structural diagram of a fitness test system based on identification according to an embodiment of the present invention.
In the figure: 1. an identity information acquisition module; 2. an identity recognition module; 3. a health data acquisition module; 4. a bone identification module; 5. a main control module; 6. a data identification module; 7. a physique test module; 8. a bone scoring module; 9. a prediction module; 10. a comprehensive scoring module; 11. a query module; 12. a cloud storage module; 13. and a display module.
Fig. 2 is a flowchart of a fitness test method based on identification according to an embodiment of the present invention.
Detailed Description
In order to further understand the contents, features and effects of the present invention, the following embodiments are illustrated and described in detail with reference to the accompanying drawings.
The structure of the present invention will be described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the fitness test system based on identification provided by the embodiment of the present invention includes:
the system comprises an identity information acquisition module 1, an identity recognition module 2, a health data acquisition module 3, a bone recognition module 4, a main control module 5, a data recognition module 6, a physique test module 7, a bone grading module 8, a prediction module 9, a comprehensive grading module 10, an inquiry module 11, a cloud storage module 12 and a display module 13.
And the identity information acquisition module 1 is connected with the main control module 5 and is used for acquiring user identity information data by using identity information acquisition equipment.
And the identity recognition module 2 is connected with the main control module 5 and is used for matching and recognizing the collected user identity information data and the user identity information in the user information database.
And the health data acquisition module 3 is connected with the main control module 5 and is used for acquiring the health data of the user through the health detection equipment.
And the bone identification module 4 is connected with the main control module 5 and used for identifying the bone structure of the user through the Kinect camera.
The main control module 5 is connected with the identity information acquisition module 1, the identity recognition module 2, the health data acquisition module 3, the bone recognition module 4, the data recognition module 6, the physique test module 7, the bone grading module 8, the prediction module 9, the comprehensive grading module 10, the query module 11, the cloud storage module 12 and the display module 13, and is used for controlling the normal work of each module through a host.
And the data identification module 6 is connected with the main control module 5 and is used for identifying the health data source through an identification program.
And the physique test module 7 is connected with the main control module 5 and used for testing the physique of the user through the test equipment and outputting a physique test result.
And the bone scoring module 8 is connected with the main control module 5 and used for comparing the bone structure data of the user with the standard bone data and outputting a bone score.
And the prediction module 9 is connected with the main control module 5 and used for predicting the physical condition of the user through a prediction program.
And the comprehensive scoring module 10 is connected with the main control module 5 and is used for outputting a user physique comprehensive evaluation score based on the physique test result, the skeleton score and the body prediction result.
And the query module 11 is connected with the main control module 5 and is used for inputting user identity information data through input equipment, and querying user-related health data and identification results, physique test results, bone structure data, bone score remembering, prediction results and physique comprehensive evaluation scores.
And the cloud storage module 12 is connected with the main control module 5 and is used for carrying out cloud storage on the user identity information, the health data, the bone data, the standard bone data, the bone score, the physical testing result, the prediction result and the user physical comprehensive evaluation score through a cloud server and generating a user information database.
And the display module 13 is connected with the main control module 5 and used for displaying the user identity information, the health data, the bone data, the standard bone data, the bone score, the physical testing result, the prediction result and the user physical comprehensive evaluation score through a display.
As shown in fig. 2, the fitness test method based on identification provided by the embodiment of the invention includes the following steps:
s101, acquiring user identity information data by using identity information acquisition equipment; matching and identifying the collected user identity information data with the user identity information in the user information database; if the matching is successful, outputting the relevant user information stored in the user information database; and if the matching is not successful, automatically inputting user information, and turning to the step two to perform the physical fitness test.
S102, acquiring user health data through health detection equipment; carrying out user skeleton structure identification through a Kinect camera; and identifying the health data source through an identification program.
S103, testing the physique of the user through the testing equipment, and outputting a physique testing result; comparing the user skeleton structure data with the standard skeleton data, and outputting a skeleton score; and predicting the physical condition of the user through a prediction program.
And S104, outputting a user physique comprehensive evaluation score based on the obtained user health data, physique test result, skeleton score and body prediction result.
And S105, displaying the user identity information, the health data, the bone data, the standard bone data, the bone score, the physique test result, the prediction result and the user physique comprehensive evaluation score through a display.
In step S102, the data identification method provided in the embodiment of the present invention is as follows:
1) receiving first identity authentication information input by a first user through an identification program; and judging whether the first identity authentication information is stored in a preset authentication information base or not.
2) And if not, acquiring a first identification mark corresponding to the first identity authentication information, and correspondingly storing the first identity authentication information and the first identification mark through the authentication information base.
3) And dividing a first storage area corresponding to the first identification mark from a preset storage, and correspondingly storing the first identification mark and the storage address of the first storage area through a preset mapping table.
4) And when the first user uses a health detection device connected in advance to carry out health detection, receiving health detection data sent by the health detection device.
5) Storing the health detection data in the first memory area.
The data identification method provided by the embodiment of the invention further comprises the following steps:
if the first identity authentication information is stored in a preset authentication information base, acquiring a first identification mark corresponding to the first identity authentication information through the authentication information base; determining a first storage area corresponding to the first identification mark through the mapping table; performing said 4); receiving a health data management instruction and at least one identity authentication information input by a second user; determining the management authority of the second user according to the at least one identity authentication information; displaying a health data management interface corresponding to the management authority; receiving newly-added identity authentication information input by the second user according to the health data management interface; determining a second identification mark of the second user according to the at least one identity authentication information; and storing the newly-added identity authentication information to the authentication information base according to the second identification mark.
In step S103, the prediction method provided in the embodiment of the present invention is as follows:
first, biological data of a target person, body motion data of motion of a body of the target person, is acquired by a medical detection apparatus, and in the determination, the sleep state is always determined based on the body motion data.
Secondly, the sleep state of the target person is always determined based on the acquired biological data.
Finally, based on the determined sleep state, a change in the physical condition of the target person is predicted.
In the prediction, when the physical motion data is lower than a predetermined value for a predetermined period, deterioration of the physical condition of the target person is predicted.
In the prediction, deterioration of the physical condition of the target person is predicted based on the frequency of waking up of the target person at night.
In the prediction, when the frequency of the wake-up of the target person at night is equal to or more than a predetermined number of times, deterioration of the physical condition of the target person is predicted.
The deterioration of the physical condition of the target person includes the onset of peripheral symptoms of dementia.
In the prediction, the onset of dementia peripheral symptoms of the target person is predicted based on at least one of the frequency of nighttime awakening of the target person and the frequency of afternoon nap or early evening nap of the target person.
The physique test method based on identity recognition provided by the embodiment of the invention also comprises the following steps:
(1) the user identity information data can be input through the input equipment, and the relevant health data and the identification result, the physique test result, the bone structure data, the bone score record, the prediction result and the physique comprehensive assessment score of the user are inquired;
(2) and cloud storage is carried out on the user identity information, the health data, the bone data, the standard bone data, the bone score, the constitution test result, the prediction result and the user constitution comprehensive evaluation score through a cloud server, and a user information database is generated.
The working principle of the invention is as follows:
when the invention works, firstly, the identity information acquisition module 1 acquires user identity information data by using identity information acquisition equipment; matching and identifying the collected user identity information data and the user identity information in the user information database through the identity identification module 2; when the matching is successful, the main control module 5 calls the relevant information stored in the cloud storage module 12, and displays the relevant health data and the identification result, the physique test result, the bone structure data, the bone score, the prediction result and the physique comprehensive evaluation score of the user by using the display module 13; if the matching is not successful, the main control module 5 stores the user information into the cloud storage module 12, and meanwhile, the main control module 5 controls the health data acquisition module 3 to acquire the health data of the user through the health detection equipment; the control skeleton recognition module 4 recognizes the skeleton structure of the user through a Kinect camera; the control data identification module 6 is used for identifying the health data source through an identification program; the control physique test module 7 tests the physique of the user through test equipment and outputs physique test results; comparing the user skeleton structure data with the standard skeleton data through a skeleton scoring module 8, and outputting a skeleton score; the control prediction module 9 predicts the physical condition of the user through a prediction program; the control comprehensive scoring module 10 outputs a user constitution comprehensive evaluation score based on the constitution test result, the skeleton score and the body prediction result. Secondly, inputting user identity information data by using an input device through an inquiry module 11, inquiring user related health data and identification results, physique test results, bone structure data, bone score remembering, prediction results and physique comprehensive assessment scores; the cloud storage module 12 carries out cloud storage on the user identity information, the health data, the bone data, the standard bone data, the bone score, the physique test result, the prediction result and the user physique comprehensive evaluation score through a cloud server and generates a user information database; the display module 13 displays the user identity information, the health data, the bone data, the standard bone data, the bone score, the physical testing result, the prediction result and the user physical comprehensive evaluation score through a display.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the present invention in any way, and all simple modifications, equivalent changes and modifications made to the above embodiment according to the technical spirit of the present invention are within the scope of the technical solution of the present invention.
Claims (10)
1. A physique test method based on identity recognition is characterized by comprising the following steps:
acquiring user identity information data by using identity information acquisition equipment; matching and identifying the collected user identity information data with the user identity information in the user information database; if the matching is successful, outputting the relevant user information stored in the user information database; if the matching is not successful, automatically inputting user information, and turning to the step two to perform the physical fitness test;
acquiring user health data through health detection equipment; carrying out user skeleton structure identification through a Kinect camera; identifying the health data source through an identification program;
step three, testing the physique of the user through the testing equipment, and outputting a physique testing result; comparing the user skeleton structure data with the standard skeleton data, and outputting a skeleton score; predicting the physical condition of the user through a prediction program;
outputting a user physique comprehensive evaluation score based on the obtained user health data, physique test result, skeleton score and body prediction result;
and fifthly, displaying the collected user identity information, the health data, the bone data, the standard bone data, the bone score, the physique test result, the prediction result and the user physique comprehensive evaluation score through a display.
2. The identity-based fitness test method of claim 1, wherein in step two, the data recognition method comprises the following steps:
(1) receiving first identity authentication information input by a first user through an identification program; judging whether the first identity authentication information is stored in a preset authentication information base or not;
(2) if not, acquiring a first identification mark corresponding to the first identity authentication information, and correspondingly storing the first identity authentication information and the first identification mark through the authentication information base;
(3) dividing a first storage area corresponding to the first identification mark from a preset storage, and correspondingly storing the first identification mark and a storage address of the first storage area through a preset mapping table;
(4) when the first user uses a health detection device connected in advance to carry out health detection, receiving health detection data sent by the health detection device;
(5) storing the health detection data in the first memory area.
3. The identity-based fitness test method of claim 1, wherein the data recognition method further comprises:
if the first identity authentication information is stored in a preset authentication information base, acquiring a first identification mark corresponding to the first identity authentication information through the authentication information base; determining a first storage area corresponding to the first identification mark through the mapping table; performing said (4); receiving a health data management instruction and at least one identity authentication information input by a second user; determining the management authority of the second user according to the at least one identity authentication information; displaying a health data management interface corresponding to the management authority; receiving newly-added identity authentication information input by the second user according to the health data management interface; determining a second identification mark of the second user according to the at least one identity authentication information; and storing the newly-added identity authentication information to the authentication information base according to the second identification mark.
4. The method for fitness test based on identification as claimed in claim 1, wherein the prediction method comprises the following steps:
1) acquiring biological data of a target person, body motion data of a motion of a body of the target person, by a medical detection apparatus, the sleep state being always determined based on the body motion data in the determination;
2) always determining a sleep state of the target person based on the acquired biological data,
3) predicting a change in the physical condition of the target person based on the determined sleep state.
5. The identity-based fitness test method of claim 4, wherein, in the prediction, in a case where the physical motion data is lower than a predetermined value for a predetermined period, deterioration of the physical condition of the target person is predicted.
6. The method for testing physical fitness according to claim 4, wherein in the predicting, deterioration of the physical condition of the target person is predicted based on a frequency of waking up of the target person at night;
predicting deterioration of the physical condition of the target person when the frequency of the wake-up of the target person at night is equal to or more than a predetermined number of times in the prediction;
the deterioration of the physical condition of the target person includes the onset of dementia peripheral symptoms,
in the prediction, the onset of dementia peripheral symptoms of the target person is predicted based on at least one of the frequency of nighttime awakening of the target person and the frequency of afternoon nap or early evening nap of the target person.
7. The identity-based fitness test method of claim 4, further comprising:
(1) the user identity information data can be input through the input equipment, and the relevant health data and the identification result, the physique test result, the bone structure data, the bone score record, the prediction result and the physique comprehensive assessment score of the user are inquired;
(2) and cloud storage is carried out on the user identity information, the health data, the bone data, the standard bone data, the bone score, the constitution test result, the prediction result and the user constitution comprehensive evaluation score through a cloud server, and a user information database is generated.
8. An identity-based fitness test system based on the method 1-7, wherein the identity-based fitness test system comprises:
the system comprises an identity information acquisition module, an identity recognition module, a health data acquisition module, a bone recognition module, a main control module, a data recognition module, a physique test module, a bone grading module, a prediction module, a comprehensive grading module, an inquiry module, a cloud storage module and a display module;
the identity information acquisition module is connected with the main control module and is used for acquiring user identity information data by using identity information acquisition equipment;
the identity recognition module is connected with the main control module and is used for matching and recognizing the collected user identity information data and the user identity information in the user information database;
the health data acquisition module is connected with the main control module and is used for acquiring user health data through the health detection equipment;
the skeleton recognition module is connected with the main control module and used for recognizing the skeleton structure of the user through the Kinect camera;
the main control module is connected with the identity information acquisition module, the identity recognition module, the health data acquisition module, the bone recognition module, the data recognition module, the physique test module, the bone grading module, the prediction module, the comprehensive grading module, the query module, the cloud storage module and the display module and is used for controlling each module to normally work through the host;
the data identification module is connected with the main control module and used for identifying the health data source through an identification program;
the physique test module is connected with the main control module and used for testing the physique of the user through the test equipment and outputting a physique test result;
the skeleton scoring module is connected with the main control module and used for comparing the skeleton structure data of the user with the standard skeleton data and outputting a skeleton score;
the prediction module is connected with the main control module and used for predicting the physical condition of the user through a prediction program;
the comprehensive evaluation module is connected with the main control module and used for outputting a user physical fitness comprehensive evaluation score based on the physical fitness test result, the skeletal evaluation and the physical body prediction result;
the query module is connected with the main control module and used for inputting user identity information data through input equipment, and querying user related health data and identification results, physique test results, bone structure data, bone score record, prediction results and physique comprehensive evaluation scores;
the cloud storage module is connected with the main control module and used for carrying out cloud storage on the user identity information, the health data, the bone data, the standard bone data, the bone score, the physique test result, the prediction result and the user physique comprehensive evaluation score through a cloud server and generating a user information database;
and the display module is connected with the main control module and used for displaying the user identity information, the health data, the bone data, the standard bone data, the bone score, the physique test result, the prediction result and the user physique comprehensive evaluation score through a display.
9. An information data processing terminal for implementing the identity recognition-based physical fitness test method according to any one of claims 1 to 7.
10. A computer-readable storage medium comprising instructions which, when executed on a computer, cause the computer to perform the method for fitness testing based on identification according to any one of claims 1 to 7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112773155A (en) * | 2021-01-25 | 2021-05-11 | 深圳联达技术实业有限公司 | Intelligent pillow control method, device, equipment and storage medium |
| CN113140319A (en) * | 2021-05-14 | 2021-07-20 | 上海拼历客信息科技有限公司 | Children treatment evaluation management system |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104834946A (en) * | 2015-04-09 | 2015-08-12 | 清华大学 | Method and system for non-contact sleep monitoring |
| CN105653856A (en) * | 2015-12-29 | 2016-06-08 | 欧阳锡伟 | Health data acquisition method |
| CN107731307A (en) * | 2017-10-13 | 2018-02-23 | 安徽师范大学 | A kind of physical health self-measuring system |
| KR20190091788A (en) * | 2018-01-29 | 2019-08-07 | 연세대학교 산학협력단 | System and Method for Providing and Evaluating Preventive Medical Information based on Data Base |
-
2019
- 2019-12-23 CN CN201911339834.4A patent/CN112151171A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104834946A (en) * | 2015-04-09 | 2015-08-12 | 清华大学 | Method and system for non-contact sleep monitoring |
| CN105653856A (en) * | 2015-12-29 | 2016-06-08 | 欧阳锡伟 | Health data acquisition method |
| CN107731307A (en) * | 2017-10-13 | 2018-02-23 | 安徽师范大学 | A kind of physical health self-measuring system |
| KR20190091788A (en) * | 2018-01-29 | 2019-08-07 | 연세대학교 산학협력단 | System and Method for Providing and Evaluating Preventive Medical Information based on Data Base |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112773155A (en) * | 2021-01-25 | 2021-05-11 | 深圳联达技术实业有限公司 | Intelligent pillow control method, device, equipment and storage medium |
| CN113140319A (en) * | 2021-05-14 | 2021-07-20 | 上海拼历客信息科技有限公司 | Children treatment evaluation management system |
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