CN113496767A - Healthy moving target evaluation method based on big data - Google Patents
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Abstract
The invention discloses a healthy exercise target evaluation method based on big data, which comprises the following steps: acquiring basic health information of a user through a basic information filling sheet of the health exercise risk assessment, wherein the basic information filling sheet further comprises: whether a user needs to carry out healthy exercise target evaluation or not; and screening out a preliminary target user suitable for performing healthy exercise from the basic health information of the user needing to perform healthy exercise target evaluation. The invention mainly depends on the information filled by the user, the historical physical examination data and medical record data of the user and various data before, during and after the user exercises, and has long-term and systematic planning on the exercise scheme or the exercise target of the user, the health exercise guidance is scientific and continuous, and the health information of the user is continuously and perfectly updated, so that an individually applicable exercise health target scheme is provided for each target user, correct exercise health guidance can be given, and the exercise risk is extremely low.
Description
Technical Field
The invention belongs to the technical field of exercise health assessment, and particularly relates to a healthy exercise target assessment method based on big data.
Background
With the improvement of national living standard and the rapid development of economy, people pay attention to clothes and eating and housing, the requirements on health and stress relief are increased, the health and stress relief cannot be carried out without any movement, and the field of sports is gradually developed.
The fitness exercise coaching of a user on a fitness sport field relies primarily on the personal experience of a coach or instructor, lacks long-term, systematic planning of the user's exercise regimen or exercise goals, and lacks scientificity and continuity.
The health information of the users in the health sports field is lack of batch management, most of the attention of coaches or instructors is body shaping, and the comprehensive grasp of health knowledge is lacked, so that the users with chronic diseases or disease histories cannot generate scientific exercise schemes, correct exercise health guidance cannot be given, and the exercise risk is large.
Therefore, there is a need to provide a method for evaluating a healthy exercise target based on big data to overcome the above-mentioned drawbacks.
Disclosure of Invention
The invention aims to provide a healthy exercise target evaluation method based on big data, which is used for solving one of the technical problems in the prior art, such as: the fitness exercise coaching of a user on a fitness sport field relies primarily on the personal experience of a coach or instructor, lacks long-term, systematic planning of the user's exercise regimen or exercise goals, and lacks scientificity and continuity. The health information of the users in the health sports field is lack of batch management, most of the attention of coaches or instructors is body shaping, and the comprehensive grasp of health knowledge is lacked, so that the users with chronic diseases or disease histories cannot generate scientific exercise schemes, correct exercise health guidance cannot be given, and exercise risks are high.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a healthy exercise target evaluation method based on big data comprises the following steps:
s1, acquiring basic health information of the user through a basic information filling sheet for the health exercise risk assessment, wherein the basic information filling sheet further comprises: whether a user needs to carry out healthy exercise target evaluation or not; screening out a primary target user suitable for performing healthy exercise from basic health information of a user needing to perform healthy exercise target evaluation; acquiring physical examination data and medical record data which are stored in a hospital from the primary target user, and judging whether the primary target user is suitable for performing healthy exercise again according to the physical examination data and the medical record data so as to acquire a target user;
s2, on the basis of the step S1, the target user is subjected to health sign testing, exercise capacity testing, body type detection and gene detection; the physical fitness test is to acquire test index data of physical fitness of the target user, the exercise capacity test is to acquire aerobic endurance test data, muscle strength test data, flexibility test data, coordination test data and cardiopulmonary capacity test data of the target user, the body type test is to acquire body type data and posture data of the target user, and the gene test is to acquire exercise gene data of the user;
s3, on the basis of the step S2, performing feature fusion on the basic health information, physical examination data and medical record data of the target user and results of health sign testing, exercise capacity testing, body type detection and gene detection, and inputting the fused data into a big data health exercise target evaluation model so as to obtain a health exercise target scheme of the target user, wherein the health exercise target scheme comprises exercise items, exercise item equipment indication, exercise item difficulty degree, exercise intensity, exercise duration, exercise frequency, exercise period, whether exercise partner is needed, whether medical supervision is needed, and whether mentor supervision is needed;
s4, on the basis of the step S3, the target user executes the target scheme according to the healthy movement, performs healthy sign test, movement ability test, body type detection and gene detection on the target user in the execution process, records corresponding real-time movement data, performs comparative analysis on the real-time movement data and execution prediction data which are stored in a cloud platform and correspond to the fusion data, and judges whether the execution process of the target scheme of the healthy movement of the target user is abnormal; after the implementation of the healthy exercise target scheme is completed, performing healthy sign test, exercise capacity test, body type detection and gene detection on the target user, recording corresponding exercise completion data, comparing and analyzing the exercise completion data with exercise completion prediction data corresponding to the fusion data stored in a cloud platform, and judging whether the implementation of the healthy exercise target scheme of the target user is abnormal or not;
and S5, on the basis of the step S4, performing big data analysis processing on the fusion data, the real-time motion data, the implementation prediction data, the motion completion data and the motion completion prediction data, and performing independent optimization design on the health motion target scheme of the target user according to the big data analysis processing result to obtain the optimized health motion target scheme.
Preferably, the apparatus for body type detection in step S2 includes a body measurement instrument, a 3D image scan acquisition device, and a body type data display device, the body type data display device is connected to the body measurement instrument and the 3D image scan acquisition device respectively, the body measurement instrument is used to detect body composition data of the target user, the 3D image scan acquisition device is used to acquire a body state image and a dynamic motion image of the user, and the body type data display device is used to display the body composition data, the body state image, and the dynamic motion image of the target user.
Preferably, the device for flexibility testing and coordination testing in step S2 includes a flexibility detection device, a camera, an action analysis device and a data display device, the data display device is respectively connected with the action analysis device and the flexibility detection device, the action analysis device is connected with the camera, the flexibility detection device is used for detecting the flexibility of the target user, the camera is used for collecting the action of the target user, the action analysis device is used for analyzing the coordination of the target user from the action of the target user, and the data display device is used for displaying the flexibility and coordination of the target user.
Preferably, the apparatus for testing cardiopulmonary ability in step S2 includes a gas collector, an electrocardiograph collector, a heart rate collector, a blood pressure monitor, a blood oxygen collector, and an analysis computer, where the gas collector, the electrocardiograph collector, the heart rate collector, the blood pressure monitor, and the blood oxygen collector are connected to the analysis computer through data lines, the gas collector is configured to collect gas environment data of the target user during breathing, the electrocardiograph collector is configured to collect electrocardiograph data of the target user, the heart rate collector is configured to collect heart rate data of the target user, the blood pressure monitor is configured to collect blood pressure data of the target user, the blood oxygen collector is configured to collect blood oxygen data of the target user, and the analysis computer is configured to generate an evaluation result of cardiopulmonary exercise ability of the user according to the data.
Preferably, the gas collector includes turbine flow sensor, oxygen concentration sensor, carbon dioxide concentration sensor, humidity transducer, baroceptor and temperature sensor, turbine flow sensor is used for detecting the flow of user's expired gas, and oxygen concentration sensor is used for detecting oxygen concentration, carbon dioxide concentration sensor and is used for detecting gaseous carbon dioxide concentration, humidity transducer is used for detecting gaseous humidity, baroceptor is used for detecting gaseous atmospheric pressure, and temperature sensor is used for detecting gaseous temperature.
Preferably, each line of the analysis computer connected with the turbine flow sensor, the oxygen concentration sensor, the carbon dioxide concentration sensor, the humidity sensor, the air pressure sensor and the temperature sensor is separately provided with a signal amplification circuit, and the signal amplification circuit comprises a first NPN-type bipolar transistor, a second NPN-type bipolar transistor, a PNP-type bipolar transistor, a first resistor, a second resistor, a polar capacitor and a diode; the negative pole of the polar capacitor is used as the input end of the signal amplification module, the positive pole of the polar capacitor is respectively connected with one end of the first resistor and the base electrode of the first NPN type bipolar transistor, the emitter set of the first NPN type bipolar transistor is grounded, the collector of the first NPN type bipolar transistor is respectively connected with the other end of the first resistor, the cathode of the diode and the base of the PNP type bipolar transistor, the anode of the diode is connected to a power supply through a second resistor, the anode of the diode is connected with the base of a second NPN type bipolar transistor, the collector of the second NPN type bipolar transistor is connected with a power supply, the emitter of the second NPN type bipolar transistor is connected with the emitter of the PNP type bipolar transistor, the collector of the PNP type bipolar transistor is grounded, and the emitter of the PNP type bipolar transistor is used as the output end of the signal amplification module.
Preferably, the healthy exercise goal scheme in step S3 informs the target user through a video image display mode and/or a voice broadcast mode.
Preferably, in step S4, if it is determined that the implementation process of the target exercise target scheme of the target user is in an abnormal state, performing an audible and visual alarm; and if the target user is judged to be in an abnormal state after the implementation of the healthy movement target scheme is completed, performing sound and light alarm.
The beneficial technical effects of the invention are as follows: the method mainly depends on information filled by a user, historical physical examination data and medical record data of the user and various data before, during and after the user exercises, the exercise scheme or the exercise target of the user is planned in a long-term and systematic way, the exercise guidance is scientific and continuous, the health information of the user is continuously and perfectly updated, an independently applicable exercise health target scheme is provided for each target user, correct exercise health guidance can be given, and the exercise risk is extremely low.
Drawings
FIG. 1 is a flow chart illustrating steps of an embodiment of the present invention.
Fig. 2 is a schematic diagram of a body type detection apparatus according to an embodiment of the present invention.
FIG. 3 is a schematic diagram of the flexibility testing and coordination testing apparatus according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of a cardiopulmonary ability testing apparatus according to an embodiment of the present invention.
Fig. 5 is a schematic view of a gas collector according to an embodiment of the present invention.
Fig. 6 is a schematic diagram of a signal amplifying circuit according to an embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to fig. 1 to 6 of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example (b):
as shown in fig. 1, a healthy exercise target evaluation method based on big data includes the following steps:
s1, acquiring basic health information of the user through a basic information filling sheet for the health exercise risk assessment, wherein the basic information filling sheet further comprises: whether a user needs to carry out healthy exercise target evaluation or not; screening out a primary target user suitable for performing healthy exercise from basic health information of a user needing to perform healthy exercise target evaluation; acquiring physical examination data and medical record data which are stored in a hospital from the primary target user, and judging whether the primary target user is suitable for performing healthy exercise again according to the physical examination data and the medical record data so as to acquire a target user;
the basic health information actively filled by the user is obtained health original information for the first time, on the basis, the user selects whether the health exercise target needs to be evaluated, then the needed physical examination data and medical record data provided by the user are obtained health original data for the second time, and on the basis, judgment and analysis are carried out, and whether the user is suitable for carrying out health exercise is carried out. Therefore, the scheme has the layering and comprehensiveness for acquiring the health data of the user, and comprehensively acquires and acquires all historical data related to the health movement of the user under the condition that the user needs to be known, so that whether the user is suitable for the health movement is judged and analyzed. This is a prerequisite for scientific health assessment of the user.
S2, on the basis of the step S1, the target user is subjected to health sign testing, exercise capacity testing, body type detection and gene detection; the physical fitness test is to acquire test index data of physical fitness of the target user, the exercise capacity test is to acquire aerobic endurance test data, muscle strength test data, flexibility test data, coordination test data and cardiopulmonary capacity test data of the target user, the body type test is to acquire body type data and posture data of the target user, and the gene test is to acquire exercise gene data of the user;
s3, on the basis of the step S2, performing feature fusion on the basic health information, physical examination data and medical record data of the target user and results of health sign testing, exercise capacity testing, body type detection and gene detection, and inputting the fused data into a big data health exercise target evaluation model so as to obtain a health exercise target scheme of the target user, wherein the health exercise target scheme comprises exercise items, exercise item equipment indication, exercise item difficulty degree, exercise intensity, exercise duration, exercise frequency, exercise period, whether exercise partner is needed, whether medical supervision is needed, and whether mentor supervision is needed;
after the target user is determined, the comprehensive data detection is carried out on the user on site, all the data are necessary to be collected comprehensively due to risks existing in the health exercise, the more comprehensive the data are collected, the lower the corresponding risk is, and the detected data are used as the input of a big-data health exercise target evaluation model.
S4, on the basis of the step S3, the target user executes the target scheme according to the healthy movement, performs healthy sign test, movement ability test, body type detection and gene detection on the target user in the execution process, records corresponding real-time movement data, performs comparative analysis on the real-time movement data and execution prediction data which are stored in a cloud platform and correspond to the fusion data, and judges whether the execution process of the target scheme of the healthy movement of the target user is abnormal; after the implementation of the healthy exercise target scheme is completed, performing healthy sign test, exercise capacity test, body type detection and gene detection on the target user, recording corresponding exercise completion data, comparing and analyzing the exercise completion data with exercise completion prediction data corresponding to the fusion data stored in a cloud platform, and judging whether the implementation of the healthy exercise target scheme of the target user is abnormal or not;
the step of judging the abnormality of the two links can effectively protect a target user, avoid accidents during healthy exercise and make relevant reflection at the first time of data abnormality. In addition, partial data can be imported and exported and can be brought into a large cloud database for storage and updating, and the scheme of the healthy exercise target is favorably perfected.
And S5, on the basis of the step S4, performing big data analysis processing on the fusion data, the real-time motion data, the implementation prediction data, the motion completion data and the motion completion prediction data, and performing independent optimization design on the health motion target scheme of the target user according to the big data analysis processing result to obtain the optimized health motion target scheme.
Through the technical scheme, the method for guiding the user to the healthy movement mainly depends on information filled by the user, historical physical examination data and medical record data of the user and various data before, during and after the user moves, the exercise scheme or the exercise target of the user is planned in a long-term and systematic way, the healthy movement guidance is scientific and continuous, the healthy information of the user is continuously and perfectly updated, an independently applicable exercise healthy target scheme is provided for each target user, the correct exercise healthy guidance can be given, and the exercise risk is extremely low.
As shown in fig. 2, it is preferable in this embodiment that the apparatus for body type detection in step S2 includes a body measurement instrument, a 3D image scan acquisition device, and a body type data display apparatus, the body measurement instrument being connected to the body measurement instrument and the 3D image scan acquisition device, respectively, the body measurement instrument being used to detect body composition data of the target user, the 3D image scan acquisition device being used to acquire a body state image and a dynamic motion image of the user, the body type data display apparatus being used to display the body composition data, the body state image, and the dynamic motion image of the target user.
As shown in fig. 3, in this embodiment, it is preferable that the apparatus for flexibility testing and coordination testing in step S2 includes a flexibility detection device, a camera, a motion analysis device, and a data display device, the data display device is respectively connected to the motion analysis device and the flexibility detection device, the motion analysis device is connected to the camera, the flexibility detection device is used for detecting the flexibility of the target user, the camera is used for collecting the motion of the target user, the motion analysis device is used for analyzing the coordination of the motion of the target user, and the data display device is used for displaying the flexibility and coordination of the target user.
Through above-mentioned scheme, equipment such as appearance, flexibility detection device, camera can be adjusted according to target user's kind to the body, if: the detection result is definitely inaccurate if different kinds of users are detected by the same and fixed equipment, such as old people, children or teenagers, fat, thin or common users, and tall, short or common users, so that the key equipment needs to perform an adaptive process according to the types of the users.
As shown in fig. 4, in this embodiment, preferably, the apparatus for testing cardiopulmonary capacity in step S2 includes a gas collector, an electrocardiogram collector, a heart rate collector, a blood pressure monitor, a blood oxygen collector, and an analysis computer, where the gas collector, the electrocardiogram collector, the heart rate collector, the blood pressure monitor, and the blood oxygen collector are connected to the analysis computer through data lines, the gas collector is configured to collect gas environment data of a target user during breathing, the electrocardiogram collector is configured to collect electrocardiographic data of the target user, the heart rate collector is configured to collect heart rate data of the target user, the blood pressure monitor is configured to collect blood pressure data of the target user, the blood oxygen collector is configured to collect blood oxygen data of the target user, and the analysis computer is configured to generate an evaluation result of cardiopulmonary exercise capacity of the user according to the data.
Through the scheme, the heart-lung capacity is one of the most important links of the movement, and the data related to the heart-lung capacity can reflect the real state of the user during the movement, so that the real-time comprehensive acquisition of gas, electrocardio, heart rate, blood pressure, blood oxygen and the like is necessary.
As shown in fig. 5, in this embodiment, it is preferable that the gas collector includes a turbine flow sensor, an oxygen concentration sensor, a carbon dioxide concentration sensor, a humidity sensor, an air pressure sensor and a temperature sensor, the turbine flow sensor is used for detecting the flow rate of the exhaled gas of the user, the oxygen concentration sensor is used for detecting the oxygen concentration, the carbon dioxide concentration sensor is used for detecting the carbon dioxide concentration of the gas, the humidity sensor is used for detecting the air humidity, the air pressure sensor is used for detecting the air pressure, and the temperature sensor is used for detecting the air temperature.
As shown in fig. 6, preferably, each line of the analysis computer connected to the turbine flow sensor, the oxygen concentration sensor, the carbon dioxide concentration sensor, the humidity sensor, the air pressure sensor and the temperature sensor is separately provided with a signal amplification circuit, and the signal amplification circuit includes a first NPN-type bipolar transistor, a second NPN-type bipolar transistor, a PNP-type bipolar transistor, a first resistor, a second resistor, a polar capacitor and a diode; the negative pole of the polar capacitor is used as the input end of the signal amplification module, the positive pole of the polar capacitor is respectively connected with one end of the first resistor and the base electrode of the first NPN type bipolar transistor, the emitter set of the first NPN type bipolar transistor is grounded, the collector of the first NPN type bipolar transistor is respectively connected with the other end of the first resistor, the cathode of the diode and the base of the PNP type bipolar transistor, the anode of the diode is connected to a power supply through a second resistor, the anode of the diode is connected with the base of a second NPN type bipolar transistor, the collector of the second NPN type bipolar transistor is connected with a power supply, the emitter of the second NPN type bipolar transistor is connected with the emitter of the PNP type bipolar transistor, the collector of the PNP type bipolar transistor is grounded, and the emitter of the PNP type bipolar transistor is used as the output end of the signal amplification module.
Through the scheme, various sensors send various data to the analysis computer through the signal amplification circuit which is connected independently, and the accuracy of the various data is guaranteed.
Preferably, the healthy exercise goal scheme in step S3 informs the target user through a video image display mode and/or a voice broadcast mode.
By the scheme, the method is suitable for target users with related sensory disorders, such as visually-impaired people, and can obtain the healthy movement target scheme in a voice broadcasting mode, and further, for the hearing-impaired people, the healthy movement target scheme can be obtained in a video image display mode.
Preferably, in step S4, if it is determined that the implementation process of the target exercise target scheme of the target user is in an abnormal state, performing an audible and visual alarm; and if the target user is judged to be in an abnormal state after the implementation of the healthy movement target scheme is completed, performing sound and light alarm.
By the scheme, a target user in motion may wear the earphone to listen to music, and if only the sound alarm is given, the alarm information cannot be transmitted to the target user, so that the simultaneous sound and light alarm is more reasonable. And meanwhile, the sound and light alarm can remind people around the target user, so that the risk brought by healthy movement is reduced.
In the description of the present invention, it is to be understood that the terms "counterclockwise", "clockwise", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate orientations or positional relationships based on those shown in the drawings, and are used for convenience of description only, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be considered as limiting.
Claims (8)
1. A healthy exercise target evaluation method based on big data is characterized by comprising the following steps:
s1, acquiring basic health information of the user through a basic information filling sheet for the health exercise risk assessment, wherein the basic information filling sheet further comprises: whether a user needs to carry out healthy exercise target evaluation or not; screening out a primary target user suitable for performing healthy exercise from basic health information of a user needing to perform healthy exercise target evaluation; acquiring physical examination data and medical record data which are stored in a hospital from the primary target user, and judging whether the primary target user is suitable for performing healthy exercise again according to the physical examination data and the medical record data so as to acquire a target user;
s2, on the basis of the step S1, the target user is subjected to health sign testing, exercise capacity testing, body type detection and gene detection; the physical fitness test is to acquire test index data of physical fitness of the target user, the exercise capacity test is to acquire aerobic endurance test data, muscle strength test data, flexibility test data, coordination test data and cardiopulmonary capacity test data of the target user, the body type test is to acquire body type data and posture data of the target user, and the gene test is to acquire exercise gene data of the user;
s3, on the basis of the step S2, performing feature fusion on the basic health information, physical examination data and medical record data of the target user and results of health sign testing, exercise capacity testing, body type detection and gene detection, and inputting the fused data into a big data health exercise target evaluation model so as to obtain a health exercise target scheme of the target user, wherein the health exercise target scheme comprises exercise items, exercise item equipment indication, exercise item difficulty degree, exercise intensity, exercise duration, exercise frequency, exercise period, whether exercise partner is needed, whether medical supervision is needed, and whether mentor supervision is needed;
s4, on the basis of the step S3, the target user executes the target scheme according to the healthy movement, performs healthy sign test, movement ability test, body type detection and gene detection on the target user in the execution process, records corresponding real-time movement data, performs comparative analysis on the real-time movement data and execution prediction data which are stored in a cloud platform and correspond to the fusion data, and judges whether the execution process of the target scheme of the healthy movement of the target user is abnormal; after the implementation of the healthy exercise target scheme is completed, performing healthy sign test, exercise capacity test, body type detection and gene detection on the target user, recording corresponding exercise completion data, comparing and analyzing the exercise completion data with exercise completion prediction data corresponding to the fusion data stored in a cloud platform, and judging whether the implementation of the healthy exercise target scheme of the target user is abnormal or not;
and S5, on the basis of the step S4, performing big data analysis processing on the fusion data, the real-time motion data, the implementation prediction data, the motion completion data and the motion completion prediction data, and performing independent optimization design on the health motion target scheme of the target user according to the big data analysis processing result to obtain the optimized health motion target scheme.
2. The big-data based healthy exercise target assessment method according to claim 1, wherein the device for body shape detection in step S2 comprises a body measurement instrument, a 3D image scanning and collecting device and a body shape data display device, the body shape data display device is respectively connected with the body measurement instrument and the 3D image scanning and collecting device, the body measurement instrument is used for detecting body composition data of the target user, the 3D image scanning and collecting device is used for acquiring body state images and dynamic motion images of the user, and the body shape data display device is used for displaying the body composition data, the body state images and the dynamic motion images of the target user.
3. The big-data-based healthy exercise target assessment method according to claim 1, wherein the apparatus for flexibility test and coordination test in step S2 comprises a flexibility detection device, a camera, an action analysis device and a data display device, the data display device is respectively connected with the action analysis device and the flexibility detection device, the action analysis device is connected with the camera, the flexibility detection device is used for detecting the flexibility of the target user, the camera is used for collecting the action of the target user, the action analysis device is used for analyzing the coordination from the action of the target user, and the data display device is used for displaying the flexibility and coordination of the target user.
4. The big data based healthy moving object assessment method according to claim 1, it is characterized in that the device for testing the cardio-pulmonary capacity in the step S2 comprises a gas collector, an electrocardio collector, a heart rate collector, a blood pressure monitor, a blood oxygen collector and an analysis computer, the gas collector, the electrocardio collector, the heart rate collector, the blood pressure monitor and the blood oxygen collector are connected to an analysis computer through data lines, the gas collector is used for collecting gas environment data of a target user during breathing, the electrocardio collector is used for collecting electrocardio data of the target user, the heart rate collector is used for collecting heart rate data of a target user, the blood pressure monitor is used for collecting blood pressure data of the target user, the blood oxygen collector is used for collecting blood oxygen data of a target user, and the analysis computer is used for generating an evaluation result of the heart-lung movement ability of the user according to the data.
5. The big data based healthy movement target evaluation method according to claim 4, wherein the gas collector comprises a turbine flow sensor, an oxygen concentration sensor, a carbon dioxide concentration sensor, a humidity sensor, a gas pressure sensor and a temperature sensor, the turbine flow sensor is used for detecting the flow of the gas exhaled by the user, the oxygen concentration sensor is used for detecting the oxygen concentration, the carbon dioxide concentration sensor is used for detecting the carbon dioxide concentration of the gas, the humidity sensor is used for detecting the humidity of the gas, the gas pressure sensor is used for detecting the gas pressure, and the temperature sensor is used for detecting the temperature of the gas.
6. The big-data-based healthy moving object assessment method according to claim 5, wherein a signal amplification circuit is separately arranged on each line connecting the analysis computer with the turbine flow sensor, the oxygen concentration sensor, the carbon dioxide concentration sensor, the humidity sensor, the air pressure sensor and the temperature sensor, and the signal amplification circuit comprises a first NPN type bipolar transistor, a second NPN type bipolar transistor, a PNP type bipolar transistor, a first resistor, a second resistor, a polar capacitor and a diode; the negative pole of the polar capacitor is used as the input end of the signal amplification module, the positive pole of the polar capacitor is respectively connected with one end of the first resistor and the base electrode of the first NPN type bipolar transistor, the emitter set of the first NPN type bipolar transistor is grounded, the collector of the first NPN type bipolar transistor is respectively connected with the other end of the first resistor, the cathode of the diode and the base of the PNP type bipolar transistor, the anode of the diode is connected to a power supply through a second resistor, the anode of the diode is connected with the base of a second NPN type bipolar transistor, the collector of the second NPN type bipolar transistor is connected with a power supply, the emitter of the second NPN type bipolar transistor is connected with the emitter of the PNP type bipolar transistor, the collector of the PNP type bipolar transistor is grounded, and the emitter of the PNP type bipolar transistor is used as the output end of the signal amplification module.
7. The big data-based healthy moving object assessment method according to claim 1, wherein the healthy moving object scheme in step S3 informs the target user through a video image display mode and/or a voice broadcast mode.
8. The big-data-based healthy exercise target assessment method according to claim 1, wherein in step S4, if it is determined that the implementation process of the healthy exercise target scheme of the target user is abnormal, an audible and visual alarm is performed; and if the target user is judged to be in an abnormal state after the implementation of the healthy movement target scheme is completed, performing sound and light alarm.
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| CN202010265995.XA CN113496767A (en) | 2020-04-07 | 2020-04-07 | Healthy moving target evaluation method based on big data |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114098658A (en) * | 2021-11-26 | 2022-03-01 | 芯原微电子(南京)有限公司 | Health state monitoring method and device |
| CN114373549A (en) * | 2022-03-22 | 2022-04-19 | 北京大学 | Self-adaptive exercise prescription health intervention method and system for old people |
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2020
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114098658A (en) * | 2021-11-26 | 2022-03-01 | 芯原微电子(南京)有限公司 | Health state monitoring method and device |
| CN114373549A (en) * | 2022-03-22 | 2022-04-19 | 北京大学 | Self-adaptive exercise prescription health intervention method and system for old people |
| CN114373549B (en) * | 2022-03-22 | 2022-06-10 | 北京大学 | Self-adaptive exercise prescription health intervention method and system for old people |
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