CN113744884A - Student health data early warning and intervention method and system - Google Patents

Student health data early warning and intervention method and system Download PDF

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CN113744884A
CN113744884A CN202111156352.2A CN202111156352A CN113744884A CN 113744884 A CN113744884 A CN 113744884A CN 202111156352 A CN202111156352 A CN 202111156352A CN 113744884 A CN113744884 A CN 113744884A
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张艳红
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Southwest University Of Political Science & Law
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Abstract

The invention provides a student physical health data early warning and intervention method and system, comprising the following steps: acquiring student physical health data of a target student, and respectively calculating a vital capacity index, a height and weight index, a body composition index and a balance ability index of the target student according to the student physical health data; and comparing the vital capacity index, the height and weight index, the body composition index and/or the balance ability index of the target student with the corresponding preset standard index, and if the vital capacity index, the height and weight index, the body composition index and/or the balance ability index of the target student do not meet the preset standard index, early warning and intervention are carried out on the target student. By analyzing the physical health data of the students, the invention not only can make an individualized exercise scheme for the students, adjust exercise habits and make up for the short health board to provide reliable support; the analysis result of the invention also helps education administrative department, school, sports teacher and parents of students to know the physical condition of students in time, provides scientific basis for the later exercise intervention of the students, and achieves the purpose of improving the physical health condition.

Description

Student health data early warning and intervention method and system
Technical Field
The invention relates to the technical field of health data processing, in particular to a method and a system for early warning and intervening of student health data.
Background
The student physical health data early warning is to perform systematic analysis and judge the source, type, degree and tendency of physical decline risks according to the physical health test data of students for student groups or individuals, and sends out corresponding early warning methods.
According to the latest national physique monitoring bulletin about the physique and health of students in the country, the results show that the physique and health data of most students are still in the level of passing and failing, and the proportion of the students reaching good and excellent is small. The reason is mainly two points: first, most students attach less attention to physical fitness tests, and do not perform targeted exercises before testing, or even pay attention to physical fitness test results, resulting in that they are less concerned about their physical fitness. Second, to the problem that the student does not pay attention to self physique health too much, lack one set of effective early warning intervention system at present, if can carry out early warning in advance and control to student's physique health data, make the student can realize that the health condition of oneself is not good enough, can let self physical stamina test unqualified, the student that corresponds may initiatively go to improve the physique health of oneself.
Therefore, the invention provides a student health data early warning and intervention method and system, which are used for timely early warning and intervention on students with poor physique.
Disclosure of Invention
In view of the above disadvantages of the prior art, the present invention provides a method and a system for early warning and intervention of student health data, which are used to solve the problems that a system for early warning and intervention of student physical data is lacked and timely early warning and intervention of students with poor physical quality is not available in the prior art.
In order to achieve the above objects and other related objects, the present invention provides a student physical health data early warning and intervention method, comprising the steps of:
acquiring student physical health data of a target student;
respectively calculating a vital capacity index, a height and weight index, a body composition index and a balance ability index of the target student according to the student physical health data;
and comparing the vital capacity index, the height and body weight index, the body composition index and the balance ability index with corresponding preset standard indexes respectively, and if the vital capacity index, the height and body weight index, the body composition index and/or the balance ability index of the target student do not meet the preset standard indexes, early warning and intervening the target student.
Optionally, the pre-warning comprises a third-level pre-warning;
if the height and weight index of the target student is less than 18.5, performing first-level early warning on the target student;
if the height and weight index of the target student is more than or equal to 24 and less than 26.9, performing second-stage early warning on the target student;
and if the height and weight index of the target student is more than or equal to 27, performing third-level early warning on the target student.
Optionally, when the height-weight index of the target student is greater than or equal to 27 and less than 29.9, marking the third-level early warning at the current moment as an obesity I-degree-class third-level early warning; and the number of the first and second groups,
and when the height and body weight index of the target student is more than or equal to 30, recording the third-level early warning at the current moment as the obesity II-degree third-level early warning.
Optionally, when calculating the vital capacity index, height and weight index, body composition index or balance ability index of the target student, the method further comprises:
the student physical health data are subjected to standardized processing, and the method comprises the following steps:
Figure BDA0003288737350000021
in the formula, XiThe ith physical fitness test contained in the student physical health data;
Xi，minthe minimum value of the ith physical fitness test contained in the student physical health data;
Xi，maxthe maximum value of the ith physical fitness test contained in the student physical health data;
X′iand the normalized physical health data of the students are tested for the physical fitness of the ith item.
Optionally, the physical fitness test included in the student physical health data comprises: height test, weight test, one minute rope skipping test, fifty meters sprint test, seat anteflexion test and vital capacity test.
Optionally, the method further comprises the steps of obtaining vision test data of the target student at the current moment, comparing the vision test data of the target student at the current moment with the vision standard table, and performing early warning and intervention on the target student when the vision test data of the target student is lower than 1.0 of the vision standard table.
Optionally, before calculating the vital capacity index, height and weight index, body composition index and balance ability index of the target student according to the student physical health data, the method further includes determining the reliability of the student physical health data, including:
acquiring the physical health data of students in historical years and current years in a target area;
determining data growth amplitudes of the target area in two adjacent historical years according to the acquired student physical health data;
determining the data discrete degree of the target area in the same historical year according to the acquired student physical health data;
acquiring the data growth amplitude and the data dispersion degree of the target area, and establishing a data reliability evaluation model according to the data growth amplitude and the data dispersion degree of the target area;
and verifying the student physical health data of the target area in the current year by using the data credibility evaluation model, and determining the credibility of the student physical health data of the target area in the current year.
Optionally, when the data credibility evaluation model is used for verifying the student physical health data of the current year,
if any one of the data increase amplitude and the data discrete degree in the target area is abnormal, judging that the student physical health data of the target area in the current year is not credible;
if the data growth amplitude and the data dispersion degree in the target area are all abnormal, judging that the data reliability evaluation model is abnormal;
and if the data increase amplitude and the data discrete degree in the target area are all normal, judging that the student physical health data of the target area in the current year is credible.
The invention also provides a student physical health data early warning and intervention system, which comprises:
the data acquisition module is used for acquiring student physical health data of a target student;
the index calculation module is used for calculating the vital capacity index, the height and weight index, the body composition index and the balance ability index of the target student according to the student physical health data;
the data comparison module is used for comparing the vital capacity index, the height and weight index, the body composition index and the balance ability index with corresponding preset standard indexes respectively;
and the early warning and intervention module is used for early warning and intervening the target students when the vital capacity index, the height and weight index, the body composition index and/or the balance ability index of the target students do not meet the preset standard index.
Optionally, the system further comprises:
the vision comparison module is used for acquiring vision test data of the target student at the current moment and comparing the vision test data of the target student at the current moment with the vision standard table; and when the vision test data of the target students are lower than 1.0 in the vision standard table, early warning and intervention are carried out on the target students.
As described above, the invention provides a student physical health data early warning and intervention method and system, which have the following beneficial effects: according to the method, student physical health data of a target student are obtained, and then the vital capacity index, the height and weight index, the body composition index and the balance ability index of the target student are respectively calculated according to the student physical health data; and comparing the vital capacity index, the height and body weight index, the body composition index and the balance ability index with corresponding preset standard indexes respectively, and if the vital capacity index, the height and body weight index, the body composition index and/or the balance ability index of the target student do not meet the preset standard indexes, early warning and intervening the target student. Because the vital capacity of the human body, the highest oxygen absorption amount, the weight, the height, the body surface area, the chest circumference, the sitting height and the like are closely related, the physical health data of the students of the target students are analyzed by utilizing the vital capacity index, and the differences among different students can be objectively reflected, so that the students with poor physical health can be conveniently early warned and intervened by schools or physical education, and the physical quality of the students can be improved. In addition, the obesity and the emaciation of the student directly influence the physical health level, and one standard for measuring the obesity and the emaciation of the individual is the body height Body Mass Index (BMI), and the fat and the emaciation level of the individual can be known according to the BMI value, so that the invention can assist a school or sports teacher to further control the obesity rate and the overweight rate of the student by analyzing the body height Body Mass Index (BMI) and assist the school or sports teacher to early warn and intervene the students which may be overweight or obese in advance. Meanwhile, the body composition comprises internal indexes related to physical health level, such as bone density, muscles and the like, so that the existing level and balance and coordination capacity of each index in the body of the tested person can be reflected, and the balance capacity is obtained by analyzing the individual balance capacity condition through the completion result of a given action. When the two indexes of the body composition and the balance ability of a certain student are too low, early warning and intervention are needed to assist the student to carry out targeted exercise, and the physical health level of the student is improved. Therefore, by analyzing the physical health data of the students, the invention not only can make an individualized exercise scheme for the students, adjust exercise habits and make up for the short health board to provide reliable support; the analysis result of the invention also helps education administrative department, school, sports teacher and parents of students to know the physical condition of students in time, provides scientific basis for the later exercise intervention of the students, and achieves the purpose of improving the physical health condition.
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Fig. 1 is a schematic flow chart of a student health data early warning and intervention method according to an embodiment;
FIG. 2 is a schematic diagram illustrating a structure of a data reliability evaluation model according to an embodiment;
FIG. 3 is a standard difference plot of height and weight provided by an embodiment;
FIG. 4 is a standard differential layout of one minute jump rope, fifty meters run, and sit-up forward flexion provided by an embodiment;
fig. 5 is a schematic hardware structure diagram of a student health data early warning and intervention system according to an embodiment.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
It should be noted that the drawings provided in the present embodiment are only for illustrating the basic idea of the present invention, and the components related to the present invention are only shown in the drawings rather than drawn according to the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated.
Referring to fig. 1, the present embodiment provides a method for early warning and intervention of student physical health data, including the following steps:
s100, acquiring student physical health data of a target student;
s200, respectively calculating a vital capacity index, a height and weight index, a body composition index and a balance ability index of a target student according to the student physical health data;
s300, comparing the vital capacity index, the height and weight index, the body composition index and the balance ability index with corresponding preset standard indexes respectively, and if the vital capacity index, the height and weight index, the body composition index and/or the balance ability index of the target student do not meet the preset standard indexes, early warning and intervening are carried out on the target student.
As the vital capacity of the human body, the highest oxygen absorption amount, the weight, the height, the body surface area, the chest circumference, the sitting height and the like are closely related, the method analyzes the student physical health data of the target student by utilizing the vital capacity index, and can objectively reflect the difference among different students, thereby facilitating the early warning and intervention of schools or physical education on students with poor physical health and helping the students to improve the physical quality. In addition, the obesity and the emaciation of the student directly influence the physical health level, and one standard for measuring the obesity and the emaciation of the individual is the body height Body Mass Index (BMI), and the fat and the emaciation level of the individual can be known according to the BMI value, so the method can assist a school or sports teacher to further control the obesity rate and the overweight rate of the student by analyzing the body height Body Mass Index (BMI), and assist the school or sports teacher to early warn and intervene the students which may be overweight or obese in advance. Meanwhile, the body composition comprises internal indexes related to physical health level, such as bone density, muscles and the like, so that the existing level and balance and coordination capacity of each index in the body of the tested person can be reflected, and the balance capacity is obtained by analyzing the individual balance capacity condition through the completion result of a given action. When the two indexes of the body composition and the balance ability of a certain student are too low, early warning and intervention are needed to assist the student to carry out targeted exercise, and the physical health level of the student is improved. The physical fitness test included in the student physical fitness data in the method comprises the following steps: height test, weight test, one minute rope skipping test, fifty meters sprint test, seat anteflexion test and vital capacity test.
According to the records, the method divides the early warning degree into three levels. For the body height and body weight index BMI, if the body height and body weight index of the target student is less than 18.5, performing first-level early warning on the target student; if the height and weight index of the target student is more than or equal to 24 and less than 26.9, performing second-stage early warning on the target student; and if the height and weight index of the target student is more than or equal to 27, performing third-level early warning on the target student. When the height and weight index of the target student is more than or equal to 27 and less than 29.9, marking the third-level early warning at the current moment as an obesity I-degree-class third-level early warning; and when the height and weight index of the target student is more than or equal to 30, recording the third-level early warning of the current moment as the third-level early warning of obesity class II. Therefore, as the obesity of the individual student directly affects the physical health level, and one standard for measuring the obesity of the individual is the body height Body Mass Index (BMI), and the fat-lean level of the individual body can be known according to the BMI value, the embodiment can assist the school or sports teacher to further control the obesity rate and the overweight rate of the student by analyzing the body height Body Mass Index (BMI), and assist the school or sports teacher to perform early warning and intervention on the student who may be overweight or obese in advance. The standard parameters corresponding to the BMI in the method are referred to as BMI parameters in national student physical health standards (revised 2014).
According to the above description, in the present method, the vital capacity index is the vital capacity of the student at the present time ÷ body weight; wherein the unit of vital capacity is milliliter and the unit of body weight is kilogram. The standard index corresponding to the vital capacity index in the method is calculated from the standard vital capacity and the standard body weight in national student physical health standards (revised 2014). In the method, the body composition index can be obtained by a body composition analyzer, and the standard index corresponding to the body composition index refers to the body composition analyzer. Wherein, the body composition index comprises: metabolic rate, moisture content, body fat rate, waist-hip ratio, muscle content, etc. In the method, the balance ability index includes a static balance ability index and a dynamic balance ability index. Wherein, the static balance capability test comprises: standing normally to open eyes, standing normally to close eyes, standing on one foot with one eye closed; the dynamic balance capability test comprises the following steps: score, maximum angular velocity, average angular velocity, percentage of time in front, middle, back, left, middle, and right zones to the total time tested by the tester, time of ball stay in the center zone, zones 1, 2, 3, and 4, and test result rating. The method can utilize the static balancing instrument to carry out static balancing capability test, in order to ensure that a subject is not interfered, the static balancing instrument is placed in a quiet space with moderate light and no noise, a cross is placed at a position 1.50 meters in front of the center of a stress flat plate of the balancing instrument and 1.70 meters in height, and the target center is clear and easy to see. The method for testing the static balance capability by using the static balance instrument comprises the following steps:
(1) normal standing and eye opening: the feet of the testee stand on two sides of the central circle of the stress plate in parallel and opposite, the distance from the central line is 4cm., the testee puts two hands on the iliac part, two eyes of the testee look directly at the front target center, the testee keeps quiet in the test process, the body is upright as much as possible without random shaking, and the duration lasts for 20 seconds.
(2) Normally standing to close eyes: the feet of the testee stand on two sides of the central circle of the stress plate in parallel and opposite, the distance from the central line is 4cm., the two hands are placed on the iliac part, the two eyes are closed, the testee keeps quiet in the test process, the body is enabled to stand as much as possible without random shaking, and the duration is 20 seconds.
(3) Standing on one foot: the dominant foot arch of the testee stands on the central circle of the stress flat plate, the two hands are placed on the skeleton part, the non-dominant foot is lifted, the supporting leg cannot be relied on, the front target center is directly viewed by two eyes, the test is quiet, the body is kept upright as much as possible, the body is not required to shake randomly, and the test lasts for 30 seconds.
(4) Standing with eyes closed and feet open: the dominant foot arch of the testee stands on the central circle of the stress flat plate, the two hands are placed on the skeleton part, the non-dominant feet are lifted, the feet cannot lean on the supporting legs, the two eyes are closed, the rest is kept in the test process, the body is kept upright as much as possible, the body is not required to shake randomly, and the test lasts for 30 seconds. Note that all tests required close attention by the tester to prevent dizziness or falls by the subjects.
In addition, the method can also utilize a dynamic balancing instrument to carry out dynamic balancing capability test. Dynamic balance ability test instrument: the dynamic balancing instrument consists of a computer, an upper pedal, a lower pedal and a handrail, wherein the upper pedal and the lower pedal are connected with a sensor. Dynamic balance test principle: the test screen is divided into five annular areas, namely a central area, a first area, a second area, a third area and a fourth area from inside to outside, after the test is started, a red ball positioned in the central area moves due to different forces of two lower limbs of a subject, the small ball stays in the five different areas for 50ms and is recorded, different points are obtained at the same time, corresponding scores are obtained, and 30, 5, 2, 1 and 0 minutes are obtained when the small ball stays in the central area, the first area, the second area, the third area and the fourth area for 50 ms. The movement of the ball is controlled by the lower limbs of the testee, the ball is kept in the central area as much as possible, if the red ball has the tendency of sliding out of the central area, the testee judges in advance, and subjectively makes the foot exert force in the direction opposite to the moving direction of the small ball, so that the red ball returns to the central area as soon as possible, and the red ball is kept in the central area as much as possible, so as to obtain the score as high as possible. Testing indexes are as follows: maximum angular velocity, average angular velocity, percentage of time taken in front, middle, back, left, middle, and right zones to the total time tested by the tester, time of ball staying in the center zone, first zone, second zone, third zone, and fourth zone, and test result rating. The test method comprises the following steps: establishing and entering a system, double-clicking a starting icon, establishing the information of the subject at the department of department, storing the information including name, age, height, weight and sex, and selecting the subject. Then the testee takes off the shoes and socks, holds the handrail to stand at the fixed position on the upper pedal and the lower pedal connected with the sensor, and can stand stably by releasing the handrail, so that the testee can start the experiment by maintaining self balance and no dizziness. And clicking the starting setting, wherein a countdown is carried out for ten seconds at the beginning of the test on a computer display screen, when the countdown is 0, the testee releases the handrail, the red small ball positioned in the central area slides due to uneven exertion of the lower limbs, and the testee needs to keep the body stable and keep the body not to slide down from the upper pedal and the lower pedal on one hand, and needs to keep the small ball in the middle area as much as possible by coordinating exertion of the whole body to obtain the score as high as possible on the other hand. After the test experience of one minute is finished, the test time is changed into 1 minute for formal test under the same test mode and test difficulty, the experiment is finished, and the result is printed. Obtaining the test score of the subject, the maximum angular velocity and the average angular velocity of a rotating shaft between an upper pedal and a lower pedal, the staying time of the small balls in different areas and the staying time percentage of each area, printing a result after the test is finished, and manually inputting the result into an Excel table for analysis.
In an exemplary embodiment, when calculating the vital capacity index, height and weight index, body composition index or balance ability index of the target student, the method further comprises: the student physical health data are subjected to standardized processing, and the method comprises the following steps:
Figure BDA0003288737350000071
in the formula, XiThe ith physical fitness test contained in the student physical health data; xi，minThe minimum value of the ith physical fitness test contained in the student physical health data; xi，maxThe maximum value of the ith physical fitness test contained in the student physical health data; x'iAnd the normalized physical health data of the students are tested for the physical fitness of the ith item. According to the method, the student physical health data are subjected to standardized processing, so that a unified early warning standard can be conveniently established, and a school or a sports teacher can conveniently know the physical health states of all students in the current region. And meanwhile, the system also provides help for schools or sports teachers to establish standard sports schemes.
According to the records, the method further comprises the steps of obtaining vision test data of the target student at the current moment, comparing the vision test data of the target student at the current moment with the vision standard table, and when the vision test data of the target student is lower than 1.0 of the vision standard table, early warning and intervening are conducted on the target student. The method can protect the eyesight of the students in advance and avoid the shortsightedness of the students by early warning and intervening the eyesight of the students.
In an exemplary embodiment, before calculating the vital capacity index, height and weight index, body composition index and balance ability index of the target student according to the student physical health data, the method further comprises judging the reliability of the student physical health data, including: acquiring the physical health data of students in historical years and current years in a target area; determining data growth amplitudes of the target area in two adjacent historical years according to the acquired student physical health data; determining the data discrete degree of the target area in the same historical year according to the acquired student physical health data; acquiring the data growth amplitude and the data dispersion degree of the target area, and establishing a data reliability evaluation model according to the data growth amplitude and the data dispersion degree of the target area; and verifying the student physical health data of the target area in the current year by using the data credibility evaluation model, and determining the credibility of the student physical health data of the target area in the current year. In this embodiment, when the data reliability evaluation model is used to verify the student physical health data of the current year, if any one of the data growth amplitude and the data dispersion degree in the target region is abnormal, it is determined that the student physical health data of the target region in the current year is not reliable; if the data growth amplitude and the data dispersion degree in the target area are all abnormal, judging that the data reliability evaluation model is abnormal; and if the data increase amplitude and the data discrete degree in the target area are all normal, judging that the student physical health data of the target area in the current year is credible.
As a specific example, as shown in fig. 2, a data reliability evaluation model is constructed by taking a part of the fitness test item as an example. The evaluation indexes of the data reliability evaluation model comprise qualitative indexes and quantitative indexes, wherein the qualitative indexes comprise: data growth amplitude and data dispersion degree; the quantitative indexes are test items contained in the student physical health data. For example, the quantitative indicators of the data increase amplitude can be a height test, a weight test, a one-minute rope skipping test, a fifty-meter sprint test, a seat anteflexion test, a vital capacity test and the like; the quantitative indicators of the data dispersion degree can be a height test, a weight test, a one-minute rope skipping test, a fifty-meter sprint test, a seat forward bending test, a vital capacity test and the like.
And analyzing the physical health data of the students in 2019 and 2020 in the target area A to determine the data growth amplitude of the target area A. As an example, if the average height of all students in the target area a in 2019 is 1.20 meters, and the average height of all students in the target area a in 2020 is 1.32 meters, then the height growth range of the target area a is: (1.56-1.50) ÷ 1.50 × 100% ═ 10%. Similarly, the weight test data, the one-minute rope skipping test data, the fifty-meter sprint test data, the seat forward flexion test data and the vital capacity test data of all students in the target area a are respectively obtained, then the data growth amplitudes of the weight, the one-minute rope skipping, the fifty-meter sprint, the seat forward flexion and the vital capacity are respectively calculated, then a data set is formed according to the data growth amplitudes of the height, the weight, the one-minute rope skipping, the fifty-meter sprint, the seat forward flexion and the vital capacity, and the formed data set is used as the data growth amplitude of the target area a.
Calculating the standard deviation of height and weight of the M students in the 2020 th grade in the target area a, and forming a standard deviation distribution map of the corresponding height and weight according to the calculated values, as shown in fig. 3. As can be seen in fig. 3, the heights of the 2020 annual class M students in the target area a are between the intervals [4, 8] and are substantially near the value 6 at a plurality of values; the standard deviation of most of the weights is [4, 6], but the weights of the students in the grade M in the fifth school in the target area a exceed the value 12, which indicates that there may be errors or unreal data of the physical health of the students in the fifth school in the target area a, because the difference of the heights and weights of the children in the same age group is not so large. Similarly, the standard deviations of the one minute skipping rope, the fifty meter dash and the sitting posture forward flexion of the student at the 2020 year grade M in the target area a are calculated, and a corresponding standard deviation layout of the one minute skipping rope, the fifty meter dash and the sitting posture forward flexion is formed according to the calculated values, as shown in fig. 4. As can be seen from fig. 4, the standard deviation value distribution of one minute rope skipping, 50 meter running and seat forward flexion of students of grade M; wherein, the standard deviation range of the one minute rope skipping of the students of grade M is [10, 19], the standard deviation range of the 50 meter rope skipping of the students of grade M is [10, 20], and the standard deviation range of the forward bending of the sitting position of the students of grade M is [9, 13 ]. As can be seen from fig. 4, the 50 meters of the class M students in the twelfth and fifteenth schools in the target area a run more than 20, which indicates that there may be errors or unreal physical health data of the students in the twelfth and fifteenth schools in the target area a because the 50 meters of the children in the same age group do not run as much differently. In addition, if the forward flexion of the sitting position of the grade M students in the fifteenth school in the target area a exceeds the value 13, it indicates that there may be errors or unreal physical health data of the students in the fifteenth school in the target area a because the forward flexion of the sitting position of the students in the same age group is not so large. Therefore, the authenticity of the data can be measured according to the standard deviation range of the corresponding test item, if the data exceeds the standard deviation range, the corresponding data is unreasonable, and further, the student physical health data of the corresponding school is considered to be possibly wrong or unreal.
Therefore, the method can also begin to analyze based on the physical health data of students in the same batch of students in two adjacent years, and the growth amplitude of the students in certain measurement items is selected as a first measurement index; secondly, selecting the data discrete degree as another measuring index according to the consideration of the internal consistency reliability of the data in the same year, thereby establishing an evaluation model of the credibility of the evaluation data; and meanwhile, verifying the data reliability model by using the physical measurement data of the current year, verifying whether the data reliability model is reasonable and feasible, and judging whether the corresponding student physical health data is reliable.
In summary, the invention provides a student physical health data early warning and intervention method, which includes the steps of obtaining student physical health data of a target student, and then respectively calculating a vital capacity index, a height and weight index, a body composition index and a balance ability index of the target student according to the student physical health data; and comparing the vital capacity index, the height and body weight index, the body composition index and the balance ability index with corresponding preset standard indexes respectively, and if the vital capacity index, the height and body weight index, the body composition index and/or the balance ability index of the target student do not meet the preset standard indexes, early warning and intervening the target student. As the vital capacity of the human body, the highest oxygen absorption amount, the weight, the height, the body surface area, the chest circumference, the sitting height and the like are closely related, the method analyzes the student physical health data of the target student by utilizing the vital capacity index, and can objectively reflect the difference among different students, thereby facilitating the early warning and intervention of schools or physical education on students with poor physical health and helping the students to improve the physical quality. In addition, the obesity and the emaciation of the student directly influence the physical health level, and one standard for measuring the obesity and the emaciation of the individual is the body height Body Mass Index (BMI), and the fat and the emaciation level of the individual can be known according to the BMI value, so the method can assist a school or sports teacher to further control the obesity rate and the overweight rate of the student by analyzing the body height Body Mass Index (BMI), and assist the school or sports teacher to early warn and intervene the students which may be overweight or obese in advance. Meanwhile, the body composition comprises internal indexes related to physical health level, such as bone density, muscles and the like, so that the existing level and balance and coordination capacity of each index in the body of the tested person can be reflected, and the balance capacity is obtained by analyzing the individual balance capacity condition through the completion result of a given action. When the two indexes of the body composition and the balance ability of a certain student are too low, early warning and intervention are needed to assist the student to carry out targeted exercise, and the physical health level of the student is improved. Therefore, by analyzing the student physical health data, the method can not only make an individual exercise scheme for students, adjust exercise habits and make up for the short health board to provide reliable support; the analysis result of the method also helps education administrative departments, schools, sports teachers and student parents to know the physical conditions of students in time, provides scientific basis for performing exercise intervention on the students in the later period, and achieves the purpose of improving the physical and health conditions.
As shown in fig. 5, the present invention further provides a student physical health data early warning and intervention system, which comprises:
the data acquisition module M10 is used for acquiring student physical health data of a target student;
the index calculation module M20 is used for calculating the vital capacity index, the height and weight index, the body composition index and the balance ability index of the target student according to the student physical health data;
the data comparison module M30 is used for comparing the vital capacity index, the height and weight index, the body composition index and the balance ability index with corresponding preset standard indexes respectively;
and the early warning and intervention module M40 is used for early warning and intervening the target students when the vital capacity index, the height and weight index, the body composition index and/or the balance ability index of the target students do not meet the preset standard index.
Because the vital capacity and the highest oxygen absorption capacity of the human body are closely related to the weight, the height, the body surface area, the chest circumference, the sitting height and the like, the system analyzes the student physical health data of the target student by utilizing the vital capacity index, and can objectively reflect the difference among different students, thereby facilitating the early warning and intervention of schools or physical education on students with poor physical health and helping the students to improve the physical quality. In addition, the obesity of the individual student directly affects the physical health level, and one standard for measuring the obesity of the individual is the body height Body Mass Index (BMI), and the fat-lean level of the individual body can be known according to the BMI value, so the system can assist the school or sports teacher to further control the obesity rate and the overweight rate of the student by analyzing the body height Body Mass Index (BMI), and assist the school or sports teacher to early warn and intervene in advance for the students who may be overweight or obese. Meanwhile, the body composition comprises internal indexes related to physical health level, such as bone density, muscles and the like, so that the existing level and balance and coordination capacity of each index in the body of the tested person can be reflected, and the balance capacity is obtained by analyzing the individual balance capacity condition through the completion result of a given action. When the two indexes of the body composition and the balance ability of a certain student are too low, early warning and intervention are needed to assist the student to carry out targeted exercise, and the physical health level of the student is improved. Wherein, the physical fitness test that student's physique health data in this system contained includes: height test, weight test, one minute rope skipping test, fifty meters sprint test, seat anteflexion test and vital capacity test.
According to the records, the system divides the early warning degree into three levels. For the body height and body weight index BMI, if the body height and body weight index of the target student is less than 18.5, performing first-level early warning on the target student; if the height and weight index of the target student is more than or equal to 24 and less than 26.9, performing second-stage early warning on the target student; and if the height and weight index of the target student is more than or equal to 27, performing third-level early warning on the target student. When the height and weight index of the target student is more than or equal to 27 and less than 29.9, marking the third-level early warning at the current moment as an obesity I-degree-class third-level early warning; and when the height and weight index of the target student is more than or equal to 30, recording the third-level early warning of the current moment as the third-level early warning of obesity class II. Therefore, as the obesity of the individual student directly affects the physical health level, and one standard for measuring the obesity of the individual is the body height Body Mass Index (BMI), and the fat-lean level of the individual body can be known according to the BMI value, the embodiment can assist the school or sports teacher to further control the obesity rate and the overweight rate of the student by analyzing the body height Body Mass Index (BMI), and assist the school or sports teacher to perform early warning and intervention on the student who may be overweight or obese in advance. The standard parameters corresponding to the BMI in the system are referred to as BMI parameters in national student physical health standards (revised 2014).
According to the above description, in the present system, the vital capacity index is the vital capacity of the student at the present time ÷ body weight; wherein the unit of vital capacity is milliliter and the unit of body weight is kilogram. The standard index corresponding to the lung capacity index in the system is calculated from the standard lung capacity and the standard body weight in national student physical health standards (revised 2014). In the system, the body composition index can be obtained by a body composition analyzer, and the standard index corresponding to the body composition index refers to the body composition analyzer. Wherein, the body composition index comprises: metabolic rate, moisture content, body fat rate, waist-hip ratio, muscle content, etc. In the present system, the balance capability index includes a static balance capability index and a dynamic balance capability index. Wherein, the static balance capability test comprises: standing normally to open eyes, standing normally to close eyes, standing on one foot with one eye closed; the dynamic balance capability test comprises the following steps: score, maximum angular velocity, average angular velocity, percentage of time in front, middle, back, left, middle, and right zones to the total time tested by the tester, time of ball stay in the center zone, zones 1, 2, 3, and 4, and test result rating. The system can utilize the static balancing instrument to carry out static balancing capability test, in order to ensure that a testee is not interfered, the static balancing instrument is placed in a quiet space with moderate light and no noise, a cross is placed at a position 1.50 meters in front of the center of a stress flat plate of the balancing instrument and 1.70 meters in height, and the target center is clear and easy to see. The method for testing the static balance capability by using the static balance instrument comprises the following steps:
(1) normal standing and eye opening: the feet of the testee stand on two sides of the central circle of the stress plate in parallel and opposite, the distance from the central line is 4cm., the testee puts two hands on the iliac part, two eyes of the testee look directly at the front target center, the testee keeps quiet in the test process, the body is upright as much as possible without random shaking, and the duration lasts for 20 seconds.
(2) Normally standing to close eyes: the feet of the testee stand on two sides of the central circle of the stress plate in parallel and opposite, the distance from the central line is 4cm., the two hands are placed on the iliac part, the two eyes are closed, the testee keeps quiet in the test process, the body is enabled to stand as much as possible without random shaking, and the duration is 20 seconds.
(3) Standing on one foot: the dominant foot arch of the testee stands on the central circle of the stress flat plate, the two hands are placed on the skeleton part, the non-dominant foot is lifted, the supporting leg cannot be relied on, the front target center is directly viewed by two eyes, the test is quiet, the body is kept upright as much as possible, the body is not required to shake randomly, and the test lasts for 30 seconds.
(4) Standing with eyes closed and feet open: the dominant foot arch of the testee stands on the central circle of the stress flat plate, the two hands are placed on the skeleton part, the non-dominant feet are lifted, the feet cannot lean on the supporting legs, the two eyes are closed, the rest is kept in the test process, the body is kept upright as much as possible, the body is not required to shake randomly, and the test lasts for 30 seconds. Note that all tests required close attention by the tester to prevent dizziness or falls by the subjects.
In addition, the system can also utilize the dynamic balancing instrument to carry out dynamic balancing capability test. Dynamic balance ability test instrument: the dynamic balancing instrument consists of a computer, an upper pedal, a lower pedal and a handrail, wherein the upper pedal and the lower pedal are connected with a sensor. Dynamic balance test principle: the test screen is divided into five annular areas, namely a central area, a first area, a second area, a third area and a fourth area from inside to outside, after the test is started, a red ball positioned in the central area moves due to different forces of two lower limbs of a subject, the small ball stays in the five different areas for 50ms and is recorded, different points are obtained at the same time, corresponding scores are obtained, and 30, 5, 2, 1 and 0 minutes are obtained when the small ball stays in the central area, the first area, the second area, the third area and the fourth area for 50 ms. The movement of the ball is controlled by the lower limbs of the testee, the ball is kept in the central area as much as possible, if the red ball has the tendency of sliding out of the central area, the testee judges in advance, and subjectively makes the foot exert force in the direction opposite to the moving direction of the small ball, so that the red ball returns to the central area as soon as possible, and the red ball is kept in the central area as much as possible, so as to obtain the score as high as possible. Testing indexes are as follows: maximum angular velocity, average angular velocity, percentage of time taken in front, middle, back, left, middle, and right zones to the total time tested by the tester, time of ball staying in the center zone, first zone, second zone, third zone, and fourth zone, and test result rating. The test method comprises the following steps: establishing and entering a system, double-clicking a starting icon, establishing the information of the subject at the department of department, storing the information including name, age, height, weight and sex, and selecting the subject. Then the testee takes off the shoes and socks, holds the handrail to stand at the fixed position on the upper pedal and the lower pedal connected with the sensor, and can stand stably by releasing the handrail, so that the testee can start the experiment by maintaining self balance and no dizziness. And clicking the starting setting, wherein a countdown is carried out for ten seconds at the beginning of the test on a computer display screen, when the countdown is 0, the testee releases the handrail, the red small ball positioned in the central area slides due to uneven exertion of the lower limbs, and the testee needs to keep the body stable and keep the body not to slide down from the upper pedal and the lower pedal on one hand, and needs to keep the small ball in the middle area as much as possible by coordinating exertion of the whole body to obtain the score as high as possible on the other hand. After the test experience of one minute is finished, the test time is changed into 1 minute for formal test under the same test mode and test difficulty, the experiment is finished, and the result is printed. Obtaining the test score of the subject, the maximum angular velocity and the average angular velocity of a rotating shaft between an upper pedal and a lower pedal, the staying time of the small balls in different areas and the staying time percentage of each area, printing a result after the test is finished, and manually inputting the result into an Excel table for analysis.
In an exemplary embodiment, when calculating the vital capacity index, height and weight index, body composition index or balance ability index of the target student, the method further comprises: the student physical health data are subjected to standardized processing, and the method comprises the following steps:
Figure BDA0003288737350000121
in the formula, XiThe ith physical fitness test contained in the student physical health data; xi，minThe minimum value of the ith physical fitness test contained in the student physical health data; xi，maxThe maximum value of the ith physical fitness test contained in the student physical health data; x'iAnd the normalized physical health data of the students are tested for the physical fitness of the ith item. The system can conveniently establish a unified early warning standard by carrying out standardized processing on the physical health data of the students, and is convenient for schools or sports teachers to know the physical health states of all students in the current region. And meanwhile, the system also provides help for schools or sports teachers to establish standard sports schemes.
According to the above, the system further comprises: the vision comparison module M50 is used for acquiring the vision test data of the target student at the current moment and comparing the vision test data of the target student at the current moment with the vision standard table; and when the vision test data of the target students are lower than 1.0 in the vision standard table, early warning and intervention are carried out on the target students. The system can protect the eyesight of the students in advance by early warning and intervening the eyesight of the students and avoid the shortsightedness of the students.
In an exemplary embodiment, before calculating the vital capacity index, height and weight index, body composition index and balance ability index of the target student according to the student physical health data, the method further comprises judging the reliability of the student physical health data, including: acquiring the physical health data of students in historical years and current years in a target area; determining data growth amplitudes of the target area in two adjacent historical years according to the acquired student physical health data; determining the data discrete degree of the target area in the same historical year according to the acquired student physical health data; acquiring the data growth amplitude and the data dispersion degree of the target area, and establishing a data reliability evaluation model according to the data growth amplitude and the data dispersion degree of the target area; and verifying the student physical health data of the target area in the current year by using the data credibility evaluation model, and determining the credibility of the student physical health data of the target area in the current year. In this embodiment, when the data reliability evaluation model is used to verify the student physical health data of the current year, if any one of the data growth amplitude and the data dispersion degree in the target region is abnormal, it is determined that the student physical health data of the target region in the current year is not reliable; if the data growth amplitude and the data dispersion degree in the target area are all abnormal, judging that the data reliability evaluation model is abnormal; and if the data increase amplitude and the data discrete degree in the target area are all normal, judging that the student physical health data of the target area in the current year is credible.
As a specific example, as shown in fig. 2, a data reliability evaluation model is constructed by taking a part of the fitness test item as an example. The evaluation indexes of the data reliability evaluation model comprise qualitative indexes and quantitative indexes, wherein the qualitative indexes comprise: data growth amplitude and data dispersion degree; the quantitative indexes are test items contained in the student physical health data. For example, the quantitative indicators of the data increase amplitude can be a height test, a weight test, a one-minute rope skipping test, a fifty-meter sprint test, a seat anteflexion test, a vital capacity test and the like; the quantitative indicators of the data dispersion degree can be a height test, a weight test, a one-minute rope skipping test, a fifty-meter sprint test, a seat forward bending test, a vital capacity test and the like.
And analyzing the physical health data of the students in 2019 and 2020 in the target area A to determine the data growth amplitude of the target area A. As an example, if the average height of all students in the target area a in 2019 is 1.20 meters, and the average height of all students in the target area a in 2020 is 1.32 meters, then the height growth range of the target area a is: (1.56-1.50) ÷ 1.50 × 100% ═ 10%. Similarly, the weight test data, the one-minute rope skipping test data, the fifty-meter sprint test data, the seat forward flexion test data and the vital capacity test data of all students in the target area a are respectively obtained, then the data growth amplitudes of the weight, the one-minute rope skipping, the fifty-meter sprint, the seat forward flexion and the vital capacity are respectively calculated, then a data set is formed according to the data growth amplitudes of the height, the weight, the one-minute rope skipping, the fifty-meter sprint, the seat forward flexion and the vital capacity, and the formed data set is used as the data growth amplitude of the target area a.
Calculating the standard deviation of height and weight of the M students in the 2020 th grade in the target area a, and forming a standard deviation distribution map of the corresponding height and weight according to the calculated values, as shown in fig. 3. As can be seen in fig. 3, the heights of the 2020 annual class M students in the target area a are between the intervals [4, 8] and are substantially near the value 6 at a plurality of values; the standard deviation of most of the weights is [4, 6], but the weights of the students in the grade M in the fifth school in the target area a exceed the value 12, which indicates that there may be errors or unreal data of the physical health of the students in the fifth school in the target area a, because the difference of the heights and weights of the children in the same age group is not so large. Similarly, the standard deviations of the one minute skipping rope, the fifty meter dash and the sitting posture forward flexion of the student at the 2020 year grade M in the target area a are calculated, and a corresponding standard deviation layout of the one minute skipping rope, the fifty meter dash and the sitting posture forward flexion is formed according to the calculated values, as shown in fig. 4. As can be seen from fig. 4, the standard deviation value distribution of one minute rope skipping, 50 meter running and seat forward flexion of students of grade M; wherein, the standard deviation range of the one minute rope skipping of the students of grade M is [10, 19], the standard deviation range of the 50 meter rope skipping of the students of grade M is [10, 20], and the standard deviation range of the forward bending of the sitting position of the students of grade M is [9, 13 ]. As can be seen from fig. 4, the 50 meters of the class M students in the twelfth and fifteenth schools in the target area a run more than 20, which indicates that there may be errors or unreal physical health data of the students in the twelfth and fifteenth schools in the target area a because the 50 meters of the children in the same age group do not run as much differently. In addition, if the forward flexion of the sitting position of the grade M students in the fifteenth school in the target area a exceeds the value 13, it indicates that there may be errors or unreal physical health data of the students in the fifteenth school in the target area a because the forward flexion of the sitting position of the students in the same age group is not so large. Therefore, the authenticity of the data can be measured according to the standard deviation range of the corresponding test item, if the data exceeds the standard deviation range, the corresponding data is unreasonable, and further, the student physical health data of the corresponding school is considered to be possibly wrong or unreal.
Therefore, the system can start analysis based on the physical health data of students in two adjacent years of the same batch of students, and the growth amplitude of the students in certain measurement items is selected as a first measurement index; secondly, selecting the data discrete degree as another measuring index according to the consideration of the internal consistency reliability of the data in the same year, thereby establishing an evaluation model of the credibility of the evaluation data; and meanwhile, verifying the data reliability model by using the physical measurement data of the current year, verifying whether the data reliability model is reasonable and feasible, and judging whether the corresponding student physical health data is reliable.
In summary, the invention provides a student physical health data early warning and intervention method, which includes the steps of obtaining student physical health data of a target student, and then respectively calculating a vital capacity index, a height and weight index, a body composition index and a balance ability index of the target student according to the student physical health data; and comparing the vital capacity index, the height and body weight index, the body composition index and the balance ability index with corresponding preset standard indexes respectively, and if the vital capacity index, the height and body weight index, the body composition index and/or the balance ability index of the target student do not meet the preset standard indexes, early warning and intervening the target student. Because the vital capacity and the highest oxygen absorption capacity of the human body are closely related to the weight, the height, the body surface area, the chest circumference, the sitting height and the like, the system analyzes the student physical health data of the target student by utilizing the vital capacity index, and can objectively reflect the difference among different students, thereby facilitating the early warning and intervention of schools or physical education on students with poor physical health and helping the students to improve the physical quality. In addition, the obesity of the individual student directly affects the physical health level, and one standard for measuring the obesity of the individual is the body height Body Mass Index (BMI), and the fat-lean level of the individual body can be known according to the BMI value, so the system can assist the school or sports teacher to further control the obesity rate and the overweight rate of the student by analyzing the body height Body Mass Index (BMI), and assist the school or sports teacher to early warn and intervene in advance for the students who may be overweight or obese. Meanwhile, the body composition comprises internal indexes related to physical health level, such as bone density, muscles and the like, so that the existing level and balance and coordination capacity of each index in the body of the tested person can be reflected, and the balance capacity is obtained by analyzing the individual balance capacity condition through the completion result of a given action. When the two indexes of the body composition and the balance ability of a certain student are too low, early warning and intervention are needed to assist the student to carry out targeted exercise, and the physical health level of the student is improved. Therefore, the system can not only make an individual exercise scheme for students, adjust exercise habits and make up for the short health board to provide reliable support by analyzing the physical health data of the students; and the analysis result of the system also helps education administrative department, school, sports teacher and parents of students to know the physical conditions of students in time, so that scientific basis is provided for the later exercise intervention of the students, and the purpose of improving the physical health conditions is achieved. In conclusion, the present invention effectively overcomes various disadvantages of the prior art and has high industrial utilization value.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.

Claims (10)

1. A student physical health data early warning and intervention method is characterized by comprising the following steps:
acquiring student physical health data of a target student;
respectively calculating a vital capacity index, a height and weight index, a body composition index and a balance ability index of the target student according to the student physical health data;
and comparing the vital capacity index, the height and body weight index, the body composition index and the balance ability index with corresponding preset standard indexes respectively, and if the vital capacity index, the height and body weight index, the body composition index and/or the balance ability index of the target student do not meet the preset standard indexes, early warning and intervening the target student.
2. The student physical health data early warning and intervention method of claim 1, wherein the early warning comprises a tertiary early warning;
if the height and weight index of the target student is less than 18.5, performing first-level early warning on the target student;
if the height and weight index of the target student is more than or equal to 24 and less than 26.9, performing second-stage early warning on the target student;
and if the height and weight index of the target student is more than or equal to 27, performing third-level early warning on the target student.
3. The student physical health data early warning and intervention method as claimed in claim 2, further comprising marking a third-level early warning at the current time as a third-level early warning of obesity class I when the height-weight index of the target student is greater than or equal to 27 and less than 29.9; and the number of the first and second groups,
and when the height and body weight index of the target student is more than or equal to 30, recording the third-level early warning at the current moment as the obesity II-degree third-level early warning.
4. The student physical health data early warning and intervention method as claimed in claim 1, further comprising, when calculating the vital capacity index, height and weight index, body composition index or balance ability index of the target student:
the student physical health data are subjected to standardized processing, and the method comprises the following steps:
Figure FDA0003288737340000011
in the formula, XiThe ith physical fitness test contained in the student physical health data;
Xi，minthe minimum value of the ith physical fitness test contained in the student physical health data;
Xi，maxthe maximum value of the ith physical fitness test contained in the student physical health data;
X′iand the normalized physical health data of the students are tested for the physical fitness of the ith item.
5. The student physical health data early warning and intervention method of claim 1, wherein the physical fitness tests included in the student physical health data comprise: height test, weight test, one minute rope skipping test, fifty meters sprint test, seat anteflexion test and vital capacity test.
6. The student physical health data early warning and intervening method as claimed in claim 1, further comprising obtaining vision test data of the target student at the current time, comparing the vision test data of the target student at the current time with the vision standard table, and performing early warning and intervening on the target student when the vision test data of the target student is lower than 1.0 in the vision standard table.
7. The student physical health data early warning and intervention method as claimed in claim 1, wherein before calculating the vital capacity index, height and weight index, body composition index and balance ability index of the target student according to the student physical health data, the method further comprises determining the reliability of the student physical health data, and comprises:
acquiring the physical health data of students in historical years and current years in a target area;
determining data growth amplitudes of the target area in two adjacent historical years according to the acquired student physical health data;
determining the data discrete degree of the target area in the same historical year according to the acquired student physical health data;
acquiring the data growth amplitude and the data dispersion degree of the target area, and establishing a data reliability evaluation model according to the data growth amplitude and the data dispersion degree of the target area;
and verifying the student physical health data of the target area in the current year by using the data credibility evaluation model, and determining the credibility of the student physical health data of the target area in the current year.
8. The student physical health data early warning and intervention method of claim 7, wherein when the data credibility evaluation model is used to verify the student physical health data of the current year,
if any one of the data increase amplitude and the data discrete degree in the target area is abnormal, judging that the student physical health data of the target area in the current year is not credible;
if the data growth amplitude and the data dispersion degree in the target area are all abnormal, judging that the data reliability evaluation model is abnormal;
and if the data increase amplitude and the data discrete degree in the target area are all normal, judging that the student physical health data of the target area in the current year is credible.
9. The utility model provides a student's physique health data early warning and intervention system which characterized in that, the system including:
the data acquisition module is used for acquiring student physical health data of a target student;
the index calculation module is used for calculating the vital capacity index, the height and weight index, the body composition index and the balance ability index of the target student according to the student physical health data;
the data comparison module is used for comparing the vital capacity index, the height and weight index, the body composition index and the balance ability index with corresponding preset standard indexes respectively;
and the early warning and intervention module is used for early warning and intervening the target students when the vital capacity index, the height and weight index, the body composition index and/or the balance ability index of the target students do not meet the preset standard index.
10. The student physical health data early warning and intervention system of claim 9, further comprising:
the vision comparison module is used for acquiring vision test data of the target student at the current moment and comparing the vision test data of the target student at the current moment with the vision standard table; and when the vision test data of the target students are lower than 1.0 in the vision standard table, early warning and intervention are carried out on the target students.
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CN115860537A (en) * 2022-11-30 2023-03-28 杭州光海科技有限公司 Campus card based physique test system and method
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