Teenager growth and development level evaluation method and system based on multi-factor conditions

Abstract

The invention relates to a teenager growth and development level evaluation method and system based on multi-factor conditions, and belongs to the field of growth and development detection. The method comprises the following steps: obtaining teenager height data, and obtaining teenager height development level based on the teenager height data; juvenile growth and development information is obtained, a juvenile growth and development prediction model is constructed according to the juvenile growth and development information, and the juvenile growth and development prediction model comprises a juvenile height prediction model and a juvenile growth level prediction model; and outputting teenager growth and development prediction results based on the teenager growth and development prediction model, wherein the teenager growth and development prediction results comprise a good expected result, a normal expected result and an unfavorable expected result. According to the invention, the growth and development level of the teenagers can be evaluated scientifically, reasonably and comprehensively, and the adult height of the teenagers can be predicted.

Description

Technical Field

[0001] The present invention belongs to the technical field of growth and development detection, and specifically relates to a method and system for evaluating the growth and development level of adolescents based on multi-factor conditions. Background Art

[0002] By evaluating the growth and development of adolescents, we can summarize and study the laws and characteristics of adolescent growth and development, put forward the key points of health care work, and promote the healthy development of adolescents. By measuring the growth and development of adolescents on a large scale, we can formulate normal values ​​or evaluation standards for adolescent growth and development in countries and regions, and provide a basis for the government to formulate policies and measures for adolescent health care. We can also timely understand the development level and speed of adolescents, carry out targeted health care work, and promptly identify problems and implement health care interventions. The current evaluation methods for adolescent growth and development levels have relatively single evaluation factors, and the prediction of adolescent height and development level is not comprehensive enough, resulting in the inability to intervene in early abnormal development that may occur in adolescents. Summary of the invention

[0003] In order to solve the above problems existing in the prior art, the present invention provides a method and system for evaluating the growth and development level of adolescents based on multi-factor conditions.

[0004] The purpose of the present invention can be achieved through the following technical solutions:

[0005] A method for evaluating the growth and development level of adolescents based on multi-factor conditions, the implementation of the method for evaluating the growth and development level of adolescents comprising the following steps:

[0006] Acquire the height data of the adolescents, and obtain the height development level of the adolescents based on the height data of the adolescents, wherein the height development level of the adolescents includes upper height development, upper-middle height development, middle height development, lower-middle height development, and lower height development;

[0007] Acquire adolescent growth and development information, and construct an adolescent growth and development prediction model based on the adolescent growth and development information, wherein the adolescent growth and development information includes the adolescent age, adolescent gender, adolescent weight, adolescent sitting height, adolescent father height, and adolescent mother height, and the adolescent growth and development prediction model includes an adolescent height prediction model and an adolescent growth level prediction model;

[0008] Based on the adolescent growth and development prediction model, the adolescent growth and development prediction results are output, and the adolescent growth and development prediction results include good expected results, normal expected results and unfavorable expected results.

[0009] Preferably, constructing a prediction model for adolescent growth and development based on the adolescent growth and development information includes:

[0010] Constructing the adolescent height prediction model based on the adolescent bone age, the adolescent sleeping posture and the adolescent growth and development information;

[0011] The adolescent growth level prediction model is constructed based on the adolescent maturity deviation.

[0012] Preferably, the constructing of the adolescent height prediction model based on the adolescent bone age, the adolescent sleeping posture and the adolescent growth and development information comprises:

[0013] Obtain an X-ray of the wrist bones of the adolescent, obtain the adolescent's bone age based on the X-ray of the wrist bones of the adolescent, and obtain the adolescent's bone age-predicted height based on the adolescent's bone age;

[0014] Calculating the genetically predicted height of the adolescent based on the height of the adolescent's father, the height of the adolescent's mother, and the adolescent's gender;

[0015] Based on the improved sleeping posture recognition method, the sleeping posture of the teenager is obtained, and the sleeping posture standard of the teenager is obtained according to the sleeping posture of the teenager;

[0016] Based on the adolescent's predicted height by bone age, the adolescent's predicted height by genetics and the adolescent's sleeping posture standard, the adolescent's comprehensive predicted height is calculated and the adolescent's height prediction model is constructed.

[0017] Preferably, the adolescent maturity offset is calculated based on the adolescent sitting height, the adolescent height data, the adolescent weight and the adolescent age.

[0018] Preferably, obtaining the adolescent's bone age based on the adolescent's wrist bone X-ray, and obtaining the adolescent's bone age-predicted height according to the adolescent's bone age includes:

[0019] Based on the X-ray film of the adolescent wrist bones, the adolescent wrist bones are divided into radius, metacarpal Ⅰ, metacarpal Ⅲ, metacarpal Ⅴ, proximal phalanx Ⅰ, proximal phalanx Ⅲ, proximal phalanx Ⅴ, middle phalanx Ⅲ, middle phalanx Ⅴ, distal phalanx Ⅰ, distal phalanx Ⅲ, distal phalanx Ⅴ, capitate, and hamate;

[0020] The radius is divided into 10 bone age grades, the capitate is divided into 7 bone age grades, the metacarpal I, metacarpal III, metacarpal V, proximal phalanx I, proximal phalanx III, proximal phalanx V, middle phalanx III, middle phalanx V, distal phalanx I, distal phalanx III, distal phalanx V, and hamate are divided into 8 bone age grades respectively;

[0021] According to the gender of the adolescent and the wrist bones of the adolescent, a bone age score is assigned to each bone age grade and a total bone development score is obtained, wherein the total bone development score is the sum of all the bone age scores;

[0022] Obtaining the adolescent's bone age based on the total bone development score and the adolescent's gender;

[0023] The age difference is obtained according to the difference between the adolescent bone age and the adolescent age, and the adolescent development status is obtained based on the age difference. When the age difference is (-1, 1), the adolescent development status is normal; when the age difference is greater than or equal to 1, the adolescent development status is early development; when the age difference is less than or equal to -1, the adolescent development status is late development;

[0024] Obtaining an adult height percentile based on the adolescent's gender, the adolescent's bone age, and the adolescent's developmental status;

[0025] The adolescent's bone age-predicted height is calculated based on the adult height percentage.

[0026] Preferably, the step of obtaining the adolescent's sleeping posture based on the improved sleeping posture recognition method and obtaining the adolescent's sleeping posture standard according to the adolescent's sleeping posture comprises:

[0027] A sleep monitoring cycle is preset, and a pressure simulation value is obtained through a pressure sensor based on the sleep monitoring cycle. The pressure sensor includes a first pressure sensor, a second pressure sensor, and a third pressure sensor. The first pressure sensor is arranged in the left area below the human body during sleep, the second pressure sensor is arranged in the middle area below the human body during sleep, and the third pressure sensor is arranged in the right area below the human body during sleep. The pressure simulation value is the pressure value of the jth pressure sensor in the i-th sleep monitoring cycle, where j=1, 2, 3;

[0028] Calculating a resistance value based on the pressure simulation value;

[0029] Calculating a resistance average based on the resistance value;

[0030] The teenager's sleeping position and the teenager's sleeping position standard are obtained based on the average resistance value. When the average resistance value of the first pressure sensor is the smallest, the teenager's sleeping position is lying on the left side, and the teenager's sleeping position standard is 0.993. When the average resistance value of the second pressure sensor is the smallest, the teenager's sleeping position is lying flat on the back, and the teenager's sleeping position standard is 1. When the average resistance value of the third pressure sensor is the smallest, the teenager's sleeping position is lying on the right side, and the teenager's sleeping position standard is 0.992.

[0031] Preferably, the outputting of the adolescent growth and development prediction results based on the adolescent growth and development prediction model includes:

[0032] Obtaining the local average height, wherein the local average height includes the local average height of females and the local average height of males, and presetting a youth maturity deviation threshold, wherein the youth maturity deviation threshold includes a female youth maturity deviation threshold and a male youth maturity deviation threshold;

[0033] When the comprehensive predicted height of the teenager is greater than or equal to the local average height and the teenager's maturity deviation is greater than or equal to the teenager's maturity deviation threshold, the good expected result is output; when the comprehensive predicted height of the teenager is greater than or equal to the local average height and the teenager's maturity deviation is less than the teenager's maturity deviation threshold, the normal expected result is output; when the comprehensive predicted height of the teenager is less than the local average height and the teenager's maturity deviation is greater than or equal to the teenager's maturity deviation threshold, the normal expected result is output; when the comprehensive predicted height of the teenager is less than the local average height and the teenager's maturity deviation is less than the teenager's maturity deviation threshold, the unfavorable expected result is output.

[0034] A method and system for evaluating the growth and development level of adolescents based on multi-factor conditions, which is used to implement the above-mentioned method for evaluating the growth and development level of adolescents, including a data acquisition module, a model building module, and a growth and development prediction module;

[0035] The data acquisition module is used to acquire the height data of teenagers, and obtain the height development level of teenagers based on the height data of teenagers, wherein the height development level of teenagers includes upper height development, upper-middle height development, middle height development, lower-middle height development, and lower height development;

[0036] The model building module is used to obtain adolescent growth and development information, and to build an adolescent growth and development prediction model based on the adolescent growth and development information, wherein the adolescent growth and development information includes the adolescent age, adolescent gender, adolescent weight, adolescent sitting height, adolescent father height, and adolescent mother height, and the adolescent growth and development prediction model includes an adolescent height prediction model and an adolescent growth level prediction model;

[0037] The growth and development prediction module is used to output adolescent growth and development prediction results based on the adolescent growth and development prediction model, and the adolescent growth and development prediction results include good expected results, normal expected results and unfavorable expected results.

[0038] An electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the above-mentioned method for evaluating the growth and development level of adolescents is implemented.

[0039] A storage medium containing computer executable instructions, which are used to execute the above-mentioned method for evaluating the growth and development level of adolescents when executed by a computer processor.

[0040] The beneficial effects of the present invention are:

[0041] (1) Through the adolescent height data and adolescent growth and development information, the adolescent bone age, adolescent sleeping position and adolescent maturity deviation are obtained, and an adolescent growth and development prediction model is constructed, so as to evaluate the multi-factor adolescent growth and development level assessment method and comprehensively predict the adolescent height and development level, which is conducive to early intervention of possible abnormal development of adolescents;

[0042] (2) The bone age of adolescents can be obtained through wrist bone X-rays, which is convenient for statistical analysis and can achieve the goals of being fast, efficient and accurate;

[0043] (3) Based on the improved sleeping posture recognition method, the sleeping posture of adolescents is obtained and the sleeping posture standard of adolescents is obtained according to the sleeping posture of adolescents, and the possible impact of sleeping posture on the growth and development of adolescents is comprehensively considered;

[0044] (4) The adolescent maturity deviation degree can be used to comprehensively evaluate the adolescent growth level. The adolescent maturity deviation degree can assess the distance between the adolescent and the peak age of growth spurt, which is helpful in judging whether the adolescent still has the potential to continue to develop. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0046] Figure 1 The present invention is a flowchart of the steps of a method for evaluating the growth and development level of adolescents based on multiple factors. DETAILED DESCRIPTION

[0047] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0048] The working principle and use process of the present invention:

[0049] See also Figure 1 , a method for evaluating the growth and development level of adolescents based on multiple factors, including:

[0050] S1: Obtain the height data of adolescents, and obtain the height development level of adolescents based on the "Evaluation of Height Development Levels of Children and Adolescents Aged 7 to 18" (WS / T612-2018), which includes upper height development, upper-middle height development, middle height development, lower-middle height development, and lower height development;

[0051] S2: Acquire adolescent growth and development information, and construct an adolescent growth and development prediction model based on the adolescent growth and development information, wherein the adolescent growth and development information includes the adolescent age, adolescent gender, adolescent weight, adolescent sitting height, adolescent father height, and adolescent mother height, and the adolescent growth and development prediction model includes an adolescent height prediction model and an adolescent growth level prediction model;

[0052] S3: Outputting adolescent growth and development prediction results based on the adolescent growth and development prediction model, wherein the adolescent growth and development prediction results include good expected results, normal expected results and unfavorable expected results.

[0053] In this embodiment, a prediction model for adolescent growth and development is constructed based on the adolescent growth and development information, which can be implemented by the following steps:

[0054] S201: constructing the adolescent height prediction model based on the adolescent bone age, the adolescent sleeping posture and the adolescent growth and development information;

[0055] S202: The adolescent growth level prediction model is constructed based on the adolescent maturity deviation degree. The adolescent maturity deviation degree can evaluate the distance between the adolescent and the peak age of growth spurt, which is helpful for judging whether the adolescent still has the potential for further development.

[0056] In this embodiment, the adolescent height prediction model is constructed based on the adolescent bone age, the adolescent sleeping position and the adolescent growth and development information, which can be implemented by the following steps:

[0057] S201-1: Obtain an X-ray of the wrist bones of the adolescent, obtain the adolescent's bone age based on the X-ray of the wrist bones of the adolescent, and obtain the adolescent's bone age-predicted height based on the adolescent's bone age, so as to facilitate statistical analysis and achieve the purpose of being fast, efficient and accurate;

[0058] S201-2: Calculate the adolescent's genetic predicted height based on the adolescent's father's height, the adolescent's mother's height, and the adolescent's gender, using the following formula: in, Genetic prediction of height for female adolescents, Genetic prediction of height for male adolescents, h f is the height of the father of the teenager, h m Height for teenage mothers;

[0059] S201-3: obtaining the sleeping posture of the teenager based on the improved sleeping posture recognition method and obtaining the sleeping posture standard of the teenager according to the sleeping posture of the teenager;

[0060] S201-4: Calculate the comprehensive predicted height of the adolescent based on the adolescent's bone age predicted height, the adolescent's genetic predicted height and the adolescent's sleeping posture standard and construct the adolescent's height prediction model. The calculation formula for the comprehensive predicted height of the adolescent is: Among them, h yw Comprehensive predicted height for female adolescents, h ym is the comprehensive predicted height of male adolescents, α is the standard sleeping posture of adolescents, and FH1 is the height predicted by the adolescent bone age.

[0061] In this embodiment, an X-ray film of the wrist bones of a teenager is obtained, the bone age of the teenager is obtained based on the X-ray film of the wrist bones of the teenager, and the height predicted by the bone age of the teenager is obtained according to the bone age of the teenager. Specifically, the following steps can be implemented:

[0062] Based on the X-ray film of the adolescent wrist bones, the adolescent wrist bones are divided into radius, metacarpal Ⅰ, metacarpal Ⅲ, metacarpal Ⅴ, proximal phalanx Ⅰ, proximal phalanx Ⅲ, proximal phalanx Ⅴ, middle phalanx Ⅲ, middle phalanx Ⅴ, distal phalanx Ⅰ, distal phalanx Ⅲ, distal phalanx Ⅴ, capitate, and hamate;

[0063] The radius is divided into 10 bone age grades, the capitate is divided into 7 bone age grades, the metacarpal I, metacarpal III, metacarpal V, proximal phalanx I, proximal phalanx III, proximal phalanx V, middle phalanx III, middle phalanx V, distal phalanx I, distal phalanx III, distal phalanx V, and hamate are divided into 8 bone age grades respectively;

[0064] Based on the Chinese Wrist Bone Development Standard (CHN Method), a bone age score is assigned to each bone age grade according to the gender of the adolescent and the wrist bone of the adolescent, and a total bone development score is obtained. The total bone development score is the sum of all the bone age scores;

[0065] Based on the total bone development score and the gender of the adolescent, the adolescent's bone age is obtained by comparing with the Chinese Wrist Bone Development Standard (CHN Method);

[0066] The age difference is obtained according to the difference between the adolescent bone age and the adolescent age, and the adolescent development status is obtained based on the age difference. When the age difference is (-1, 1), the adolescent development status is normal; when the age difference is greater than or equal to 1, the adolescent development status is early development; when the age difference is less than or equal to -1, the adolescent development status is late development;

[0067] Based on the gender of the adolescent, the bone age of the adolescent, and the developmental status of the adolescent, the percentage of adult height is obtained by comparing with the "Chinese Wrist Bone Development Standard CHN Method";

[0068] The adolescent bone age predicted height is calculated based on the percentage of the adult height, and the calculation formula is: Among them, FH1 is the predicted height of adolescents based on bone age, h is the height data of adolescents, and P is the percentage of adult height.

[0069] In this embodiment, the sleeping posture of the teenager is obtained based on the improved sleeping posture recognition method and the sleeping posture standard of the teenager is obtained according to the sleeping posture of the teenager, which can be specifically implemented by the following steps:

[0070] A sleep monitoring cycle is preset, and a pressure simulation value is obtained through a pressure sensor based on the sleep monitoring cycle. The pressure sensor includes a first pressure sensor, a second pressure sensor, and a third pressure sensor. The first pressure sensor is arranged in the left area below the human body during sleep, the second pressure sensor is arranged in the middle area below the human body during sleep, and the third pressure sensor is arranged in the right area below the human body during sleep. The pressure simulation value is the pressure value of the jth pressure sensor in the i-th sleep monitoring cycle, where j=1, 2, 3;

[0071] The resistance value is calculated based on the pressure simulation value, and the calculation formula is: in, is the resistance value of the jth pressure sensor in the i-th sleep monitoring cycle, R0 is the pull-up resistor, and its value is 1 kilo-ohm. is the pressure simulation value of the jth pressure sensor in the i-th sleep monitoring cycle;

[0072] The average resistance is calculated based on the resistance value, and the calculation formula is: Among them, R j is the average resistance of the jth pressure sensor, and I is the number of sleep monitoring cycles;

[0073] The teenager's sleeping position and the teenager's sleeping position standard are obtained based on the average resistance value. When the average resistance value of the first pressure sensor is the smallest, the teenager's sleeping position is lying on the left side, and the teenager's sleeping position standard is 0.993. When the average resistance value of the second pressure sensor is the smallest, the teenager's sleeping position is lying flat on the back, and the teenager's sleeping position standard is 1. When the average resistance value of the third pressure sensor is the smallest, the teenager's sleeping position is lying on the right side, and the teenager's sleeping position standard is 0.992.

[0074] In this embodiment, the adolescent growth level prediction model is constructed based on the adolescent maturity deviation, which can be implemented by the following steps:

[0075] The adolescent maturity deviation is calculated based on the adolescent sitting height, the adolescent height data, the adolescent weight and the adolescent age. The calculation formula is: Among them, θ w is the adolescent maturity offset of females, θ m is the adolescent maturity offset of males, age is the adolescent age, h Z is the sitting height of teenagers, G is the weight of teenagers, and h is the height data of teenagers.

[0076] In this embodiment, outputting the adolescent growth and development prediction results based on the adolescent growth and development prediction model can be implemented by the following steps:

[0077] Obtaining the local average height, the local average height being the average height of adults in the location of the adolescents undergoing growth and development level assessment, the local average height including the local average height of females and the local average height of males, and presetting the adolescent maturity deviation threshold, the adolescent maturity deviation threshold including the female adolescent maturity deviation threshold and the male adolescent maturity deviation threshold;

[0078] When the comprehensive predicted height of the teenager is greater than or equal to the local average height and the teenager's maturity deviation is greater than or equal to the teenager's maturity deviation threshold, the good expected result is output; when the comprehensive predicted height of the teenager is greater than or equal to the local average height and the teenager's maturity deviation is less than the teenager's maturity deviation threshold, the normal expected result is output; when the comprehensive predicted height of the teenager is less than the local average height and the teenager's maturity deviation is greater than or equal to the teenager's maturity deviation threshold, the normal expected result is output; when the comprehensive predicted height of the teenager is less than the local average height and the teenager's maturity deviation is less than the teenager's maturity deviation threshold, the unfavorable expected result is output.

[0079] A system for evaluating the growth and development level of adolescents based on multi-factor conditions, comprising a data acquisition module, a model building module, and a growth and development prediction module;

[0080] The data acquisition module is used to obtain the height data of adolescents, and obtain the height development level of adolescents based on the "Evaluation of Height Development Levels of Children and Adolescents Aged 7 to 18" (WS / T 612-2018), wherein the height development level of adolescents includes upper height development, upper-middle height development, middle height development, lower-middle height development, and lower height development;

[0081] The model building module is used to obtain adolescent growth and development information, and to build an adolescent growth and development prediction model based on the adolescent growth and development information, wherein the adolescent growth and development information includes the adolescent age, adolescent gender, adolescent weight, adolescent sitting height, adolescent father height, and adolescent mother height, and the adolescent growth and development prediction model includes an adolescent height prediction model and an adolescent growth level prediction model;

[0082] The growth and development prediction module is used to output adolescent growth and development prediction results based on the adolescent growth and development prediction model, and the adolescent growth and development prediction results include good expected results, normal expected results and unfavorable expected results.

[0083] The computer storage medium of the embodiment of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device.

[0084] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0085] The program code included on the computer readable medium can be transmitted with any appropriate medium, including but not limited to wireless, electric wire, optical cable, RF, etc., or any suitable combination of the above. The computer program code for performing the operation of the present invention can be written in one or more programming languages ​​or their combinations, and the programming language includes object-oriented programming languages-such as Java, Smalltalk, C++, and also includes conventional procedural programming languages-such as "C" language or similar programming languages. The program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0086] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A method for evaluating the growth and development level of adolescents based on multi-factor conditions, characterized in that: The implementation of the adolescent growth and development level assessment method comprises the following steps: Acquire the height data of the adolescents, and obtain the height development level of the adolescents based on the height data of the adolescents, wherein the height development level of the adolescents includes upper height development, upper-middle height development, middle height development, lower-middle height development, and lower height development; Acquire adolescent growth and development information, and construct an adolescent growth and development prediction model based on the adolescent growth and development information, wherein the adolescent growth and development information includes the adolescent age, adolescent gender, adolescent weight, adolescent sitting height, adolescent father height, and adolescent mother height, and the adolescent growth and development prediction model includes an adolescent height prediction model and an adolescent growth level prediction model; Based on the adolescent growth and development prediction model, the adolescent growth and development prediction results are output, and the adolescent growth and development prediction results include good expected results, normal expected results and unfavorable expected results.

2. The method for evaluating the growth and development level of adolescents according to claim 1, characterized in that: The constructing of the adolescent growth and development prediction model according to the adolescent growth and development information comprises: Constructing the adolescent height prediction model based on the adolescent bone age, the adolescent sleeping posture and the adolescent growth and development information; The adolescent growth level prediction model is constructed based on the adolescent maturity deviation.

3. The method for evaluating the growth and development level of adolescents according to claim 2, characterized in that: The constructing of the adolescent height prediction model based on the adolescent bone age, the adolescent sleeping position and the adolescent growth and development information comprises: Obtain an X-ray of the wrist bones of the adolescent, obtain the adolescent's bone age based on the X-ray of the wrist bones of the adolescent, and obtain the adolescent's bone age-predicted height based on the adolescent's bone age; Calculating the genetically predicted height of the adolescent based on the height of the adolescent's father, the height of the adolescent's mother, and the adolescent's gender; Based on the improved sleeping posture recognition method, the sleeping posture of the teenager is obtained, and the sleeping posture standard of the teenager is obtained according to the sleeping posture of the teenager; Based on the adolescent's predicted height by bone age, the adolescent's predicted height by genetics and the adolescent's sleeping posture standard, the adolescent's comprehensive predicted height is calculated and the adolescent's height prediction model is constructed.

4. The method for evaluating the growth and development level of adolescents according to claim 2, characterized in that: The youth maturity offset is calculated based on the youth sitting height, the youth height data, the youth weight and the youth age.

5. The method for evaluating the growth and development level of adolescents according to claim 3, characterized in that: The step of obtaining the adolescent's bone age based on the adolescent's wrist bone X-ray and obtaining the adolescent's bone age predicted height according to the adolescent's bone age includes: Based on the X-ray film of the adolescent wrist bones, the adolescent wrist bones are divided into radius, metacarpal Ⅰ, metacarpal Ⅲ, metacarpal Ⅴ, proximal phalanx Ⅰ, proximal phalanx Ⅲ, proximal phalanx Ⅴ, middle phalanx Ⅲ, middle phalanx Ⅴ, distal phalanx Ⅰ, distal phalanx Ⅲ, distal phalanx Ⅴ, capitate, and hamate; The radius is divided into 10 bone age grades, the capitate is divided into 7 bone age grades, the metacarpal I, metacarpal III, metacarpal V, proximal phalanx I, proximal phalanx III, proximal phalanx V, middle phalanx III, middle phalanx V, distal phalanx I, distal phalanx III, distal phalanx V, and hamate are divided into 8 bone age grades respectively; According to the gender of the adolescent and the wrist bones of the adolescent, a bone age score is assigned to each bone age grade and a total bone development score is obtained, wherein the total bone development score is the sum of all the bone age scores; Obtaining the adolescent's bone age based on the total bone development score and the adolescent's gender; The age difference is obtained according to the difference between the adolescent bone age and the adolescent age, and the adolescent development status is obtained based on the age difference. When the age difference is (-1, 1), the adolescent development status is normal; when the age difference is greater than or equal to 1, the adolescent development status is early development; when the age difference is less than or equal to -1, the adolescent development status is late development; Obtaining an adult height percentile based on the adolescent's gender, the adolescent's bone age, and the adolescent's developmental status; The adolescent's bone age-predicted height is calculated based on the adult height percentage.

6. The method for evaluating the growth and development level of adolescents according to claim 3, characterized in that: The method of obtaining the adolescent sleeping posture based on the improved sleeping posture recognition method and obtaining the adolescent sleeping posture standard according to the adolescent sleeping posture comprises: A sleep monitoring cycle is preset, and a pressure simulation value is obtained through a pressure sensor based on the sleep monitoring cycle. The pressure sensor includes a first pressure sensor, a second pressure sensor, and a third pressure sensor. The first pressure sensor is arranged in the left area below the human body during sleep, the second pressure sensor is arranged in the middle area below the human body during sleep, and the third pressure sensor is arranged in the right area below the human body during sleep. The pressure simulation value is the pressure value of the jth pressure sensor in the i-th sleep monitoring cycle, where j=1, 2, 3; Calculating a resistance value based on the pressure simulation value; Calculating a resistance average based on the resistance value; The teenager's sleeping position and the teenager's sleeping position standard are obtained based on the average resistance value. When the average resistance value of the first pressure sensor is the smallest, the teenager's sleeping position is lying on the left side, and the teenager's sleeping position standard is 0.

993. When the average resistance value of the second pressure sensor is the smallest, the teenager's sleeping position is lying flat on the back, and the teenager's sleeping position standard is 1. When the average resistance value of the third pressure sensor is the smallest, the teenager's sleeping position is lying on the right side, and the teenager's sleeping position standard is 0.

992.

7. The method for evaluating the growth and development level of adolescents according to claim 1, characterized in that: Outputting the adolescent growth and development prediction results based on the adolescent growth and development prediction model includes: Obtaining the local average height, wherein the local average height includes the local average height of females and the local average height of males, and presetting a youth maturity deviation threshold, wherein the youth maturity deviation threshold includes a female youth maturity deviation threshold and a male youth maturity deviation threshold; When the comprehensive predicted height of the teenager is greater than or equal to the local average height and the teenager's maturity deviation is greater than or equal to the teenager's maturity deviation threshold, the good expected result is output; when the comprehensive predicted height of the teenager is greater than or equal to the local average height and the teenager's maturity deviation is less than the teenager's maturity deviation threshold, the normal expected result is output; when the comprehensive predicted height of the teenager is less than the local average height and the teenager's maturity deviation is greater than or equal to the teenager's maturity deviation threshold, the normal expected result is output; when the comprehensive predicted height of the teenager is less than the local average height and the teenager's maturity deviation is less than the teenager's maturity deviation threshold, the unfavorable expected result is output.

8. A system for evaluating the growth and development level of adolescents based on multiple factors, characterized in that: The system is applied to the method for evaluating the growth and development level of adolescents as described in any one of claims 1 to 7, including a data acquisition module, a model building module, and a growth and development prediction module; The data acquisition module is used to acquire the height data of teenagers, and obtain the height development level of teenagers based on the height data of teenagers, wherein the height development level of teenagers includes upper height development, upper-middle height development, middle height development, lower-middle height development, and lower height development; The model building module is used to obtain adolescent growth and development information, and to build an adolescent growth and development prediction model based on the adolescent growth and development information, wherein the adolescent growth and development information includes the adolescent age, adolescent gender, adolescent weight, adolescent sitting height, adolescent father height, and adolescent mother height, and the adolescent growth and development prediction model includes an adolescent height prediction model and an adolescent growth level prediction model; The growth and development prediction module is used to output adolescent growth and development prediction results based on the adolescent growth and development prediction model, and the adolescent growth and development prediction results include good expected results, normal expected results and unfavorable expected results.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, it implements the method for evaluating the growth and development level of adolescents as described in any one of claims 1-7.

10. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions, when executed by a computer processor, are used to execute the method for assessing the growth and development level of adolescents as described in any one of claims 1-7.

Images