CN114271796B - Method and device for measuring human body components by using body state density method - Google Patents
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Abstract
The invention discloses a method and a device for measuring human body components by a body state density method. The method comprises the following steps: acquiring two whole-body photos of the front side and the side of a user; reconstructing a human body three-dimensional model by using the two pictures; further obtaining the body volume; further obtaining body density according to a body state density algorithm formula; further obtaining the body fat rate; further calculating the body fat content; the local fat content is finally obtained.
Description
Technical Field
The invention relates to the technical field of measuring human body components, in particular to a method and a device for measuring human body components by a body state density method.
Background
In medical clinics and basic research, body composition is one of laboratory examination data which is most closely related to nutrition in basic assessment of nutrition state, and has important value for assessing nutrition and guiding nutrition. The methods for directly measuring body components on the market comprise a dual-energy X-ray absorption method, a nuclear magnetic resonance imaging method, a CT method, an underwater weighing method, an air replacement method, a bioelectrical impedance analysis method, a dilution method, a fat dissolved gas method, an ultrasonic wave method, a human body measurement algorithm and the like.
Among them, the underwater weighing method is a widely used, classical laboratory method, and is often used as a standard method for evaluating body composition. The method divides the human body into fat and non-fat components (including bones, muscles and other non-fat tissues), and indirectly estimates the effective measurement method of the body fat rate and the fat-free weight through measuring the body density. The measurement is based on the measurement of the lean body mass and the density of the fat tissue, and the presumed result is reasonable and accurate and is a 'gold' standard for comparing and evaluating other methods. However, the underwater density method has the disadvantage of complicated operation procedures and cannot provide segment muscle data.
Air displacement is more comfortable but more costly. At present, no ideal method for measuring the components of the human body based on the density method, which is simple, accurate, fully safe, and the like, exists.
The bioelectrical impedance method is a method for measuring human body components with more applications, and the basic principle is that different components in a human body have different resistivity, the resistivity of muscles, body fluids and the like is low, the conductivity is good, the resistivity of fat, bones and the like is high, the conductor is an electric poor conductor, a constant current with certain frequency is introduced into the human body, the volume of non-fat substances in the human body can be calculated by combining the measured electrical impedance according to the fact that the resistance R of the conductor is in direct proportion to the resistivity beta and the length L and is in inverse proportion to the cross section product S, namely R = rho (L/S), and V = rho (L/R) is obtained through conversion, and the volume of the non-fat substances in the human body can be obtained by multiplying the average specific gravity of the non-fat substances by measuring partial parameters of the human body. The bioelectrical impedance method assumes that four limbs and a trunk of a human body are cylinders, the electrical resistivity of each part of the cylinders is the same, the shapes of the four limbs and the trunk of the human body are different actually, and the electrical impedance of the four limbs accounts for most of the electrical impedance, so the method is developed recently to measure the distribution conditions of internal and external liquid of cells of the human body by using multi-frequency resistors and the sectional resistance of the human body, and the sectional measurement of the human body can calculate the non-fat substances and the fat substances of each part of the human body so as to improve the measurement accuracy and predict the distribution condition of fat.
The research results show that the fat people and the normal weight people have obvious difference in body shape and body composition (such as the content of the combined water in the body, the distribution of the body water and the like). When using bioelectrical impedance to measure body fat content, using the extrapolation equation for a population with normal weight will significantly underestimate the fat content in a obese person's body. In addition, in practical application, the difference between the calculation result and the measured value of the calculation equation is found to be significant when the body fat content calculated by the bioelectrical impedance calculation equation of different countries and regions is compared with the standard result of the underwater weighing method.
Therefore, the bioelectrical impedance method is adopted to estimate the body fat content result by the influence of the change of the measuring position, the change of the resistivity of different race human bodies, the change of the ion concentration in the body fluid and the applicability of different estimation equations.
Therefore, the technical personnel in the field provide a method and a device for measuring the human body components by a body state density method, and provide a more accurate measuring method, and simultaneously solve the problems that the density method has great operation difficulty in the process of measuring the human body components, high implementation cost and incapability of measuring segmental muscles.
Disclosure of Invention
In order to solve the technical problems, the invention provides a method and a detection device for accurately calculating body fat weight and local fat content by using a human body three-dimensional model reconstruction technology to obtain human body modeling volume and body density based on a density Archimedes principle.
The invention provides a method and a device for measuring human body components by a body state density method, wherein the method comprises the following steps:
The user wears the body suit tightly, two front and side full-body photos of the user are collected through image collecting equipment or a mobile terminal, such as mobile phones, tablet computers and other photographing equipment, and are uploaded to an upper computer to reconstruct a human body model.
And 102, reconstructing a human body three-dimensional model.
The pixel edges of the front and side full-body photographs belonging to a human are extracted through an edge defining technology, and other pixel points forming a human body model are further calculated by utilizing a machine learning algorithm, so that a complete human body pixel model is constructed.
And further obtaining the pixel distance of the three-dimensional model of the user by combining the measured height and thickness values of the human body characteristic data. And further obtaining the local volume and the whole body volume of the body according to an algorithm formula.
And acquiring basic information, height, weight and sex of the user, and combining the volume acquired in the step 103 to acquire body density.
The formula algorithm for measuring the body density by the body state density method is as follows:
(1) Body density is obtained by techniques of three-dimensional modeling and edge definition:
Db＝Wa/(V-RV-GV)
wherein: wa is the onshore body weight; v is a modeling volume (mm 3) obtained after image recognition and three-dimensional modeling are carried out to reconstruct clear data; RV is residual gas (ml); GV is the volume (ml) of the gastrointestinal tract
(2) Residual gas amount:
male RV = (0.017 age) + (0.06858 ah) -3.447
Female RV = (0.009 × age) + (0.08128 × h) -3.9
And 105, obtaining the body fat rate.
The body fat ratio is further calculated from the body density obtained at 104. The formula is as follows:
fat% = (4.950/Db-4.500) × 100% wherein: db is body density
Body fat is calculated from the body fat rate obtained at 105 in combination with the measured body weight data. The formula: body fat weight = body weight x body fat rate.
And further calculating the fat of the body part by establishing a human body state standard logic calculation model base by combining the values obtained in the previous step.
Preferably: the specific algorithm for obtaining the body volume is: the method comprises the steps of dividing each part of the body of the three-dimensional model of the user, cutting each part into a plurality of layers of slices, calculating the area of each layer of pixel interval, converting the actual area through pixel distance, calculating the volume of the part in an accumulation mode, and calculating the volume of the human body by accumulating the volumes of all the parts. The area of each slice layer is calculated by dividing the pixel interval of the slice layer into squares with the area length and width of 1 mm, and the areas are the area of the inner area and the area of the edge area. According to the coordinate interval of the layer, calculating an internal complete area region, wherein the total circumference of an edge part curve is L, the edge curve is divided into n parts, the side length of each square area is L/n mm, and the formula is as follows: s = lim n→∞ L/n, the edge portion area is negligible without affecting the overall data.
Preferably: the body fat rate is measured by a body state intensity method, the body fat content is further obtained, a body state standard logical calculation model base is established according to human anatomy data and machine learning in the data operation process, the circumference value of the body part such as the trunk, the limbs and the like obtained by the reconstruction of the three-dimensional model of the user is compared with the circumference value of the body part under the same characteristic factors such as height, weight, sex, body fat rate and the like in the body state standard logical model base, and the proportion value is calculated, so that the fat of the body part is calculated.
The utility model provides a device through attitude density method measurement human composition, the device includes host computer, next computer main control board, image acquisition module, height range finding module, body thickness range finding module, weighing module.
The host computer comprises a display, a keyboard, a memory, and one or more computer programs, wherein the one or more computer programs are stored in the memory, the one or more computer programs comprising instructions that, when executed by the apparatus, cause the apparatus to perform the method of measuring body composition by densitometry;
and the lower computer main control board is used for receiving the instruction output by the upper computer, processing data and issuing the instruction to each functional module. And transmitting the measurement data returned by the height ranging module, the body thickness ranging module and the weighing module to the upper computer.
The image acquisition module is used for acquiring human body image data, receiving an image acquisition instruction issued by a lower computer main control board, finishing an image acquisition function and transmitting the acquired image data to the upper computer.
The height ranging module is used for measuring height data of a human body, receiving height measuring instructions issued by the main control board of the lower computer, completing a height measuring function, and returning the measured height data to the main control board of the lower computer.
The body thickness ranging module is used for measuring the thickness data of the human body, finishing the measurement function of the body thickness value after receiving a body thickness measurement instruction issued by the lower computer main control board, and returning the measured thickness data to the lower computer main control board.
The weighing module is used for measuring the weight data of a human body, finishing the function of measuring the weight after receiving a weight measuring instruction issued by the lower computer main control board, and returning the measured thickness data to the lower computer main control board.
The invention has the technical effects and advantages that:
the system of the invention optimizes the realization mode once on the basis of the gold standard 'underwater density method', obtains the volume and density of the human body through the three-dimensional reconstruction of the human body, and further obtains the components of the human body. The method has the characteristics of convenient and fast measurement method, low detection cost, high accuracy and wide measurement range. The problems that the operation difficulty is high, the realization cost is high and the local fat cannot be measured in the process of measuring the human body components by using the density method are solved.
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FIG. 1 is a schematic flow chart of the present application;
FIG. 2 is a diagram of a system architecture of an apparatus according to an embodiment of the present application;
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments. The embodiments of the present invention have been presented for purposes of illustration and description, and are not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to practitioners skilled in this art. The embodiment was chosen and described in order to best explain the principles of the invention and the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.
The underwater density method obtains the density of the body by using a drainage method according to the archimedes principle, the density of the body is the ratio of the weight of the body to the volume, the weight of the body can be directly measured by a weight scale, and the volume of the body can be obtained by the drainage method. The density is then substituted into the formula to determine the percent fat in the body.
V = (BW-Uww)/Dw.
The actual body volume should be subtracted from the residual gas in the lungs, the gas volume in the trachea and the gas volume in the intestines.
Db＝BW/{(BW-UWw)/Dw-Rv}
Db: body density, BW: body weight in air, UWw: the body weight in the water minus the additional weight,
dw is the water density corresponding to the water temperature at the time of measurement,
rv is the in vivo residual capacity (L).
After obtaining the body density, substituting the body density into a fat percentage calculation formula to calculate the fat amount of the human body, wherein the formula for calculating the fat percentage comprises the following steps:
brozek formula: fat% = (4.57 ÷ Db-4.142) X100%
Siri formula: fat% = (4.95 ÷ Db-4.5) X100%
Lohman formula: fat% = (5.30 ÷ Db-4.89) X100%
Forbes equation: fat% = (5.750 ÷ Db-5.389) X100%
Miymoto formula: fat% = (5.075 ÷ D b-4.604) X100%.
The invention uses three-dimensional modeling and edge definition technology to restore the Siri equation for calculating the human body components proposed by William Siri.
Referring to fig. 1-2, in the present embodiment, a method and a device for measuring body composition by a body state density method are provided, the method includes the following steps:
The user wears a tight dress, the front and the side two full-body photos of the user are collected by the image collecting module 3 in the device and are uploaded to the upper computer 1 for rebuilding the human body model.
And 102, reconstructing a human body three-dimensional model.
The pixel edges of the front and side two full-body photographs belonging to the human body are extracted through an edge definition technology, and other pixel points forming the human body model are further calculated by utilizing a machine learning algorithm, so that the complete pixel model of the human body is constructed.
And further obtaining the pixel distance of the three-dimensional model of the user by combining the height value measured by the height ranging module 4 and the body thickness value measured by the body thickness ranging module 5 in the device. And further obtaining the local volume and the whole body volume of the body according to an algorithm formula.
The specific algorithm is as follows: dividing each part of the body of the three-dimensional model of the user, cutting each part into a plurality of layers of slices, calculating the area of each layer of pixel interval, converting the actual area through pixel distance, accumulating and calculating the volume of the part, and further accumulating the volumes of all the parts to calculate the volume of the human body. The area of each slice layer is calculated by dividing the pixel interval of the slice layer into squares with the area length and width of 1 mm, and the area of each square is the area of the inner area and the area of the edge area. According to the coordinate interval of the layer, calculating an internal complete area region, wherein the total circumference of an edge part curve is L, dividing the edge curve into n parts, the side length of each square area is L/n mm, and the formula is as follows: s = lim n→∞ L/n, the edge portion area is negligible without affecting the overall data.
And acquiring the basic information sex characteristics of the user, and combining the volume acquired in the step 103 to acquire the body density.
The formula algorithm for measuring the body density by the body state density method is as follows:
(1) Body density is obtained by techniques of three-dimensional modeling and edge definition:
Db＝Wa/(V-RV-GV)
wherein: wa is the onshore body weight; v is a modeling volume (mm 3) obtained after image recognition and three-dimensional modeling are carried out to reconstruct clear data; RV is residual gas (ml); GV is the volume (ml) of the gastrointestinal tract
(2) Residual gas amount:
male RV = (0.017 × ge) + (0.06858 × h) -3.447
Female RV = (0.009 × age) + (0.08128 × h) -3.9
And step 105, obtaining the body fat rate.
The body fat rate is further calculated from the body density obtained at 104. The formula is as follows:
fat% = (4.950/Db-4.500) × 100% wherein: db is body density
Body fat is calculated according to the body fat rate obtained by 105 and the weight data measured by the weighing module 4 in the device. The formula: body fat weight = body weight x body fat rate.
And combining the values obtained in the previous step, and further calculating the fat of the body part by establishing a human body state standard logic calculation model library.
The specific algorithm is as follows: the method comprises the steps of establishing a human body posture standard logical calculation model base according to human anatomy data and machine learning in the data operation process, comparing the circumference value of a body part such as a trunk, four limbs and the like obtained by reconstructing a three-dimensional model of a user with the circumference value of the part under the same characteristic factors such as height, weight, sex, body fat rate and the like in the human body posture standard logical model base, calculating a proportional value, and calculating the fat of the body part.
Body fat percentage: it is the ratio of the weight of fat in human body to the total weight of human body, also called the percentage of body fat, and it reflects the content of fat in human body. Obesity increases the risk of developing various diseases. For example, hypertension, diabetes, hyperlipidemia, etc. Women who intend to become pregnant cannot ignore the risk of pregnancy complications and dystocia caused by obesity. Body composition refers to the total composition of all human tissues and organs, and is divided into fat and non-fat components. The former is called body fat weight (or fat body weight) and the latter is called lean body weight (or lean body weight).
A device for measuring human body composition through a body state density method comprises an upper computer 1, a lower computer main control board 2, an image acquisition module 3, a height ranging module 4, a body thickness ranging module 5 and a weighing module 6.
The upper computer 1 comprises a display, a keyboard, a memory, and one or more computer programs, wherein the one or more computer programs are stored in the memory, the one or more computer programs comprising instructions that, when executed by the functional module, cause the functional module to perform the method for measuring body composition by a body state density method.
And the lower computer main control board 2 is used for receiving the instruction output by the upper computer 1, processing data and sending the instruction to each functional module. And transmits the measurement data returned by the height ranging module 4, the body thickness ranging module 5 and the weighing module 6 to the upper computer 1. The lower computer main control board 2 and the upper computer 1 carry out measurement control and transmit height, weight and thickness measurement data through a communication interface.
The image acquisition module 3 is used for acquiring human body image data, finishing the image acquisition function after receiving an image acquisition instruction issued by the lower computer main control board 2, and transmitting the acquired image data to the upper computer 1 through a USB interface.
The height ranging module 4 is used for measuring height data of a human body, receives a height measuring instruction issued by the lower computer main control board 2 through the communication interface, then completes the height measuring function, and returns the measured height data to the lower computer main control board 2 through the communication interface.
The body thickness ranging module 5 is used for measuring human thickness data, receiving a body thickness measuring instruction issued by the lower computer main control board 2 through the communication interface, then completing the body thickness value measuring function, and returning the measured thickness data to the lower computer main control board 2 through the communication interface.
The weighing module 6 is used for measuring the weight data of a human body, receiving a weight measuring instruction issued by the lower computer main control board 2 through the communication interface, finishing the function of measuring the weight, and returning the measured thickness data to the lower computer main control board 2 through the communication interface.
The upper computer 1 receives the image data returned by the image acquisition module 3 to carry out three-dimensional model reconstruction, then the pixel distance is obtained by calculating the height data and the body thickness data returned by the lower computer main control board 2, and further the local body volume and the whole body volume of the body are obtained according to the algorithm for calculating the body volume disclosed by the invention. The body density and the body fat rate are further obtained according to a formula algorithm for calculating the body density and the body fat rate by the body state density method disclosed by the invention. And further establishing a human body posture standard logical calculation model base, and further calculating to obtain the body local fat.
The working principle of the device is as follows:
s1: acquiring two whole-body photos of the front side and the side of a user;
s2: reconstructing a three-dimensional model according to the user picture;
s3: measuring the height and thickness values of the characteristic dimension data of the human body;
s4: obtaining the pixel distance of the three-dimensional model of the user according to the height value and the thickness value of the characteristic dimension data of the human body;
s5: cutting and calculating each part of the body of the three-dimensional model of the user to obtain the body volume and the local volume so as to obtain the body density;
s6: and (3) accurately calculating the body fat rate by using a body state density method, and further calculating the body fat content so as to obtain the local fat content of the user.
It is to be understood that the described embodiments are merely a few embodiments of the invention, and not all embodiments. All other embodiments, which can be derived by one of ordinary skill in the art and related arts based on the embodiments of the present invention without any creative effort, shall fall within the protection scope of the present invention. Structures, devices, and methods of operation not specifically described or illustrated herein are generally practiced in the art without specific details or limitations.
Claims (2)
1. A method for measuring body composition by densitometry of states, the method comprising the steps of:
step 101, acquiring two whole-body photos of the front side and the side of a user;
the user wears the suit tightly, two full-body photos of the front side and the side of the user are collected through image collection equipment or photographing equipment of a mobile end and are uploaded to an upper computer to reconstruct a human body model;
step 102, reconstructing a human body three-dimensional model;
extracting pixel edges of the front and side full-body photographs belonging to a human through an edge definition technology, and further calculating other pixel points forming a human body model by utilizing a machine learning algorithm so as to construct a complete human body pixel model;
step 103, obtaining a body volume;
combining the measured height and thickness values of the human body characteristic data to further obtain the pixel distance of the three-dimensional model of the user, and further obtaining the local volume and the whole body volume of the body according to an algorithm formula;
step 104, obtaining body density;
the formula algorithm for measuring the body fat content by the body state density method is as follows:
(1) Body density is obtained by techniques of three-dimensional modeling and edge definition:
Db＝Wa/(V-RV-GV)
wherein: wa is the onshore body weight; v is a modeling volume (mm) obtained after image recognition and three-dimensional modeling are carried out to reconstruct clear data 3 ) (ii) a RV is residual gas (ml); GV is the volume (ml) of the gastrointestinal tract
(2) Residual air volume:
male RV = (0.017 age) + (0.06858 ah) -3.447
Female RV = (0.009 × age) + (0.08128 × h) -3.9
Step 105, obtaining the body fat rate;
further calculating the body fat rate according to the body density obtained by 104, wherein the formula is as follows:
fat% = (4.950/Db-4.500) × 100% wherein: db is body density
Step 106, obtaining fat;
calculating body fat according to the body fat rate obtained by 105 and combining the body weight data, and obtaining the formula: body fat weight = body weight x body fat rate;
step 107, obtaining local fat;
calculating the fat of the body part by establishing a body state standard logic calculation model base in combination with the numerical values obtained in the previous step;
the algorithm for obtaining the body volume is to divide all parts of the body of the three-dimensional model of the user, cut each part into a plurality of layers of slices, and calculate each layer of pixel areaThe area between, convert actual area through the pixel distance, thereby add up and calculate the volume of this position, further add up each position volume and calculate human volume, the sliced area calculation mode of each layer does, the pixel interval on this layer, divide into the square that area length and width are 1 millimeter respectively, its area is interior region area and marginal area, according to the coordinate interval on this layer, calculate the inside complete area region, the total girth of marginal part curve is L, divide this marginal curve into n, the length of side of its each square area is L/n millimeter, its formula is:
the area of the edge part can be ignored under the condition of not influencing the whole data;
the algorithm for obtaining the local fat is as follows: the body state standard logical calculation model base is established according to the human anatomy data and machine learning in the data operation process, and the body fat of the body part is calculated by comparing the circumference value of the partial part of the trunk and the four limbs of the body, which is obtained by reconstructing the three-dimensional model of the user, with the circumference value of the partial part of the body in the body state standard logical model base under the same characteristic factors of height, weight, sex and body fat rate.
2. The method for measuring the human body composition by the body state density method according to claim 1, comprising a device using the method, wherein the device comprises an upper computer, a lower computer main control board, an image acquisition module, a height ranging module, a body thickness ranging module and a weighing module;
the host computer comprises a display, a keyboard, a memory, and one or more computer programs, wherein the one or more computer programs are stored in the memory, the one or more computer programs comprising instructions that, when executed by the apparatus, cause the apparatus to perform the method of measuring body composition by densitometry;
the lower computer main control board is used for receiving an instruction output by the upper computer, processing data, issuing the instruction to each functional module, and transmitting measurement data returned by the height ranging module, the body thickness ranging module and the weighing module to the upper computer;
the image acquisition module is used for acquiring human body image data, finishing an image acquisition function after receiving an image acquisition instruction issued by a lower computer main control board and transmitting the acquired image data to an upper computer;
the height ranging module is used for measuring height data of a human body, completing a height measuring function after receiving a height measuring instruction issued by the lower computer main control board and returning the measured height data to the lower computer main control board;
the body thickness ranging module is used for measuring the thickness data of the human body, finishing the measurement function of the body thickness value after receiving a body thickness measurement instruction issued by the lower computer main control board, and returning the measured thickness data to the lower computer main control board;
the weighing module is used for measuring weight data of a human body, finishing the function of weight measurement after receiving a weight measurement instruction issued by the lower computer main control board, and returning the measured thickness data to the lower computer main control board.
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