Method, device and system for measuring waist-hip ratio of human body based on millimeter wave radar

Abstract

The invention discloses a human body waist-hip ratio measuring method, device and system based on millimeter-wave radar. The method comprises the following steps: acquiring original point cloud data synchronously acquired by a plurality of millimeter-wave radar arrays from multiple angles of a measured human body; expanding all the original point cloud data according to row indexes, and converting the original point cloud data into global coordinates to obtain three-dimensional point cloud data of the measured human trunk; performing hierarchical slicing on the three-dimensional point cloud data according to a preset thickness in the height direction of the body, and extracting a point cloud subset in each slice to form a plurality of sections; determining section contours of the plurality of sections; sequentially arranging all the section contours along the height direction of the body to obtain a trunk model of the measured human body; identifying a waistline position and a hipline position of the trunk model, and calculating the waistline and the hipline; and calculating the waist-hip ratio according to the waist circumference and the hip circumference. According to the human body waist-hip ratio measurement method based on the millimeter wave radar, measurement errors can be effectively eliminated, and high-precision measurement of the human body waist-hip ratio is achieved.

Description

Technical Field

[0001] The present application relates to the technical field of human body size measurement, and in particular to a method, device and system for measuring human waist-to-hip ratio based on millimeter-wave radar. Background Art

[0002] As a key indicator of human health and body shape, waist-to-hip ratio (WHR) has important applications in health management, medical diagnosis, clothing customization, and many other fields. Traditional WHR measurement methods rely primarily on manual measurement using a tape measure. This method is not only time-consuming and labor-intensive, but also highly susceptible to differences in operator technique and experience, resulting in limited accuracy and significant errors. Furthermore, manual measurement requires direct contact with the subject's body, which can cause discomfort and distress in situations where privacy or hygiene are paramount.

[0003] With the continuous advancement of technology, optical measurement technology has gradually been applied to the field of human dimensional measurement. However, optical measurement technology relies on the principle of light reflection, which has inherent drawbacks such as its inability to penetrate clothing and its demanding requirements for ambient lighting conditions. In actual application scenarios, if the subject is wearing loose clothing or in complex environments such as dim lighting or direct sunlight, optical measurement equipment often has difficulty obtaining accurate and complete body contour data, resulting in a significant decrease in the accuracy of waist-to-hip ratio measurements, which cannot meet actual needs.

[0004] Millimeter-wave radar technology offers a new approach to solving these problems, thanks to its significant advantages, including its ability to penetrate insulating materials (such as common clothing), lack of radiation hazards to the human body, and immunity to interference from ambient light. Currently, there are no devices on the market specifically designed to measure waist-to-hip ratio using millimeter-wave radar. While some devices, such as those used for airport security, use millimeter-wave radar for body detection, such as those used for airport security, could theoretically measure waist-to-hip ratio and other body dimensions through future software and hardware upgrades. However, to meet requirements for measurement accuracy, range, and adaptability to complex human morphology, these devices require thousands of radar arrays. For example, Vayyar's vTetra imaging system features 120x120 = 14,400 array channels, resulting in equipment costs often reaching several million or even tens of millions of yuan, making it prohibitive for widespread use in physical examinations and healthcare settings.

[0005] Therefore, the development of a new, low-cost, high-precision human waist-to-hip ratio measurement device based on millimeter-wave radar technology has urgent practical needs and important application value. Summary of the Invention

[0006] To this end, the present application provides a method, device and system for measuring the waist-to-hip ratio of a human body based on millimeter-wave radar to solve the problem of low measurement accuracy of the waist-to-hip ratio measurement method in the prior art.

[0007] In order to achieve the above objectives, this application provides the following technical solutions:

[0008] In a first aspect, a method for measuring waist-to-hip ratio of a human body based on millimeter-wave radar comprises:

[0009] Step 1: Obtain the original point cloud data collected synchronously by multiple millimeter-wave radar arrays from multiple angles of the human body under test;

[0010] Step 2: Expand all original point cloud data by row index and convert them to global coordinates to obtain the three-dimensional point cloud data of the human torso;

[0011] Step 3: Slicing the three-dimensional point cloud data along the height direction of the body at a preset thickness, and extracting a subset of the point cloud within each slice to form multiple cross sections;

[0012] Step 4: Determine the cross-sectional profiles of multiple sections;

[0013] Step 5: Arrange all cross-sectional contours in sequence along the height direction of the body to obtain the torso model of the human body being measured;

[0014] Step 6: Identify the waist and hip positions of the torso model, and calculate the waist and hip circumferences;

[0015] Step 7: Calculate the waist-to-hip ratio based on the waist circumference and the hip circumference.

[0016] Preferably, step 4 specifically includes:

[0017] Step 401: Project the point cloud in each cross section onto a plane perpendicular to the Z axis;

[0018] Step 402: extracting the minimum circumscribed contour of the projected point cloud in the plane;

[0019] Step 403: Smoothing the minimum circumscribed contour by moving least squares method to generate a final cross-sectional contour.

[0020] Preferably, in step 6, identifying the waist circumference position and hip circumference position of the torso model specifically includes: obtaining the sagittal plane of the measured human body according to the torso model, and comparing the intercept points of all contours on the sagittal plane one by one, wherein the contour at the most concave point of the sagittal plane is the position of the waist circumference, and the contour at the most convex point of the sagittal plane is the position of the hip circumference.

[0021] Preferably, in step 6, an electronic tape measure is used to calculate waist circumference and hip circumference.

[0022] Preferably, in step 7, an internationally accepted waist-to-hip ratio calculation formula is used when calculating the waist-to-hip ratio based on the waist circumference and the hip circumference.

[0023] Preferably, the method further comprises: comparing the waist-to-hip ratio with a health standard database, and generating a health assessment report of the tested person based on the comparison result.

[0024] In a second aspect, a millimeter-wave radar-based device for measuring waist-to-hip ratio of a human body comprises:

[0025] The point cloud data acquisition module is used to obtain the original point cloud data collected synchronously by multiple millimeter-wave radar arrays from multiple angles of the human body under test;

[0026] The multi-source data fusion module is used to expand all the original point cloud data by row index and convert them into global coordinates to obtain the three-dimensional point cloud data of the measured body;

[0027] a section creation module, configured to slice the three-dimensional point cloud data in layers according to a preset thickness along the height direction of the body, and extract a subset of the point cloud within each slice to form a plurality of sections;

[0028] A section profile creation module for determining the section profiles of multiple sections;

[0029] The torso model reconstruction module is used to arrange all cross-sectional contours in sequence along the height direction of the body to obtain the torso model of the human body being tested;

[0030] A waist and hip recognition module, used to recognize the waist and hip positions of the torso model and calculate the waist and hip circumferences;

[0031] A waist-to-hip ratio calculation module is used to calculate the waist-to-hip ratio based on the waist circumference and the hip circumference.

[0032] In a third aspect, a computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the steps of a method for measuring human waist-to-hip ratio based on millimeter-wave radar.

[0033] In a fourth aspect, a human waist-to-hip ratio measurement system based on millimeter-wave radar includes a floor, four scanning columns are fixedly provided on the four edges of the floor, each scanning column is fixedly provided with a millimeter-wave radar module on the side close to the person being measured, and the computer device, switch and power module are fixedly provided at the bottom of the floor, each millimeter-wave radar in the millimeter-wave radar module communicates with the computer device through the switch, and the power module supplies power to the computer device.

[0034] Preferably, the millimeter-wave radar module includes 2x16 millimeter-wave radars.

[0035] Compared with the prior art, this application has at least the following beneficial effects:

[0036] 1. This application provides a method for measuring waist-to-hip ratio based on millimeter-wave radar. This method uses a millimeter-wave radar array to synchronously acquire raw point cloud data of the human body contour from multiple angles. After converting all the raw point cloud data to global coordinates, cross-sections are created layer by layer. Cross-sectional contours are then created based on the cross-sections, and a torso model is reconstructed. The waist and hip circumferences are determined based on the torso model, and the waist-to-hip ratio is calculated. Compared to traditional measurement methods, the millimeter-wave radar-based method for measuring waist-to-hip ratio provided in this application can accurately calculate the waist-to-hip ratio using less point cloud data. This significantly improves data processing efficiency, reduces computational complexity, and lowers costs while ensuring measurement accuracy.

[0037] 2. This application also provides a millimeter-wave radar-based waist-to-hip ratio measurement system. The system comprises four scanning columns fixed to the four edges of the floor, each of which is equipped with a millimeter-wave radar module on the side closest to the person being measured. This system utilizes the non-contact detection characteristics of millimeter-wave radar to accurately capture the three-dimensional contours of the waist and hips. Millimeter-wave radar can penetrate ordinary clothing and is not restricted by ambient light, making it highly applicable, reliable, and low-cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] To more intuitively illustrate the prior art and the present application, exemplary drawings are provided below. It should be understood that the specific shapes and structures shown in the drawings should not generally be considered as limiting conditions for implementing the present application. For example, based on the technical concepts disclosed in this application and the exemplary drawings, those skilled in the art are capable of easily making routine adjustments or further optimizations to the addition / reduction / attribution division of certain units (components), the specific shapes, positional relationships, connection methods, and dimensional ratios.

[0039] Figure 1 A flow chart of a method for measuring waist-to-hip ratio of a human body based on millimeter-wave radar provided in Example 1 of the present application;

[0040] Figure 2 A schematic structural diagram of a method for measuring waist-to-hip ratio of a human body based on millimeter-wave radar provided in Example 1 of the present application;

[0041] Figure 3 This is a schematic diagram of the front point cloud of the torso provided in Example 1 of this application;

[0042] Figure 4 This is a schematic diagram of the side point cloud of the torso provided in Example 1 of this application;

[0043] Figure 5A schematic diagram of a layered section of a torso provided in Example 1 of the present application;

[0044] Figure 6 This is a schematic diagram of the interface point cloud projection provided in Example 1 of this application;

[0045] Figure 7 This is a schematic diagram of point cloud projection partitioning provided in Example 1 of this application;

[0046] Figure 8 A schematic diagram of extracting cross-sectional contour lines provided in Example 1 of the present application;

[0047] Figure 9 This is a schematic diagram of the optimized contour line provided in Example 1 of the present application;

[0048] Figure 10 A schematic diagram of a torso model provided in Example 1 of the present application;

[0049] Figure 11 A schematic diagram of a sagittal plane provided in Example 1 of the present application;

[0050] Figure 12 A schematic diagram of waist and hip positions provided in Example 1 of the present application;

[0051] Figure 13 This is a schematic diagram of an electronic tape measure provided in Example 1 of the present application;

[0052] Figure 14 A schematic structural diagram of a human waist-to-hip ratio measurement system based on millimeter-wave radar provided in Example 4 of the present application;

[0053] Figure 15 A schematic diagram of the millimeter-wave radar module structure provided in Example 4 of the present application;

[0054] Figure 16 A schematic diagram of a human waist-to-hip ratio measurement system based on millimeter-wave radar provided in Example 4 of the present application.

[0055] Description of reference numerals:

[0056] 1. Floor; 2. Scan the columns. DETAILED DESCRIPTION

[0057] The present application will be further described below in detail through specific embodiments in conjunction with the accompanying drawings.

[0058] In the description of this application: unless otherwise specified, "plurality" means two or more. The terms "first," "second," "third," etc. in this application are intended to distinguish the objects referred to and do not have any special technical connotations (for example, they should not be understood as emphasizing importance or order). Expressions such as "including," "comprising," and "having" also mean "not limited to" (certain units, components, materials, steps, etc.).

[0059] The terms such as "upper", "lower", "left", "right", "middle", etc. cited in this application are usually used to indicate the general relative position relationship for the convenience of intuitive understanding by referring to the drawings, and are not absolute limitations on the position relationship in the actual product.

[0060] Example 1

[0061] See also Figure 1 and Figure 2 This embodiment provides a method for measuring waist-to-hip ratio of a human body based on millimeter-wave radar, including:

[0062] S1: Acquire the original point cloud data collected synchronously by multiple millimeter-wave radar arrays from multiple angles of the human body;

[0063] Specifically, this embodiment uses four millimeter-wave radar arrays to synchronously collect point cloud data from the front, back, left, and right angles of the measured person. Each millimeter-wave radar array is a 2x16 array, so a total of 8 columns and 16 rows of radar data can be obtained.

[0064] Because each radar independently collects the distance, angle and speed information of the space target (the human body being measured), the original output of each radar is: N i ×3 matrix, so the raw output of all radars can be composed into the following matrix:

[0065]

[0066] Among them, r ij ,θ ij 、v ij They represent the distance, angle, and speed of the jth point of the i-th radar, respectively, where i = 1, 2, ..., 128, corresponding to the position in the millimeter-wave radar array. , ( , ), and satisfies .

[0067] S2: Expand all original point cloud data by row index and convert them to global coordinates to obtain the three-dimensional point cloud data of the measured body, that is, the multi-source data fusion point cloud;

[0068] Specifically, in this step, all the original point cloud data are expanded by row index to form an N×5 matrix, which can be expressed as follows:

[0069]

[0070] in, , the first two columns explicitly record the row and column positions of the radar.

[0071] Then the radar point Converted to global coordinates, expressed as:

[0072] .

[0073] Through the above calculations, this step integrates the data information of all radar arrays, thereby obtaining the human body three-dimensional point cloud data of the human torso being measured, such as Figure 3 and Figure 4 shown.

[0074] S3: Slice the 3D point cloud data along the body height direction according to a preset thickness, and extract the point cloud subset within each slice to form multiple cross sections, that is, create cross sections layer by layer;

[0075] Specifically, this step requires creating and extracting cross sections layer by layer along the axis in the height direction of the body (Z axis), such as Figure 5 However, due to the low density of the point cloud, too few points extracted from the cross section will affect the accuracy of the contour. Therefore, this embodiment pre-sets a configurable cross-section thickness parameter Hm. The point cloud matrix P of the k-th cross section is k Contains all points that satisfy ki=k, expressed as:

[0076] .

[0077] Assume the Z coordinate range of the point cloud is: , then the total number of sections is: .

[0078] Because the parameter Hm is an adjustable parameter, when the number of radar modules is large, the value of Hm can be lowered, and when the number of radar modules is small, the value of Hm can be appropriately increased. According to the test, the ideal Hm value should ensure that the number of point clouds in each section is P k No less than 80.

[0079] S4: determining the cross-sectional profiles of multiple cross-sections, i.e., cross-sectional profile creation;

[0080] The step S4 specifically includes:

[0081] S401: Projecting the point cloud in each section onto a plane perpendicular to the Z axis, i.e., section point cloud projection;

[0082] This step projects all spatial points in the cross section onto a plane perpendicular to the Z axis (xy plane). Figure 6 As shown, it can be expressed as:

[0083] ;

[0084] The two-dimensional coordinates after projection onto the XY plane are:

[0085] .

[0086] S402: extracting the minimum circumscribed contour of the projected point cloud in the plane, i.e., plane partitioning and contour line extraction;

[0087] See also Figure 7 In this step, the projected plane is divided into 1x1cm squares. The point cloud projection in each square is treated as a group and a circumscribed circle is drawn. If there is only one point in the group, the point is directly selected; if there are two points in the group, the center of the two points is selected; if there are three or more points in the group, the minimum circumscribed circle containing all the points is drawn and the center of the circumscribed circle is selected. Connect the points selected above to generate the original contour line, as shown in Figure 8 shown.

[0088] This extraction method in this step ensures that the contour lines can evenly cover as much area as possible, and avoids the point cloud density weight of a single area being too high.

[0089] S403: Smoothing the minimum circumscribed contour by moving least square method and generating a final cross-sectional contour, ie, contour line optimization.

[0090] See also Figure 9 In this step, the moving least squares method (MLS) is used to fit the quadratic surface to each contour point using local neighborhood points, and smoothing is achieved through coordinate transformation. The fitting function is:

[0091] .

[0092] S5: Arrange all cross-sectional contours in sequence along the height direction of the body to obtain the torso model of the human body being measured, that is, reconstruct the torso model, such as Figure 10 As shown;

[0093] S6: Identify the waist and hip positions of the torso model and calculate the waist and hip circumferences;

[0094] This step uses the "sagittal plane intercept point comparison" algorithm to identify the location of the waist and hip circumference, specifically including: obtaining the cross section of the human body in the sagittal plane direction (y axis) of the torso model (such as Figure 11 As shown in ), compare the intercept points of all contours on the sagittal plane one by one. Among them, the contour where the most concave point of the sagittal plane is located is the location of the waist circumference, and the contour where the most convex point of the sagittal plane is located is the location of the hip circumference (as shown in Figure 12 shown).

[0095] After obtaining the positions of waist and hip circumferences, an electronic tape measure is used to calculate waist and hip circumferences. Specifically, this embodiment uses the convex hull algorithm of the "electronic tape measure" to simulate the actual measurement method of using a tape measure to avoid circumference calculation errors caused by the concavity of the human body, such as Figure 13 shown.

[0096] S7: Calculate waist-to-hip ratio based on waist and hip circumferences.

[0097] Specifically, this step uses the internationally accepted waist-to-hip ratio calculation formula (waist circumference ÷ hip circumference) to quickly calculate the human waist-to-hip ratio.

[0098] The millimeter-wave radar-based method for measuring waist-to-hip ratio of a human body provided in this embodiment further includes: comparing the waist-to-hip ratio with a health standard database, and generating a health assessment report of the measured human body based on the comparison result.

[0099] Specifically: This embodiment compares the calculated results with a built-in health standard database, which contains healthy reference ranges for waist-to-hip ratios for people of different genders, ages, and ethnicities; based on the comparison results, a detailed health assessment report is generated for the subject, for example: indicating whether the subject's waist-to-hip ratio is within a healthy range, and if it is outside the normal range, possible health risks and corresponding improvement suggestions, etc.

[0100] The millimeter-wave radar-based method for measuring waist-to-hip ratio of a human body provided in this embodiment has the following advantages:

[0101] 1. High data processing efficiency and low cost: Existing methods typically rely on the entire point cloud to reconstruct the body trunk mesh, requiring the point cloud data to have a high density (e.g., 200p / cm², with a total of 1-3 million points) and a uniform distribution. However, this embodiment uses a smaller number of matrices, with a total number of collected point clouds less than 5,000 and a density less than 0.5p / cm². Using traditional point cloud mesh reconstruction methods would result in large errors. To this end, this method specifically targets the characteristics of a small number of point clouds and low point cloud density, and innovatively designs the method provided in this embodiment, thereby effectively addressing the shortcomings of existing technologies. Therefore, compared to traditional measurement methods, this embodiment significantly improves data processing efficiency, reduces computational complexity, and lowers costs while ensuring measurement accuracy.

[0102] 2. High-precision measurement: Using a millimeter-wave radar array to simultaneously acquire human body contour data from multiple angles, combined with advanced data fusion and processing algorithms, this method effectively eliminates measurement errors and achieves high-precision measurement of waist-to-hip ratio. Experimental verification has shown that this method can achieve a waist-to-hip ratio measurement accuracy of ±3%, significantly improving accuracy compared to traditional measurement methods and existing measurement technologies.

[0103] 3. Health Assessment: This function not only accurately measures waist-to-hip ratio (WHR) but also simultaneously measures BMI (Body Mass Index). Combined with a built-in health standard database, it provides professional health assessment recommendations. This helps users understand their physical condition and take appropriate health management measures, which is crucial for preventing and controlling WHR-related diseases (such as cardiovascular disease and diabetes). It also provides a convenient and efficient method for assessing human health for medical professionals and health management experts.

[0104] Example 2

[0105] This embodiment provides a human waist-to-hip ratio measurement device based on millimeter-wave radar, comprising:

[0106] The point cloud data acquisition module is used to obtain the original point cloud data collected synchronously by multiple millimeter-wave radar arrays from multiple angles of the human body under test;

[0107] The multi-source data fusion module is used to expand all the original point cloud data by row index and convert them into global coordinates to obtain the three-dimensional point cloud data of the measured body;

[0108] a section creation module, configured to slice the three-dimensional point cloud data in layers according to a preset thickness along the height direction of the body, and extract a subset of the point cloud within each slice to form a plurality of sections;

[0109] A section profile creation module for determining the section profiles of multiple sections;

[0110] The torso model reconstruction module is used to arrange all cross-sectional contours in sequence along the height direction of the body to obtain the torso model of the human body being tested;

[0111] A waist and hip recognition module, used to recognize the waist and hip positions of the torso model and calculate the waist and hip circumferences;

[0112] A waist-to-hip ratio calculation module is used to calculate the waist-to-hip ratio based on the waist circumference and the hip circumference.

[0113] For the specific implementation content of each module in a human waist-to-hip ratio measurement method based on millimeter-wave radar, please refer to the above definition of a human waist-to-hip ratio measurement method based on millimeter-wave radar, which will not be repeated here.

[0114] Example 3

[0115] This embodiment provides a computer device including a memory and a processor. The memory stores a computer program. When the processor executes the computer program, it implements the steps of a method for measuring waist-to-hip ratio of a human body based on millimeter-wave radar.

[0116] Example 4

[0117] See also Figure 14 This embodiment provides a human waist-to-hip ratio measurement system based on millimeter-wave radar, including a floor 1. Four scanning columns 2 are fixedly installed on the four edges of the floor 1. Each scanning column 2 is fixedly installed with a millimeter-wave radar module on the side close to the person standing under measurement. Computer equipment, switches, and power modules are fixedly installed at the bottom of the floor 1. Each millimeter-wave radar in the millimeter-wave radar module communicates with the computer equipment through the switch, and the power module supplies power to the computer equipment.

[0118] See also Figure 15 The millimeter-wave radar module consists of 2 x 16 millimeter-wave radars. Floor 1 also houses a weight module and a height module. Each of the four scanning columns 2 is equipped with a touchscreen for interactive scanning operations and displaying calculation results. The four scanning columns 2 are located in the front, back, left, and right directions of the body. The front scanning column 2 has a handle, which the user grasps to keep the body still during measurement.

[0119] In the human waist-to-hip ratio measurement system based on millimeter-wave radar provided in this embodiment, the height of the scanning column 2 is 1.3 meters, which can cover the scanning of the body trunk between the waist and hips of a human body with a height of 1.4-2.0 meters. The millimeter-wave radar of the millimeter-wave radar module adopts the FMCW 60GHz frequency band and can transmit and receive millimeter-wave signals. Each millimeter-wave radar has independent signal transmission and reception and processing capabilities, and can detect the human body from multiple angles at the same time, and obtain the angle information and distance data of the human body contour. The four scanning columns 2 have a total of 8x16 radar arrangements, which ensures 360° all-round detection of the human body from the waist to the hips, and does not miss key human body contour information, such as Figure 16 shown.

[0120] This embodiment provides a millimeter-wave radar-based waist-to-hip ratio measurement system. A floor 1 is primarily used to vertically secure four scanning columns 2. Weight sensors are also installed on the floor 1, enabling weight measurements ranging from 0 to 200 kg. A height module includes a height sensor and data cables. Data from the weight sensor, height sensor, and millimeter-wave radar on each scanning column 2 is transmitted to a host computer via an RJ45 network interface using the TCP / IPv4 communication protocol and a switch. The host computer (computer) controls the scanning process, filters, analyzes, and performs 3D reconstruction on the large amounts of radar data, stores the data, and ultimately outputs the measurement results.

[0121] Because the system provided in this embodiment uses a small number of radars, the density of the acquired human point cloud is low, and the accuracy of the human body model created using traditional full-body point cloud triangulation mesh reconstruction methods is low. Therefore, a layer-by-layer cross-sectional contour reconstruction method (the method provided in Example 1) was developed. Its basic principle is to sequentially create a 3cm thick cross section (the parameters are configurable and suitable for different numbers of radar modules) along the body's axis (Z). Based on the point cloud enclosed within the cross section, a cross section outline is created, and all cross section outlines are combined to form a body model.

[0122] The specific workflow of a human waist-to-hip ratio measurement system based on millimeter-wave radar provided in this embodiment is as follows:

[0123] Initialization phase: After the device is powered on, the system is initialized. The millimeter-wave radar array performs a self-test to ensure that each radar sensor is functioning properly and calibrates parameters such as transmit power and receive sensitivity. The computer loads the relevant algorithm program and initializes the health standard database. The display and interaction module initializes the interface, prompting the user to prepare for measurement. Simultaneously, the weight sensor and height sensor are initialized and reset to zero.

[0124] During the data collection phase, the subject stands within the system's designated measurement area, and the millimeter-wave radar array begins operating. Multiple millimeter-wave radar sensors simultaneously transmit millimeter-wave signals, which penetrate the subject's clothing, strike the body surface, and reflect back. The radar sensors receive the reflected signals, convert them into electrical signals, and transmit them to a computer via a high-speed data line. During the data collection process, the subject must remain standing still to ensure comprehensive body contour data is captured.

[0125] Data processing and calculation stage: After the computer equipment receives the data transmitted by the millimeter-wave radar array, it first uses a multi-source data fusion layer-by-layer cross-section algorithm to process the data and generate a three-dimensional model of the human body. Then, it uses the sagittal plane intercept point comparison method to identify the location of the waist and hips, and then calculates the waist and hip circumferences using an electronic tape measure. Finally, the waist-to-hip ratio calculation formula is applied and combined with the health standard database to generate a health assessment report. The entire data processing and calculation process is completed in approximately 3 seconds.

[0126] Results Output Stage: Measurement results and health assessment reports are intuitively presented to the user via the display screen of the Display and Interaction Module. Users can view detailed waist circumference, hip circumference, waist-to-hip ratio values, and health assessment recommendations on the screen. Data is uploaded to the user's database system, such as a physical examination management system or HIS system, through an interface. Users can also use the interface provided by the Display and Interaction Module to transfer data via Bluetooth or Wi-Fi to their mobile phone, computer, or other device for storage and further analysis, or print out a paper report for recordkeeping.

[0127] The millimeter-wave radar-based human waist-to-hip ratio measurement system provided in this embodiment can be applied to the following scenarios:

[0128] 1. Hospital health checkup center: In a hospital health checkup center, the system provided by this embodiment is placed in a special physical examination area. When the examinee is undergoing relevant physical examination items, he or she only needs to stand in the measurement area of ​​the system and perform simple operations according to the prompts on the display screen. The system can quickly and accurately measure the examinee's waist-to-hip ratio in a short period of time, and generate a detailed health assessment report based on his or her age, gender and other information. Based on the report, the doctor can conduct a comprehensive assessment of the examinee's physical condition, providing an important reference for the early prevention and diagnosis of diseases. For example, after the system was introduced in a health checkup center of a hospital, waist-to-hip ratio measurements can be performed for hundreds of examinees every day, which greatly improves the efficiency and quality of physical examinations, and also provides doctors with more comprehensive and accurate human health data.

[0129] 2. Gyms and health management institutions: In gyms and health management institutions, the system can be used as an important health monitoring tool. Fitness coaches and health managers can use the system to regularly measure the waist-to-hip ratio for members and track changes in their body shape and health status. Based on the measurement results, personalized fitness plans and diet plans are developed for members to help them better achieve their health management goals. For example, a gym has equipped its members with the system provided by this embodiment. Members measure their waist-to-hip ratio before each fitness session or regularly. Fitness coaches adjust the members' training intensity and diet recommendations in a timely manner based on the measurement data, allowing members to perform fitness exercises more scientifically and effectively, thereby improving member satisfaction and loyalty.

[0130] 3. Community health service centers, neighborhood committee "health huts," and elderly care service stations: Provide residents with free or low-cost waist-to-hip ratio testing. Residents can scan their ID card / health code to perform a self-measurement. The system automatically calculates their waist-to-hip ratio and generates health risk alerts (e.g., "WHR exceeds the standard; attention should be paid to blood lipids and blood sugar"). This data is then connected to the community health record system to form a long-term health tracking record. Measurement results provide intuitive health risk information (e.g., "People with an excessive waist-to-hip ratio have a 2.3 times higher risk of diabetes than those without a normal ratio"), raising residents' health awareness. Collaboration with businesses or nonprofit organizations can provide free follow-up testing (e.g., ultrasound screening for fatty liver disease) for those with abnormal results, creating a closed "testing-intervention" loop.

[0131] This embodiment provides a millimeter-wave radar-based waist-to-hip ratio measurement system that addresses the low accuracy of existing manual measurement methods, the inconvenience of contact measurement, and the limitations of optical measurement due to clothing and environmental factors. This system enables rapid, accurate, and contactless measurement of waist-to-hip ratio, meeting the need for precise waist-to-hip ratio measurement in various scenarios. It offers the following significant advantages:

[0132] 1. Low-cost measurement equipment: Compared to millimeter-wave security inspection equipment on the market that utilizes tens of thousands of modules and complex mechanical structures, this waist-to-hip ratio measurement system, through optimized structure and algorithms, utilizes a relatively small number of radar modules and a simple structure to quickly and accurately measure waist-to-hip ratio. The system equipment cost is less than one-tenth of the cost of existing complex testing equipment. This significant cost reduction enables the device to be used in primary care and general consumer scenarios, addressing the high cost of traditional equipment that has limited widespread adoption. For example, it can be used as a routine health checkup device to assist community hospitals and township health centers in rapidly screening for obesity-related diseases (such as metabolic syndrome), thereby lowering the barrier to entry for purchasing medical testing equipment.

[0133] 2. Strong Adaptability: Leveraging the non-contact detection properties of millimeter waves, this device accurately captures the three-dimensional contours of the waist and hips without requiring the user to undress. It can penetrate ordinary clothing (such as thin sweaters and shirts) and accurately capture the contours of the waist and hips. This addresses the challenges of traditional contact measurement methods (such as tape measures and 3D scanners) such as poor user experience (requiring exposure and complex movements) and susceptibility to environmental interference (such as measurement errors caused by wrinkles in clothing). Because millimeter-wave radar technology is not sensitive to ambient light, the system operates stably in a variety of complex environments. Whether in dimly lit indoors or outdoors in direct sunlight, it can accurately measure waist-to-hip ratio, demonstrating its wide applicability and reliability.

[0134] 3. Fast and Efficient: The entire measurement process is highly automated, taking only 5 seconds from the start of measurement to obtaining the measurement results and health assessment report, greatly improving measurement efficiency. This makes the system ideal for use in scenarios requiring large-scale waist-to-hip ratio measurements, such as large-scale health check-up activities.

[0135] The technical features of the above embodiments can be combined arbitrarily (as long as there is no contradiction in the combination of these technical features). In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described; these embodiments that are not explicitly written should also be considered to be within the scope of this specification.

Claims

1. A method for measuring human waist-to-hip ratio based on millimeter-wave radar, characterized in that: include: Step 1: Obtain the original point cloud data collected synchronously by multiple millimeter-wave radar arrays from multiple angles of the human body under test; Step 2: Expand all original point cloud data by row index and convert them to global coordinates to obtain the three-dimensional point cloud data of the human torso; Step 3: Slicing the three-dimensional point cloud data along the height direction of the body at a preset thickness, and extracting a subset of the point cloud within each slice to form multiple cross sections; Step 4: Determine the cross-sectional profiles of multiple sections; Step 5: Arrange all cross-sectional contours in sequence along the height direction of the body to obtain the torso model of the human body being measured; Step 6: Identify the waist and hip positions of the torso model, and calculate the waist and hip circumferences; Step 7: Calculate the waist-to-hip ratio based on the waist circumference and the hip circumference.

2. The method for measuring waist-to-hip ratio of a human body based on millimeter-wave radar according to claim 1, characterized in that: Step 4 specifically includes: Step 401: Project the point cloud in each cross section onto a plane perpendicular to the Z axis; Step 402: extracting the minimum circumscribed contour of the projected point cloud in the plane; Step 403: Smoothing the minimum circumscribed contour by moving least squares method to generate a final cross-sectional contour.

3. The method for measuring waist-to-hip ratio of a human body based on millimeter-wave radar according to claim 1, characterized in that: In step 6, identifying the waist and hip positions of the torso model specifically includes: obtaining the sagittal plane of the human body being measured based on the torso model, and comparing the intercept points of all contours on the sagittal plane one by one, wherein the contour at the most concave point of the sagittal plane is the location of the waist, and the contour at the most convex point of the sagittal plane is the location of the hip.

4. The method for measuring waist-to-hip ratio of a human body based on millimeter-wave radar according to claim 1, wherein: In step 6, use a digital tape measure to calculate waist and hip circumference.

5. The method for measuring waist-to-hip ratio of a human body based on millimeter-wave radar according to claim 1, characterized in that: In step 7, the waist-to-hip ratio is calculated based on the waist circumference and the hip circumference using an internationally accepted waist-to-hip ratio calculation formula.

6. The method for measuring waist-to-hip ratio of a human body based on millimeter-wave radar according to claim 1, characterized in that: Also includes: The waist-to-hip ratio is compared with a health standard database, and a health assessment report of the tested person is generated based on the comparison result.

7. A human waist-to-hip ratio measuring device based on millimeter-wave radar, characterized in that: include: The point cloud data acquisition module is used to obtain the original point cloud data collected synchronously by multiple millimeter-wave radar arrays from multiple angles of the human body under test; The multi-source data fusion module is used to expand all the original point cloud data by row index and convert them into global coordinates to obtain the three-dimensional point cloud data of the measured body; a section creation module, configured to slice the three-dimensional point cloud data in layers according to a preset thickness along the height direction of the body, and extract a subset of the point cloud within each slice to form a plurality of sections; A section profile creation module for determining the section profiles of multiple sections; The torso model reconstruction module is used to arrange all cross-sectional contours in sequence along the height direction of the body to obtain the torso model of the human body being tested; A waist and hip recognition module, used to recognize the waist and hip positions of the torso model and calculate the waist and hip circumferences; A waist-to-hip ratio calculation module is used to calculate the waist-to-hip ratio based on the waist circumference and the hip circumference.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A human waist-to-hip ratio measurement system based on millimeter-wave radar, characterized in that: The invention comprises a floor, wherein four scanning columns are fixedly provided on the four edges of the floor respectively, and each scanning column is fixedly provided with a millimeter-wave radar module on the side close to the person standing to be measured, and the computer device, switch and power module according to claim 8 are fixedly provided at the bottom of the floor, each millimeter-wave radar in the millimeter-wave radar module communicates with the computer device through the switch, and the power module supplies power to the computer device.

10. The human waist-to-hip ratio measurement system based on millimeter-wave radar according to claim 9, characterized in that: The millimeter-wave radar module includes 2x16 millimeter-wave radars.

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