WO2022042200A1 - Human body composition detection method and system, and electronic device and storage medium - Google Patents

Abstract

Provided is a human body composition detection method, which relates to the field of artificial intelligence. The method comprises: acquiring the weight of a user and a pressure distribution graph of foot soles of the user (S101); inputting the weight and the pressure distribution graph into a preset first detection model to obtain auxiliary information of the user which is output by the first detection model (S102), wherein the auxiliary information is information for assisting with the detection of human body composition, and comprises the height and the gender of the user; and then, determining body composition information of the user on the basis of the weight of the user and the auxiliary information (S103). Therefore, the human body composition can be detected without the need for a user to manually input auxiliary information, thereby reducing user operations and effectively improving the detection efficiency. Further disclosed are a corresponding system, an electronic device and a storage medium.

Description

Method, system, electronic device and storage medium for body composition detection

This application claims the priority of the Chinese patent application filed with the State Intellectual Property Office on August 27, 2020, the application number is 202010878555.1, and the application name is "Method, System, Electronic Device and Storage Medium for Human Body Composition Detection", the entire content of which is Incorporated herein by reference.

technical field

The present application relates to the field of artificial intelligence (Artificial Intelligence, AI), and in particular, to a method, system, electronic device and storage medium for detecting body composition.

Background technique

At present, most of the body fat scales on the market can only measure the user's weight information. When the body fat scale combines the measured user weight information to detect the user's other body components (such as body fat, muscle, protein, minerals, etc.) Or when evaluating, the user needs to manually input some auxiliary information of himself, such as height, gender and other information, the operation is cumbersome, the detection efficiency is low, and the user experience is affected.

SUMMARY OF THE INVENTION

The present application provides a method, system, electronic device and storage medium for detecting body composition, which can detect body composition without requiring the user to manually input auxiliary information, reduce user operations, and effectively improve detection efficiency.

To achieve the above object, the application adopts the following technical solutions:

In a first aspect, a method for detecting body composition is provided, comprising:

Obtain the user's weight and the pressure distribution map of the user's sole; input the weight and the pressure distribution map into a preset first detection model, and obtain the user's assistance output from the first detection model information, wherein the auxiliary information is information used to assist in detecting human body composition, the auxiliary information includes the user's height and gender, and the first detection model is used for the user's weight and the pressure distribution map of the sole of the foot The auxiliary information of the user is predicted; the body composition information of the user is determined according to the weight of the user and the auxiliary information.

In the above embodiment, the electronic device obtains the user's weight and the pressure distribution map of the user's soles, inputs the weight and the pressure distribution map into the preset first detection model, and obtains the user's auxiliary information output by the first detection model, The auxiliary information is the information used to assist in detecting body composition. The auxiliary information includes the user's height and gender, and then the user's body composition information can be determined according to the user's weight and auxiliary information. Since the user's weight and the pressure distribution of the sole of the foot are in the It can be measured when the user is standing, so that the detection of human body composition can be realized without the need for the user to manually input auxiliary information, the user operation is reduced, and the detection efficiency is effectively improved.

In a possible implementation manner of the first aspect, the acquiring a pressure distribution map of the sole of the user's foot includes:

Acquire the pressure distribution value of the sole of the user's foot, the pressure distribution value of the sole of the foot is obtained by the user standing on the body weight measurement device with both feet and collected by the pressure sensor of the body weight measurement device; The distribution value is converted into an initial pressure distribution map, and the initial pressure distribution map is preprocessed to obtain a final pressure distribution map for inputting the first detection model. By preprocessing the initial pressure distribution map to obtain the pressure distribution map for inputting the first detection model, the image quality of the pressure distribution map can be improved, thereby improving the calculation accuracy.

In a possible implementation manner of the first aspect, the pressure sensor includes at least one sensor unit, the at least one sensor unit forms an array according to a preset arrangement rule, and the pressure distribution value includes at least one pressure value, each Each of the sensor units corresponds to one of the pressure values, and the converting the pressure distribution value into an initial pressure distribution map includes: converting the pressure distribution value into an initial pressure distribution map according to the preset arrangement rule . Therefore, the pressure distribution map can reflect the pressure information of the pressure on each part of the sole of the user's foot.

In a possible implementation manner of the first aspect, the initial pressure distribution map includes at least one gray area, each gray area corresponds to a gray value, and the predetermined arrangement rule Converting the pressure distribution value into an initial pressure distribution map includes: converting the pressure distribution value into an initial pressure distribution map according to the preset arrangement rule and a pre-stored mapping relationship between pressure values and grayscale values.

In a possible implementation manner of the first aspect, the determining the user's body composition information according to the user's weight and the auxiliary information includes:

Obtain the body impedance of the user, the body impedance is obtained by the user standing on the body weight measurement device with both feet and collected by the impedance measurement device of the body weight measurement device; and the auxiliary information is input into a preset second detection model, and the body composition information output by the second detection model is obtained, wherein the second detection model is used according to the user's body impedance, weight and auxiliary information Body composition information of the user is determined. Human body impedance can reflect the electrical conductivity of human organs. Therefore, it is related to body composition. The user's body composition information can be determined through the user's body impedance, weight and auxiliary information, which can improve the calculation accuracy.

In a possible implementation manner of the first aspect, before inputting the body impedance, the body weight and the auxiliary information into a preset second detection model, the method further includes:

acquiring a detection mode, the detection mode includes a first detection mode and a second detection mode;

Correspondingly, the inputting the body impedance, the body weight and the auxiliary information into a preset second detection model to obtain the body composition information output by the second detection model includes:

If the detection mode is the first detection mode, the body impedance, the body weight and the auxiliary information are input into a preset second detection model to obtain the body composition information output by the second detection model.

Among them, the first detection mode is a visitor mode, and the second detection mode is a host mode, and different calculation models of body composition information are selected according to the detection modes to adapt to user needs and improve user experience.

In a possible implementation manner of the first aspect, the method further includes:

If the detection mode is the second detection mode, acquiring the age of the user;

Input the body impedance, the weight, the age and the auxiliary information into a preset third detection model, and obtain the body composition information output by the third detection model, wherein the third detection model uses to determine the user's body composition information according to the user's body impedance, weight, age and auxiliary information. The age factor is added to the third detection model to calculate the user's body composition information, which improves the calculation accuracy.

In a possible implementation manner of the first aspect, after determining the body composition information of the user according to the weight of the user and the auxiliary information, the method further includes: according to the weight of the user and the auxiliary information and the body composition information, determine a health report containing the user's physical health status and/or health guidance advice, and output the health report.

In a second aspect, a device for detecting body composition is provided, comprising:

an acquisition module for acquiring the user's weight and the pressure distribution map of the user's sole;

A calculation module, configured to input the body weight and the pressure distribution map into a preset first detection model, and obtain auxiliary information of the user output by the first detection model, wherein the auxiliary information is used for Auxiliary detection of body composition information, the auxiliary information includes the height and gender of the user, and the first detection model is used to predict and obtain the auxiliary information of the user according to the weight of the user and the pressure distribution map of the sole of the foot;

A determination module, configured to determine the body composition information of the user according to the weight of the user and the auxiliary information.

In a possible implementation manner of the second aspect, the obtaining module includes:

An acquisition unit, configured to acquire the pressure distribution value of the sole of the user's foot, where the pressure distribution value of the sole of the foot is obtained by the user standing on the body weight measurement device and collected by the pressure sensor of the body weight measurement device ;

The processing unit is configured to convert the pressure distribution value into an initial pressure distribution map, and preprocess the initial pressure distribution map to obtain a final pressure distribution map for inputting the first detection model.

In a possible implementation manner of the second aspect, the pressure sensor includes at least one sensor unit, the at least one sensor unit forms an array according to a preset arrangement rule, and the pressure distribution value includes at least one pressure value, each Each of the sensor units corresponds to one of the pressure values, and the processing unit is specifically used for:

The pressure distribution value is converted into an initial pressure distribution map according to the preset arrangement rule.

In a possible implementation manner of the second aspect, the initial pressure distribution map includes at least one gray area, each gray area corresponds to a gray value, and the processing unit is further configured to:

The pressure distribution value is converted into an initial pressure distribution map according to the preset arrangement rule and the pre-stored mapping relationship between the pressure value and the gray value.

In a possible implementation manner of the second aspect, the determining module is specifically configured to:

acquiring the body impedance of the user, the body impedance is obtained by the user standing on the body weight measurement device with both feet and collected by the impedance measurement device of the body weight measurement device;

Inputting the body impedance, the body weight and the auxiliary information into a preset second detection model, and obtaining the body composition information output by the second detection model, wherein the second detection model is used according to the The user's body impedance, weight, and auxiliary information determine the user's body composition information.

In a possible implementation manner of the second aspect, the determining module is specifically configured to:

acquiring a detection mode, the detection mode includes a first detection mode and a second detection mode;

If the detection mode is the first detection mode, the body impedance, the body weight and the auxiliary information are input into a preset second detection model to obtain the body composition information output by the second detection model.

In a possible implementation manner of the second aspect, the determining module is further configured to:

If the detection mode is the second detection mode, acquiring the age of the user;

Input the body impedance, the weight, the age and the auxiliary information into a preset third detection model, and obtain the body composition information output by the third detection model, wherein the third detection model uses to determine the user's body composition information according to the user's body impedance, weight, age and auxiliary information.

In a possible implementation manner of the second aspect, the determining module is further configured to:

According to the user's weight, auxiliary information and the body composition information, a health report containing the user's physical health status and/or health guidance advice is determined, and the health report is output.

In a third aspect, an electronic device is provided, including a processor configured to execute a computer program stored in a memory, so as to implement the method for detecting body composition described in the first aspect.

In a fourth aspect, a system for detecting body composition is provided, comprising a weight measurement device and the electronic device according to the third aspect, wherein a pressure sensor is provided in the weight measurement device.

In a possible implementation manner of the fourth aspect, the body weight detection device is further provided with an impedance measurement device.

In a fifth aspect, a computer-readable storage medium is provided, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, implements the method for detecting body composition described in the first aspect.

A sixth aspect provides a computer program product that, when the computer program product runs on a terminal device, enables the terminal device to perform the method for detecting body composition described in the first aspect above.

It can be understood that, for the beneficial effects of the foregoing second aspect to the sixth aspect, reference may be made to the relevant descriptions in the foregoing first aspect, and details are not described herein again.

Description of drawings

1 is a schematic diagram of a system for detecting body composition to which the method for detecting body composition provided by an embodiment of the present application is applicable;

2 is a schematic diagram of a pressure sensor provided by an embodiment of the present application;

3 is a schematic diagram of a body weight measurement device provided by an embodiment of the present application;

4 is a schematic flowchart of a method for detecting body composition provided by an embodiment of the present application;

5 is a schematic diagram of the pressure values at the positions of the sensor units in an embodiment of the application;

6 is a schematic diagram of a pressure distribution diagram provided by an embodiment of the present application;

7 is a schematic diagram of a training method of a first detection model provided by an embodiment of the present application;

FIG. 8 is a schematic diagram of a method for predicting auxiliary information provided by an embodiment of the present application;

9 is a schematic diagram of a method for detecting body composition provided by an embodiment of the present application;

10 is a schematic diagram of an interface in a first detection mode provided by an embodiment of the present application;

11 is a schematic diagram of a registration interface provided by an embodiment of the present application;

12 is a schematic diagram of an interface in a second detection mode provided by an embodiment of the present application;

FIG. 13 is a schematic diagram of an electronic device provided by an embodiment of the present application.

detailed description

In the following description, for the purpose of illustration rather than limitation, specific details such as a specific system structure and technology are set forth in order to provide a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be practiced in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

It is to be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described feature, integer, step, operation, element and/or component, but does not exclude one or more other The presence or addition of features, integers, steps, operations, elements, components and/or sets thereof.

It will also be understood that, as used in this specification and the appended claims, the term "and/or" refers to and including any and all possible combinations of one or more of the associated listed items.

As used in the specification of this application and the appended claims, the term "if" may be contextually interpreted as "when" or "once" or "in response to determining" or "in response to detecting ". Similarly, the phrases "if it is determined" or "if the [described condition or event] is detected" may be interpreted, depending on the context, to mean "once it is determined" or "in response to the determination" or "once the [described condition or event] is detected. ]" or "in response to detection of the [described condition or event]".

In addition, in the description of the present application, the terms "first", "second" and the like are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

References in this specification to "one embodiment" or "some embodiments" and the like mean that a particular feature, structure or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in other embodiments," etc. in various places in this specification are not necessarily All refer to the same embodiment, but mean "one or more but not all embodiments" unless specifically emphasized otherwise. The terms "including", "including", "having" and their variants mean "including but not limited to" unless specifically emphasized otherwise.

Body composition refers to the content information of fat, muscle, protein, minerals and other components in the human body. Detection of body composition information is of great significance for evaluating the user's physical state and guiding the user's medical care. At present, a body fat scale is generally used to detect body composition. When using a body fat scale to detect body composition, in addition to the user's weight information, the user's auxiliary information is also required. The user's auxiliary information includes the user's height and gender.

In order to obtain the user's auxiliary information, the user can manually input the method, or a height measuring device can be attached to the body fat scale to measure the user's height. The height measuring device can be an infrared measuring device or an ultrasonic measuring device fixed on the top of the user's head, the infrared measuring device transmits infrared rays to the top of the user's head, calculates the user's height according to the time of transmitting and receiving infrared rays, and the ultrasonic measuring device transmits ultrasonic waves to the top of the user's head, Calculate the user's height based on the time of transmitting and receiving ultrasonic waves. After measuring the height of the user, the height measuring device sends the measured height to the body fat scale.

However, when the user manually enters the auxiliary information, the user needs to know his height in advance, or he needs to measure the height with the help of the soft ruler attached to the body fat scale, and then input the height into the body fat scale, which is cumbersome to operate and affects the user experience; The height measuring device attached to the scale results in a large volume of the body fat scale, which is inconvenient for transportation and storage.

To this end, the present application provides a method for body composition detection, in which the electronic device obtains the user's weight and the pressure distribution map of the user's sole, inputs the weight and the pressure distribution map into a preset first detection model, and obtains the first detection model. Auxiliary information of the user output by the detection model, the auxiliary information includes the user's height and gender, and then the user's body composition information can be determined according to the user's weight and auxiliary information, so that the body fat scale can be adjusted without increasing the volume of the body fat scale. The detection of human body composition can be realized by requiring the user to manually input auxiliary information, thereby reducing user operations and effectively improving the detection efficiency.

The method for detecting body composition provided by the present application will be exemplarily described below with reference to specific embodiments.

FIG. 1 is a schematic diagram of a system for detecting body composition to which the method for detecting body composition provided by an embodiment of the present application is applied. As shown in FIG. 1 , the system for detecting body composition provided by this embodiment of the present application includes an electronic device 100 , a body weight measurement device 200 , and a pressure sensor 300 . The weight measuring device 200 may be a body fat scale or an electronic scale. Both the weight measuring device 200 and the pressure sensor 300 are connected in communication with the electronic device 100. The pressure sensor 300 is arranged on the weight measuring device 200. When the device 200 is on, the electronic device acquires the user's weight sent by the weight measuring device 200 and the pressure distribution map of the user's sole sent by the pressure sensor 300 . The electronic device determines the user's auxiliary information according to the user's weight and the pressure distribution map of the sole of the foot, and then determines the user's body composition information according to the user's auxiliary information and weight.

Exemplarily, as shown in FIG. 2 , the pressure sensor 300 includes a piezoresistive sensor 301 and a circuit module 302 , and the piezoresistive sensor 301 is connected in communication with the circuit module 302 . The piezoresistive sensor 301 includes a left foot piezoresistive sensor and a right foot piezoresistive sensor. Both the left foot piezoresistive sensor and the right foot piezoresistive sensor include at least one sensor unit 303, and the at least one sensor unit 303 is formed according to a preset arrangement rule Each sensor unit 303 is used to collect the pressure value applied to the sensor unit 303, and the circuit module 302 is used to convert the pressure value collected by each sensor unit 303 into a resistance, and according to the pressure value corresponding to the resistance and the preset arrangement rule And determine the pressure distribution map.

In a possible implementation manner, the piezoresistive sensor 301 is a thin film structure, and the thin film structure and the circuit module 302 are embedded in the body weight measuring device 200 . For example, as shown in FIG. 3 , the weight measurement device 200 includes a weight measurement module 201 and two flat plates 202 arranged on the weight measurement module 201 , and the pressure sensor 300 is arranged between the two flat plates 202 , thereby reducing the size of the weight measurement device. volume.

As shown in FIG. 1 , in a possible implementation manner, the system further includes an impedance measurement device 400 , the impedance measurement device 400 is connected in communication with the electronic device 100 , and the impedance measurement device 400 is a device for measuring human body impedance. Because the fat, muscle and other components in the human body have different electrical conductivity, the impedance of the human body of different users is different, and the impedance of the human body can be measured by passing a weak current in the human body. In a possible implementation manner, the impedance measurement device 400 is arranged on the body weight measurement device 200 , for example, it can be arranged between the two flat plates 202 of the body weight measurement device 200 . When the user stands barefoot on the body weight measuring apparatus 200, the impedance measuring apparatus 400 passes a weak current in the human body to obtain the impedance of the human body, and sends the impedance of the human body to the electronic device. The electronic device determines the user's auxiliary information according to the user's weight and the pressure distribution map of the sole, and then determines the user's body composition information according to the user's auxiliary information, body impedance and weight.

The electronic device 100 may be integrated into the body weight measurement apparatus 200 , or may be provided independently of the body weight measurement apparatus 200 . If the electronic device is independent of the weight measuring apparatus 200, the electronic device may be a terminal device such as a mobile phone, a tablet computer, a handheld computer, and a personal digital assistant (PDA).

If the electronic device 100 is integrated on the body weight measurement device 200, the system may further include a terminal that is connected to the electronic device 100 in communication. After the electronic device 100 determines the body composition information, it sends the body composition information to the terminal, and the terminal displays the body composition on the display interface. Ingredient information.

The following describes the method for detecting body composition provided by the embodiments of the present application by taking an electronic device integrated into a body weight measuring device as an example.

As shown in FIG. 4 , the method for detecting body composition provided by the embodiment of the present application includes:

S101: Acquire a user's weight and a pressure distribution map of the user's sole.

Specifically, the user stands with both feet on the weight measuring device, the weight measuring device sends the measured user's weight to the electronic device, and the pressure sensor sends the measured pressure distribution value of the sole of the foot to the electronic device. The pressure sensor includes at least one sensor unit, each sensor unit can measure a pressure value, the pressure distribution value includes the pressure value corresponding to each sensor unit, and the pressure value can be the average value of the pressure values within a preset time period, such as 5 The average of the pressure values in seconds to improve the accuracy of the collected pressure values.

After obtaining the pressure distribution value of the user's sole, the electronic device converts the pressure distribution value into a pressure distribution map according to the arrangement rule of the sensor units of the pressure sensor. For example, as shown in FIG. 5 , the sensor units are arranged in the form of a matrix, and the pressure sensor can obtain the pressure value at the location of each sensor unit according to the arrangement rule of each sensor unit and the pressure distribution value. After the electronic device obtains the pressure value at the location of each sensor unit, it obtains the gray value of the location of each sensor unit according to the pre-stored mapping relationship between the pressure value and the gray value, and then according to the gray value of the location of each sensor unit. The pressure distribution map can be determined.

The range of the gray value is 0 to 255. The larger the pressure value is, the larger the gray value is. On the contrary, the smaller the pressure value is, the smaller the gray value is. For example, the maximum pressure value among the pressure distribution values corresponds to a grayscale value of 255, and the minimum pressure value corresponds to a grayscale value of 0. The pressure distribution map can be a grayscale map or a color map. If the pressure distribution map is a grayscale map, one pressure value corresponds to one grayscale value, and if the pressure distribution map is a color map, one pressure value corresponds to the grayscale values of the red, green, and yellow channels. As shown in FIG. 6 , in a possible implementation manner, the pressure distribution map is a grayscale map, that is, the pressure distribution map includes at least one grayscale region, and each grayscale region corresponds to a grayscale value. According to the pressure distribution map, information such as the user's foot length, foot contour, and pressure on different parts of the foot can be determined.

In a possible implementation manner, after the electronic device obtains the pressure distribution value, according to the arrangement rule of the sensor units and the mapping relationship between the pressure value and the gray value, the pressure distribution value is first converted into an initial pressure distribution map, and then After preprocessing the initial pressure distribution map, the pressure distribution map is obtained. Among them, the preprocessing includes image enhancement, image denoising, histogram equalization, normalization and other operations on the initial pressure distribution map. After the preprocessing operation, the image quality of the initial pressure distribution map can be improved, so as to obtain the image quality Higher pressure profile.

In a possible implementation, the pressure sensor can also convert the pressure distribution value into a pressure distribution map according to the arrangement rule of the sensor units and the mapping relationship between the pressure value and the gray value, and then send the pressure distribution map to the electronic equipment.

S102: Input the body weight and the pressure distribution map into a preset first detection model, and obtain auxiliary information of the user output by the first detection model, where the auxiliary information is used to assist in detecting a human body The auxiliary information includes the height and gender of the user, and the first detection model is used to predict and obtain the auxiliary information of the user according to the weight of the user and the pressure distribution map of the sole of the foot.

The first detection model is obtained after training a preset first algorithm model by using a machine learning algorithm. Specifically, as shown in FIG. 7 , first collect training samples, the training samples include plantar pressure distribution maps of multiple users, each plantar pressure distribution map is preprocessed, and the preprocessed plantar pressure distribution map is set to The label includes height and gender, and the weight corresponding to each plantar pressure distribution map is recorded. Take part of the training samples as the training set and part of the training samples as the test set. The pressure distribution map in the training set and the weight corresponding to the pressure distribution map are input into the preset first algorithm model, the loss function is set, and the preset first algorithm model is trained. When the training iteration of the first algorithm model reaches a preset number of times or the loss function no longer decreases, the training ends, and the trained first algorithm model is obtained. Then input the pressure distribution map in the test set and the weight corresponding to the pressure distribution map into the first algorithm model after training. If the height and gender predicted by the first algorithm model after training are consistent with the labels corresponding to the test set, the training will be The latter first algorithm model is used as the first detection model. The first algorithm model may be a model using machine learning algorithms such as convolutional neural networks, random forests, and SVM support vector machines.

After obtaining the first detection model, the electronic device can predict the user's auxiliary information according to the first detection model. Specifically, as shown in FIG. 8 , the electronic device obtains the initial pressure distribution map sent by the pressure collection device, and after preprocessing the initial pressure distribution map, obtains the pressure distribution map of the user's sole, and simultaneously obtains the pressure distribution map collected by the body weight measurement device. Weight, the weight and the pressure distribution map of the sole of the foot are input into the first detection model, and the height and gender of the user are output.

S103: Determine the body composition information of the user according to the weight of the user and the auxiliary information.

Specifically, the electronic device determines the user's body composition information according to the user's weight, the correspondence between the auxiliary information and the body composition information, and the user's weight and the auxiliary information.

In a possible implementation manner, the electronic device determines the user's body composition information according to a preset second detection model, wherein the second detection model is used to determine the user's body composition information according to the user's body impedance, weight, and auxiliary information , which is obtained by pre-training the second computing model by using a machine learning algorithm. Specifically, a training sample is obtained first, and the training sample includes the user's body impedance, weight, auxiliary information and corresponding body composition information. The electronic device can obtain the second detection model by training the preset second calculation model according to the training sample.

The electronic device obtains the body impedance from the impedance measuring device, and inputs the body impedance, body weight, and auxiliary information into the second detection model, so as to obtain the user's body composition information.

In a possible implementation manner, in addition to the second detection model stored on the electronic device, a third detection model is also stored, and the third detection model is used to determine the user's human body according to the user's body impedance, weight, age, and auxiliary information. Ingredient information. The third detection model is obtained after training the preset third calculation model by using a machine learning algorithm, and the training samples used for training include the user's body impedance, weight, auxiliary information and corresponding body composition information. , including the corresponding age.

As shown in FIG. 9 , after determining the auxiliary information of the user according to the pressure distribution map, the electronic device obtains the current detection mode, and the detection mode includes a first detection mode and a second detection mode, wherein the first detection mode is a visitor mode, and the first detection mode is a visitor mode. The second detection mode is the master mode. If the detection mode is the first detection mode, input the user's body impedance, body weight, and auxiliary information into the second detection model to obtain the user's body composition information, and output the body composition information, for example, send the body composition information to the terminal, the terminal Display body composition information on the display interface. If the detection mode is the second detection mode, the electronic device obtains the identity information input by the user, the identity information includes the user's age, and inputs the user's body impedance, age, weight, and auxiliary information into the third detection model to obtain the user's body composition information , and output the body composition information, for example, send the body composition information to the terminal, and the terminal displays the body composition information on the display interface. At the same time, the identity information input by the user is sent to the terminal for display.

For example, in an application scenario, the electronic device is integrated on the body weight measurement device, the electronic device is also connected in communication with a mobile phone, and application software paired with the electronic device is installed on the mobile phone. As shown in Figure 10, the user experiences using the weight measurement device for the first time, sets the detection mode to the first detection mode, namely the guest mode, on the application software of the mobile phone, stands on the weight measurement device, and then clicks "Start" on the mobile phone interface Measurement" option. The mobile phone sends the visitor mode set by the user and the instruction to start the measurement to the electronic device, and the electronic device instructs the weight measuring device to measure the user's weight according to the instruction to start the measurement, instructs the pressure sensor to measure the pressure distribution map of the user's sole, and instructs the impedance measurement. The device measures and obtains the impedance of the human body, and obtains the user's weight, the pressure distribution map of the sole of the foot, and the impedance of the human body. The electronic device determines the user's auxiliary information according to the user's weight and the pressure distribution map of the sole of the foot, and then inputs the user's body impedance, weight, and auxiliary information into the second detection model to obtain the user's body composition information. After obtaining the body composition information, the electronic device sends the body composition information to the mobile phone, and the mobile phone displays the body composition information on the display interface.

If the current detection mode is the visitor mode, the user does not need to input any information, but only needs to stand on the body weight measurement device for a period of time to obtain the body composition information, so that the user can experience the product and protect personal privacy, which improves the user experience.

In another application scenario, the electronic device is integrated on the body weight measurement device, the electronic device is also connected in communication with a mobile phone, and application software paired with the electronic device is installed on the mobile phone. As shown in FIG. 11 , the user inputs the identity information through the application software on the mobile phone in advance, completes the identity registration, and the mobile phone sends the identity information to the electronic device. The registered identity information includes the user's identification information, such as name or nickname, and also includes the user's age, personal profile and other information.

As shown in Figure 12, when the user uses the weight measurement device, the user first completes the identity authentication through the application software, the mobile phone sends the identity authentication information to the electronic device, and the electronic device determines the identity information that matches the identity authentication information according to the identity authentication information, and It is determined that the current detection mode is the master mode, and at the same time, the identity information is sent to the mobile phone, and the mobile phone displays it on the display interface. When the user stands on the weight measuring device and clicks the "start measurement" option on the mobile phone interface, the mobile phone sends the instruction to start the measurement to the electronic device, and the electronic device instructs the weight measuring device to measure the user's weight according to the instruction to start the measurement. The pressure distribution diagram of the user's sole is measured by the instructing pressure sensor, the impedance of the human body is measured by the instructing impedance measuring device, and the weight of the user, the pressure distribution diagram of the sole of the foot and the human body impedance are acquired. The electronic device determines the user's auxiliary information according to the user's weight and the pressure distribution map of the sole of the foot, and then inputs the age, body impedance and weight, and auxiliary information in the user's identity information into the third detection model to obtain a more accurate user's body composition. information. After the electronic device obtains the body composition information, it sends the user's body composition information, body impedance, weight and auxiliary information to the mobile phone, and the mobile phone supplements the user's body composition information, body impedance, The weight and auxiliary information can be displayed in the form of text or pictures.

If the current detection mode is the master mode, after the electronic device obtains the user's identity information, the user does not need to input any more information, and only needs to stand on the weight measuring device for a period of time to obtain complete user information.

In a possible implementation manner, after determining the body composition information, the electronic device evaluates the user's physical health status according to the user's weight, auxiliary information and body composition information, and determines the health guidance advice corresponding to the user, according to The physical health status and health guidance suggest generating a health report, outputting the health report, and sending the health report to a terminal that is communicatively connected to the electronic device. Among them, the health report can include the user's body shape, whether the body shape is standard, weight change curve, health level, exercise suggestions, fitness methods, etc. If the user is male, the fitness method is generally based on strength exercises. If the user is female, the fitness method Generally, plastic fat loss is the main method.

Wherein, the second detection model and the third detection model may be a multiple linear regression model or a machine learning algorithm model. In a possible implementation manner, the second detection model and the third detection model are multiple linear regression models, and the third detection model is expressed by a formula as y _i =a _i1 H+a _i2 W+a _i3 G+a _i4 Z +a _i5 Age+a _i6 , where H is height, W is weight, G is gender, Z is body impedance, y _i is muscle mass, protein, basal metabolic rate, body fat rate, bone salt, visceral fat, For any body composition such as 5-item segmental muscle mass and 5-item segmental fat mass, a _i1 , a _i2 , a _i3 , a _i4 , a _i5 and a _i6 all represent coefficients corresponding to each body composition. In a possible implementation manner, the second detection model is expressed by a formula as y _i =a _i1 H+a _i2 W+a _i3 G+a _i4 Z+a _i5 Age+a _i6 , and a _i5 =0.

In the above embodiment, the electronic device obtains the user's weight and the pressure distribution map of the user's soles, inputs the weight and the pressure distribution map into the preset first detection model, and obtains the user's auxiliary information output by the first detection model, The auxiliary information is the information used to assist in detecting body composition. The auxiliary information includes the user's height and gender, and then the user's body composition information can be determined according to the user's weight and auxiliary information. Since the user's weight and the pressure distribution of the sole of the foot are in the It can be measured when the user is standing, so that the body composition detection can be realized without the need to increase the volume of the body weight measurement device or the user to manually input auxiliary information, reduce user operations, and effectively improve the detection efficiency.

It should be understood that the size of the sequence numbers of the steps in the above embodiments does not mean the sequence of execution, and the execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

Based on the same inventive concept, an embodiment of the present application also provides an electronic device. As shown in FIG. 13 , the electronic device provided by the embodiment of the present application includes a processor 110, a memory 120, an input unit 130, a display unit 140, a sensor 150, Audio circuit 160 and communication module 170 . Those skilled in the art can understand that the structure shown in FIG. 13 does not constitute a limitation on the electronic device, and may include more or less components than the one shown, or combine some components, or arrange different components.

The memory 120 may be used to store software programs and modules, and the processor 110 executes various functional applications and data processing of the electronic device by running the software programs and modules stored in the memory 120 . The memory 120 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function (such as a sound playback function, an image playback function, etc.), and the like; Data (such as audio data) created by the use of electronic equipment, etc. Additionally, memory 120 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.

The input unit 130 may be used to receive input numerical or character information, and generate key signal input related to user settings and function control of the electronic device. Specifically, the input unit 130 may include a touch panel 131 and other input devices 132 . The touch panel 131, also referred to as a touch screen, can collect the user's touch operations on or near it (such as the user's finger, stylus, etc., any suitable objects or accessories on or near the touch panel 131 ). operation), and drive the corresponding connection device according to the preset program. Optionally, the touch panel 131 may include two parts, a touch detection device and a touch controller. Among them, the touch detection device detects the user's touch orientation, detects the signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, converts it into contact coordinates, and then sends it to the touch controller. To the processor 110, and can receive the command sent by the processor 110 and execute it. In addition, the touch panel 131 can be implemented in various types such as resistive, capacitive, infrared, and surface acoustic waves. In addition to the touch panel 131, the input unit 130 may also include other input devices 132. Specifically, other input devices 132 may include, but are not limited to, one or more of physical keyboards, function keys (such as volume control keys, switch keys, etc.), trackballs, mice, joysticks, and the like.

The display unit 140 may be used to display information input by the user or information provided to the user and various menus of the electronic device. The display unit 140 may include a display panel 141, and optionally, the display panel 141 may be configured in the form of a liquid crystal display (Liquid Crystal Display, LCD), an organic light-emitting diode (Organic Light-Emitting Diode, OLED), and the like. Further, the touch panel 131 can cover the display panel 141. When the touch panel 131 detects a touch operation on or near it, it transmits it to the processor 110 to determine the type of the touch event, and then the processor 110 determines the type of the touch event according to the touch event. Type provides corresponding visual output on display panel 141 . Although in FIG. 13 , the touch panel 131 and the display panel 141 are used as two independent components to realize the input and input functions of the electronic device, but in some embodiments, the touch panel 131 and the display panel 141 may be integrated And realize the input and output functions of electronic equipment.

The electronic device may also include at least one sensor 150, such as light sensors, motion sensors, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor may adjust the brightness of the display panel 141 according to the brightness of the ambient light, and the proximity sensor may turn off the display panel 141 and the display panel 141 when the electronic device is moved to the ear. / or backlight. As a type of motion sensor, the accelerometer sensor can detect the magnitude of acceleration in all directions (generally three axes), and can detect the magnitude and direction of gravity when stationary, and can be used for applications that recognize the posture of electronic devices (such as horizontal and vertical screen switching, related games, magnetometer attitude calibration), vibration recognition related functions (such as pedometer, tapping), etc.; as for other sensors such as gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc. that can be configured on electronic devices, here No longer.

The audio circuit 160, the speaker 161, and the microphone 162 may provide an audio interface between the user and the electronic device. The audio circuit 160 can transmit the received audio data converted electrical signal to the speaker 161, and the speaker 161 converts it into a sound signal for output; on the other hand, the microphone 162 converts the collected sound signal into an electrical signal, which is converted by the audio circuit 160 After receiving, it is converted into audio data, and then the audio data is output to the processor 110 for processing, and then sent to, for example, another electronic device through the RF circuit 110, or the audio data is output to the memory 120 for further processing.

The communication module 170 can be used to support data exchange between the electronic device and other electronic devices including wireless communication such as BT, WLAN (such as Wi-Fi), Zigbee, FM, NFC, IR, or general 2.4G/5G wireless communication technologies .

The processor 110 is the control center of the electronic device, using various interfaces and lines to connect various parts of the entire electronic device, by running or executing the software programs and/or modules stored in the memory 120, and calling the data stored in the memory 120. , perform various functions of electronic equipment and process data, so as to monitor electronic equipment as a whole. Optionally, the processor 110 may include one or more processing units; preferably, the processor 110 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, etc. , the modem processor mainly deals with wireless communication. It can be understood that, the above-mentioned modulation and demodulation processor may not be integrated into the processor 110 .

In the foregoing embodiments, the description of each embodiment has its own emphasis. For parts that are not described or described in detail in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. Module completion, that is, dividing the internal structure of the device into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment may be integrated in one processing unit, or each unit may exist physically alone, or two or more units may be integrated in one unit, and the above-mentioned integrated units may adopt hardware. It can also be realized in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing from each other, and are not used to limit the protection scope of the present application. For the specific working processes of the units and modules in the above-mentioned system, reference may be made to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

The integrated unit, if implemented in the form of a software functional unit and sold or used as an independent product, may be stored in a computer-readable storage medium. Based on this understanding, the present application realizes all or part of the processes in the methods of the above embodiments, which can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When executed by a processor, the steps of each of the above method embodiments can be implemented. Wherein, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file or some intermediate form, and the like. The computer-readable medium may include at least: any entity or device capable of carrying the computer program code to the photographing device/electronic device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signals, telecommunication signals, and software distribution media. For example, U disk, mobile hard disk, disk or CD, etc.

The units described as separate components may or may not be physically separated, and components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.

In the embodiments provided in this application, it should be understood that the disclosed apparatus/network device and method may be implemented in other manners. For example, the apparatus/network device embodiments described above are only illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units. Or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. On the other hand, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in electrical, mechanical or other forms.

Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each particular application, but such implementations should not be considered beyond the scope of this application.

Finally, it should be noted that: the above are only specific embodiments of the present application, but the protection scope of the present application is not limited to this, and any changes or replacements within the technical scope disclosed in the present application should be covered by the present application. within the scope of protection of the application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims (12)

1. A method for detecting body composition, comprising:

   Obtain the user's weight and the pressure distribution map of the user's sole;

   Input the body weight and the pressure distribution map into a preset first detection model, and obtain the auxiliary information of the user output by the first detection model, wherein the auxiliary information is used for auxiliary detection of body composition. information, the auxiliary information includes the height and gender of the user, and the first detection model is used to predict and obtain the auxiliary information of the user according to the weight of the user and the pressure distribution map of the sole of the foot;

   The body composition information of the user is determined according to the weight of the user and the auxiliary information.
2. The method according to claim 1, wherein the acquiring the pressure distribution map of the sole of the user comprises:

   acquiring the pressure distribution value of the sole of the user's foot, where the pressure distribution value of the sole of the foot is obtained by the user standing on the body weight measurement device with both feet and collected by the pressure sensor of the body weight measurement device;

   The pressure distribution value is converted into an initial pressure distribution map, and the initial pressure distribution map is preprocessed to obtain a final pressure distribution map for inputting the first detection model.
3. The method according to claim 2, wherein the pressure sensor comprises at least one sensor unit, the at least one sensor unit forms an array according to a preset arrangement rule, and the pressure distribution value comprises at least one pressure value, each Each of the sensor units corresponds to one of the pressure values, and the converting the pressure distribution value into an initial pressure distribution diagram includes:

   The pressure distribution value is converted into an initial pressure distribution map according to the preset arrangement rule.
4. The method according to claim 3, wherein the initial pressure distribution map includes at least one gray area, each gray area corresponds to a gray value, and the predetermined distribution rule The above pressure distribution value is converted into the initial pressure distribution map, including:

   The pressure distribution value is converted into an initial pressure distribution map according to the preset arrangement rule and the pre-stored mapping relationship between the pressure value and the gray value.
5. The method according to any one of claims 2 to 4, wherein the determining the user's body composition information according to the user's weight and the auxiliary information comprises:

   acquiring the body impedance of the user, the body impedance is obtained by the user standing on the body weight measurement device with both feet and collected by the impedance measurement device of the body weight measurement device;

   Inputting the body impedance, the body weight and the auxiliary information into a preset second detection model, and obtaining the body composition information output by the second detection model, wherein the second detection model is used according to the The user's body impedance, weight, and auxiliary information determine the user's body composition information.
6. The method according to claim 5, wherein before inputting the body impedance, the body weight and the auxiliary information into a preset second detection model, the method further comprises:

   acquiring a detection mode, the detection mode includes a first detection mode and a second detection mode;

   Correspondingly, the inputting the body impedance, the body weight and the auxiliary information into a preset second detection model to obtain the body composition information output by the second detection model includes:

   If the detection mode is the first detection mode, the body impedance, the body weight and the auxiliary information are input into a preset second detection model to obtain the body composition information output by the second detection model.
7. The method according to claim 6, wherein the method further comprises:

   If the detection mode is the second detection mode, acquiring the age of the user;

   Input the body impedance, the weight, the age and the auxiliary information into a preset third detection model, and obtain the body composition information output by the third detection model, wherein the third detection model uses to determine the user's body composition information according to the user's body impedance, weight, age, and auxiliary information.
8. The method according to any one of claims 1 to 7, wherein after determining the body composition information of the user according to the weight of the user and the auxiliary information, the method further comprises:

   According to the user's weight, auxiliary information and the body composition information, a health report containing the user's physical health status and/or health guidance advice is determined, and the health report is output.
9. An electronic device, characterized by comprising a processor, which is configured to execute a computer program stored in a memory, so as to implement the method according to any one of claims 1 to 8.
10. A system for detecting body composition, comprising a weight measurement device and an electronic device as claimed in claim 9, wherein a pressure sensor is provided in the weight measurement device.
11. The system for detecting body composition according to claim 10, wherein the body weight detecting device is further provided with an impedance measuring device.
12. A computer-readable storage medium storing a computer program, characterized in that, when the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

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