State information determination, health index information determination method and device

Abstract

This disclosure proposes a method for determining state information, comprising: acquiring first state information of a first user; determining similar users of the first user among the at least one second user based on the first state information of the first user and the first state information of at least one second user that has been stored; and determining second state information of the first user based on the second state information of the similar user.

Description

Technical Field

[0001] This disclosure relates to the field of data processing, and more specifically, to methods for determining state information, methods for determining health indicator information, devices for determining state information, devices for determining health indicator information, component analysis systems, electronic devices, and computer-readable storage media. Background Technology

[0002] When a user undergoes body composition analysis, they need to input status information. Based on this information, information about certain components in the user's body can be determined. Among the status information that users need to input, some can be determined relatively accurately, such as the user's age and gender, but some cannot be determined accurately. Summary of the Invention

[0003] Some embodiments of this disclosure provide a method for determining state information, a method for determining health indicator information, a device for determining state information, a device for determining health indicator information, a component analysis system, an electronic device, and a computer-readable storage medium.

[0004] According to some aspects of embodiments of this disclosure, a method for determining state information is proposed, comprising: acquiring first state information of a first user; determining a similar user of the first user among the at least one second user based on the first state information of the first user and the first state information of at least one second user that has been stored; and determining second state information of the first user based on the second state information of the similar user.

[0005] In some embodiments, determining similar users of the first user among the at least one second user based on the first state information of the first user and the first state information of at least one second user stored includes: determining a first feature vector based on the first state information of the first user, determining a second feature vector based on the first state information of the second user; calculating the similarity between the first feature vector and the second feature vector, and determining the second user whose similarity is greater than a similarity threshold as the similar user.

[0006] In some embodiments, the first feature vector X includes n-dimensional elements, where each element in the first feature vector X corresponds to the first state information, and the element of the i-th dimension is x. i The second feature vector Y includes n-dimensional elements, and the elements in the second feature vector X correspond to the second state information, where the i-th element is y. i , where n is an integer greater than or equal to 1, 1≤i≤n; the calculation of the similarity between the first feature vector and the second feature vector includes: calculating the similarity γ(X,Y) between the first feature vector X and the second feature vector Y according to the following formula:

[0007]

[0008] Wherein, the first feature vector X includes n-dimensional elements, the second feature vector Y includes n-dimensional elements, and x i Let y be the i-th element in the first eigenvector X. i Let be the i-th element in the second eigenvector Y, where n is an integer greater than or equal to 1, and 1 ≤ i ≤ n.

[0009] In some embodiments, determining similar users of the first user among the at least one second user includes: sorting second users whose similarity is greater than a similarity threshold according to the similarity from largest to smallest; and determining the second user whose sorting order is before the first order threshold as the similar user.

[0010] In some embodiments, determining similar users of the first user among the at least one second user includes: determining a first feature vector based on the first state information of the first user, and determining a second feature vector based on the first state information of the second user; calculating the similarity between the first feature vector and the second feature vector, and sorting the second users from largest to smallest based on the similarity; and determining the second users whose sorting order is before the second order threshold as the similar users.

[0011] In some embodiments, determining the second state information of the first user based on the second state information of the similar users includes: calculating the average of the second state information of all the similar users as the second state information of the first user.

[0012] In some embodiments, determining the second state information of the first user based on the second state information of the similar users includes: determining the target state information confirmed by the similar users and the corresponding target user in the second state information of the similar users; calculating the average state information of the target state information belonging to the same target user; and determining the second state information of the first user based on the similarity between the target user and the first user and the average state information.

[0013] In some embodiments, the second state information of the first user is determined according to the following formula:

[0014]

[0015] Where S(a,U) represents the set of similar users U to the first user a, and N(p) represents the set of target users. ab This represents the similarity between the first user a and the target user b. This represents the average of the above status information.

[0016] In some embodiments, the status information determination method is applicable to a terminal.

[0017] In some embodiments, the first status information includes at least one of the following: gender information, age information, height information, weight information, location information, time information, and occupation information.

[0018] In some embodiments, the second status information includes at least one of the following: pelvic weight information, blood pressure information, pulse information, and heart rate information.

[0019] According to some aspects of the embodiments of this disclosure, a method for determining health indicator information is proposed, including: determining the body composition information of the first user based on the first state information and the second state information of the first user in the above-described state information determination method.

[0020] In some embodiments, the method further includes providing the first user with second status information of the first user.

[0021] In some embodiments, the method further includes: upon receiving a modification instruction for the second status information of the first user, determining the health indicator information of the first user based on the modified second status information of the first user.

[0022] In some embodiments, the method is applicable to health monitoring devices.

[0023] According to some aspects of embodiments of this disclosure, a component analysis system is proposed, including a terminal and a health monitoring device; the terminal is configured to acquire first state information of a first user; determine similar users of the first user among the at least one second user based on the first state information of the first user and first state information of at least one second user already stored; determine second state information of the first user based on second state information of the similar user; and transmit the second state information of the first user to the health monitoring device; the health monitoring device is configured to determine health indicator information of the first user based on the first state information and the second state information of the first user.

[0024] In some embodiments, the terminal is configured to determine, from the second state information of the similar users, the target state information confirmed by the similar users and the corresponding target users; calculate the average state information of the target state information belonging to the same target user; and determine the second state information of the first user based on the similarity between the target user and the first user and the average state information.

[0025] In some embodiments, the health monitoring device is further configured to provide the second user's second status information to the second user, and upon receiving a confirmation instruction from the second user regarding the second user's second status information, to determine that the second user's second status information is the target status information confirmed by the second user.

[0026] In some embodiments, the terminal is configured to determine the target status information confirmed by the similar user and the corresponding target user from the second status information of the similar user based on the target status information confirmed by the second user obtained from the health detection device.

[0027] In some embodiments, the health monitoring device is further configured to provide the first user with second status information of the first user.

[0028] In some embodiments, the health monitoring device is further configured to determine the health indicator information of the first user based on the modified second status information of the first user when receiving a modification instruction for the second status information of the first user.

[0029] In some embodiments, the terminal is configured to determine at least one of the following first status information of the first user based on information input by the first user: gender information, age information, height information, weight information, location information, time information, and occupation information.

[0030] In some embodiments, the second status information includes at least one of the following: pelvic weight information, blood pressure information, pulse information, and heart rate information.

[0031] According to some aspects of embodiments of this disclosure, a state information determination apparatus is proposed, comprising: a state acquisition module for acquiring first state information of a first user; a similarity determination module for determining a similar user of the first user among the at least one second user based on the first state information of the first user and first state information of at least one second user that has been stored; and a state determination module for determining second state information of the first user based on second state information of the similar user.

[0032] According to some aspects of the embodiments of this disclosure, a health indicator information determination device is proposed, including: a component analysis module, used to determine the body composition information of the first user based on the first user's first state information and the first user's second state information in the above-described state information determination method.

[0033] According to some aspects of embodiments of this disclosure, an electronic device is proposed, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured for the aforementioned state information determination method and / or the aforementioned health indicator information determination method.

[0034] According to some aspects of embodiments of the present disclosure, a computer-readable storage medium is provided that stores a computer program thereon, which, when executed by a processor, implements the above-described state information determination method and / or the steps in the above-described health indicator information determination method. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of this disclosure, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 This is a schematic flowchart illustrating a method for determining state information according to some embodiments of the present disclosure.

[0037] Figure 2 This is a schematic flowchart illustrating a method for determining state information according to some embodiments of the present disclosure.

[0038] Figure 3A This is a schematic flowchart illustrating a method for determining state information according to some embodiments of the present disclosure.

[0039] Figure 3B This is a schematic flowchart illustrating a method for determining state information according to some embodiments of the present disclosure.

[0040] Figure 4 This is a schematic flowchart illustrating a method for determining state information according to some embodiments of the present disclosure.

[0041] Figure 5 This is a schematic flowchart illustrating a method for determining state information according to some embodiments of the present disclosure.

[0042] Figure 6 This is a schematic flowchart illustrating a method for determining health indicator information according to some embodiments of the present disclosure.

[0043] Figure 7 This is a schematic diagram of a component analysis system according to some embodiments of the present disclosure.

[0044] Figure 8 This is a schematic block diagram illustrating a status information determination device according to some embodiments of the present disclosure.

[0045] Figure 9 This is a schematic block diagram illustrating a health indicator information determination device according to some embodiments of the present disclosure.

[0046] Figure 10 This is a schematic block diagram illustrating an apparatus for determining state information according to some embodiments of the present disclosure. Detailed Implementation

[0047] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this disclosure.

[0048] In related technologies, for status information that users cannot accurately determine, users need to enter values ​​based on subjective guesses. However, the accuracy of these subjective guesses is often low, making it difficult to accurately analyze the user's body composition based on the entered status information. In the application scenario of health kiosks, after entering personal information at the workstation, users need to go to the testing equipment to enter another set of user parameters, which is cumbersome and inconvenient.

[0049] Figure 1 This is a schematic flowchart illustrating a method for determining status information according to some embodiments of this disclosure. The method shown in this embodiment can be applied to electronic devices such as terminals that allow users to input status information. The terminals include, but are not limited to, mobile phones, tablets, personal computers, wearable devices, workstations, etc.

[0050] like Figure 1 As shown, the state information determination method may include the following steps:

[0051] In step S101, the first status information of the first user is obtained;

[0052] In step S102, based on the first state information of the first user and the first state information of at least one stored second user, a similar user of the first user is determined among the at least one second user.

[0053] In step S103, the second state information of the first user is determined based on the second state information of the similar users.

[0054] In some embodiments, a first user can input first status information into the terminal, enabling the terminal to acquire the first user's first status information. The methods by which the first user inputs the first status information include, but are not limited to, touch input, voice input, and direct measurement. For example, the terminal is a workstation in a health kiosk, through which the first user can input the first status information.

[0055] In the application scenario of health kiosks, each kiosk is equipped with at least one workstation and at least one type of testing equipment. Each type of testing equipment can include multiple devices. Users can log in and enter their initial user information at the workstation. Users can then select the desired device through the workstation, which provides testing guidance through a user interface. Following the guidance provided by the workstation, users can move to the corresponding testing device and undergo the required testing. After the user completes the testing, the results are sent to and displayed at the workstation. Health kiosks can be set up in communities and other locations, allowing residents to use the equipment for health testing and facilitating self-health management.

[0056] In some embodiments, the first state information can be state information that the user can accurately determine, such as including at least one of the following: gender information, age information, height information, weight information, location information, time information, season information, occupation information, and population classification information (e.g., ordinary person, athlete). For example, the health kiosk workstation provides a user interface that prompts the user to enter at least one of the following information: gender information, age information, height information, weight information, occupation information, and population classification information (e.g., ordinary person, athlete). The user can enter this information through the user interface. For example, the health kiosk workstation can obtain local geographical location information through automatic positioning and can automatically obtain local time and season information through the workstation system. For example, some of the first state information can be stored after the user's first use, so that it does not need to be entered again in subsequent uses, but can be automatically retrieved based on login information. The user can also modify some of the first state information as needed and then store the modified information. For example, fixed first-state information such as gender will not change after the first entry. First-state information such as age, which changes according to a specific pattern, can be updated according to that pattern after the first entry. Information such as weight and occupation may change during subsequent use, and can therefore be modified as needed. In some embodiments, the second-state information can be state information that the user cannot generally determine accurately, such as at least one of the following: tare weight, blood pressure, pulse, and heart rate. Tare weight refers to the weight of items on the user's body other than their own weight, including but not limited to clothing, shoes, mobile phone, and jewelry.

[0057] In some embodiments, the terminal may pre-store first and second state information of at least one second user. For example, a large number of second users may be pre-determined as a sample, and then their first and second state information may be measured / recorded, thereby obtaining accurate first and second state information for the second users.

[0058] In some embodiments, the first state information of the first user and the second state information determined by the first user can be stored as samples for use by subsequent users.

[0059] In some embodiments, the first state information of the subsequent first user and the second state information determined by the first user can also be added to the pre-stored sample to expand the sample. The second state information determined by the first user refers to information based on... Figure 1 In the illustrated embodiment, after the first user determines the second status information, the determined second status information is pushed to the first user. The first user selects and confirms the second status information. Since this part of the second status information has been confirmed by the user, it is accurate and can be stored as a valid sample.

[0060] According to some embodiments of this disclosure, after obtaining the first state information of the first user, similar users to the first user can be determined among the second users based on the first state information of the second user and the first user's first state information. For example, second users whose similarity to the first user is greater than a similarity threshold can be identified. If the first state information of a similar user is similar to the state information of the first user, then the second state information of the similar user is also likely to be similar to that of the first user. Therefore, the second state information of the first user can be determined based on the second state information of the similar user.

[0061] Therefore, instead of relying on subjective guesses to determine the second state information, a large number of similar users with similar states to the first user can be identified based on a large number of samples. Then, the first state information of the first user can be predicted based on the second state information of similar users, which helps to improve the accuracy of determining the second state information. This facilitates accurate health indicator analysis of the first user based on the second state information.

[0062] It should be noted that there can be one or more identified similar users. If only one similar user is identified, the second state information of that similar user can be pushed to the first user as the second state information of the first user. If multiple similar users are identified, the second state information of the first user can be determined based on the second state information of the multiple similar users. For example, the second state information of multiple similar users can be weighted and summed using the similarity between the similar user and the first user as the weight, and the result can be used as the second state information of the first user. Alternatively, the second state information of the similar user with the highest similarity can be taken as the second state information of the first user.

[0063] Figure 2 This is a schematic flowchart illustrating a method for determining state information according to some embodiments of this disclosure. Figure 2 As shown, determining similar users of the first user among the at least one second user based on the first user's first state information and the first state information of at least one stored second user includes:

[0064] In step S201, a first feature vector is determined based on the first state information of the first user, and a second feature vector is determined based on the first state information of the second user.

[0065] In step S202, the similarity between the first feature vector and the second feature vector is calculated, and the second user whose similarity is greater than the similarity threshold is determined to be the similar user.

[0066] In some embodiments, in order to determine the similarity between a second user and a first user, a first feature vector can be determined based on the first state information of the first user, and a second feature vector can be determined based on the first state information of the second user. Thus, the first user is represented by the first feature vector, and the second user is guaranteed by the second feature vector. Furthermore, the similarity between the first feature vector and the second feature vector can be calculated as the similarity between the first user and the second user, so as to determine that the second user with a similarity greater than a similarity threshold is a similar user.

[0067] In some implementations, a similarity threshold can be set to identify any second user with a similarity greater than the threshold as a similar user. For example, the similarity threshold can be set as needed and is not limited here. For instance, when the similarity threshold is set to 0.5, any second user with a similarity threshold greater than 0.5 can be identified as a similar user.

[0068] The number of first state information of the first user can be n, and the number of first state information of the second user can also be n. Then the first feature vector X can be an n-dimensional vector containing the first state information xi of n first users. Correspondingly, the second feature vector Y can be an n-dimensional vector containing the first state information yi of n second users, where n is an integer greater than or equal to 1, and 1≤i≤n.

[0069] An example is given using five primary state information: gender, age, height, weight, and time.

[0070] Among them, gender information can be represented by 0 to indicate female and 1 to indicate male; age information, height information, and weight information can be corresponding numerical values, for example, age 28 years old corresponds to age information 28, height 174 cm corresponds to height information 174, weight 50 kg corresponds to weight information 50; time information can be represented by 1 to indicate 6 o'clock to 9 o'clock, 2 to indicate 9 o'clock to 12 o'clock, 3 to indicate 12 o'clock to 15 o'clock, and 4 to indicate 15 o'clock to 18 o'clock.

[0071] For example, if the first user's first state information is female, 25 years old, 167 cm tall, and 50 kg in weight, and the time the first user inputs the first state information is 2 PM, the first feature vector generated based on this first state information can be represented as (0, 25, 167, 50, 14). Similarly, the second feature vector can be generated for the second user's first state information in the same way, which will not be elaborated further here.

[0072] In some implementations, the first and second state information can be converted into feature vectors using one-hot encoding, word2vec, TransE, or other methods.

[0073] In some embodiments, the number of first state information entries for the first user and the second user can also be different, as long as their similarity can be calculated. For example, if the number of first state information entries for the first user is different from that for the second user, missing values ​​can be padded with empty values ​​to make their numbers the same, and the corresponding vector element positions can be set to 0, so that their corresponding vector dimensions are also the same.

[0074] In some embodiments, the similarity between the first feature vector and the second feature vector can be determined by calculating the angle between the first feature vector and the second feature vector. For example, the distance between the two can be calculated by calculating their dot product, cosine value, etc., or it can be determined in the following ways, but it is not limited to these two methods. The specific method can be selected as needed.

[0075] In some embodiments, the first feature vector X includes n-dimensional elements, where each element in the first feature vector X corresponds to the first state information, and the element of the i-th dimension is x. i The second feature vector Y includes n-dimensional elements, and the elements in the second feature vector X correspond to the second state information, where the i-th element is y. i ;

[0076] The calculation of the similarity between the first feature vector and the second feature vector includes:

[0077] The similarity γ(X,Y) between the first feature vector X and the second feature vector Y is calculated according to the following formula:

[0078]

[0079] Figure 3A This is a schematic flowchart illustrating a method for determining state information according to some embodiments of this disclosure. Figure 3A As shown, determining the second user whose similarity is greater than the similarity threshold as the similar user includes:

[0080] In step S301, the second users whose similarity is greater than the similarity threshold are sorted from largest to smallest according to the similarity.

[0081] In step S302, the second user whose sorting order is before the first sorting threshold is determined to be the similar user.

[0082] In some implementations, the first-order threshold can be set as needed, and is not limited here. For example, when the order threshold is set to 3, the three second users with the highest similarity can be identified as similar users.

[0083] In some embodiments, if similar users are determined solely based on the relationship between similarity and similarity threshold, the number of similar users determined among the second users may differ for different first users. For some first users, a very large number of similar users may be determined, resulting in a large amount of data that is inconvenient for subsequent analysis and calculation.

[0084] Based on the determined similarity, this implementation example sorts the second users whose similarity is greater than the similarity threshold according to the similarity from largest to smallest, and determines the second users whose sorting order is before the first order threshold as similar users. In this way, it can be ensured that the number of similar users determined for different first users is basically the same, which is convenient for subsequent analysis and calculation.

[0085] For example, if 200 second users with a similarity greater than the similarity threshold to the first user are identified, these 200 second users can be sorted from largest to smallest similarity, and the second users whose sorting order is before 10 (this first sorting order threshold can be set as needed) are identified. In other words, the top 10 second users among the 200 are identified as similar users. This narrows down the range of similar users, making subsequent analysis and calculation easier.

[0086] Figure 3B This is a schematic flowchart illustrating a method for determining state information according to some embodiments of this disclosure. Figure 3B As shown, determining similar users of the first user among the at least one second user includes:

[0087] In step S303, a first feature vector is determined based on the first state information of the first user, and a second feature vector is determined based on the first state information of the second user.

[0088] In step S304, the similarity between the first feature vector and the second feature vector is calculated, and the second users are sorted from largest to smallest according to the similarity.

[0089] In step S305, the second user whose sorting order is before the second sorting threshold is determined to be the similar user.

[0090] In some embodiments, the similarity between the first user and the second user can be determined by measuring the similarity between the first feature vector and the second feature vector. The method for determining the similarity can be the same as that shown in the previous embodiments, and will not be repeated here.

[0091] After determining the similarity, the second users can be sorted from highest to lowest similarity, and the second users whose sorting order is before the second order threshold are identified as the similar users. For example, if the similarity between 1000 second users and the first user is determined, these 1000 second users can be sorted from highest to lowest similarity, and the second users whose sorting order is before number 20 (this second order threshold can be set as needed) are identified. That is, the top 20 second users out of the 1000 are identified as similar users. This ensures that the number of similar users identified for different first users is the same, facilitating subsequent analysis and calculation. In some implementations, the sorting can also be done from lowest to highest, which will not be elaborated here.

[0092] Figure 4 This is a schematic flowchart illustrating a method for determining state information according to some embodiments of this disclosure. Figure 4 As shown, determining the second state information of the first user based on the second state information of the similar users includes:

[0093] In step S401, the average of the second state information of all the similar users is calculated as the second state information of the first user.

[0094] In some embodiments, when multiple similar users similar to the first user are identified, the average of the second state information of all similar users can be used as the second state information of the first user.

[0095] When the second state information consists of a single piece of information, the mean can be calculated for that single piece of second state information; when the second state information includes multiple pieces of information, the mean needs to be calculated separately for each piece of second state information.

[0096] For example, if 10 similar users are identified with tare weights of 500g, 550g, 600g, 650g, 700g, 750g, 800g, 860g, 900g, and 950g respectively, then the calculated average is 725g. Therefore, 725g is provided to the first user as the second status information of the first user. Figure 5 This is a schematic flowchart illustrating a method for determining state information according to some embodiments of this disclosure. Figure 5 As shown, determining the second state information of the first user based on the second state information of the similar users includes:

[0097] In step S501, the target status information confirmed by the similar user and the corresponding target user are determined from the second status information of the similar user;

[0098] In step S502, the average value of the state information of the target state information belonging to the same target user is calculated;

[0099] In step S503, the second state information of the first user is determined based on the similarity between the target user and the first user and the mean value of the state information.

[0100] In some embodiments, the determined similar user may be a first user who previously inputted first status information to the terminal, and whose second status information was determined by the terminal based on the above embodiments. That is, after determining the second status information of the first user based on the first user's first status information, the terminal can store the first and second status information of the first user, and when it is necessary to determine the second status information for the first user later, the first user with the stored first and second status information can be used as the second user to determine the second status information for the subsequent first user.

[0101] For example, user A uses the terminal. Based on A's first state information and the first state information of at least one stored second user, the terminal identifies a similar user among the second users and determines A's second state information based on the similar user. This second state information is then stored. Since user A's second state information is stored, for user B who subsequently uses the terminal, A has essentially become a historical user, i.e., a second user. Therefore, if A and B's first user information is similar, A may become B's similar user, and B's second user information will be determined based on A's second user information.

[0102] In this scenario, the second status information of similar users can also be determined by the terminal based on the above embodiments. However, the second status information determined by the terminal may not be accurate. After being pushed to similar users, it is necessary to determine whether the similar users will confirm it. If the similar users confirm it, then the second status information pushed to them can be determined to be accurate. That is, for similar users, not all the second status information of all similar users is accurate. Only when the second status information of similar users is confirmed by the similar users is the second status information of those users accurate.

[0103] The operation of confirming the target status information by a similar user can be performed on the terminal. For example, the terminal can display the target status information and has "modify" and "confirm" buttons. If the similar user clicks the "confirm" button, the generated confirmation command indicates that the similar user has confirmed the target status information provided to them. If the similar user clicks the "modify" button, the generated modification command indicates that the target status information can be adjusted. In this case, the similar user has not confirmed the target status information provided to them.

[0104] It should be noted that the operation of similar users confirming the target status information can also be completed on the subsequent health monitoring device. For example, the terminal sends the target status information to the health monitoring device, which has "modify" and "confirm" buttons. If the similar user clicks the "confirm" button, the generated confirmation command indicates that the similar user has confirmed the target status information provided to them. If the similar user clicks the "modify" button, the generated modification command indicates that the target status information can be adjusted, and the adjusted target status information is sent to the terminal. In this case, the similar user has not confirmed the target status information provided to them.

[0105] In some implementations, after determining the second status information of the first user based on the second status information of similar users, the second status information can be provided to the first user for confirmation / modification, and the method is the same as described above, and will not be repeated here.

[0106] Therefore, the target state information confirmed by similar users, and the corresponding target users, can be determined from the second state information of similar users. In other words, for all similar users' second state information, the second state information confirmed by similar users can be identified as the target state information, and this portion of the target state information is accurate.

[0107] In this case, since similar users are not pre-measured samples but actual users from the past, body composition analysis can be performed multiple times for similar users. During this process, target state information will be determined multiple times. Therefore, for similar users, their second state information is the average of these multiple target state information. Thus, the average state information of target state information belonging to the same target user can be calculated.

[0108] Then, when determining the second state information of the first user, the second state information of the first user can be determined based on the similarity between the target user and the first user, as well as the average state information of the target user. Since the state information of the target user has been confirmed by the target user, it is accurate. Determining the second state information of the second user based on this can ensure accuracy.

[0109] For example, the value of the second state information p of the first user a can be determined by the following formula:

[0110]

[0111] Where S(a,U) represents the set of similar users U to the first user a, and N(p) represents the set of target users. ab This represents the similarity between the first user a and the target user b. This represents the average of the above status information.

[0112] Figure 6 This is a schematic flowchart illustrating a method for determining health indicator information according to some embodiments of this disclosure. For example, in some embodiments, this method can be applied to health monitoring devices, such as component analyzers, blood glucose meters, and other health monitoring devices. Health indicator information includes body composition information, blood glucose information, etc. When the health monitoring device is a component analyzer, the device can analyze body composition, and at this time, the health indicator information includes body composition information. The health monitoring device communicates with the aforementioned terminal to receive second status information determined by the aforementioned terminal. For example, the component analyzer can communicate with the terminal to which the above status information determination method is applicable, such as receiving the second status information determined by the terminal in the above embodiments.

[0113] For example, in the application scenario of a health kiosk, after a user logs in and enters their first status information (height, weight, age, etc.) through a workstation terminal, the workstation can calculate the user's second status information (e.g., skin removal information). Then, the workstation sends the first and second status information to a body composition analyzer. The body composition analyzer performs body composition analysis based on the received first and second status information and provides the body composition analysis results.

[0114] Since users no longer need to re-enter the second status information on the body composition analyzer during use, but can directly use the second information transmitted from the workstation, the operation becomes more convenient and user-friendly, thus improving the user experience.

[0115] like Figure 6 As shown, taking health indicator information as body composition information as an example, the method may include the following steps:

[0116] In step S601, the body composition information of the first user is determined based on the first state information and the second state information of the first user in the state information determination method described in any of the above embodiments.

[0117] In some embodiments, the health monitoring device can analyze the body composition of the first user based on the first user's first state information and second state information to obtain the first user's body composition information. The body composition information includes at least one of the following: fat percentage, water percentage, and fatigue level.

[0118] Since the first state information can be accurately determined by the first user, and the second state information determined according to the above embodiments is also relatively accurate, the human body composition information can be accurately determined based on the first state information and the second state information.

[0119] In some embodiments, the method further includes providing the first user with second status information of the first user.

[0120] In some implementations, the body composition analyzer may be equipped with a screen, through which the second status information from the terminal of the above embodiments can be provided to the first user, so that the first user can view, confirm, or modify it. For example, the body composition analyzer can prompt the user with the second status information from the terminal of the above embodiments via voice broadcast, and the user can confirm or modify the second status information through voice control.

[0121] In some embodiments, the method further includes: upon receiving a modification instruction for the second state information of the first user, determining the human body composition information of the first user based on the modified second state information of the first user.

[0122] Regarding the second status information provided by the component analyzer, the first user can choose to confirm or adjust it as needed. If the first user confirms the second status information, for example by clicking the confirm button, the first user's body composition information can be determined based on the first status information and the second status information provided to the first user. If the first user modifies the second status information, for example by clicking the modify button to re-enter the second status information, the first user's body composition information can be determined based on the first status information and the modified second status information.

[0123] Therefore, if the second state information of the first user cannot be accurately determined based on the second state information of similar users, the first user can modify the second state information according to their own actual situation, which is conducive to improving the accuracy of calculating human body composition information.

[0124] Figure 7 This is a schematic diagram illustrating a health indicator information determination system according to some embodiments of this disclosure. Figure 7 As shown, the health indicator information determination system may include a terminal 701 and a health detection device 702; the terminal includes, but is not limited to, mobile phones, tablets, personal computers, wearable devices, workstations, etc. The health detection device may include a body composition analyzer, a height and weight scale, a bone density analyzer, etc., and the number of health detection devices may be one or more; the type and number of health detection devices are not limited here.

[0125] The terminal is configured to acquire first status information of a first user; determine a similar user of the first user among the at least one second user based on the first status information of the first user and the first status information of at least one second user that has been stored; determine second status information of the first user based on the second status information of the similar user; and transmit the first status information and the second status information of the first user to the health detection device.

[0126] The health indicator information determination is configured to determine the health indicator information of the first user based on the first user's first state information and the first user's second state information.

[0127] In some embodiments, a first user can input first status information into the terminal, enabling the terminal to acquire the first user's first status information. The methods by which the first user inputs the first status information include, but are not limited to, touch input, voice input, and direct measurement. For example, the terminal is a workstation in a health kiosk, through which the first user can input the first status information.

[0128] The system can be deployed in health kiosks. Each kiosk contains at least one workstation and at least one type of testing equipment, with each type of equipment potentially including multiple devices. Users can log in and enter their initial user information at the workstation. Users can then select the desired equipment through the workstation, which provides testing guidance via a user interface. Following the workstation's guidance, users can navigate to the corresponding testing equipment and undergo the required testing. After testing, the results are sent to and displayed at the workstation. Health kiosks can be set up in communities or similar locations, allowing residents to use the equipment for health checks and facilitating self-health management.

[0129] In some embodiments, the first state information can be state information that the user can accurately determine, such as including at least one of the following: gender information, age information, height information, weight information, location information, time information, season information, occupation information, and population classification information (e.g., ordinary person, athlete). For example, the health kiosk workstation provides a user interface that prompts the user to enter at least one of the following information: gender information, age information, height information, weight information, occupation information, and population classification information (e.g., ordinary person, athlete). The user can enter this information through the user interface. For example, the health kiosk workstation can obtain local geographical location information through automatic positioning and can automatically obtain local time and season information through the workstation system. For example, some of the first state information can be stored after the user's first use, so that it does not need to be entered again in subsequent uses, but can be automatically retrieved based on login information. The user can also modify some of the first state information as needed and then store the modified information. For example, fixed first-state information such as gender will not change after the first entry. First-state information such as age, which changes according to a specific pattern, can be updated according to that pattern after the first entry. Information such as weight and occupation may change during subsequent use, and can therefore be modified as needed. In some embodiments, the second-state information can be state information that the user cannot generally determine accurately, such as at least one of the following: tare weight, blood pressure, pulse, and heart rate. Tare weight refers to the weight of items on the user's body other than their own weight, including but not limited to clothing, shoes, mobile phone, and jewelry.

[0130] In some embodiments, the terminal may pre-store first and second state information of at least one second user. For example, a large number of second users may be pre-determined as a sample, and then their first and second state information may be measured / recorded, thereby obtaining accurate first and second state information for the second users.

[0131] In some embodiments, the first state information of the first user and the second state information determined by the first user can be stored as samples for use by subsequent users.

[0132] In some embodiments, the first state information of the subsequent first user and the second state information determined by the first user can also be added to the pre-stored sample to expand the sample. The second state information determined by the first user refers to information based on... Figure 1 In the illustrated embodiment, after the first user determines the second status information, the determined second status information is pushed to the first user. The first user selects and confirms the second status information. Since this part of the second status information has been confirmed by the user, it is accurate and can be stored as a valid sample.

[0133] According to some embodiments of this disclosure, after obtaining the first state information of the first user, similar users to the first user can be determined among the second users based on the first state information of the second user and the first user's first state information. For example, second users whose similarity to the first user is greater than a similarity threshold can be identified. If the first state information of a similar user is similar to the state information of the first user, then the second state information of the similar user is also likely to be similar to that of the first user. Therefore, the second state information of the first user can be determined based on the second state information of the similar user.

[0134] Therefore, instead of relying on subjective guesswork to determine the second state information, a large sample size can be used to identify similar users with similar states to the first user. The first user's first state information can then be predicted based on the second state information of these similar users, thus improving the accuracy of determining the second state information. Furthermore, the first user's first and second state information can be transmitted to the health monitoring device, further ensuring the accurate determination of the first user's health indicators based on the first and second state information.

[0135] In some embodiments, the terminal is configured to determine at least one of the following first status information of the first user based on information input by the first user: gender information, age information, height information, weight information, location information, time information, occupation information, and population classification information.

[0136] In some embodiments, the second status information includes at least one of the following: pelvic weight information, blood pressure information, pulse information, and heart rate information.

[0137] In some embodiments, the health indicator information includes at least one of the following: body fat percentage, body water percentage, and fatigue level.

[0138] It should be noted that there can be one or more identified similar users. If only one similar user is identified, the second state information of that similar user can be pushed to the first user as the second state information of the first user. If multiple similar users are identified, the second state information of the first user can be determined based on the second state information of the multiple similar users. For example, the second state information of multiple similar users can be weighted and summed using the similarity between the similar user and the first user as the weight, and the result can be used as the second state information of the first user. Alternatively, the second state information of the similar user with the highest similarity can be taken as the second state information of the first user.

[0139] In some embodiments, the terminal is configured to determine a first feature vector based on the first state information of the first user, and to determine a second feature vector based on the first state information of the second user; calculate the similarity between the first feature vector and the second feature vector; and determine a similar user of the first user among the at least one second user.

[0140] In some embodiments, in order to determine the similarity between a second user and a first user, a first feature vector can be determined based on the first state information of the first user, and a second feature vector can be determined based on the first state information of the second user. Thus, the first user is represented by the first feature vector, and the second user is guaranteed by the second feature vector. Furthermore, the similarity between the first feature vector and the second feature vector can be calculated as the similarity between the first user and the second user, so as to determine that the second user with a similarity greater than a similarity threshold is a similar user.

[0141] In some implementations, a similarity threshold can be set to identify any second user with a similarity greater than the threshold as a similar user. For example, the similarity threshold can be set as needed and is not limited here. For instance, when the similarity threshold is set to 0.5, any second user with a similarity threshold greater than 0.5 can be identified as a similar user.

[0142] The number of first state information of the first user can be n, and the number of first state information of the second user can also be n. Then the first feature vector X can be an n-dimensional vector containing the first state information xi of n first users. Correspondingly, the second feature vector Y can be an n-dimensional vector containing the first state information yi of n second users, where n is an integer greater than or equal to 1, and 1≤i≤n.

[0143] An example is given using five primary state information: gender, age, height, weight, and time.

[0144] Among them, gender information can be represented by 0 to indicate female and 1 to indicate male; age information, height information, and weight information can be corresponding numerical values, for example, age 28 years old corresponds to age information 28, height 174 cm corresponds to height information 174, weight 50 kg corresponds to weight information 50; time information can be represented by 1 to indicate 6 o'clock to 9 o'clock, 2 to indicate 9 o'clock to 12 o'clock, 3 to indicate 12 o'clock to 15 o'clock, and 4 to indicate 15 o'clock to 18 o'clock.

[0145] For example, if the first user's first state information is female, 25 years old, 165 cm tall, and 50 kg in weight, and the time the first user inputs the first state information is 2 PM, the first feature vector generated based on this first state information can be represented as (0, 25, 167, 50, 14). Similarly, the second feature vector can be generated for the second user's first state information in the same way, which will not be elaborated further here.

[0146] In some embodiments, the number of first state information entries for the first user and the second user can also be different, as long as their similarity can be calculated. For example, if the number of first state information entries for the first user is different from that for the second user, missing values ​​can be padded with empty values ​​to make their numbers the same, and the corresponding vector element positions can be set to 0, so that their corresponding vector dimensions are also the same.

[0147] In some embodiments, the similarity between the first feature vector and the second feature vector can be determined by calculating the angle between the first feature vector and the second feature vector. For example, the distance between the two can be calculated by calculating their dot product, cosine value, etc., or it can be determined in the following ways, but it is not limited to these two methods. The specific method can be selected as needed.

[0148] In some embodiments, the first feature vector X includes n-dimensional elements, where each element in the first feature vector X corresponds to the first state information, and the element of the i-th dimension is x. i The second feature vector Y includes n-dimensional elements, and the elements in the second feature vector X correspond to the second state information, where the i-th element is y. i n is an integer greater than or equal to 1, where 1 ≤ i ≤ n;

[0149] The terminal is configured to calculate the similarity γ(X,Y) between the first feature vector X and the second feature vector Y according to the following formula:

[0150]

[0151] In some embodiments, the terminal is configured to sort second users whose similarity is greater than a similarity threshold according to the similarity from largest to smallest; and determine the second user whose sorting order is before the first sorting threshold as the similar user.

[0152] In some implementations, the first-order threshold can be set as needed, and is not limited here. For example, when the order threshold is set to 3, the three second users with the highest similarity can be identified as similar users.

[0153] In some embodiments, if similar users are determined solely based on the relationship between similarity and similarity threshold, the number of similar users determined among the second users may differ for different first users. For some first users, a very large number of similar users may be determined, resulting in a large amount of data that is inconvenient for subsequent analysis and calculation.

[0154] Based on the determined similarity, this implementation example sorts the second users whose similarity is greater than the similarity threshold according to the similarity from largest to smallest, and determines the second users whose sorting order is before the first order threshold as similar users. In this way, it can be ensured that the number of similar users determined for different first users is basically the same, which is convenient for subsequent analysis and calculation.

[0155] For example, if 200 second users with a similarity greater than the similarity threshold to the first user are identified, these 200 second users can be sorted from largest to smallest similarity, and the second users whose sorting order is before 10 (this first sorting order threshold can be set as needed) are identified. In other words, the top 10 second users among the 200 are identified as similar users. This narrows down the range of similar users, making subsequent analysis and calculation easier.

[0156] In some embodiments, the terminal is configured to determine a first feature vector based on the first state information of the first user, and to determine a second feature vector based on the first state information of the second user; to sort the second users in descending order of similarity; and to determine the second users whose sorting order is before the second order threshold as the similar users.

[0157] In some embodiments, the similarity between the first user and the second user can be determined by measuring the similarity between the first feature vector and the second feature vector. The method for determining the similarity can be the same as that shown in the previous embodiments, and will not be repeated here.

[0158] After determining the similarity, the second users can be sorted from highest to lowest similarity. The second users whose sorting order is before the second order threshold are then identified as similar users. For example, if the similarity between 1000 second users and the first user is determined, these 1000 second users can be sorted from highest to lowest similarity, and the second users whose sorting order is before number 20 (this second order threshold can be set as needed) are identified. That is, the top 20 second users out of the 1000 are identified as similar users. This ensures that the number of similar users identified for different first users is the same, facilitating subsequent analysis and calculation.

[0159] In some embodiments, the terminal is configured to calculate the average of the second state information of all the similar users as the second state information of the first user.

[0160] In some embodiments, when multiple similar users similar to the first user are identified, the average of the second state information of all similar users can be used as the second state information of the first user.

[0161] When the second state information consists of a single piece of information, the mean can be calculated for that single piece of second state information; when the second state information includes multiple pieces of information, the mean needs to be calculated separately for each piece of second state information.

[0162] For example, if 10 similar users are identified with tare weights of 500g, 550g, 600g, 650g, 700g, 750g, 800g, 860g, 900g, and 950g respectively, then the calculated average is 725g. Therefore, 725g is provided to the first user as the second status information of the first user.

[0163] In some embodiments, the terminal is configured to determine, from the second state information of the similar users, the target state information confirmed by the similar users and the corresponding target users; calculate the average state information of the target state information belonging to the same target user; and determine the second state information of the first user based on the similarity between the target user and the first user and the average state information.

[0164] In some embodiments, the determined similar user may be a first user who previously inputted first status information to the terminal, and whose second status information was determined by the terminal based on the above embodiments. That is, after determining the second status information of the first user based on the first user's first status information, the terminal can store the first and second status information of the first user, and when it is necessary to determine the second status information for the first user in a subsequent instance, the first user with the stored first and second status information can be used as the second user to determine the second status information for the subsequent first user.

[0165] For example, user A uses the terminal. Based on A's first state information and the first state information of at least one stored second user, the terminal identifies a similar user among the second users and determines A's second state information based on the similar user. This second state information is then stored. Since user A's second state information is stored, for user B who subsequently uses the terminal, A has essentially become a historical user, i.e., a second user. Therefore, if A and B's first user information is similar, A may become B's similar user, and B's second user information will be determined based on A's second user information.

[0166] In this scenario, the second status information of similar users can also be determined by the terminal based on the above embodiments. However, the second status information determined by the terminal may not be accurate. After being pushed to similar users, it is necessary to determine whether the similar users will confirm it. If the similar users confirm it, then the second status information pushed to them can be determined to be accurate. That is, for similar users, not all the second status information of all similar users is accurate. Only when the second status information of similar users is confirmed by the similar users is the second status information of those users accurate.

[0167] The operation of confirming the target status information by a similar user can be performed on the terminal. For example, the terminal can display the target status information and has "modify" and "confirm" buttons. If the similar user clicks the "confirm" button, the generated confirmation command indicates that the similar user has confirmed the target status information provided to them. If the similar user clicks the "modify" button, the generated modification command indicates that the target status information can be adjusted. In this case, the similar user has not confirmed the target status information provided to them.

[0168] It should be noted that the operation of similar users confirming the target status information can also be completed on the subsequent health monitoring device. For example, the terminal sends the target status information to the health monitoring device, which has "modify" and "confirm" buttons. If the similar user clicks the "confirm" button, the generated confirmation command indicates that the similar user has confirmed the target status information provided to them. If the similar user clicks the "modify" button, the generated modification command indicates that the target status information can be adjusted, and the adjusted target status information is sent to the terminal. In this case, the similar user has not confirmed the target status information provided to them.

[0169] Therefore, the target state information confirmed by similar users, and the corresponding target users, can be determined from the second state information of similar users. In other words, for all similar users' second state information, the second state information confirmed by similar users can be identified as the target state information, and this portion of the target state information is accurate.

[0170] In this case, since similar users are not pre-measured samples but actual users from the past, body composition analysis can be performed multiple times for similar users. During this process, target state information will be determined multiple times. Therefore, for similar users, their second state information is the average of these multiple target state information. Thus, the average state information of target state information belonging to the same target user can be calculated.

[0171] Then, when determining the second state information of the first user, the second state information of the first user can be determined based on the similarity between the target user and the first user, as well as the average state information of the target user. Since the state information of the target user has been confirmed by the target user, it is accurate. Determining the second state information of the second user based on this can ensure accuracy.

[0172] For example, the value of the second state information p of the first user a can be determined by the following formula:

[0173]

[0174] Where S(a,U) represents the set of similar users U to the first user a, and N(p) represents the set of target users. ab This represents the similarity between the first user a and the target user b. This represents the average of the above status information.

[0175] In some embodiments, the health monitoring device is further configured to provide the second user's second status information to the second user, and upon receiving a confirmation instruction from the second user regarding the second user's second status information, to determine that the second user's second status information is the target status information confirmed by the second user. In some embodiments, a screen may be provided on the health monitoring device (e.g., a body composition analyzer), through which the second status information from the terminal described in the above embodiments can be provided (e.g., displayed) to the first user for viewing. The user can confirm or modify the second status information displayed by the component analysis (e.g., through operation via the device's touchscreen or voice control). Upon receiving a confirmation instruction from the second user regarding the second user's second status information, it can be determined that the second user's second status information is the target status information confirmed by the second user.

[0176] In some embodiments, the terminal is configured to determine the target status information confirmed by the similar user and the corresponding target user from the second status information of the similar user based on the target status information confirmed by the second user obtained from the health detection device.

[0177] After the health monitoring device detects that the second user has confirmed the second status information, the confirmed second status information can be recorded as the target status information. The target status information confirmed by the similar user and the corresponding target user can be determined from the second status information of the similar users. The target status information and the corresponding target user are then informed to the terminal so that the terminal can determine the second status information of the first user based on the similarity between the target user and the first user and the average value of the status information.

[0178] In some embodiments, the health monitoring device is further configured to determine the second status information of the first user based on the modified second status information of the first user when receiving a modification instruction for the second status information of the first user.

[0179] In some embodiments, a user can confirm or modify the second status information displayed by the component analysis. When a confirmation instruction is received from the second user regarding the second user's second status information, it can be determined that the second user's second status information is the target status information confirmed by the second user.

[0180] In the application scenario of health kiosks, in related technologies, after a user enters first-state information such as height and weight at a workstation, the workstation sends this information to health detection devices such as a body composition analyzer. Then, the user moves to the health detection device and needs to enter second-state information such as tareum weight before the device can begin measurement. According to some embodiments of this disclosure, after a user enters first-state information such as height and weight at the workstation, the workstation (or a server communicating with the workstation) can determine the user's second-state information such as tareum weight and send this information along with the height, weight, and tareum weight to the health detection device such as the body composition analyzer. When the user moves to the health detection device, manual entry is no longer required; measurement can begin directly. The health indicator information determination system provided by some embodiments of this disclosure makes operation more convenient and user-friendly, improving the user experience.

[0181] Corresponding to the embodiments of the aforementioned methods for determining status information and health indicator information, this disclosure also provides embodiments of a device for determining status information and a device for determining health indicator information.

[0182] Figure 8This is a schematic block diagram illustrating a status information determination device according to some embodiments of the present disclosure. The device shown in this embodiment can be applied to electronic devices such as terminals that allow users to input status information, including but not limited to mobile phones, tablets, personal computers, wearable devices, etc.

[0183] like Figure 8 As shown, the status information determining device may include:

[0184] The status acquisition module 801 is used to acquire the first status information of the first user;

[0185] The similarity determination module 802 is used to determine a similar user of the first user among the at least one second user based on the first state information of the first user and the first state information of at least one second user that has been stored.

[0186] The status determination module 803 is used to determine the second status information of the first user based on the second status information of the similar users.

[0187] In some embodiments, the similarity determination module is configured to determine a first feature vector based on the first state information of the first user, determine a second feature vector based on the first state information of the second user, calculate the similarity between the first feature vector and the second feature vector, and determine the second user whose similarity is greater than a similarity threshold as the similar user.

[0188] In some embodiments, the first feature vector X includes n-dimensional elements, where each element in the first feature vector X corresponds to the first state information, and the element of the i-th dimension is x. i The second feature vector Y includes n-dimensional elements, and the elements in the second feature vector X correspond to the second state information, where the i-th element is y. i n is an integer greater than or equal to 1, where 1 ≤ i ≤ n;

[0189] The similarity determination module is used to calculate the similarity γ(X,Y) between the first feature vector X and the second feature vector Y according to the following formula:

[0190]

[0191] In some embodiments, the similarity determination module is used to sort second users whose similarity is greater than a similarity threshold according to the similarity from largest to smallest; and to determine the second users whose sorting order is before the first sorting threshold as the similar users.

[0192] In some embodiments, the similarity determination module is configured to determine a first feature vector based on the first state information of the first user, and determine a second feature vector based on the first state information of the second user; calculate the similarity between the first feature vector and the second feature vector, and sort the second users in descending order of the similarity; and determine the second users whose sorting order is before the second order threshold as the similar users.

[0193] In some embodiments, the state determination module is used to calculate the average of the second state information of all similar users as the second state information of the first user.

[0194] In some embodiments, the state determination module is configured to determine the target state information confirmed by the similar user and the corresponding target user from the second state information of the similar users; calculate the average state information of the target state information belonging to the same target user; and determine the second state information of the first user based on the similarity between the target user and the first user and the average state information.

[0195] In some embodiments, the status information determination method is applicable to a terminal.

[0196] In some embodiments, the first status information includes at least one of the following: gender information, age information, height information, weight information, location information, time information, and occupation information.

[0197] In some embodiments, the second status information includes at least one of the following: pelvic weight information, blood pressure information, pulse information, and heart rate information.

[0198] Figure 9 This is a schematic block diagram illustrating a health indicator information determination device according to some embodiments of this disclosure. For example, in some embodiments, the method can be applied to health monitoring devices, such as component analyzers, blood glucose meters, etc. When the health monitoring device is a component analyzer, the device can analyze human body composition, and the health indicator information includes human body composition information. The health monitoring device communicates with the aforementioned terminal to receive second status information determined by the terminal. For example, the component analyzer can communicate with the terminal to which the status information determination method is applicable, for example, to receive the second status information determined by the terminal.

[0199] like Figure 9 As shown, taking human body composition information as an example, the health indicator information determining device may include:

[0200] The component analysis module 901 is used to determine the human body composition information of the first user based on the first state information and the second state information of the first user in the state information determination method described in any of the above embodiments.

[0201] In some embodiments, the method further includes: a status display module, configured to provide the first user with second status information of the first user.

[0202] In some embodiments, the component analysis module is further configured to determine the human body composition information of the first user based on the modified second state information of the first user when receiving a modification instruction for the second state information of the first user.

[0203] In some embodiments, the method for determining health indicator information is applicable to health monitoring devices.

[0204] In some embodiments, the body composition information includes at least one of the following: fat percentage, water percentage, and fatigue level.

[0205] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments of the relevant methods, and will not be elaborated upon here.

[0206] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0207] Figure 10 This is a schematic block diagram illustrating an apparatus 1000 for determining status information according to some embodiments of the present disclosure. For example, apparatus 1000 may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness equipment, personal digital assistant, etc.

[0208] Reference Figure 10 The device 1000 may include one or more of the following components: a processing component 1002, a memory 1004, a power supply component 1006, a multimedia component 1008, an audio component 1010, an input / output (I / O) interface 1012, a sensor component 1014, and a communication component 1016.

[0209] Processing component 1002 typically controls the overall operation of device 1000, such as operations associated with display, telephone calls, data communication, camera operation, and recording operations. Processing component 1002 may include one or more processors 1020 to execute instructions to complete all or part of the steps of the aforementioned state information determination method. Furthermore, processing component 1002 may include one or more modules to facilitate interaction between processing component 1002 and other components. For example, processing component 1002 may include a multimedia module to facilitate interaction between multimedia component 1008 and processing component 1002.

[0210] Memory 1004 is configured to store various types of data to support the operation of device 1000. Examples of such data include instructions for any application or method operating on device 1000, contact data, phonebook data, messages, pictures, videos, etc. Memory 1004 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0211] Power supply component 1006 provides power to various components of device 1000. Power supply component 1006 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to device 1000.

[0212] The multimedia component 1008 includes a screen that provides an output interface between the device 1000 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of the touch or swipe action but also the duration and pressure associated with the touch or swipe operation. In some embodiments, the multimedia component 1008 includes a front-facing camera and / or a rear-facing camera. When the device 1000 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or the rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0213] Audio component 1010 is configured to output and / or input audio signals. For example, audio component 1010 includes a microphone (MIC) configured to receive external audio signals when device 1000 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 1004 or transmitted via communication component 1016. In some embodiments, audio component 1010 also includes a speaker for outputting audio signals.

[0214] I / O interface 1012 provides an interface between processing component 1002 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0215] Sensor assembly 1014 includes one or more sensors for providing state assessments of various aspects of device 1000. For example, sensor assembly 1014 may detect the on / off state of device 1000, the relative positioning of components such as the display and keypad of device 1000, changes in the position of device 1000 or a component of device 1000, the presence or absence of user contact with device 1000, the orientation or acceleration / deceleration of device 1000, and temperature changes of device 1000. Sensor assembly 1014 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 1014 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 1014 may also include an accelerometer, a gyroscope, a magnetometer, a pressure sensor, or a temperature sensor.

[0216] Communication component 1016 is configured to facilitate wired or wireless communication between device 1000 and other devices. Device 1000 can access wireless networks based on communication standards, such as WiFi, 2G or 3G, 4G LTE, 5G NR, or combinations thereof. In one exemplary embodiment, communication component 1016 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 1016 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0217] In an exemplary embodiment, the apparatus 1000 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described state information determination method.

[0218] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 1004 including instructions, which can be executed by the processor 1020 of the device 1000 to complete the aforementioned state information determination method. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0219] The various components / modules / units disclosed herein may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof.

[0220] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0221] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0222] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

[0223] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0224] The methods and apparatus provided in the embodiments of this disclosure have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this disclosure. The descriptions of the embodiments above are only for the purpose of helping to understand the methods and core ideas of this disclosure. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this disclosure. Therefore, the content of this specification should not be construed as a limitation of this disclosure.

Claims

1. A state information determination method characterized by comprising: include: Obtain the first user's first state information; Based on the first state information of the first user and the first state information of at least one second user that has been stored, determine the similar user of the first user among the at least one second user; The second status information of the first user is determined based on the second status information of the similar users; The first status information is status information that the user can accurately determine, and the first status information includes at least one of the following: gender information, age information, height information, weight information, location information, time information, and occupation information. The second status information is status information that the user cannot accurately determine, and the second status information includes at least one of the following: tare weight information, blood pressure information, pulse information, and heart rate information.

2. The method of claim 1, wherein, The step of determining similar users of the first user among the at least one second user based on the first user's first state information and the first state information of at least one second user that has been stored includes: A first feature vector is determined based on the first state information of the first user, and a second feature vector is determined based on the first state information of the second user. Calculate the similarity between the first feature vector and the second feature vector, and determine the second user whose similarity is greater than the similarity threshold as the similar user.

3. The method of claim 2, wherein, The first feature vector X comprises n elements, and each element in the first feature vector X corresponds to the first state information, wherein the element of the i-th dimension is x. i The second feature vector Y includes n-dimensional elements, and the elements in the second feature vector X correspond to the second state information, where the i-th element is y. i n is an integer greater than or equal to 1, where 1 ≤ i ≤ n; The calculation of the similarity between the first feature vector and the second feature vector includes: The similarity of the first feature vector X and the second feature vector Y is calculated according to the following formula : ； Wherein, the first feature vector X includes n-dimensional elements, the second feature vector Y includes n-dimensional elements, and x i Let y be the i-th element in the first eigenvector X. i Let be the i-th element in the second eigenvector Y, where n is an integer greater than or equal to 1, and 1 ≤ i ≤ n.

4. The method of claim 2, wherein, The step of determining the second user whose similarity is greater than the similarity threshold as the similar user includes: The second users whose similarity is greater than the similarity threshold are sorted from largest to smallest according to the similarity score. The second user whose sorting order is before the first sorting threshold is identified as the similar user.

5. The method according to claim 1, characterized in that, The step of determining similar users of the first user among the at least one second user includes: A first feature vector is determined based on the first state information of the first user, and a second feature vector is determined based on the first state information of the second user. Calculate the similarity between the first feature vector and the second feature vector, and sort the second users from largest to smallest based on the similarity. The second user whose sorting order is before the second sorting threshold is identified as the similar user.

6. The method according to claim 1, characterized in that, Determining the second state information of the first user based on the second state information of the similar users includes: The mean of the second state information of all similar users is calculated as the second state information of the first user.

7. The method of claim 1, wherein, Determining the second state information of the first user based on the second state information of the similar users includes: The target status information confirmed by the similar user and the corresponding target user are determined from the second status information of the similar user. Calculate the average value of the state information of target state information belonging to the same target user; The second state information of the first user is determined based on the similarity between the target user and the first user and the average value of the state information.

8. The method of claim 7, wherein, The second state information of the first user is determined according to the following formula: ； in, Let U represent the set of users U similar to the first user a. Represents the set of target users. This represents the similarity between the first user a and the target user b. This represents the average of the above status information.

9. The method according to any one of claims 1 to 8, characterized in that, The status information determination method described herein is applicable to terminals.

10. A health indicator information determination method characterized by comprising: include: The health indicator information of the first user is determined by the first status information and the second status information of the first user in the status information determination method according to any one of claims 1 to 9.

11. The method according to claim 10, characterized in that, The method further includes: Provide the first user with the second status information.

12. The method of claim 11, wherein, The method further includes: Upon receiving an instruction to modify the second status information of the first user, the health indicator information of the first user is determined based on the modified second status information of the first user.

13. The method according to any one of claims 10 to 12, characterized in that, The method is applicable to health monitoring equipment.

14. A health indicator information determination system characterized by comprising: Including terminals and health monitoring equipment; The terminal is configured to acquire first status information of a first user; and, based on the first status information of the first user and the first status information of at least one second user already stored, determine a similar user of the first user among the at least one second user. And determine the second state information of the first user based on the second state information of the similar users; The first user's first and second status information are transmitted to the health detection device. The health monitoring device is configured to determine the health indicator information of the first user based on the first user's first state information and the first user's second state information. The first status information is status information that the user can accurately determine, and the first status information includes at least one of the following: gender information, age information, height information, weight information, location information, time information, and occupation information. The second status information is status information that the user cannot accurately determine, and the second status information includes at least one of the following: tare weight information, blood pressure information, pulse information, and heart rate information.

15. The system of claim 14, wherein, The terminal is configured to determine, from the second status information of the similar user, the target status information confirmed by the similar user and the corresponding target user; Calculate the average value of the state information of target state information belonging to the same target user; The second state information of the first user is determined based on the similarity between the target user and the first user and the average value of the state information.

16. The system according to claim 15, characterized in that, The health monitoring device is also configured to provide the second user's second status information to the second user, and to determine, upon receiving a confirmation instruction from the second user regarding the second user's second status information, that the second user's second status information is the target status information confirmed by the second user.

17. The system of claim 16, wherein, The terminal is configured to determine the target status information confirmed by the similar user and the corresponding target user from the second status information of the similar user, based on the target status information confirmed by the second user obtained from the health detection device.

18. The system of claim 14, wherein, The health monitoring device is also configured to provide the first user with the first user's second status information.

19. The system of claim 14, wherein, The health monitoring device is also configured to determine the health indicator information of the first user based on the modified second status information of the first user when it receives a modification instruction for the second status information of the first user.

20. An electronic device, comprising: include: processor; Memory used to store processor-executable instructions; The processor is configured to implement the state information determination method according to any one of claims 1 to 9, and / or the health indicator information determination method according to any one of claims 10 to 13.

21. A computer readable storage medium having stored thereon a computer program, characterized in that, When the program is executed by the processor, it implements the steps of the state information determination method according to any one of claims 1 to 9, and / or the health indicator information determination method according to any one of claims 10 to 13.

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