Health data affiliation determination method, apparatus and device, and readable storage medium

Abstract

The invention provides a health data affiliation determination method, device and equipment and a readable storage medium, and the method comprises the steps: comparing to-be-processed health data with corresponding historical health data of each member in a target group based on a principle that specific health data is relatively stable in a certain period; therefore, the detection result is attributed based on the comparison result of the historical health data corresponding to each member, automatic attribution of the health detection data is realized, additional operation of health data detection by the members in the group is reduced, and user experience is improved.

Description

Technical Field

[0001] The present application relates to the field of health management technology, and in particular to a method, device, equipment and readable storage medium for determining the ownership of health data. Background Art

[0002] In the scenario where multiple members of the same group share health data and use the same group permissions to perform health data testing, when a group member uses the group permissions to enable health testing, the health testing provider can determine the group to which the group member belongs based on the group permissions, but cannot specifically determine which member of the group is performing the health test. Because health data has the characteristic of determining the member to whom the data belongs, an operation to manually determine the identity of the members must be performed before or after the health test to determine the group member to which the health data measured this time belongs.

[0003] For example, the property management company issues owner cards to families. All family members hold the same owner card, and each owner card records the information of all family members. Since the owner card records the information of all family members, when any family member uses the owner card to activate the community health service equipment for health check, the equipment cannot automatically determine the identity of the card swipeer, and the card swipeer is required to manually select his or her own identity to determine the identity of the card swipeer, which brings additional user operations.

[0004] However, the user operation of performing health data detection in the above scenario is rather cumbersome, which affects the user experience. Summary of the invention

[0005] In view of this, in order to solve the above-mentioned technical problems, the present application provides a method, device, equipment and readable storage medium for determining the ownership of health data.

[0006] Specifically, the present application is implemented through the following technical solutions:

[0007] According to a first aspect of an embodiment of the present application, a method for determining attribution of health data is provided, the method comprising:

[0008] Obtain health data for processing;

[0009] Determine the target group to which the health data belongs, and obtain historical data of each member in the target group of the same type as the health data; share the health data of each member in the target group;

[0010] Obtaining a comparison result between the health data and the historical data of each member;

[0011] The target member to which the health data belongs is determined according to the comparison results corresponding to each member in the target group.

[0012] Optionally, the health data to be processed corresponds to a threshold value of a change amplitude of the health data within a set period; and obtaining a comparison result between the health data and the historical data of each member includes:

[0013] Obtaining a change range of the health data compared to the historical data of the member;

[0014] In response to the change amplitude being less than or equal to the change amplitude threshold, determining that the comparison result corresponding to the historical data of the member is a first type of result;

[0015] In response to the change amplitude being greater than the change amplitude threshold, determining that the comparison result corresponding to the historical data of the member is a second type of result; the first type of result and the second type of result are used to mark the size relationship between the change amplitude and the change amplitude threshold.

[0016] Optionally, the health data to be processed corresponds to a data priority that meets the change amplitude threshold; and determining the target member to which the health data belongs includes:

[0017] Determine, according to the priority sequence of the historical data of the member, the distribution of the first category results and the second category results in the comparison result corresponding to the member in the priority sequence;

[0018] The target member to which the health data belongs is determined according to a matching result between the distribution situation and a preset first attribution determination rule belonging to different data priorities.

[0019] Optionally, the health data to be processed corresponds to an attribution determination weight; the attribution determination weight is determined according to the change amplitude threshold; the comparison result includes a weight value corresponding to the historical data of the member; and the obtaining of the comparison result between the health data and the historical data of each member includes:

[0020] In response to the change amplitude being less than or equal to the change amplitude threshold, determining the weight value corresponding to the historical data of the member as the attribution determination weight;

[0021] In response to the change amplitude being greater than the change amplitude threshold, determining that the weight value corresponding to the historical data of the member is zero.

[0022] Optionally, the health data to be processed corresponds to a data priority that meets the change amplitude threshold; and determining the target member to which the health data belongs includes:

[0023] Determining a priority sequence corresponding to the historical data of the member;

[0024] According to the order of the priority sequence, the results of the weight values ​​corresponding to the historical data of the member are matched with the second attribution determination rule related to the priority in sequence;

[0025] In response to the existence of a result with the weight value satisfying the second attribution determination rule, the target member is determined to be the member to which the result with the weight value satisfying the determination rule belongs.

[0026] Optionally, the method further comprises:

[0027] In response to the comparison results corresponding to the respective members not satisfying the attribution determination rule, generating a selection page according to member information in the target group to which the health data belongs;

[0028] It is determined that the target member to which the health data belongs is the member selected by the user in the selection page.

[0029] Optionally, after determining the target member to which the health data belongs, the method further includes:

[0030] According to the health data, corresponding historical data of the target members in the target group are updated.

[0031] According to a second aspect of an embodiment of the present application, a device for determining attribution of health data is provided, the device comprising:

[0032] A health data acquisition module, used to acquire health data to be processed;

[0033] A target group determination module, used to determine the target group to which the health data belongs, and obtain the historical data of each member in the target group of the same type as the health data; the health data of each member in the target group is shared;

[0034] A comparison result acquisition module, used to acquire the comparison result between the health data and the historical data of each member;

[0035] The data belonging member determination module is used to determine the target member to which the health data belongs according to the comparison results corresponding to each member in the target group.

[0036] In some embodiments, the health data to be processed corresponds to a threshold value of a change amplitude of the health data within a set period; and the comparison result acquisition module is specifically used to:

[0037] Obtaining a change range of the health data compared to the historical data of the member;

[0038] In response to the change amplitude being less than or equal to the change amplitude threshold, determining that the comparison result corresponding to the historical data of the member is a first type of result;

[0039] In response to the change amplitude being greater than the change amplitude threshold, determining that the comparison result corresponding to the historical data of the member is a second type of result; the first type of result and the second type of result are used to mark the size relationship between the change amplitude and the change amplitude threshold.

[0040] In some embodiments, the health data to be processed corresponds to the data priority that meets the change amplitude threshold; based on the comparison result including the first category result and the second category result, the data belonging member determination module is specifically used to:

[0041] Determine, according to the priority sequence of the historical data of the member, the distribution of the first category results and the second category results in the comparison result corresponding to the member in the priority sequence;

[0042] The target member to which the health data belongs is determined according to a matching result between the distribution situation and a preset first attribution determination rule belonging to different data priorities.

[0043] In some embodiments, the health data to be processed corresponds to an attribution determination weight; the attribution determination weight is determined according to the change amplitude threshold; the comparison result includes a weight value corresponding to the historical data of the member; and the comparison result acquisition module is specifically used to:

[0044] In response to the change amplitude being less than or equal to the change amplitude threshold, determining the weight value corresponding to the historical data of the member as the attribution determination weight;

[0045] In response to the change amplitude being greater than the change amplitude threshold, determining that the weight value corresponding to the historical data of the member is zero.

[0046] In some embodiments, the health data to be processed corresponds to the data priority that meets the change amplitude threshold; the data belonging member determination module is specifically used to:

[0047] Determining a priority sequence corresponding to the historical data of the member;

[0048] According to the order of the priority sequence, the results of the weight values ​​corresponding to the historical data of the member are matched with the second attribution determination rule related to the priority in sequence;

[0049] In response to the existence of a result with the weight value satisfying the second attribution determination rule, the target member is determined to be the member to which the result with the weight value satisfying the determination rule belongs.

[0050] In some embodiments, the apparatus further comprises:

[0051] In response to the comparison results corresponding to the respective members not satisfying the attribution determination rule, generating a selection page according to member information in the target group to which the health data belongs;

[0052] It is determined that the target member to which the health data belongs is the member selected by the user in the selection page.

[0053] In some embodiments, the apparatus further comprises:

[0054] According to the health data, corresponding historical data of the target members in the target group are updated.

[0055] According to a third aspect of an embodiment of the present application, an electronic device is provided, comprising: a memory and a processor; the memory is used to store a computer program; and the processor is used to execute the above-mentioned method for determining the attribution of health data by calling the computer program.

[0056] According to a fourth aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the above-mentioned method for determining the attribution of health data is implemented.

[0057] The technical solution provided by the embodiments of the present application may have the following beneficial effects:

[0058] In the technical solution provided in the present application, based on the principle that specific health data is relatively stable within a certain period, the specific health data in the test results to be processed are compared with the corresponding specific historical health data of each member in the target group, so that the test results are attributed based on the comparison results of the specific historical health data corresponding to each member, thereby realizing automatic attribution of health test data, reducing the additional operations of health data testing for members in the group, and improving the user experience.

[0059] It should be understood that the above general description and the following detailed description are only exemplary and explanatory and cannot limit the present application. In addition, any embodiment in the present application does not need to achieve all the above effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0061] Figure 1 is a flow chart of a method for determining the ownership of health data shown in an exemplary embodiment of the present application;

[0062] Figure 2 is a flow chart showing a comparison result of obtaining health data and historical data of each member, as shown in an exemplary embodiment of the present application;

[0063] Figure 3 is a flowchart of determining a target member to which the health data belongs, shown in an exemplary embodiment of the present application;

[0064] Figure 4 is another flow chart showing another method of obtaining the comparison result of health data and historical data of each member according to an exemplary embodiment of the present application;

[0065] Figure 5 is another flowchart of determining the target member to which the health data belongs, shown in an exemplary embodiment of the present application;

[0066] Figure 6 It is a flowchart of a processing method for a scenario where the target member to which the health data belongs cannot be automatically determined, as shown in an exemplary embodiment of the present application;

[0067] Figure 7 It is a flow chart of a method for determining the ownership of health data in a scenario where family members share a health detection device in a specific real estate scenario, shown in an exemplary embodiment of the present application;

[0068] Figure 8 It is a flowchart of an exemplary embodiment of the present application showing a method of determining the member to which a certain owner belongs based on an actual example of the health test result of the owner;

[0069] Fig. 9 is a structural schematic diagram of a device for determining attribution of health data shown in an exemplary embodiment of the present application;

[0070] Fig.10 It is a hardware schematic diagram of an electronic device shown in an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0071] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0072] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0073] It should be understood that although the terms first, second, third, etc. may be used in the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first classification threshold may also be referred to as the second classification threshold, and similarly, the second classification threshold may also be referred to as the first classification threshold. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0074] In a scenario where multiple members belonging to the same group use the same group authority identifier to enable health checks, since the group authority identifier records the information of all members in the group, when a member uses the group authority identifier to enable a health device to perform his or her own health check, the smart health device can identify the group to which the member belongs based on the group authority identifier, but cannot determine the exact identity of the member currently using the group authority. Therefore, group members must perform additional identity confirmation operations before or after performing a health check to determine the member to whom the measured health data belongs. For example, if member A uses the smart health device to complete a full body check, the user must select the member to whom the body measurement data belongs on the control page.

[0075] For example, the health device is a physical examination machine, and group members have the same card to share the physical examination machine. The card includes all member information and group identification in the group. When any member of the group logs in to the physical examination machine with the card to start the health data detection function, the physical examination machine can determine the group to which the member belongs based on the card, but cannot determine which member of the group is using the card. Therefore, when obtaining the test result of the member, the member identity selected by the user must be obtained first to determine that the test result belongs to the selected member identity.

[0076] However, the above method in which users manually determine the member to which health data belongs makes the user operation more cumbersome and affects the user experience.

[0077] In order to solve the above technical problems, the present application provides a method for determining the ownership of health data, which can be applied to electronic devices for managing health data, such as an all-in-one health data measuring machine, a health data management device connected to multiple health data measuring devices, etc. Figure 1 As shown, the method may include the following steps:

[0078] S101, obtaining health data to be processed;

[0079] The health data to be processed may be a set of health data generated by the user's health data detection. The set of health data can only determine the group to which it belongs, but cannot determine which member of the group the health data belongs to. The user can perform human health data detection through the health data detection function provided by a device, equipment or system with health data detection function.

[0080] Alternatively, the health data to be processed may also be health data belonging to a set health data type in a group of health data generated by the user performing health data detection. The set health data type refers to a pre-set type of different health data that can be used to implement the health data attribution determination of the present application. The embodiment of the present application implements health data attribution determination based on the relatively stable characteristics of specific health data within a certain period of time. The set type depends on the change range of the health data within a set period. The data change range of the health data of the set health data type within the set period does not exceed the preset maximum change range threshold.

[0081] For example, if the preset maximum change threshold is 10%, the type of health data whose increase or decrease in the set period does not exceed 10% will be used as the set type. Assuming the set period is one month, the change in height, bone density T value, and bone density Z value within one month is -2% to 2%, the change in weight, waist circumference, and hip circumference within one month is -5% to 5%, and the change in diastolic blood pressure, systolic blood pressure, and heart rate within one month is -10% to 10%, then the above 9 types of health data can all be used as the set types.

[0082] The health data to be processed can be obtained when the health test results are generated after the user completes the health data test. Alternatively, in some cases, when the user completes the health data test, the automatic attribution determination function of the health data cannot be enabled. In this case, the test results can be stored in the above-mentioned electronic device for health data management first, so as to obtain the health data or health test results stored in the storage area of ​​the device that have not yet undergone health data attribution determination.

[0083] In the case where the health data to be processed is health data of a set health data type in a group of health data generated by the user performing health data detection, the set type of health data can be obtained from the health data detection result, and the number of health data of the set type obtained depends on the number of detection data of the set type included in the detection result. For example, the health data detection result includes five types of detection data, namely height, weight, heart rate, blood oxygen saturation, and blood sugar. If the setting type is based on the above example, the three types of health data, namely height, weight, and heart rate, in the detection result are obtained as the health data to be processed, and the health data that does not belong to the set type in the detection result is not processed.

[0084] S102, determining the target group to which the health data belongs, and obtaining historical data of each member in the target group of the same type as the health data; the health data of each member in the target group is shared;

[0085] The method provided in the embodiment of the present application is applicable to the scenario in which members belonging to the same group share each other's health data. Members in the group have the same group authority identifier, and each member can use the group authority identifier to enable health data detection. The device can determine the group to which the member belongs based on the group authority identifier, and determine the group as the target group to which the member's health data belongs.

[0086] For example, for a smart health home product purchased by a family, after family member A activates the product through account information, each family member can use the product for health testing. Each family member is a target group. When any family member uses the product, the product can determine whether it is used by a family member based on the account information at the time of login. For another example, for community health service equipment, the use rights are allocated based on the owner's account number. The same owner card is allocated to the same family. Multiple members of the same family are the same group. The owner card records the information of each family member. When any family member uses the service card to enable the community health service device, the device can determine the target group to which the member using the device belongs based on the owner card, and use it as the target group to which the health data of the member belongs. Therefore, the target group to which the health data belongs can be obtained and recorded based on the group permission identifier of the enabled device when the member performs health data detection to generate the health data. The group permission identifier may include but is not limited to login cards, account information, etc. The group permission identifier corresponds to at least the personal information of two members.

[0087] The present application pre-stores the historical data records of health data detection of each member in different groups, and the historical data records may be the historical data records of the most recent historical detection time to the detection date of the current detection result. When the target group to which the detection result belongs is determined, for each member of the target group, historical data of the same type as the health data described in step S101 is obtained from the pre-stored historical data records of the member.

[0088] Taking the aforementioned acquisition of height, weight, and heart rate as health data of the set type as an example, if the health data to be processed belongs to the target group G, and the target group includes members B, C, and D, then the three historical data of height, weight, and heart rate are obtained from the pre-stored historical data records of member B. Similarly, the three historical data of height, weight, and heart rate of members C and D are obtained.

[0089] S103, obtaining a comparison result between the health data and the historical data of each member;

[0090] The comparison result is used to describe the difference information between the same type of health data and historical data, so as to evaluate the probability that the health data and the historical data belong to the same member. The comparison result can be determined based on whether the change range of the health data compared to the corresponding historical data meets the set change range of the health data.

[0091] For each member, each health data acquired in step S101 is compared with the historical data of the member having the same type as the health data, to obtain the comparison results corresponding to each of the historical data of the member.

[0092] Still taking the aforementioned acquisition of height, weight, and heart rate as the health data to be processed, and obtaining the three historical data of height, weight, and heart rate of members B, C, and D as an example, the height, weight, and heart rate are compared with the three historical data of height, weight, and heart rate of members B, C, and D respectively, so as to obtain the comparison results corresponding to the three historical data of member B, and obtain the comparison results corresponding to the three historical data of members C and D.

[0093] S104: Determine the target member to which the health data belongs according to the comparison results corresponding to each member in the target group.

[0094] That is, based on the comparison results corresponding to the historical data of each member, it is evaluated whether the difference between the historical data of each member and the health data to be processed meets the set deviation range based on the comparison results, so as to determine the member whose difference meets the set deviation range as the member to which the health data to be processed belongs. The attribution determination rule can be set in advance, and the target member to which the health data to be processed belongs is determined according to whether the comparison result meets the attribution determination rule.

[0095] After determining the target member to which the health data to be processed belongs, the corresponding historical data records of the target member that have been stored can be updated based on the acquired health data to be processed, thereby providing a good data basis for subsequent health data ownership determination.

[0096] In the embodiment of the present disclosure, based on the principle that specific health data is relatively stable within a certain period, the specific historical health data of each member in the group to which the test result to be processed belongs is pre-stored. After the test result to be processed is obtained, the specific health data in the test result is compared with the corresponding specific historical health data of each member in the target group, so that the test result is attributed based on the comparison result of the specific historical health data corresponding to each member, thereby realizing automatic attribution of health test data, reducing additional operations for members in the group to perform health data testing, and improving user experience.

[0097] In some embodiments, according to the changing trends of different types of health data over time, the changes in health data within a set period are divided into different change amplitude ranges, and the change amplitude range is determined according to a change amplitude threshold, and each type of health data corresponds to a change amplitude range.

[0098] For example, the changes in health data are divided into three categories: small changes, changes, and large changes; among them, the change amplitude threshold corresponding to the small change amplitude category is 2%, and the change amplitude range is -2% to 2%; the change amplitude threshold corresponding to the change amplitude category is 5%, and the change amplitude range is -5% to 5%; the change amplitude threshold corresponding to the large change amplitude category is 10%, and the change amplitude range is -10% to 10%.

[0099] Based on the change amplitude threshold corresponding to the acquired health data to be processed, such as Figure 2 As shown, the comparison result of obtaining the health data and the historical data of each member in the aforementioned step S103 can be achieved in the following manner:

[0100] S201, obtaining a change range of the health data compared with the historical data of the member;

[0101] For each member, the change range of the health data compared with the corresponding historical data of the member is obtained respectively. In the embodiment of the present application, the change range refers to the absolute value of the change range calculated by the following expression, which can be expressed as: change range = (health data - historical data) / historical data.

[0102] Taking the aforementioned acquisition of height, weight, and heart rate, and the acquisition of the historical height, historical weight, and historical heart rate of members B, C, and D as an example, for member B, obtain the change in height B1 compared to B's historical height, as well as obtain the change in height B2 compared to B's historical weight, and obtain the change in height B3 compared to B's historical heart rate; using the same processing method, obtain the change ranges C1, C2, and C3 corresponding to member C's historical data, and obtain the change ranges D1, D2, and D3 corresponding to member D's historical data.

[0103] S202, in response to the change amplitude being less than or equal to the change amplitude threshold, determining that the comparison result corresponding to the historical data of the member is a first type of result; the first type of result and the second type of result are used to mark the magnitude relationship between the change amplitude and the change amplitude threshold;

[0104] The amplitude of change is used to describe the degree of change of the health data compared with the corresponding historical health data. When the amplitude of change is less than the amplitude of change threshold corresponding to the health data, it means that the value of the health data is consistent with the change value of the historical data within the set period, and the data difference between the two is consistent with the set deviation range, then it is determined that the comparison result corresponding to the historical data of the member is the first type of result.

[0105] Taking the change amplitudes B1 and B2 corresponding to the historical data of the above-mentioned member B as an example, if the change amplitude B1 is smaller than the change amplitude threshold corresponding to the height, and the change amplitude B2 is equal to the change amplitude threshold corresponding to the weight, then the comparison result corresponding to the historical height of member B is determined to be a first-class result, and the comparison result corresponding to B's historical weight is a first-class result.

[0106] S203: In response to the change amplitude being greater than the change amplitude threshold, determining that the comparison result corresponding to the historical data of the member is a second type of result.

[0107] Taking the change amplitude B3 corresponding to the historical data of member B as an example, if the change amplitude B3 is greater than the change amplitude threshold corresponding to the heart rate, it is determined that the comparison result corresponding to the historical heart rate of member B is the second type of result.

[0108] The above-mentioned first type of results corresponds to the situation where the change amplitude does not exceed the change amplitude threshold, and the second type of results corresponds to the situation where the change amplitude threshold exceeds the change amplitude threshold. Therefore, the first type of results and the second type of results belong to two opposite result identifiers, which can be represented by the numbers "1" and "0", the character strings "compliant" and "non-compliant", etc., and this application does not limit this.

[0109] In the embodiment of the present disclosure, by obtaining the change amplitude of health data compared with the historical data of each member with the same type of health data, and then based on the change amplitude threshold corresponding to the preset health data, an evaluation of the difference between the health data and the corresponding historical data of each member is achieved, providing a data basis for determining the attribution of the health data.

[0110] In some embodiments, different data priorities are set in advance for different types of health data. The data priority of the health data depends on the change amplitude threshold of the health data within a set period. The larger the change amplitude threshold, the lower the accuracy of determining the health data attribution based on the data, and therefore the lower the corresponding data priority. For example, the corresponding priorities of the health data with the aforementioned change amplitude threshold of 2%, 5%, and 10% are set to decrease in sequence.

[0111] Based on the priority of the set type of health data, Figure 2 When the comparison result is determined by the process shown in FIG. Figure 3 As shown, the determination of the target member to which the health data belongs in the aforementioned step S104 may include the following implementations:

[0112] S301, determining, according to the priority sequence of the historical data of the member, the distribution of the first category results and the second category results in the comparison result corresponding to the member in the priority sequence;

[0113] The priority sequence of the historical data of the member is the priority sequence of the health data of the set type obtained in step S101. Taking the aforementioned acquisition of height, weight, and heart rate as the health data to be processed as an example, if the preset height, weight, and heart rate correspond to the change amplitude thresholds of 2%, 5%, and 10%, respectively, corresponding to data priorities Ⅰ, Ⅱ, and Ⅲ, among which priority I is the highest, then the priority sequence of the historical data of the member is data priorities Ⅰ, Ⅱ, and Ⅲ.

[0114] For each data priority in the priority sequence, the number of first-category results and the number of second-category results in the historical data belonging to the priority are determined according to the comparison result corresponding to the historical data of the member, and the quantity distribution of the two categories of results is obtained. For example, for the priority sequences I, II, and III above, the number of first-category results and the number of second-category results in the historical data of the member belonging to priorities I, II, and III are obtained respectively.

[0115] S302: Determine the target member to which the health data belongs according to the matching result of the distribution situation and the preset first attribution determination rule belonging to different data priorities.

[0116] Regarding the above-mentioned processing method of determining the comparison results corresponding to the member's historical data as the first category results and the second category results, at least one attribution determination rule for the health data with different data priorities is pre-set according to the data priority corresponding to the health data.

[0117] For example, a preset set of first attribution determination rules includes: ① If there are at least two historical data with data priority of I whose comparison results are first category results, it is determined that the detection result and the historical data belong to the same member; ② If ① is not satisfied, if there are at least four historical data with data priority of II whose comparison results are first category results, it is determined that the detection result and the historical data belong to the same member; ③ If ② is not satisfied, if there are at least two historical data with data priority of II and at least four historical data with data priority of III whose corresponding comparison results are first category results, it is determined that the detection result and the historical data belong to the same member.

[0118] After obtaining the distribution of the comparison results in the priority sequence, the distribution corresponding to each member can be matched with each rule in the first attribution determination rule of the group. If there is a member whose comparison result successfully matches the first attribution determination rule, the successfully matched member will be determined as the member to which the health data belongs.

[0119] In the disclosed embodiment, whether the health data and the historical data belong to the same object is determined by whether the change range of the health data compared to the member's historical data conforms to the set change range of the health data, thereby improving the efficiency of determining the ownership of the health data. Different data priorities are set for the health data, and corresponding ownership determination rules are set according to the data priorities, thereby enhancing the accuracy of determining the ownership of the health data.

[0120] In some embodiments, attribution determination weights are pre-set for different types of health data, and the attribution determination weight is used to characterize the importance of this type of health data for determining the attribution of the health data. The attribution determination weight is determined based on the change amplitude threshold. The smaller the change amplitude threshold, the higher the accuracy of determining the attribution of the health data based on the health data, and thus the larger the assigned attribution determination weight value. For example, the attribution determination weights corresponding to health data with change amplitude thresholds of 2%, 5%, and 10% are 90%, 50%, and 20%, respectively.

[0121] In the case where the belonging determination weight corresponding to the set type of health data is known, after obtaining the change range of the health data compared with the historical data of the member, such as Figure 4 As shown, the obtaining of the comparison result of the health data and the historical data of each member in the aforementioned step S103 may include the following method, wherein the obtained comparison result includes the weight value corresponding to the historical data of the member:

[0122] S401, in response to the change amplitude being less than or equal to the change amplitude threshold, determining that the weight value corresponding to the historical data of the member is the attribution determination weight;

[0123] S402: In response to the change amplitude being greater than the change amplitude threshold, determining that the weight value corresponding to the historical data of the member is zero.

[0124] Taking the change ranges B1, B2, and B3 corresponding to the historical data of member B as an example, the preset height, weight, and heart rate correspond to the attribution determination weights of 90%, 50%, and 20%, respectively. According to the above comparison result determination method, then:

[0125] In response to the change range B1 being less than the change range threshold corresponding to the height, determining that the weight value corresponding to the historical height of member B is 90%;

[0126] In response to the change range B2 being equal to the change range threshold corresponding to the weight, determining that the weight value corresponding to the historical weight of member B is 50%;

[0127] In response to the change amplitude B3 being greater than the change amplitude threshold corresponding to the heart rate, it is determined that the weight value corresponding to the historical heart rate of member B is 0.

[0128] In the embodiment of the present disclosure, different attribution determination weights are set according to the threshold value of the change amplitude of health data within a set period, so as to achieve the distinction of the importance of health data for data attribution determination, and based on the relationship between the change amplitude of health data compared with historical data and the change amplitude value of the health data, the attribution determination weights are enriched in the data comparison results, thereby providing a good data basis for health data attribution determination and improving the accuracy of data attribution determination.

[0129] In some embodiments, different data priorities are set in advance for different types of health data as described in the above embodiments. Figure 4 When the comparison result is determined by the process shown in FIG. Figure 5 As shown, the step S104 of determining the target member to which the health data belongs may include the following steps:

[0130] S501, determining a priority sequence corresponding to the historical data of the member;

[0131] That is, for each member's historical data of the same type as the health data to be processed in the aforementioned step S101, the priority corresponding to each historical data is determined. For the specific implementation method, please refer to the description of the aforementioned embodiment.

[0132] S502, matching the weight value corresponding to the historical data of the member with the second attribution determination rule related to the priority in sequence according to the order of the priority sequence;

[0133] In the embodiment of the present application, for the case where the comparison result includes the weight value corresponding to the historical data of the member, at least one second attribution determination rule for determining the attribution of the health data according to the weight value of the health data is pre-set. For example, one of the preset second attribution determination rules is: if the sum of the weight values ​​of the historical data with data priority II and data priority III exceeds 170%, the member to which the result of satisfying the weight value belongs is the target member.

[0134] If the priority sequence is Ⅱ or Ⅲ, the weight value corresponding to the historical data of the member is first matched with the weight attribution judgment rule of the health data with data priority Ⅱ. If the match is successful, the matching is stopped directly. Alternatively, each member of the loop group can be selected to match in the above manner to obtain the matching result corresponding to each member. If the match fails, the weight value corresponding to the historical data of the member can be matched with the weight attribution judgment rule of the health data with data priority Ⅲ. If the current member cannot be matched successfully with any attribution judgment rule, the member is replaced for further matching of the weight result.

[0135] S503: In response to the existence of the result with the weight value satisfying the second attribution determination rule, determining that the target member is the member to which the result with the weight value satisfying the attribution determination rule belongs.

[0136] If only one member has a result with a weight value that satisfies the second attribution determination rule, the target member is determined to be the member to which the result with the weight value that satisfies the attribution determination rule belongs; if at least two members have results with the weight value that satisfies the second attribution determination rule, the member to which the result with the weight value with the highest data priority involved in satisfying the second attribution determination rule belongs can be determined as the target member to which the detection result belongs.

[0137] In the embodiment of the present disclosure, according to the priority sequence corresponding to the historical data of each member, the result of the weight value corresponding to the member is matched with the second attribution determination rule involving the priority. Based on the data priority representing the importance of the data for the data attribution determination, matching according to the priority sequence achieves more accurate health data attribution determination, and only the second attribution determination rule involving the priority in the priority sequence is matched, thereby improving the matching efficiency and the efficiency of health data attribution determination.

[0138] In some embodiments, for the aforementioned Figure 3 or Figure 5 The method flow shown is a process of determining the target member to which the detection result belongs, such as Figure 6 As shown, the method may also include the following steps:

[0139] S601, in response to the comparison results corresponding to the respective members not satisfying the attribution determination rule, generating a selection page according to member information in the target group to which the health data belongs;

[0140] For the adoption Figure 3 The method flow shown is a process for determining the target member, and the attribution determination rule refers to the first attribution determination rule. If the distribution of the first category results and the second category results in the comparison results corresponding to all members in the target group in the priority sequence cannot match the first attribution determination rule, then a selection page is generated based on the member information in the target group.

[0141] For the adoption Figure 5 The method flow shown determines the process of the target member, and the attribution determination rule refers to the second attribution determination rule. If the results of the weight values ​​corresponding to all members in the target group cannot match the second attribution determination rule, a selection page is generated based on the member information in the target group.

[0142] S602: Determine that the target member to which the health data to be processed belongs is the member selected by the user in the selection page.

[0143] For scenarios where the user determines the ownership of the health data immediately after performing a health data test, the selection page can be popped up directly when the ownership of the health data cannot be automatically determined, so that the user can manually select to determine the ownership of the health data. If the test results of the health service to be processed are obtained from the storage area, in the case where the ownership of the health data cannot be determined using the above method, the test results can be marked with a status to indicate that manual confirmation by the user is required, and the selection page will be popped up when it is detected that a user in the target group uses the health service. If the user is not a member of the health data and cannot confirm his or her ownership, the status mark can be maintained until the health data is manually determined to be owned by a member.

[0144] In order to enable those skilled in the art to better understand the method for determining the ownership of health data provided by the present application, the present application will be described in detail below using the scenario in which members of the same family in a specific real estate scenario use the same owner card to activate health detection equipment as an example.

[0145] In specific real estate scenarios such as residential areas or apartments, the community health service area is equipped with a physical examination machine that can provide blood pressure, heart rate, blood sugar, uric acid, total cholesterol, height, weight, blood oxygen, body temperature, waist circumference, hip circumference, waist-to-hip ratio, bone density, body composition and other human health data detection functions. Owners can use their owner cards to conduct health checks in the community health service area. For example, after the owner swipes the owner card to log in to the physical examination machine, he selects the health test items and conducts the test, and then checks the health test results after the test is completed.

[0146] However, in the process of the owner swiping the owner card to log in to the medical examination machine or completing the test to view the health test results, since one owner card records the information of the card holder, that is, all family members of the owner, when the owner swipes the card, the system cannot determine which member of the owner's family is swiping the card, and requires the card swiper to perform additional identity recognition operations to determine the identity of the card swiper, resulting in more cumbersome operations and bringing inconvenience to the owner's daily use.

[0147] To solve the problems in the above scenario, based on the fact that specific health data is relatively stable within a certain period of time, when the owner performs a health check in the health service area, the health data of the specified type in the generated test results are compared with the corresponding historical health data of multiple family members associated with the owner's card, so as to achieve the purpose of automatically determining the attribution of health data and reducing the owner's additional operations. Among them, the specified type refers to the type of the specific health data.

[0148] Before executing the method provided by the present application, the above-mentioned multiple human health data information of the owner is stored in a specified location in advance according to the set data format, such as the database of the physical examination machine or the cloud data storage center. In addition, the change range of the health data within the set period is divided into the following three categories, and the change range of each category is set: small change range (-2% to 2%), change (-5% to 5%), and large change range (-10% to 10%). The health data with the maximum change range within the set period that meets the classification is determined as specific health data, and different data priorities and attribution determination weights are assigned according to the change range classification of the specific health data. The specific health data within the same change range has the same data priority and attribution determination weight, and the change range, data priority, attribution determination weight and other information of the specific health data can be stored according to the set data format.

[0149] For example, data with a small change range can be defined as Class I, data with changes can be defined as Class II, and data with a large change range can be defined as Class III, and the corresponding weights can be assigned according to Table 1 below.

[0150]

[0151]

[0152] Table 1 Specific health data management table

[0153] Based on the above-mentioned specific health data management table, a judgment rule is preset to realize the determination of the ownership of the test results to be processed based on the ownership judgment weight. The judgment rule can be set according to the sum of the weight values ​​of the specific health data with different data priorities. The judgment rule can be a cascade rule, which predetermines the priority between each rule, executes multiple rules one by one in order of priority, and matches the next rule if the current rule is not met. Alternatively, the judgment rule may include multiple parallel rules, so as to determine the ownership of the health data according to the number of rules met by the matching process.

[0154] When the owner swipes the owner card to start the medical examination machine to complete the health data test, Figure 7 As shown, the owner's test results can be achieved by the following methods:

[0155] S701, obtaining health data of a specified type from the owner's health check results; the specified type refers to the type of health data in a specific health data management table.

[0156] The collection of the specified type can be stored in advance, and when the health test results are obtained, the health data belonging to the collection of the specified type can be obtained therefrom; alternatively, an identification variable can be set for the health data of the specified type, thereby obtaining the health data containing the identification variable attribute in the test results.

[0157] S702, for each family member recorded in the owner card, comparing the health data of a specified type with the corresponding historical data of each member having the same health data type, and obtaining a change range of the health data compared to the corresponding historical data;

[0158] In this embodiment, based on the first type of health data belonging to the specified type, the historical data of the member belonging to the first type can be first obtained from the historical health data records of each family member recorded in the owner card, and the historical data of each family member corresponds one by one to the health data belonging to the specified type; then, the health data belonging to the specified type is compared with the historical data of each family member.

[0159] Alternatively, a health database may be established in advance for each family member recorded in the owner's card according to the type of the aforementioned specific health data, and the health database may include the historical values ​​of each specific health data measured by the member most recently, and the data in the health database may be used as the baseline data of the member. When health data of a specified type is obtained from the owner's health test results, the health data of the specified type may be compared with the baseline data.

[0160] S703, for each of the historical data of each member, if the change range of the health data compared with the historical data is less than or equal to the change range threshold corresponding to the health data, then determine that the weight value corresponding to the historical data of the member is the preset attribution determination weight of the health data; otherwise, if the change range is greater than the change range threshold corresponding to the health data, then determine that the weight value corresponding to the historical data of the member is 0;

[0161] After obtaining the change range of the health data compared to the historical data, the change range threshold corresponding to the health data and the preset attribution determination weight can be obtained based on the pre-stored specific health data information.

[0162] S704, matching the weight value corresponding to the historical data of each member with a preset determination rule, and determining the family member to which the owner's health test result belongs according to the matching results of each member.

[0163] If the preset judgment rule is a cascade rule, then for each member, according to the priority order of the multiple first rules in the cascade rule, the result of the weight value corresponding to the historical data of the member is first matched with the first rule with the highest priority. If the match fails, it is matched with the first rule with the second highest priority, and so on. When the result of the weight value of the member satisfies one of the first rules, the matching process can be stopped, and the member can be determined as the family member to whom the health test result of the owner belongs; or, the priority of the first rule satisfied by the current member can be recorded, and then other members can be matched with the cascade rule in the same way as above, and the priority of the first rule satisfied can be recorded, and the member with the highest priority of the first rule satisfied among the members can be determined as the family member to whom the health test result of the owner belongs.

[0164] If the preset determination rules include multiple parallel second rules, the number of second rules satisfied by the results of the weight values ​​corresponding to the historical data of each member can be obtained respectively, and the member who satisfies the highest number of second rules that is not 0 is determined as the family member to whom the health test results of the owner belong.

[0165] In some other embodiments, when matching the results of the weight values ​​corresponding to the historical data of each member with the preset judgment rules, the order of the number of historical data whose weight values ​​corresponding to the historical data of the members are not 0 can be used as the matching order between the members from large to small, and the results of the weight values ​​corresponding to each member are matched with the preset judgment rules according to the matching order.

[0166] In response to the fact that the weight values ​​corresponding to the historical data of each member cannot be successfully matched with the preset judgment rules, the owner's health check result is a case where the data ownership cannot be automatically determined. The system can generate a prompt page based on the family member information recorded on the owner's owner card, and determine the ownership of the health check result based on the result manually selected by the owner.

[0167] Next, take the determination of the ownership of a certain owner's health test results in the above real estate scenario as an example to illustrate the above health data ownership determination method. After an owner swipes the owner card to complete the health data test, the latest test results obtained are shown in Table 2 below. The value of unmeasured health data can be 0:

[0168] Owner Card ID height weight waistline Hips Bone density T value Bone density Z score ... 00000001 180 89 90 70 3.5 1.2 ...

[0169] Table 2 The latest test results corresponding to the health data test of a certain owner

[0170] The owner's owner card records three family members. A health database is established for each of the three family members in advance. The health database contains the aforementioned specific health data. The value of the specific health data is the health data value of the member measured most recently before the current measurement of the owner. The data contained in the health database is used as the baseline data. Assuming that the owner card ID is 00000001, the pre-stored baseline data of the family members are shown in Table 3 below:

[0171] Owner Card ID Owner ID height weight waistline Hips Bone density T value Bone density Z score ... 00000001 1 180 90 90 70 3.5 1.2 ... 00000001 2 165 60 65 90 2.5 1.7 ... 00000001 3 130 30 50 50 3.0 1.8 ...

[0172] Table 3 Baseline data of each family member in the owner card

[0173] like Figure 8 As shown, first, the health data belonging to the specific health data type in the above Table 1 is obtained from the latest test results of the owner; then, the health data is compared with the baseline data corresponding to the health data of each family member in the owner's card, and the weight value corresponding to the baseline data is determined according to whether the change range of the health data compared to the baseline data meets the set change range. As shown in the following Tables 4-6, the health data is compared with the baseline data of the three family members respectively, and the weight value corresponding to the baseline data is obtained, and the comparison results corresponding to each member are obtained:

[0174]

[0175]

[0176] Table 4 Comparison results with the baseline data of family members whose owner ID is 1

[0177] Data Types Baseline data Latest data Is it within the range of variation? Weight value height 165 180 no 0 Bone density T value 2.5 3.4 no 0 Bone density Z score 1.7 1.2 no 0 weight 60 89 no 0 waistline 65 90 no 0 Hips 65 70 no 0

[0178] Table 5 Comparison results with the baseline data of family members whose owner ID is 2

[0179] Data Types Baseline data Latest data Is it within the range of variation? Weight value height 130 180 no 0 Bone density T value 3.0 3.4 no 0 Bone density Z score 1.8 1.2 no 0 weight 30 89 no 0 waistline 50 90 no 0 Hips 50 70 no 0

[0180] Table 6 Comparison results with the baseline data of family members whose owner ID is 3

[0181] If the judgment rules set based on the above Table 1 are:

[0182] (1) If the change range of at least two items of Category I health data in the comparison results meets the set change range threshold, it is determined that the test result to be processed belongs to the family member to which the comparison result belongs;

[0183] (2) If rule (1) is not satisfied, and the sum of the weight values ​​corresponding to the Class II health data in the comparison result is greater than 95%, it is determined that the test result to be processed belongs to the family member to which the comparison result belongs;

[0184] (3) If rules (1) and (2) are not satisfied, and the sum of the weight values ​​corresponding to the Class II and Class III health data in the comparison result is greater than 95%, it is determined that the test result to be processed belongs to the family member to which the comparison result belongs;

[0185] (4) If all the above rules are not met, the scenario cannot be automatically determined and the system will display a prompt interface for the owner to manually select data ownership.

[0186] So, if Figure 8 As shown, for the comparison results corresponding to each member, the comparison results are matched with the above-mentioned judgment rules in sequence according to the priority of the judgment rules. If any of the rules (1), (2), and (3) are met, the ownership of the latest test result of the owner is automatically determined; if none of the three rules are met, the ownership of the latest test result is manually determined according to rule (4).

[0187] In the disclosed embodiment, when the owner undergoes a health check, the health data that meets the requirements is compared with the baseline data of each family member, and the comparison result is determined according to the attribution judgment weight defined by the corresponding health data, thereby achieving automatic determination of data attribution based on the comparison results corresponding to each member, reducing the owner's additional operations and improving the user experience.

[0188] Corresponding to the embodiment of the above-mentioned health data attribution determination method, see Fig. 9 As shown, the present application also provides an embodiment of a device for determining health data attribution, the device comprising:

[0189] A health data acquisition module 910 is used to acquire health data to be processed;

[0190] The target group determination module 920 is used to determine the target group to which the health data belongs, and obtain the historical data of each member in the target group of the same type as the health data; the health data of each member in the target group is shared;

[0191] A comparison result acquisition module 930 is used to obtain a comparison result between the health data and the historical data of each member;

[0192] The data belonging member determination module 940 is used to determine the target member to which the health data belongs according to the comparison results corresponding to each member in the target group.

[0193] In some embodiments, the health data to be processed corresponds to a threshold value of a change amplitude of the health data within a set period; and the comparison result acquisition module is specifically used to:

[0194] Obtaining a change range of the health data compared to the historical data of the member;

[0195] In response to the change amplitude being less than or equal to the change amplitude threshold, determining that the comparison result corresponding to the historical data of the member is a first type of result;

[0196] In response to the change amplitude being greater than the change amplitude threshold, determining that the comparison result corresponding to the historical data of the member is a second type of result; the first type of result and the second type of result are used to mark the size relationship between the change amplitude and the change amplitude threshold.

[0197] In some embodiments, the health data to be processed corresponds to the data priority that meets the change amplitude threshold; based on the comparison result including the first category result and the second category result, the data belonging member determination module is specifically used to:

[0198] Determine, according to the priority sequence of the historical data of the member, the distribution of the first category results and the second category results in the comparison result corresponding to the member in the priority sequence;

[0199] The target member to which the health data belongs is determined according to a matching result between the distribution situation and a preset first attribution determination rule belonging to different data priorities.

[0200] In some embodiments, the health data to be processed corresponds to an attribution determination weight; the attribution determination weight is determined according to the change amplitude threshold; the comparison result includes a weight value corresponding to the historical data of the member; and the comparison result acquisition module is specifically used to:

[0201] In response to the change amplitude being less than or equal to the change amplitude threshold, determining the weight value corresponding to the historical data of the member as the attribution determination weight;

[0202] In response to the change amplitude being greater than the change amplitude threshold, determining that the weight value corresponding to the historical data of the member is zero.

[0203] In some embodiments, the health data to be processed corresponds to the data priority that meets the change amplitude threshold; the data belonging member determination module is specifically used to:

[0204] Determining a priority sequence corresponding to the historical data of the member;

[0205] According to the order of the priority sequence, the results of the weight values ​​corresponding to the historical data of the member are matched with the second attribution determination rule related to the priority in sequence;

[0206] In response to the existence of a result with the weight value satisfying the second attribution determination rule, the target member is determined to be the member to which the result with the weight value satisfying the determination rule belongs.

[0207] In some embodiments, the apparatus further comprises:

[0208] In response to the comparison results corresponding to the respective members not satisfying the attribution determination rule, generating a selection page according to member information in the target group to which the health data belongs;

[0209] It is determined that the target member to which the health data belongs is the member selected by the user in the selection page.

[0210] In some embodiments, the apparatus further comprises:

[0211] According to the health data, corresponding historical data of the target members in the target group are updated.

[0212] The implementation process of the functions and effects of each unit in the above-mentioned device is specifically described in the implementation process of the corresponding steps in the above-mentioned method, and will not be repeated here.

[0213] For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The device embodiment described above is only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present application scheme. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0214] The present application also provides an electronic device. The structural diagram of the electronic device is as follows: Fig.10 As shown, the electronic device 1000 includes at least one processor 1001, a memory 1002 and a bus 1003, and the at least one processor 1001 is electrically connected to the memory 1002; the memory 1002 is configured to store at least one computer-executable instruction, and the processor 1001 is configured to execute the at least one computer-executable instruction, thereby executing the steps of any health data attribution determination method provided in any embodiment or any optional implementation method of the present application.

[0215] Furthermore, the processor 1001 may be a Field-Programmable Gate Array (FPGA) or other devices with logic processing capabilities, such as a Microcontroller Unit (MCU) or a Central Process Unit (CPU).

[0216] An embodiment of the present application also provides another readable storage medium storing a computer program, which, when executed by a processor, is used to implement the steps of any health data attribution determination method provided in any embodiment or any optional implementation manner in the present application.

[0217] The readable storage medium provided in the embodiments of the present application includes, but is not limited to, any type of disk (including floppy disk, hard disk, optical disk, CD-ROM, and magneto-optical disk), ROM (Read-Only Memory), RAM (Random Access Memory), EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory, magnetic card or optical card. That is, the readable storage medium includes any medium that can store or transmit information in a readable form by a device (e.g., a computer).

[0218] Thus, specific embodiments of the subject matter have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the particular order or sequential order shown to achieve the desired results. In some implementations, multitasking and parallel processing may be advantageous.

[0219] Although the specification includes many specific implementation details, these should not be interpreted as limiting the scope of any invention or the scope of the claimed protection, but are mainly used to describe the features of the specific embodiments of the specific invention. Certain features described in multiple embodiments in this specification can be implemented in combination in a single embodiment. On the other hand, the various features described in a single embodiment can also be implemented separately in multiple embodiments or in any suitable sub-combination. In addition, features can work in certain combinations as described above, but one or more features from the claimed combination can be removed from the combination in some cases, and the claimed combination can point to a sub-combination or a variation of a sub-combination.

[0220] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for determining the ownership of health data, characterized in that: The method comprises: Obtain health data for processing; Determine the target group to which the health data belongs, and obtain historical data of each member in the target group of the same type as the health data; share the health data of each member in the target group; Obtaining a comparison result between the health data and the historical data of each member; The target member to which the health data belongs is determined according to the comparison results corresponding to each member in the target group.

2. The method according to claim 1, characterized in that The health data to be processed corresponds to a change amplitude threshold of the health data within a set period; The obtaining of the comparison result between the health data and the historical data of each member includes: Obtaining a change range of the health data compared to the historical data of the member; In response to the change amplitude being less than or equal to the change amplitude threshold, determining that the comparison result corresponding to the historical data of the member is a first type of result; In response to the change amplitude being greater than the change amplitude threshold, determining that the comparison result corresponding to the historical data of the member is a second type of result; the first type of result and the second type of result are used to mark the size relationship between the change amplitude and the change amplitude threshold.

3. The method according to claim 2, characterized in that The health data to be processed corresponds to the data priority that meets the change amplitude threshold; The determining the target member to which the health data belongs includes: Determine, according to the priority sequence of the historical data of the member, the distribution of the first category results and the second category results in the comparison result corresponding to the member in the priority sequence; The target member to which the health data belongs is determined according to a matching result between the distribution situation and a preset first attribution determination rule belonging to different data priorities.

4. The method according to claim 2, characterized in that: The health data to be processed corresponds to the attribution determination weight; the attribution determination weight is determined according to the change amplitude threshold; the comparison result includes the weight value corresponding to the historical data of the member; The obtaining of the comparison result between the health data and the historical data of each member includes: In response to the change amplitude being less than or equal to the change amplitude threshold, determining the weight value corresponding to the historical data of the member as the attribution determination weight; In response to the change amplitude being greater than the change amplitude threshold, determining that the weight value corresponding to the historical data of the member is zero.

5. The method according to claim 4, characterized in that The health data to be processed corresponds to the data priority that meets the change amplitude threshold; The determining the target member to which the health data belongs includes: Determining a priority sequence corresponding to the historical data of the member; According to the order of the priority sequence, the results of the weight values ​​corresponding to the historical data of the member are matched with the second attribution determination rule related to the priority in sequence; In response to the existence of a result with the weight value satisfying the second attribution determination rule, the target member is determined to be the member to which the result with the weight value satisfying the determination rule belongs.

6. The method according to claim 3 or 5, characterized in that The method further comprises: In response to the comparison results corresponding to the respective members not satisfying the attribution determination rule, generating a selection page according to member information in the target group to which the health data belongs; It is determined that the target member to which the health data belongs is the member selected by the user in the selection page.

7. The method according to claim 1, characterized in that After determining the target member to which the health data belongs, the method further includes: According to the health data, corresponding historical data of the target members in the target group are updated.

8. A device for determining the ownership of health data, characterized in that: The device comprises: A health data acquisition module, used to acquire health data to be processed; A target group determination module, used to determine the target group to which the health data belongs, and obtain the historical data of each member in the target group of the same type as the health data; the health data of each member in the target group is shared; A comparison result acquisition module, used to acquire the comparison result between the health data and the historical data of each member; The data belonging member determination module is used to determine the target member to which the health data belongs according to the comparison results corresponding to each member in the target group.

9. An electronic device, characterized in that: include: Processor, memory; The memory is used to store computer programs; The processor is used to call the computer program to implement the health data attribution determination method as described in any one of claims 1-7.

10. A readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, a method for determining the attribution of health data as described in any one of claims 1 to 7 is implemented.

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