Dynamic display method, client and system for blood glucose data

Abstract

The invention discloses a blood glucose data dynamic display method, client and system, and relates to the field of big data, the method comprises the following steps: receiving a first input of a first control in a blood glucose management interface; in response to the first input, a dynamic blood glucose data interface of the target user is displayed, and the dynamic blood glucose data interface comprises a blood glucose data trend chart formed by blood glucose data of the target user at different moments, and trend points and trend values corresponding to the different moments; receiving a second input of any trend point in the blood glucose data trend chart and a target prompt identifier; the target prompt identifier is at least one prompt identifier which is corresponding to the trend value of any trend point and represents a health scheme and a health state; and in response to the second input, displaying a target health prompt scheme, the target health prompt scheme being generated according to the target prompt identifier and the trend value of the corresponding trend point. The blood glucose data dynamic display efficiency can be improved, and then a user can be helped to efficiently obtain a target health prompt scheme.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of big data, and particularly relates to a blood glucose data dynamic display method, a client and a system. BACKGROUND

[0002] This section is intended to provide background or context to the embodiments of the application recited in the claims. The description herein does not constitute admission that the prior art is prior art nor, that anything in this section is "prior art" with respect to the application.

[0003] The existing personal blood glucose data display scheme mainly extracts the Raman spectrum characteristics of blood glucose data, establishes a blood glucose level prediction model according to the relationship between the Raman spectrum characteristics and the blood glucose level, and determines the user's sugar intake scheme according to the blood glucose level prediction result combined with the user's motion data. The existing personal blood glucose display scheme has the problem of low efficiency. SUMMARY

[0004] The embodiments of the present application provide a blood glucose data dynamic display method to improve the efficiency of blood glucose data dynamic display, and further efficiently help users to obtain a target health prompt scheme, which comprises the following steps:

[0005] receiving a first input to a first control in a blood glucose management interface;

[0006] In response to the first input, a dynamic blood glucose data interface of a target user is displayed, and the dynamic blood glucose data interface comprises a blood glucose data trend graph constituted by blood glucose data of the target user at different times, and corresponding trend points and trend values at different times;

[0007] receiving a second input to any trend point in the blood glucose data trend graph and a target prompt identifier; the target prompt identifier is at least one prompt identifier representing a health scheme and a health state corresponding to the trend value of the any trend point;

[0008] In response to the second input, a target health prompt scheme is displayed, and the target health prompt scheme is generated according to the target prompt identifier and the trend value of the corresponding trend point.

[0009] The embodiments of the present application also provide a blood glucose data dynamic display client to improve the efficiency of blood glucose data dynamic display, and further efficiently help users to obtain a target health prompt scheme, which comprises the following steps:

[0010] The first receiving unit is configured to receive a first input to a first control in a blood glucose management interface;

[0011] a first response unit, configured to display a dynamic blood glucose data interface of the target user in response to the first input, the dynamic blood glucose data interface comprising: a blood glucose data trend chart constituted by blood glucose data of the target user at different time points, and corresponding trend points and trend values at the different time points;

[0012] a second response unit, configured to receive a second input of any trend point in the blood glucose data trend chart and a target prompt identifier;

[0013] a second display unit, configured to display a target health prompt scheme in response to the second input, the target health prompt scheme being generated according to the target prompt identifier and the trend value of the corresponding trend point.

[0014] The embodiment of the present application also provides a dynamic display system of blood glucose data, to improve the efficiency of dynamic display of blood glucose data, and to efficiently help the user to obtain a target health prompt scheme, the system comprising:

[0015] a dynamic display client of blood glucose data as described above;

[0016] a server for providing the client with a target health prompt scheme;

[0017] and a doctor end for auditing the target health prompt scheme.

[0018] Compared with the prior art that cannot efficiently display blood glucose data by extracting Raman spectrum features of blood glucose data, the dynamic display scheme of blood glucose data provided by the embodiment of the present application can receive a first input of a first control in a blood glucose management interface, display a dynamic blood glucose data interface of a target user in response to the first input, the dynamic blood glucose data interface comprising: a blood glucose data trend chart constituted by blood glucose data of the target user at different time points, and corresponding trend points and trend values at the different time points, receive a second input of any trend point in the blood glucose data trend chart and a target prompt identifier, the target prompt identifier being at least one prompt identifier representing a health scheme and a health state corresponding to the trend value of the any trend point, and display a target health prompt scheme in response to the second input, the target health prompt scheme being generated according to the target prompt identifier and the trend value of the corresponding trend point, so that the efficiency of dynamic display of blood glucose data can be improved, and the user can efficiently obtain a target health prompt scheme. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor. In the drawings:

[0020] Figure 1 A flowchart of a blood glucose data dynamic display method in an embodiment of the present application is shown in

[0021] Figure 2 A schematic diagram of a blood glucose management interface in an embodiment of the present application is shown in

[0022] Figure 3 A schematic diagram of a blood glucose data trend interface in an embodiment of the present application is shown in

[0023] Figure 4 A structural schematic diagram of a blood glucose data dynamic display client in an embodiment of the present application is shown in

[0024] Figure 5 A structural schematic diagram of a blood glucose data dynamic display system in an embodiment of the present application is shown in DETAILED DESCRIPTION

[0025] In order to make the purpose, technical solutions and advantages of the embodiments of the present application more clear, the following will further describe the embodiments of the present application in combination with the drawings. Herein, the schematic embodiments of the present application and their descriptions are used to explain the present application, but not as a limitation to the present application.

[0026] The acquisition, storage, use, processing and the like of data in the technical solutions of the present application all comply with the relevant provisions of laws and regulations.

[0027] Figure 1 A flowchart of a blood glucose data dynamic display method in an embodiment of the present application is shown in Figure 1 The method comprises the following steps:

[0028] Step 101: receiving a first input to a first control in a blood glucose management interface;

[0029] Step 102: in response to the first input, displaying a dynamic blood glucose data interface of a target user, the dynamic blood glucose data interface comprising a blood glucose data trend graph constituted by blood glucose data of the target user at different time instants, and corresponding trend points and trend values at different time instants;

[0030] Step 103: receiving a second input of any trend point in the blood glucose data trend graph and a target prompt identifier; the target prompt identifier is at least one prompt identifier corresponding to the trend value of the trend point, which represents a health scheme and a health state;

[0031] Step 104: in response to the second input, displaying a target health prompt scheme, which is generated according to the target prompt identifier and the trend value of the corresponding trend point.

[0032] The blood glucose data dynamic display method provided by the embodiment of the present application, in work: receiving a first input of a first control in a blood glucose management interface; in response to the first input, displaying a dynamic blood glucose data interface of a target user, the dynamic blood glucose data interface including: a blood glucose data trend graph composed of blood glucose data of the target user at different times, and corresponding trend points and trend values at different times; receiving a second input of any trend point in the blood glucose data trend graph and a target prompt identifier; the target prompt identifier is at least one prompt identifier corresponding to the trend value of the trend point, which represents a health scheme and a health state; in response to the second input, displaying a target health prompt scheme, which is generated according to the target prompt identifier and the trend value of the corresponding trend point.

[0033] Compared with the technical scheme in the prior art that cannot efficiently display blood glucose data by extracting Raman spectrum characteristics of blood glucose data, the blood glucose data dynamic display method provided by the embodiment of the present application can improve the efficiency of blood glucose data dynamic display, and can help users to efficiently obtain a target health prompt scheme. The blood glucose data dynamic display method will be described in detail below. Figures 1 to 3

[0034] In the above step 101, the first input of the first control in the blood glucose management interface is received. The blood glucose management interface can be as shown in Figure 2 Figure 2 is a schematic diagram of the blood glucose management interface in the embodiment of the present application. The first control can be “dynamic blood glucose”, and the first input can be clicking the first control of “dynamic blood glucose” or hovering the mouse over the first control of “dynamic blood glucose”.

[0035] In the above step 102, in response to the first input, a dynamic blood glucose data interface of a target user is displayed, the dynamic blood glucose data interface including: a blood glucose data trend graph composed of blood glucose data of the target user at different times, and corresponding trend points and trend values at different times; the dynamic blood glucose data interface can be a dynamic blood glucose data interface including Figure 2 the blood glucose data trend graph in the following dynamic blood glucose data interface, Figure 2 can display a blood glucose data trend graph composed of 24-hour blood glucose data, Figure 2 ​​The different points on the middle trend curve can be trend points, such as a first trend point at 12:00, corresponding to a trend value of 4.2; a second trend point at 12:05, corresponding to a trend value of 5.6; a third trend point at 12:10, corresponding to a trend value of 2.8; a fourth trend point at 12:15, corresponding to a trend value of 2.8; a fifth trend point at 12:20, corresponding to a trend value of 9.8; a sixth trend point at 12:25, corresponding to a trend value of 16; and a seventh trend point at 12:30, corresponding to a trend value of 16.

[0036] In step 103, a second input is received for any trend point in the blood glucose data trend graph and a target prompt identifier, which can be a mouse floating over the trend point and further floating over any prompt identifier. The target prompt identifier is at least one prompt identifier representing a health plan and a health status corresponding to the trend value of the trend point. The prompt identifier can be Figure 2 The multiple prompt identifiers above the trend point, such as a green medicine box prompt identifier above the third trend point, represent that the trend value of 2.8 can be used for a health plan of taking medicine. However, considering the size of the current trend value, the green color represents a good health status, and there is no need to select the health plan of taking medicine. That is, the trend value can determine the current health plan and health status, or the trend value can determine the style and color of the prompt identifier. The prompt identifier can also be a water droplet-shaped identifier as shown in Figure 2 The prompt identifier can also be a running identifier as shown in Figure 2 The prompt identifier can also be a running identifier as shown in Figure 2 The prompt identifier below the running identifier represents a health plan of diet.

[0037] In step 104, a target health prompt plan is displayed in response to the second input, such as a mouse floating over the trend point and further floating over any prompt identifier. The target health prompt plan is generated according to the target prompt identifier and the trend value of the corresponding trend point. For example, a detailed textual description of the health prompt plan corresponding to the running icon is displayed, such as "recently good, please continue to maintain good exercise habits" and the like. Figure 2 The trend value of the sixth trend point is 16, which has reached a dangerous health status. Therefore, the medicine prompt identifier is displayed in red, indicating that the medicine needs to be taken immediately. According to the prediction of the health status, the safety of the user can be ensured. The running prompt identifier is red, indicating that the user's health status cannot adopt the health plan of running. Other prompt identifier (icon) health prompt plans are not described in detail.

[0038] It can be learned from the above that the blood glucose data dynamic display method provided by the embodiment of the application can record blood glucose data and trends thereof for 24 hours, display prompt marks representing health plans and health states, and realize on-screen display of health prompt plans according to the prompt marks, so as to improve the efficiency of blood glucose data dynamic display, and further help users to efficiently obtain target health prompt plans.

[0039] Further preferred embodiments of the application are described below.

[0040] In one embodiment, the trend value is a ratio of a dynamic blood glucose data change value of the target user in a target period to a target length, which can represent a slope.

[0041] In specific implementation, for example Figure 2 The trend value calculation method of each trend point in the embodiment can be to calculate a slope value through the abscissa (collection time) and the ordinate (collected real-time blood glucose data) to represent the trend value, and the size of the trend value represents the sudden change of the trend or the gentleness of the trend. The greater the slope is, the faster the blood glucose trend changes, and the more dangerous the blood glucose condition of the user is. Further, the dynamic display precision of the blood glucose data is improved.

[0042] In one embodiment, the dynamic display of the blood glucose data can further include: when the trend value of the trend point is within a preset abnormal value range, changing the display mode of the trend point to give a warning prompt to the target user.

[0043] In specific implementation, for example Figure 2 The trend value 16 of the sixth trend point in the embodiment is within the preset abnormal value range, and the display mode of the trend point is changed, for example Figure 2 In the embodiment, the trend point is changed to red display to give a warning prompt to the target user, and the target user needs to prepare for medication. Of course, the trend point can also be changed to other shapes for display, as long as it can play a role in warning the user. Further, the dynamic display efficiency of the blood glucose data is improved, and the user experience is improved.

[0044] In one embodiment, the dynamic display of the blood glucose data can further include:

[0045] receiving a third input to the second control in the blood glucose management interface;

[0046] In response to the third input, displaying a blood glucose data trend interface of the target user, the blood glucose data trend interface including: a comparison between different types of blood glucose data and corresponding blood glucose data indicators of the target user in a preset period.

[0047] In specific implementation, for example Figure 2 As shown in the embodiment, a third input to the second control (for example Figure 2a third input (which can be a mouse click on "data trend report", or a mouse hover over the second control "data trend report"), in response to the third input, displaying an interface of blood glucose data trend of the target user as shown in FIG. 10B, Figure 3 Figure 3 FIG. 10A is a schematic diagram of a blood glucose data trend interface in an embodiment of the present application, which includes a preset time period (e.g. 09.19-09.30 in FIG. 10A) of a target user, and different types of blood glucose data (e.g. CGM, MBG, glucose management target value, CV, etc.) and corresponding blood glucose data indicators (e.g. 70% of the 14 days are valid data, reference value 4.3-6.6 mmol / L, reference value <7%, reference value 18%-36%) in the preset time period of the target user. Figure 3 Figure 3 The comparison of different types of blood glucose data (e.g. CGM, MBG, glucose management target value, CV, etc.) and corresponding blood glucose data indicators (e.g. 70% of the 14 days are valid data, reference value 4.3-6.6 mmol / L, reference value <7%, reference value 18%-36%) in the preset time period of the target user further improves the dynamic display efficiency of blood glucose data.

[0048] In an embodiment, the blood glucose data trend interface can further include different abnormal data proportion threshold values or proportion combination threshold values corresponding to different types of users.

[0049] The dynamic display of blood glucose data can further include:

[0050] Monitoring the proportion of abnormal data of different types of users in the preset monitoring time period;

[0051] According to the proportion of abnormal data of different types of users in the preset monitoring time period, and the different abnormal data proportion threshold values or proportion combination threshold values corresponding to different types of users, the health status of the user is warned, different monitoring standards are implemented for different types of users, the monitoring accuracy of the health status of the user is further improved, and the user experience is further improved.

[0052] Figure 3 TAR in FIG. 10A is the time when glucose is higher than the target range: the yellow column and / or the orange column area is shown. For general adult diabetic users, it is recommended that the yellow column be <25% and the orange column be <5%; for elderly and high-risk diabetic users, it is recommended that the yellow column be <50% and the orange column be <10% (the yellow column <50% and the orange column <10% are the proportion combination threshold values); for gestational diabetes users, it is recommended that the yellow column be <25%.

[0053] Figure 3 TIR in FIG. 10A is the time when glucose is in the target range: the green column area is shown. For general adult diabetic users, it is recommended that the green column be >70%; for elderly and high-risk diabetic users, it is recommended that the green column be >50%; for gestational diabetes users, it is recommended that the green column be >70%.

[0054] Figure 3 ​​Time of TBR below target range for glucose: shown as red bars and / or dark red bar area. For general adult diabetes users, red bars <4% and dark red bars <1% are recommended; for elderly and high-risk diabetes users, red bars <1% and no dark red bars are recommended; for gestational diabetes users, red bars <4% and dark red bars <1% are recommended.

[0055] In one embodiment, the dynamic display of the blood glucose data can further include: when an abnormality of the device data for monitoring the dynamic blood glucose data of the target user is detected, the device data is processed more accurately.

[0056] In specific implementation, as shown in the "more accurate data", when an abnormality of the device data for monitoring the dynamic blood glucose data of the target user is detected, the device data is processed more accurately, further improving the accuracy of the dynamic display of the blood glucose data. Figure 2

[0057] In one embodiment, the dynamic display of the blood glucose data can further include: when an abnormality of the blood glucose data trend is detected, a real-time event of the target user affecting the blood glucose data trend is recorded.

[0058] In specific implementation, as shown in the "recorded event", when an abnormality of the blood glucose data trend is detected, a real-time event of the target user affecting the blood glucose data trend is recorded, which can be used to accurately predict the health status of the user later. Figure 2

[0059] In one embodiment, the dynamic display of the blood glucose data can further include: generating the health prompt scheme in the following manner:

[0060] sending the target prompt identifier and the trend value of the corresponding trend point to a server; the server is used to generate a target health prompt scheme of the target prompt identifier and the trend value of the corresponding trend point according to the target prompt identifier and the trend value of the corresponding trend point, and the relationship between the prompt identifier and the trend value of the corresponding trend point and the health prompt scheme, and feed back the target health prompt scheme to the client;

[0061] receiving the target health prompt scheme obtained according to the target prompt identifier and the trend value of the corresponding trend point.

[0062] In specific implementation, the target health prompt scheme can be generated on the client, in order to reduce the calculation amount of the client, the target prompt identifier and the trend value of the corresponding trend point can be sent to a server, the target health prompt scheme of the target prompt identifier and the trend value of the corresponding trend point is generated through the server, and fed back to the client, improving the efficiency of the client.

[0063] ​​In particular implementation, the target health prompt scheme corresponding to the current trend waveform can also be obtained by inputting the pre-established target health prompt scheme prediction model according to the current trend waveform in the preset period, the target health prompt scheme is pre-trained according to the relationship sample data between a plurality of (a large number of) historical trend waveforms and the target health prompt scheme, and the input of the target health prompt scheme prediction model is the trend waveform, and the output is the target health prompt scheme, so that the efficiency and accuracy of the target health prompt scheme generation are further improved.

[0064] In one embodiment, the dynamic display of the blood glucose data can further include that the server is specifically configured to obtain the target health prompt scheme according to the following method:

[0065] obtaining the target prompt identifier and the trend value of the corresponding trend point;

[0066] matching the target prompt identifier and the trend value of the corresponding trend point in the distributed database to obtain the correlation probability between the target prompt identifier, the trend value of the corresponding trend point and the abnormal blood glucose trend, and the distributed database is distributedly stored with the relationship between the correlation probability between the prompt identifier and the trend value of the corresponding trend point and the abnormal blood glucose trend;

[0067] matching the correlation probability between the target prompt identifier and the trend value of the corresponding trend point and the abnormal blood glucose trend as the current correlation probability in the health scheme library to obtain the optimal health scheme corresponding to the current correlation probability, and the health scheme library is pre-established with the relationship between the correlation probability and the health scheme;

[0068] converting the correlation probability between the target prompt identifier and the trend value of the corresponding trend point and the abnormal blood glucose trend into a correlation probability feature vector between the target prompt identifier and the trend value of the corresponding trend point and the abnormal blood glucose trend;

[0069] inputting the correlation probability feature vector between the target prompt identifier and the trend value of the corresponding trend point and the abnormal blood glucose trend into the health state prediction model to obtain the health state corresponding to the current correlation probability, and the health state prediction model is pre-trained according to the relationship sample data between the historical correlation probability feature vector and the health state of the user;

[0070] determining the target health prompt scheme according to the optimal health scheme and the health state corresponding to the current correlation probability and feeding back the target health prompt scheme to the client.

[0071] In specific implementation, the dynamic display method of blood glucose data provided by the embodiment of the present invention realizes the mining of the intrinsic correlation between the user's blood glucose data and the corresponding health plan through a distributed database and a health plan library, predicts the user's health status through a health status prediction model, and determines the target health prompt plan based on the optimal health plan and health status corresponding to the current correlation probability and feeds it back to the client, which can improve the efficiency and accuracy of the dynamic display of blood glucose data.

[0072] In one embodiment, the method for dynamically displaying blood sugar data according to the embodiment of the present invention may further include: pre-establishing a distributed database and a health plan library according to the following method:

[0073] Get historical blood sugar data for multiple users;

[0074] Extract historical keywords from historical blood glucose data;

[0075] Classify the historical blood glucose data to obtain the historical blood glucose data type;

[0076] Determine the historical correlation probability between the historical prompt identifier and the trend value of the corresponding trend point and the abnormal blood glucose trend based on the historical keywords and the historical blood glucose data type;

[0077] The historical correlation probability relationship between the historical prompt identifier and the trend value of the corresponding trend point and the abnormal blood glucose trend is stored in a distributed database, and the correlation probability relationship between the prompt identifier and the trend value of the corresponding trend point and the abnormal blood glucose trend is obtained;

[0078] The relationship between the historical correlation probability and the corresponding historical optimal health plan is stored in the health plan library to obtain the relationship between the correlation probability and the health plan.

[0079] In the data preparation phase, the embodiment of the present application collects historical blood glucose data of multiple users, such as physical examination data, medical record data, and the like, and performs preprocessing such as sorting and cleaning. Key words are extracted from the historical blood glucose data, the historical blood glucose data is classified, and historical blood glucose data types (such as fasting blood glucose, pre-meal blood glucose, post-meal blood glucose, and average blood glucose) are obtained. According to the historical key words and the historical blood glucose data types, the historical correlation probability between the historical blood glucose data and the abnormal blood glucose trend (the abnormal blood glucose trend in the embodiment of the present application can be in the form of an abnormal blood glucose trend graph) is determined, that is, the key words and the correlation probability are assigned, and after the assignment, distributed data storage is performed. The relationship between the historical correlation probability of the historical prompt identifier and the trend value of the corresponding trend point and the abnormal blood glucose trend is stored in the distributed database, and the relationship between the prompt identifier and the trend value of the corresponding trend point and the correlation probability of the abnormal blood glucose trend is obtained. The relationship between the historical correlation probability and the corresponding historical optimal health scheme is stored in the health scheme library, and the relationship between the correlation probability and the health scheme is obtained. Therefore, the embodiment of pre-establishing the distributed database and the health scheme library can improve the efficiency of the dynamic display of the subsequent blood glucose data.

[0080] As can be seen from the above, in one embodiment, classifying the historical blood glucose data to obtain historical blood glucose data types can include: classifying the historical blood glucose data using a decision tree or a clustering algorithm to obtain historical blood glucose data types.

[0081] In particular implementation, classifying the historical blood glucose data using a decision tree or a clustering algorithm to obtain historical blood glucose data types can improve the efficiency and accuracy of classifying the historical blood glucose data.

[0082] In one embodiment, the target prompt identifier and the trend value of the corresponding trend point are matched in the distributed database to obtain the correlation probability between the target prompt identifier and the trend value of the corresponding trend point and the abnormal blood glucose trend; the distributed database has a distributed storage of the relationship between the prompt identifier and the trend value of the corresponding trend point and the correlation probability of the abnormal blood glucose trend. The relationship can be a table or a model.

[0083] In one embodiment, the correlation probability between the target prompt identifier and the trend value of the corresponding trend point and the abnormal blood glucose trend is matched in the health scheme library as the current correlation probability to obtain the optimal health scheme corresponding to the current correlation probability; the health scheme library has a pre-established relationship between the correlation probability and the health scheme, which can be a table or a model.

[0084] In one embodiment, the optimal health scheme corresponding to the current correlation probability is pushed to a doctor terminal; the doctor terminal is configured to send the optimal health scheme corresponding to the current correlation probability to a client terminal of the user after receiving an instruction of the doctor approving the optimal health scheme corresponding to the current correlation probability. The doctor's work efficiency can be improved, and the client can efficiently obtain the optimal health scheme, and the client can be urged to manage health.

[0085] In one embodiment, the dynamic display method of the blood glucose data further includes:

[0086] detecting a current application scenario of the target prompt identifier and the trend value of the corresponding trend point;

[0087] determining a health state prediction model corresponding to a type of the current application scenario according to the current application scenario of the target prompt identifier and the trend value of the corresponding trend point;

[0088] inputting a correlation probability feature vector between the target prompt identifier and the trend value of the corresponding trend point and an abnormal blood glucose trend into the health state prediction model to obtain a health state corresponding to a current correlation probability, including: inputting the correlation probability feature vector between the target prompt identifier and the trend value of the corresponding trend point and the abnormal blood glucose trend into the health state prediction model corresponding to the type of the current application scenario to obtain a health state prediction result of the user.

[0089] In specific implementation, in the embodiment of the present application, a plurality of health state prediction models corresponding to different application scenarios are trained according to machine learning algorithms (such as logistic regression and random forest) or deep learning algorithms corresponding to types of different application scenarios. For health state prediction of a scenario with a complexity exceeding a preset threshold, a health state prediction model can be trained by a deep learning algorithm to perform health state prediction, which can further improve the flexibility and accuracy of health state prediction.

[0090] In one embodiment, the dynamic display method of the blood glucose data further includes: pre-training the health state prediction model by distributed computing on a distributed cluster.

[0091] In specific implementation, in the embodiment of the present application, a distributed cluster such as a multi-processor training scheme is used to train the health state prediction model by distributed computing, which improves the execution effect of hardware in the training process and thus obtains the technical effect of improving the internal performance of the computer system.

[0092] In summary, the embodiment of the present application links the health plan and the health prediction together through the blood glucose data and the correlation probability between the blood glucose data and the abnormal blood glucose trend, and uses the distributed data storage and technology to automatically match the health management plan of the client and predict the future health state of the client, thereby improving the efficiency of the dynamic display of the blood glucose data, and further efficiently helping the user to obtain the optimal health plan, improving the work efficiency of the doctor, urging the user to perform the health management, and improving the user experience.

[0093] The embodiment of the present application also provides a dynamic display client of blood glucose data, as described in the following embodiment. Since the principle of solving the problem of the client is similar to that of the dynamic display method of the blood glucose data, the implementation of the client can be referred to the implementation of the dynamic display method of the blood glucose data, and the repeated parts will not be described herein.

[0094] Figure 4 FIG. 1 shows a structural schematic diagram of a dynamic display client of blood glucose data in the embodiment of the present application, which includes the following components. Figure 4

[0095] The first receiving unit 11 is configured to receive a first input to a first control in a blood glucose management interface.

[0096] The first response unit 12 is configured to display a dynamic blood glucose data interface of a target user in response to the first input, wherein the dynamic blood glucose data interface includes a blood glucose trend graph constituted by blood glucose data of the target user at different time points, and corresponding trend points and trend values at different time points.

[0097] The second response unit 13 is configured to receive a second input to any trend point in the blood glucose trend graph and a target prompt identifier, wherein the target prompt identifier is at least one prompt identifier indicating a health plan and a health state corresponding to the trend value of the any trend point.

[0098] The second display unit 14 is configured to display a target health prompt plan in response to the second input, wherein the target health prompt plan is generated according to the target prompt identifier and the trend value of the corresponding trend point.

[0099] In one embodiment, the trend value is a ratio of a dynamic blood glucose data change value of the target user in a target time period to a target time length.

[0100] In one embodiment, the dynamic display client of blood glucose data can further include a warning unit configured to change the display mode of the trend point when the trend value of the trend point is within a preset abnormal value range, so as to give a warning prompt to the target user.

[0101] In one embodiment, the dynamic display client of blood glucose data can further include:

[0102] ​a third receiving unit, configured to receive a third input to the second control in the blood glucose management interface;

[0103] a third response unit, configured to display a blood glucose data trend interface of the target user in response to the third input, the blood glucose data trend interface including a comparison between different types of blood glucose data and corresponding blood glucose data indicators within a preset time period of the target user.

[0104] In an embodiment, the dynamic display client of blood glucose data further includes a more accurate processing unit configured to perform more accurate processing on the device data when detecting abnormal device data for monitoring the dynamic blood glucose data of the target user.

[0105] In an embodiment, the dynamic display client of blood glucose data further includes an abnormal event recording unit configured to record real-time events of the target user affecting the blood glucose data trend when detecting abnormal trend of the blood glucose data.

[0106] In an embodiment, the dynamic display client of blood glucose data further includes a generating unit configured to generate the health prompt scheme in the following manner:

[0107] sending the target prompt identifier and the trend value of the corresponding trend point to a server; the server is configured to generate a target health prompt scheme of the target prompt identifier and the trend value of the corresponding trend point according to the target prompt identifier and the trend value of the corresponding trend point, and a relationship between the prompt identifier and the trend value of the corresponding trend point and the health prompt scheme, and feed back the target health prompt scheme to the client.

[0108] receiving the target health prompt scheme obtained according to the target prompt identifier and the trend value of the corresponding trend point.

[0109] In an embodiment, the server is specifically configured to obtain the target health prompt scheme in the following method:

[0110] obtaining the target prompt identifier and the trend value of the corresponding trend point;

[0111] matching the target prompt identifier and the trend value of the corresponding trend point in a distributed database to obtain a correlation probability between the target prompt identifier and the trend value of the corresponding trend point and the abnormal blood glucose trend; the distributed database is distributedly stored with a relationship between the correlation probability between the prompt identifier and the trend value of the corresponding trend point and the abnormal blood glucose trend;

[0112] matching the correlation probability between the target prompt identifier and the trend value of the corresponding trend point and the abnormal blood glucose trend as a current correlation probability in a health scheme library to obtain an optimal health scheme corresponding to the current correlation probability; the health scheme library is previously established with a relationship between the correlation probability and the health scheme;

[0113] convert the correlation probability between the target prompt identifier and the trend value of the corresponding trend point and the abnormal blood glucose trend into a correlation probability feature vector between the target prompt identifier and the trend value of the corresponding trend point and the abnormal blood glucose trend;

[0114] input the correlation probability feature vector between the target prompt identifier and the trend value of the corresponding trend point and the abnormal blood glucose trend into a health state prediction model to obtain a health state corresponding to the current correlation probability, the health state prediction model being generated by pre-training according to historical correlation probability feature vectors and user health state relationship sample data;

[0115] determine a target health prompt scheme according to the optimal health scheme and the health state corresponding to the current correlation probability, and feed back the target health prompt scheme to the client.

[0116] Figure 5 A structural schematic diagram of a blood glucose data dynamic display system in an embodiment of the present application is shown in FIG. 1. Figure 5 As shown in FIG. 1, the system includes a blood glucose data dynamic display client as described above, a server providing a target health prompt scheme for the client, and a doctor terminal auditing the target health prompt scheme. The client 10 can receive user blood glucose data monitored by a blood glucose device in real time, and the blood glucose data can also be blood glucose profile data established by user input health information, which can include structured blood glucose data and unstructured blood glucose data. The structured data can include, for example, physical examination indicators, dynamic blood glucose detection data, etc., and the unstructured data can include medical images, medical record texts, etc. The blood glucose data is stored in a distributed database. The client 10 can also receive and respond to a first input, display a dynamic blood glucose data interface of a target user, send a target prompt identifier and a trend value of a corresponding trend point to the server 20, and the server 20 generates a target health prompt scheme according to the target prompt identifier and the trend value of the corresponding trend point, and sends the target health prompt scheme to the doctor terminal 30. When the doctor terminal 30 receives an instruction that the target health prompt scheme is audited by the doctor, the target health prompt scheme is fed back to the client. The client 10 receives and responds to a second input, and displays the target health prompt scheme. The client can view the health management scheme on the client, which can improve the efficiency of the blood glucose data dynamic display, and further efficiently help the user to obtain the target health prompt scheme.

[0117] The embodiment of the present application also provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the blood glucose data dynamic display method when executing the computer program.

[0118] The embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the blood glucose data dynamic display method.

[0119] The embodiment of the present application further provides a computer program product, which comprises a computer program, and the computer program is executed by a processor to realize the blood glucose data dynamic display method.

[0120] Compared with the prior art, the blood glucose data dynamic display method provided by the embodiment of the present application can improve the efficiency of blood glucose data dynamic display, and further help users to obtain a target health prompt scheme efficiently.

[0121] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt a computer program product in the form of being implemented on one or more computer usable storage media (including but not limited to disk memory, CD-ROM, optical memory, etc.) containing computer usable program codes.

[0122] The present application is described with reference to flowcharts and / or block diagrams of the method, device (system), and computer program product according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the computer or other programmable data processing devices produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in one flow or multiple flows and / or blocks Figure 1 The functions specified in one flow or multiple flows and / or blocks

[0123] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0124] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0125] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for dynamically displaying blood sugar data, which is applied to a client and is characterized in that: include: receiving a first input to a first control in the blood glucose management interface; In response to the first input, a dynamic blood glucose data interface of the target user is displayed, wherein the dynamic blood glucose data interface includes: a blood glucose data trend graph consisting of the target user's blood glucose data at different times, and trend points and trend values ​​corresponding to the different times; receiving a second input of any trend point and a target prompt identifier in the blood glucose data trend graph; the target prompt identifier being at least one prompt identifier representing a health plan and a health status corresponding to the trend value of the any trend point; In response to the second input, a target health prompt scheme is displayed, where the target health prompt scheme is generated according to the target prompt identifier and the trend value of the corresponding trend point.

2. The method according to claim 1, wherein The trend value is: the ratio of the dynamic blood glucose data change value of the target user within the target period to the target duration.

3. The method according to claim 1, wherein Also includes: When the trend value of a trend point is within the preset abnormal value range, the display mode of the trend point is changed to issue an early warning prompt to the target user.

4. The method according to claim 1, wherein Also includes: receiving a third input to a second control in the blood glucose management interface; In response to the third input, a blood glucose data trend interface of the target user is displayed, wherein the blood glucose data trend interface includes a comparison between different types of blood glucose data and corresponding blood glucose data indicators within a preset time period of the target user.

5. The method according to claim 1, wherein Also includes: When an abnormality is detected in the device data used to monitor the dynamic blood glucose data of the target user, the device data is accurately processed.

6. The method according to claim 1, wherein Also includes: When abnormal blood sugar data trends are detected, real-time events of target users that affect the blood sugar data trends are recorded.

7. The method according to claim 1, wherein The health reminder scheme is also generated in the following manner: The target prompt identifier and the trend value of the corresponding trend point are sent to a server; the server is used to generate a target health prompt scheme for the target prompt identifier and the trend value of the corresponding trend point based on the target prompt identifier and the trend value of the corresponding trend point, as well as the relationship between the prompt identifier and the trend value of the corresponding trend point and the health prompt scheme, and feed the target health prompt scheme back to the client; Receive a target health prompt solution obtained according to the target prompt identifier and the trend value of the corresponding trend point.

8. The method according to claim 7, wherein The server is specifically configured to obtain a target health reminder solution in the following manner: Get the target prompt identifier and the trend value of the corresponding trend point; Matching the target prompt identifier and the trend value of the corresponding trend point to the distributed database to obtain the correlation probability between the target prompt identifier and the trend value of the corresponding trend point and the abnormal blood sugar trend; The distributed database stores the prompt identifier and the correlation probability between the trend value of the corresponding trend point and the abnormal blood sugar trend; The correlation probability between the target prompt identifier and the trend value of the corresponding trend point and the abnormal blood sugar trend is used as the current correlation probability to match the health plan library to obtain the optimal health plan corresponding to the current correlation probability; the relationship between the correlation probability and the health plan is pre-established in the health plan library; Converting the probability of correlation between the target prompt mark and the trend value of the corresponding trend point and the abnormal blood glucose trend into a probability feature vector of correlation between the target prompt mark and the trend value of the corresponding trend point and the abnormal blood glucose trend; Inputting the correlation probability feature vector between the target prompt identifier and the trend value of the corresponding trend point and the abnormal blood sugar trend into the health status prediction model to obtain the health status corresponding to the current correlation probability; the health status prediction model is pre-trained based on sample data of the relationship between historical correlation probability feature vectors and the user's health status; According to the optimal health plan and health status corresponding to the current correlation probability, the target health prompt plan is determined and fed back to the client.

9. A client for dynamic display of blood sugar data, characterized in that: include: a first receiving unit, configured to receive a first input to a first control in the blood glucose management interface; a first response unit, configured to display a dynamic blood glucose data interface of a target user in response to the first input, wherein the dynamic blood glucose data interface includes a blood glucose data trend graph consisting of blood glucose data of the target user at different times, and trend points and trend values ​​corresponding to the different times; A second response unit is configured to receive a second input of any trend point and a target prompt identifier in the blood glucose data trend graph; the target prompt identifier is at least one prompt identifier representing a health plan and a health status corresponding to the trend value of the any trend point; The second display unit is used to display a target health prompt scheme in response to the second input, where the target health prompt scheme is generated according to the target prompt identifier and the trend value of the corresponding trend point.

10. A dynamic display system for blood sugar data, characterized in that: include: The dynamic display client for blood glucose data according to claim 9; A server that provides a target health reminder solution to the client; and a physician end for reviewing said target health reminder program.

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