CN117153366A - Blood glucose data processing method, electronic device and storage medium - Google Patents
Blood glucose data processing method, electronic device and storage medium Download PDFInfo
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- CN117153366A CN117153366A CN202310646495.4A CN202310646495A CN117153366A CN 117153366 A CN117153366 A CN 117153366A CN 202310646495 A CN202310646495 A CN 202310646495A CN 117153366 A CN117153366 A CN 117153366A
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- 239000008280 blood Substances 0.000 title claims abstract description 335
- 210000004369 blood Anatomy 0.000 title claims abstract description 335
- WQZGKKKJIJFFOK-GASJEMHNSA-N Glucose Natural products OC[C@H]1OC(O)[C@H](O)[C@@H](O)[C@@H]1O WQZGKKKJIJFFOK-GASJEMHNSA-N 0.000 title claims abstract description 272
- 239000008103 glucose Substances 0.000 title claims abstract description 272
- 238000003672 processing method Methods 0.000 title abstract description 21
- 238000001514 detection method Methods 0.000 claims abstract description 183
- 230000004044 response Effects 0.000 claims abstract description 43
- 238000000034 method Methods 0.000 claims abstract description 41
- 230000001815 facial effect Effects 0.000 claims abstract description 26
- 230000002159 abnormal effect Effects 0.000 claims abstract description 10
- 238000012360 testing method Methods 0.000 claims description 40
- 230000001610 euglycemic effect Effects 0.000 claims description 10
- 238000012790 confirmation Methods 0.000 claims description 8
- 238000012545 processing Methods 0.000 claims description 7
- 238000004590 computer program Methods 0.000 claims description 3
- 230000002641 glycemic effect Effects 0.000 claims description 2
- 238000013523 data management Methods 0.000 abstract description 4
- 238000004891 communication Methods 0.000 description 11
- 230000006870 function Effects 0.000 description 5
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Classifications
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/14532—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring glucose, e.g. by tissue impedance measurement
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
- G16H40/63—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
Abstract
The application provides a blood glucose data processing method, electronic equipment and a storage medium, wherein the method comprises the steps of collecting facial image information of a user, and determining a target user based on the facial image information of the user; in response to receiving a blood glucose detection instruction, performing blood glucose detection to obtain a current blood glucose detection result; in response to determining that the target user is unique and corresponds to a target historical blood glucose detection result, determining the unique target user as the user currently performing blood glucose detection, and acquiring the target historical blood glucose detection result: and determining whether the current blood glucose detection result is in a normal range or not based on the target historical blood glucose detection result, and outputting prompt information of abnormal blood glucose in response to the current blood glucose detection result not being in the normal range, so that personalized blood glucose data management service can be conveniently provided for household blood glucose meters used by multiple people.
Description
Technical Field
The present application relates to the field of blood glucose data technologies, and in particular, to a blood glucose data processing method, an electronic device, and a storage medium.
Background
At present, the intelligent blood glucose meter used by the medical institution detects, identifies and manages blood glucose of different users by scanning the wrist strap bar code, the two-dimensional code and inputting the ID number, but the intelligent blood glucose meter used by the medical institution is generally not provided with the conditions for village medical stations and common household users, and has a certain technical limitation of relatively high price, complex operation and portability. Therefore, some home blood glucose meters are the choice for many ordinary households, but the current home blood glucose meters in the related art cannot meet the requirement of simultaneous use by multiple people.
Disclosure of Invention
In view of the above, the present application provides a blood glucose data processing method, an electronic device and a storage medium to solve or partially solve the above-mentioned problems.
Based on the above object, the present application provides a blood glucose data processing method, which is applied to a blood glucose meter, and comprises the following steps:
collecting user face image information, and determining a target user based on the user face image information;
in response to receiving a blood glucose detection instruction, performing blood glucose detection to obtain a current blood glucose detection result;
in response to determining that the target user is unique and corresponds to a target historical blood glucose detection result, determining the unique target user as the user currently performing blood glucose detection, and acquiring the target historical blood glucose detection result:
and determining whether the current blood glucose detection result is in a normal range based on the target historical blood glucose detection result, and outputting prompt information of abnormal blood glucose in response to the current blood glucose detection result not being in the normal range.
Based on the same conception, the application also provides an electronic device which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the blood glucose data processing method when executing the program.
Based on the same conception, the present application also proposes a non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the blood glucose data processing method as described above.
From the above, it can be seen that the blood glucose data processing method, the electronic device and the storage medium provided by the application collect facial image information of a user, and determine a target user based on the facial image information of the user; in response to receiving a blood glucose detection instruction, performing blood glucose detection to obtain a current blood glucose detection result; in response to determining that the target user is unique and corresponds to a target historical blood glucose detection result, determining the unique target user as the user currently performing blood glucose detection, and acquiring the target historical blood glucose detection result: and determining whether the current blood glucose detection result is in a normal range based on the target historical blood glucose detection result, and outputting prompt information of abnormal blood glucose in response to the current blood glucose detection result not being in the normal range, so that a user currently carrying out blood glucose detection can be determined through facial image recognition, whether the current blood glucose detection result is in the normal range is determined according to the target historical blood glucose detection result of the user currently carrying out blood glucose detection, and personalized blood glucose data management service can be conveniently provided for household blood glucose meters used by multiple people.
Drawings
In order to more clearly illustrate the technical solutions of the present application or related art, the drawings that are required to be used in the description of the embodiments or related art will be briefly described below, and it is apparent that the drawings in the following description are only embodiments of the present application, and other drawings may be obtained according to the drawings without inventive effort to those of ordinary skill in the art.
FIG. 1 is a flow chart of a blood glucose data processing method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a blood glucose data processing apparatus according to an embodiment of the present application;
fig. 3 is a schematic hardware structure of a specific electronic device according to an embodiment of the present application.
Detailed Description
It will be appreciated that the data (including but not limited to the data itself, the acquisition or use of the data) involved in the present technical solution should comply with the corresponding legal regulations and the requirements of the relevant regulations.
It should be noted that unless otherwise defined, technical or scientific terms used in the embodiments of the present application should be given the ordinary meaning as understood by one of ordinary skill in the art to which the present application belongs. The terms "first," "second," and the like, as used herein, do not denote any order, quantity, or importance, but rather are used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that elements or items preceding the word are included in the element or item listed after the word and equivalents thereof, but does not exclude other elements or items. The terms "coupled" and "connected," and the like, are not limited to physical or mechanical connections, but may include electrical connections, direct connections, indirect connections, wired connections, and wireless connections. "upper", "lower", "left", "right", etc. are used merely to indicate relative positional relationships, which may also be changed when the absolute position of the object to be described is changed.
The principles and spirit of the present application will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are presented merely to enable those skilled in the art to better understand and practice the application and are not intended to limit the scope of the application in any way. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the application to those skilled in the art.
In this document, it should be understood that any number of elements in the drawings is for illustration and not limitation, and that any naming is used only for distinction and not for any limitation.
As described in the background section, the household blood glucose meter in the related art generally cannot distinguish users, so that the blood glucose meter in the related art cannot be used by multiple people, and personalized services such as blood glucose data monitoring, inquiry and the like are provided for each person.
In order to solve the above problems, an embodiment of the present application provides a blood glucose data processing method, including:
determining a target user based on the user face image information; in response to receiving a blood glucose detection instruction, performing blood glucose detection to obtain a current blood glucose detection result; in response to determining that the target user is unique and corresponds to a target historical blood glucose detection result, determining the unique target user as the user currently performing blood glucose detection, and acquiring the target historical blood glucose detection result: and determining whether the current blood glucose detection result is in a normal range based on the target historical blood glucose detection result, and outputting prompt information of abnormal blood glucose in response to the current blood glucose detection result not being in the normal range, so that a user currently carrying out blood glucose detection can be determined through facial image recognition, whether the current blood glucose detection result is in the normal range can be accurately determined according to the target historical blood glucose detection result of the user currently carrying out blood glucose detection, and personalized blood glucose data management service can be conveniently provided for household blood glucose meters used by multiple people.
Referring to fig. 1, a flow chart of a blood glucose data processing method according to an embodiment of the present application is shown, and the method is applied to a blood glucose meter, and includes the following steps:
s101, collecting user face image information, and determining a target user based on the user face image information.
In practice, the user's facial image information may be acquired by an imaging device mounted on the blood glucose meter, and then the target user may be determined from the acquired user's facial image information. It should be noted that, because the collected facial image information of the user may include facial image information of one or more users, the corresponding determined target user may be one or more, that is, each facial image in the facial image information of the user corresponds to a determined target user.
It should be noted that, the blood glucose meter provided by the embodiment of the application not only provides the most basic blood glucose detection function, but also can provide functions of data storage, management, inquiry and the like for users. In order to distinguish between different users, each time the blood glucose meter is used, the facial image information of the user needs to be acquired to perform other steps. Optionally, when the blood glucose meter collects facial image information of the user, the collected facial image information of the user can be collected through a photographing function of the camera, when the collected facial image information of the user at least comprises a facial image of a target user, the successful collection is indicated, otherwise, the user needs to be prompted to collect facial image information of the user again.
S102, in response to receiving a blood glucose detection instruction, blood glucose detection is carried out to obtain a current blood glucose detection result.
In the specific implementation, after the facial image information acquisition of the user is completed, when the glucometer receives a blood sugar detection instruction, blood sugar detection is carried out to obtain a current blood sugar detection result. Alternatively, the specific process of blood glucose measurement by the blood glucose meter may refer to the blood glucose measurement process in the related art, which is not limited, and for example, blood glucose measurement may be performed by inserting blood glucose test paper of the blood glucose meter.
S103, in response to determining that the target user is unique and corresponds to the target historical blood glucose detection result, determining the unique target user as the user currently carrying out blood glucose detection, and acquiring the target historical blood glucose detection result.
In the implementation, considering that other people such as family members may be present when the user uses the glucometer, the face image which may be included in the collected face image information of the user is not unique, at this time, it is required to further judge whether the determined target user is unique, and when the target user is determined to be unique and corresponds to the target historical blood glucose detection result, the unique target user is determined to be the current user for blood glucose detection, which means that the user for blood glucose detection is the old user at this time, and the target historical blood glucose detection result is obtained. Optionally, when it is determined that the target user is unique and does not correspond to the target historical blood glucose detection result, which indicates that the blood glucose detection is performed at this time as a new user, a corresponding database may be established for the new user, and the database is used for storing the blood glucose detection result of the new user. Alternatively, when it is determined that the user currently performing blood glucose test is a new user, since there is no corresponding historical blood glucose test result, whether the current blood glucose test result is in a normal range may be determined through a preset normal blood glucose range.
S104, determining whether the current blood sugar detection result is in a normal range based on the target historical blood sugar detection result, and outputting prompt information of abnormal blood sugar in response to the current blood sugar detection result not being in the normal range.
When the method is implemented, after a target historical blood sugar detection result is obtained, whether the current blood sugar detection result is in a normal range can be determined according to the target historical blood sugar detection result, and as the standard of blood sugar is actually different for different people, compared with the method of directly judging whether the current blood sugar detection result is in the normal range through a fixed preset threshold value, whether the blood sugar values of different users are normal can be more pertinently judged through the historical blood sugar detection result of each user, and when the current blood sugar detection result is not in the normal range, prompt information of blood sugar abnormality is output, so that the users can take corresponding measures in time.
In some embodiments, determining whether the current blood glucose test result is in a normal range based on the target historical blood glucose test result specifically includes:
determining a euglycemic fluctuation curve of the target user based on the target historical blood glucose detection result;
determining whether the current glycemic test result is in a normal range based on the euglycemic fluctuation curve.
In the implementation, whether the current blood sugar detection result is in a normal range is determined based on the historical blood sugar detection result, and a blood sugar normal fluctuation curve of the target user can be determined according to the target historical blood sugar detection result; and then determining whether the current blood sugar detection result is in a normal range according to the blood sugar normal fluctuation curve, predicting the normal band range of the current blood sugar detection result through the blood sugar normal fluctuation curve when determining whether the current blood sugar detection result is in the normal range through the blood sugar normal fluctuation curve, and then determining whether the current blood sugar detection result is in the normal range according to the normal fluctuation range.
It should be noted that, the above method for determining whether the current blood glucose detection result is in the normal range based on the historical blood glucose detection result belongs to a specific implementation manner of the embodiment of the present application, and a person skilled in the art may set other methods for determining whether the current blood glucose detection result is in the normal range according to the historical blood glucose detection result as required, for example, may directly determine the normal blood glucose range of the target user according to the historical blood glucose detection result, and then determine whether the current blood glucose detection result is in the normal range according to the normal blood glucose range.
Determining a euglycemic fluctuation curve of the target user based on the target historical blood glucose detection result, specifically comprising:
determining a historical normal blood glucose test result in the normal range from the target historical blood glucose test result;
and determining a euglycemic fluctuation curve of the target user based on the historical euglycemic detection result.
When the blood glucose level fluctuation curve of the target user is determined according to the target historical blood glucose detection result, the historical blood glucose level fluctuation curve in the normal range can be determined from the target historical blood glucose detection result, then the blood glucose level fluctuation curve of the target user is determined according to the historical blood glucose level detection result, and when the blood glucose level fluctuation curve is determined, the blood glucose level fluctuation curve can be determined by performing function fitting through the historical blood glucose level detection result.
In some embodiments, after determining the target user based on the user facial image information, the method further comprises:
in response to determining that the target user is not unique, determining candidate users corresponding to historical blood glucose detection results from all the target users;
acquiring a historical blood sugar detection result corresponding to each candidate user;
and determining the current blood sugar detection user from all the target users based on the historical blood sugar detection results and the current blood sugar detection results corresponding to each candidate user.
In practice, it is considered that the household blood glucose meter is mainly used by the elderly, and unnecessary complicated operations should be reduced when the blood glucose meter is used by the elderly. Therefore, when the determined target user is not the only one, the user who performs the blood glucose test at present is reduced as much as possible by the operation of the user, and meanwhile, the inventor of the application discovers that the blood glucose values of different users are different, and the blood glucose test results of different users can be distinguished by analyzing the previous difference. Therefore, when the target users are determined to be not unique, firstly, determining candidate users corresponding to the historical blood sugar detection results from all the target users; then, obtaining a historical blood sugar detection result corresponding to each candidate user; and determining the current blood sugar detection user from all the target users according to the historical blood sugar detection results and the current blood sugar detection results corresponding to each candidate user.
In some embodiments, determining the current user who performs blood glucose detection from all the target users based on the historical blood glucose detection result and the current blood glucose detection result corresponding to each candidate user specifically includes:
determining a blood sugar fluctuation curve of each candidate user based on a historical blood sugar detection result corresponding to each candidate user;
in response to determining that the current blood glucose test result matches a predicted result of a blood glucose excursion curve of a target candidate user, determining the target candidate user as the user currently performing blood glucose test;
and in response to determining that the current blood glucose detection result does not match with the predicted results of the blood glucose excursion curves of all the candidate users, outputting other users except the candidate users in the target users as recommended users, and in response to a first confirmation operation for the recommended users, confirming the recommended users corresponding to the first confirmation operation as the users currently carrying out blood glucose detection.
In the implementation, after determining the blood glucose fluctuation curve of each candidate user, when determining that the current blood glucose detection result matches with the predicted result of the blood glucose fluctuation curve of the target candidate user, the target candidate user may be determined as the user currently performing blood glucose detection. Alternatively, whether the current blood glucose test result and the predicted result of the blood glucose excursion curve of the target candidate user are matched can be judged by whether the difference value between the current blood glucose test result and the predicted result of the blood glucose excursion curve of the target candidate user is within a preset difference value range. When it is determined that the current blood glucose test result does not match with the predicted results of the blood glucose excursion curves of all the candidate users, it is indicated that the user currently performing blood glucose test is not an old user, and it is necessary to further find out the user currently performing blood glucose test from target users belonging to new users, and for the new users, due to lack of reference of history data, it is necessary to further determine the user currently performing blood glucose test by a user, that is, output other users than the candidate users in the target users as recommended users, and in response to a first confirmation operation for the recommended users, confirm the recommended users corresponding to the first confirmation operation as the users currently performing blood glucose test.
The blood glucose level fluctuation curve is mainly used for determining the current blood glucose level detection user, so that the normal blood glucose level of the user and the abnormal blood glucose level of the user need to be considered at the same time, and therefore, when determining the blood glucose level fluctuation curve, the blood glucose level fluctuation curve needs to be determined according to all the historical blood glucose detection results corresponding to the candidate user. Alternatively, the blood glucose excursion curve may be determined by a functional fit of all of the historical blood glucose test results.
In some embodiments, after determining the target user based on the user facial image information, the method further comprises:
determining whether the target user is unique in response to receiving a blood glucose query instruction;
outputting a target historical blood glucose detection result in response to determining that the target user is unique and corresponds to the target historical blood glucose detection result;
responsive to determining that the target user is unique and does not correspond to a target historical blood glucose test result, determining whether the unique target user corresponds to an associated user;
responding to the determination that the unique target user corresponds to the associated user, and outputting a historical blood glucose detection result corresponding to the associated user;
and outputting prompt information without query permission in response to determining that the unique target user does not correspond to the associated user.
In particular, the glucometer of the application also provides a blood sugar result query service, in order to accurately provide query service for different users, and keep privacy of each user not to be revealed, it is necessary to determine who the user currently performs blood sugar result query is according to the target user, when it is determined that the target user is unique and corresponds to the target historical blood sugar detection result, that is, the unique target user is the user currently performing blood sugar result query, so as to output the target historical blood sugar detection result. When it is determined that the target user is unique and does not correspond to the target historical blood glucose detection result, it is indicated that the collected target user does not have the queriable blood glucose detection result, however, in consideration of the use environment of the household blood glucose meter, family members of some diabetics, such as children, query the blood glucose value of the diabetics, and the family members should have the knowledge, so that the blood glucose meter in the embodiment of the application further provides a user association service, and by associating a plurality of users, any one of the plurality of users performing association can query the blood glucose value of the diabetics in the plurality of associated users. Therefore, when it is determined that the target user is unique and does not correspond to the target historical blood glucose detection result, it is further determined whether the unique target user corresponds to an associated user, and if so, the historical blood glucose detection result corresponding to the associated user is output. If the user is not associated, the current acquired target user is indicated to have no query authority, and prompt information which has no query authority is output.
In some embodiments, after determining whether the target user is unique, the method further comprises:
determining whether users to be queried uniquely corresponding to historical blood glucose detection results exist in all target users or not according to the fact that the target users are not unique;
responding to the fact that all target users exist the users to be queried, and outputting historical blood sugar detection results corresponding to the users to be queried;
and outputting prompt information for determining a target query user from a plurality of candidate users in response to determining that the candidate users with the historical blood sugar detection results exist in all the target users, and outputting the historical blood sugar detection results corresponding to the target query user in response to a second confirmation operation for the target query user.
In the implementation, considering that a plurality of users may be present when the blood glucose inquiry is performed, a plurality of target users are determined, at this time, if it is determined that all the target users have the users to be inquired, which uniquely correspond to the historical blood glucose detection results, then it is indicated that the user to be inquired at this time is the user to be inquired, and the historical blood glucose detection results corresponding to the user to be inquired can be directly output. If it is determined that a plurality of candidate users corresponding to the historical blood sugar detection results exist in all the target users, namely the current target user is not unique, the user operation needs to be further used for determining who the currently queried user is.
In some embodiments, after determining the only target user as the user currently performing blood glucose testing, the method further comprises:
and storing the current blood sugar detection result into a database corresponding to the unique target user, and marking whether the current blood sugar detection result is in the normal range in the database.
In a specific implementation, the blood glucose meter provided by the embodiment of the application further provides a data storage function, optionally, after the current blood glucose detection user is determined, the current blood glucose detection result can be stored in a database corresponding to the current blood glucose detection user, and optionally, the database can be arranged in a server or can be directly arranged in the blood glucose meter, so that the blood glucose meter is not limited. In order to help the user to better distinguish which of the historical blood glucose test results are the historical normal blood glucose test results and which are the abnormal blood glucose test results, the database may be marked whether the current blood glucose test result is in the normal range.
In some embodiments, considering that the users of some blood glucose meters do not conveniently perform face recognition each time for physical reasons, at this time, a substitute user of a special user inconvenient for the body may be bound in the blood glucose meter, and when the target user is determined to be unique and the substitute user, the special user corresponding to the substitute user is determined to be the user currently performing blood glucose detection.
In some embodiments, a unique ID may be set for each target user to distinguish between different users for ease of administration.
The blood glucose data processing method provided by the application is used for collecting facial image information of a user and determining a target user based on the facial image information of the user; in response to receiving a blood glucose detection instruction, performing blood glucose detection to obtain a current blood glucose detection result; in response to determining that the target user is unique and corresponds to a target historical blood glucose detection result, determining the unique target user as the user currently performing blood glucose detection, and acquiring the target historical blood glucose detection result: and determining whether the current blood glucose detection result is in a normal range based on the target historical blood glucose detection result, and outputting prompt information of abnormal blood glucose in response to the current blood glucose detection result not being in the normal range, so that a user currently carrying out blood glucose detection can be determined through facial image recognition, whether the current blood glucose detection result is in the normal range is determined according to the target historical blood glucose detection result of the user currently carrying out blood glucose detection, and personalized blood glucose data management service can be conveniently provided for household blood glucose meters used by multiple people.
Based on the same inventive concept, the application also provides a blood glucose data processing device which is applied to the blood glucose meter and corresponds to the method of any embodiment.
Referring to fig. 2, the blood glucose data processing apparatus includes:
the acquisition module 201 acquires user face image information and determines a target user based on the user face image information;
the detection module 202 is used for detecting blood sugar to obtain a current blood sugar detection result in response to receiving a blood sugar detection instruction;
the determining module 203 determines the unique target user as the user currently performing blood glucose detection in response to determining that the target user is unique and corresponds to a target historical blood glucose detection result, and obtains the target historical blood glucose detection result:
the prompting module 204 determines whether the current blood glucose detection result is in a normal range based on the target historical blood glucose detection result, and outputs prompting information of abnormal blood glucose in response to the current blood glucose detection result not being in the normal range.
The blood glucose detection device of the above embodiment is used for implementing the corresponding blood glucose data processing method of any of the foregoing embodiments, and has the beneficial effects of the corresponding blood glucose data processing method embodiment, which is not described herein again.
Based on the same inventive concept, the present disclosure also provides a system of a blood glucose data processing method corresponding to the method of any embodiment, where the system includes a server and a blood glucose meter, and the blood glucose meter is capable of executing the blood glucose data processing method.
The system of the foregoing embodiment is used to implement the corresponding blood glucose data processing method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiment, which is not described herein.
Based on the same inventive concept, the present disclosure also provides an electronic device corresponding to the method of any embodiment, including a memory, a processor, and a computer program stored on the memory and capable of running on the processor, where the processor implements the method of blood glucose data processing according to any embodiment when executing the program.
It should be noted that, the method of the embodiment of the present application may be performed by a single device, for example, a computer or a server. The method of the embodiment can also be applied to a distributed scene, and is completed by mutually matching a plurality of devices. In the case of such a distributed scenario, one of the devices may perform only one or more steps of the method of an embodiment of the present application, the devices interacting with each other to accomplish the method.
It should be noted that the foregoing describes some embodiments of the present application. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments described above and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
Fig. 3 shows a more specific hardware structure of the electronic device according to the present embodiment. The apparatus may include: a processor 1010, a memory 1020, an input/output interface 1030, a communication interface 1040, and a bus 1050. Wherein processor 1010, memory 1020, input/output interface 1030, and communication interface 1040 implement communication connections therebetween within the device via a bus 1050.
The processor 1010 may be implemented by a general-purpose CPU (Central Processing Unit ), microprocessor, application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits, etc. for executing relevant programs to implement the technical solutions provided in the embodiments of the present disclosure.
The Memory 1020 may be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory ), static storage device, dynamic storage device, or the like. Memory 1020 may store an operating system and other application programs, and when the embodiments of the present specification are implemented in software or firmware, the associated program code is stored in memory 1020 and executed by processor 1010.
The input/output interface 1030 is used to connect with an input/output module for inputting and outputting information. The input/output module may be configured as a component in a device (not shown) or may be external to the device to provide corresponding functionality. Wherein the input devices may include a keyboard, mouse, touch screen, microphone, various types of sensors, etc., and the output devices may include a display, speaker, vibrator, indicator lights, etc.
Communication interface 1040 is used to connect communication modules (not shown) to enable communication interactions of the present device with other devices. The communication module may implement communication through a wired manner (such as USB, network cable, etc.), or may implement communication through a wireless manner (such as mobile network, WIFI, bluetooth, etc.).
Bus 1050 includes a path for transferring information between components of the device (e.g., processor 1010, memory 1020, input/output interface 1030, and communication interface 1040).
It should be noted that although the above-described device only shows processor 1010, memory 1020, input/output interface 1030, communication interface 1040, and bus 1050, in an implementation, the device may include other components necessary to achieve proper operation. Furthermore, it will be understood by those skilled in the art that the above-described apparatus may include only the components necessary to implement the embodiments of the present description, and not all the components shown in the drawings.
The electronic device of the foregoing embodiment is configured to implement the corresponding blood glucose data processing method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiment, which is not described herein.
Based on the same inventive concept, the present disclosure also provides a non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the blood glucose data processing method according to any of the above embodiments, corresponding to any of the above embodiments.
The computer readable media of the present embodiments, including both permanent and non-permanent, removable and non-removable media, may be used to implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device.
The storage medium of the above embodiment stores computer instructions for causing the computer to execute the blood glucose data processing method according to any one of the above embodiments, and has the advantages of the corresponding method embodiments, which are not described herein.
Well-known power/ground connections to Integrated Circuit (IC) chips and other components may or may not be shown in the drawings provided to simplify the illustration and discussion, and so as not to obscure embodiments of the application. Furthermore, the devices may be shown in block diagram form in order to avoid obscuring the embodiments of the present application, and also in view of the fact that specifics with respect to implementation of such block diagram devices are highly dependent upon the platform within which the embodiments of the present application are to be implemented (i.e., such specifics should be well within purview of one skilled in the art). Where specific details (e.g., circuits) are set forth in order to describe example embodiments of the application, it should be apparent to one skilled in the art that embodiments of the application can be practiced without, or with variation of, these specific details. Accordingly, the description is to be regarded as illustrative in nature and not as restrictive.
While the application has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of those embodiments will be apparent to those skilled in the art in light of the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.
Those of ordinary skill in the art will appreciate that: the discussion of any of the embodiments above is merely exemplary and is not intended to suggest that the scope of the application (including the claims) is limited to these examples; the technical features of the above embodiments or in the different embodiments may also be combined within the idea of the application, the steps may be implemented in any order and there are many other variations of the different aspects of the application as described above, which are not provided in detail for the sake of brevity.
The present embodiments are intended to embrace all such alternatives, modifications and variances which fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, and the like, which are within the spirit and principles of the embodiments of the application, are intended to be included within the scope of the application.
Claims (10)
1. A method of processing blood glucose data, the method being applied to a blood glucose meter, the method comprising:
collecting user face image information, and determining a target user based on the user face image information;
in response to receiving a blood glucose detection instruction, performing blood glucose detection to obtain a current blood glucose detection result;
in response to determining that the target user is unique and corresponds to a target historical blood glucose detection result, determining the unique target user as a user currently performing blood glucose detection, and acquiring the target historical blood glucose detection result;
and determining whether the current blood glucose detection result is in a normal range based on the target historical blood glucose detection result, and outputting prompt information of abnormal blood glucose in response to the current blood glucose detection result not being in the normal range.
2. The method according to claim 1, wherein determining whether the current blood glucose test result is in a normal range based on the target historical blood glucose test result, in particular comprises:
determining a euglycemic fluctuation curve of the target user based on the target historical blood glucose detection result;
determining whether the current glycemic test result is in a normal range based on the euglycemic fluctuation curve.
3. The method according to claim 2, wherein determining a euglycemic profile for the target user based on the target historical blood glucose test results, in particular comprises:
determining a historical normal blood glucose test result in the normal range from the target historical blood glucose test result;
and determining a euglycemic fluctuation curve of the target user based on the historical euglycemic detection result.
4. The method of claim 1, wherein after determining a target user based on the user facial image information, the method further comprises:
in response to determining that the target user is not unique, determining candidate users corresponding to historical blood glucose detection results from all the target users;
acquiring a historical blood sugar detection result corresponding to each candidate user;
and determining the current blood sugar detection user from all the target users based on the historical blood sugar detection results and the current blood sugar detection results corresponding to each candidate user.
5. The method of claim 4, wherein determining the current blood glucose test user from all the target users based on the historical blood glucose test results and the current blood glucose test results for each of the candidate users, specifically comprises:
determining a blood sugar fluctuation curve of each candidate user based on a historical blood sugar detection result corresponding to each candidate user;
in response to determining that the current blood glucose test result matches a predicted result of a blood glucose excursion curve of a target candidate user, determining the target candidate user as the user currently performing blood glucose test;
and in response to determining that the current blood glucose detection result does not match with the predicted results of the blood glucose excursion curves of all the candidate users, outputting other users except the candidate users in the target users as recommended users, and in response to a first confirmation operation for the recommended users, confirming the recommended users corresponding to the first confirmation operation as the users currently carrying out blood glucose detection.
6. The method of claim 1, wherein after determining a target user based on the user facial image information, the method further comprises:
determining whether the target user is unique in response to receiving a blood glucose query instruction;
outputting a target historical blood glucose detection result in response to determining that the target user is unique and corresponds to the target historical blood glucose detection result;
responsive to determining that the target user is unique and does not correspond to a target historical blood glucose test result, determining whether the unique target user corresponds to an associated user;
responding to the determination that the unique target user corresponds to the associated user, and outputting a historical blood glucose detection result corresponding to the associated user;
and outputting prompt information without query permission in response to determining that the unique target user does not correspond to the associated user.
7. The method of claim 6, wherein after determining whether the target user is unique, the method further comprises:
determining whether users to be queried uniquely corresponding to historical blood glucose detection results exist in all target users or not according to the fact that the target users are not unique;
responding to the fact that all target users exist the users to be queried, and outputting historical blood sugar detection results corresponding to the users to be queried;
and outputting prompt information for determining a target query user from a plurality of candidate users in response to determining that the candidate users with the historical blood sugar detection results exist in all the target users, and outputting the historical blood sugar detection results corresponding to the target query user in response to a second confirmation operation for the target query user.
8. The method of claim 1, wherein after determining the only target user as the user currently performing blood glucose testing, the method further comprises:
and storing the current blood sugar detection result into a database corresponding to the unique target user, and marking whether the current blood sugar detection result is in the normal range in the database.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method of any one of claims 1 to 8 when the program is executed.
10. A non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the method of any one of claims 1 to 8.
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| CN202310646495.4A CN117153366A (en) | 2023-06-01 | 2023-06-01 | Blood glucose data processing method, electronic device and storage medium |
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| CN202310646495.4A CN117153366A (en) | 2023-06-01 | 2023-06-01 | Blood glucose data processing method, electronic device and storage medium |
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