Intelligent diabetes risk assessment scale based on voice interaction and application method

Abstract

The invention relates to an intelligent diabetes risk assessment scale based on voice interaction and an application method, through optimizing and upgrading a functional architecture of an existing electronic scale, the electronic scale not only has height, weight and BM I measurement and calculation service functions, but also has a voice interaction function, and through voice interaction, various voice prompts based on CDRS content can be realized, so that the diabetes risk assessment effect is improved. The age, the gender, the waistline, the systolic pressure and the diabetes family history of the diabetic patient are collected and are written into a CDRS table after being processed and calculated by the system, so that the CDRS value of the diabetic patient is obtained, and whether the diabetic patient has high-risk diabetes or not is further judged. Therefore, the electronic scale can meet the measurement and evaluation requirements of the diabetic patient, and abundant health supervision and management are realized.

Description

Technical Field

[0001] The present disclosure relates to the field of health care technology, and in particular to an intelligent diabetes risk assessment scale based on voice interaction, an application method thereof, and an electronic device. Background Art

[0002] Body mass index (BMI), also known as body mass index or body mass index, is calculated by dividing weight (kg) by height (m) squared. The ratio obtained by this formula can reflect the density of the human body to a certain extent. Due to its simple calculation method, it is now widely used to evaluate the nutritional status, fatness or physical development level of the human body.

[0003] The health of diabetic patients requires combining data such as their age, gender, waist circumference, BMI, systolic blood pressure, and family history of diabetes to provide targeted diabetes screening and risk assessment for diabetic patients.

[0004] Existing health measurement equipment, such as some electronic scales or weight scales, can only measure the patient's height, weight and corresponding BMI. However, for diabetic patients, BMI is far from enough to meet the health supervision and management of diabetic patients.

[0005] Therefore, existing electronic scales or weight scales are far from meeting the measurement and evaluation requirements of diabetic patients. Summary of the invention

[0006] In order to solve the above problems, the present application proposes an intelligent diabetes risk assessment scale based on voice interaction, an application method and an electronic device thereof.

[0007] On the one hand, the present application proposes an intelligent diabetes risk assessment scale based on voice interaction, comprising:

[0008] An electronic scale unit, used to measure height and weight, calculate BMI value according to the height and weight values, and display the height, weight and BMI values ​​on the display screen;

[0009] A memory for pre-storing voice information about the age, gender, waist circumference, systolic blood pressure and family history of diabetes of the diabetic patient;

[0010] The controller is used to retrieve the voice information about the age, gender, waist circumference, systolic blood pressure and family history of diabetes of the diabetic patient from the memory in sequence after calculating the BMI value of the diabetic patient, and send it to the voice interaction unit one by one;

[0011] A voice interaction unit is used to sequentially broadcast voice information about the age, gender, waist circumference, systolic blood pressure and family history of diabetes to the diabetic patient; and sequentially collect voice feedback data of the diabetic patient responding to the voice information about age, gender, waist circumference, systolic blood pressure and family history of diabetes and forward it to the controller, which is then forwarded to the processor by the controller;

[0012] A processor is used to parse the voice feedback data to obtain basic information of the diabetic patient, including age, gender, waist circumference, systolic blood pressure, and whether there is a family history of diabetes, and forward it to the controller, which then forwards it to the CDRS evaluation module;

[0013] The CDRS evaluation module is used to write the basic information of the diabetic patient into the preset CDRS table, calculate the CDRS value of the diabetic patient, and feed back the CDRS value of the diabetic patient to the controller, which is then forwarded to the processor; CDRS, namely the Chinese Diabetes Risk Score;

[0014] The processor is further configured to:

[0015] Receive and determine whether the CDRS value of a diabetic patient exceeds the preset value:

[0016] If it exceeds, a corresponding diabetes risk warning signal is generated and sent to the OGTT reminder module through the controller;

[0017] If it is not exceeded, a corresponding diabetes health reminder signal is generated and sent to the display screen through the controller;

[0018] An OGTT reminder module is used to receive and respond to the diabetes risk warning signal, and remind the diabetic patient to go to the hospital for an OGTT test; the OGTT test is an oral glucose tolerance test;

[0019] A display screen, used to receive and respond to the diabetes health reminder signal;

[0020] The power module, processor, display screen, memory, voice interaction unit, CDRS evaluation module, and OGTT reminder module are electrically connected to the controller respectively.

[0021] As an optional implementation scheme of the present application, optionally, the processor is further used for:

[0022] Determine whether the BMI value of a diabetic patient is within the normal range:

[0023] If it is, a corresponding BMI normal prompt message is generated and forwarded by the controller to the display for display;

[0024] If not, the corresponding BMI high / low risk prompt information is generated and forwarded by the controller to the display for display.

[0025] As an optional embodiment of the present application, optionally, the controller is further used for:

[0026] Record the BMI values ​​of diabetic patients collected every month and generate a monthly statistical log of BMI values;

[0027] Saving the monthly statistical log of BMI values ​​to the memory;

[0028] During the preset time period, the monthly statistical log of the BMI values ​​of each month is sent to the display for display.

[0029] As an optional implementation scheme of the present application, optionally, it also includes:

[0030] A communication module is used to communicate data with a diabetes monitoring server, synchronize the assessment information of the diabetic patient to the diabetes monitoring server, and perform background monitoring;

[0031] The communication module is electrically connected to the controller.

[0032] As an optional embodiment of the present application, optionally, the controller is further used for:

[0033] After generating the CDRS value of the diabetic patient, the controller synchronously sends the CDRS value of the diabetic patient to the communication module, and the communication module reports the CDRS value of the diabetic patient to the diabetes monitoring server;

[0034] The diabetes monitoring server records the CDRS value of the diabetic patient and binds the CDRS value of the diabetic patient to the identity ID of the diabetic patient.

[0035] As an optional embodiment of the present application, optionally, the controller is further used for:

[0036] After generating the corresponding diabetes risk warning signal, the controller synchronously sends the diabetes risk warning signal to the communication module, and the communication module reports the CDRS value of the diabetic patient to the diabetes monitoring server;

[0037] The diabetes monitoring server sends an OGTT test notification to the patient terminal of the diabetic patient and / or the medical terminal where the corresponding medical staff is located, notifying the diabetic patient to go to the hospital to receive the OGTT test.

[0038] On the other hand, the present application proposes an application method of an intelligent diabetes risk assessment scale based on voice interaction, comprising the following steps:

[0039] The diabetic patient gets on the scale and starts measuring;

[0040] The electronic scale unit measures height and weight, and calculates the BMI value based on the height and weight values;

[0041] After calculating the BMI value of the diabetic patient, the controller sequentially retrieves voice information about the diabetic patient's age, gender, waist circumference, systolic blood pressure and family history of diabetes from the memory, and sends it to the voice interaction unit one by one;

[0042] The voice interaction unit broadcasts voice information about the diabetic patient's age, gender, waist circumference, systolic blood pressure and family history of diabetes to the diabetic patient in sequence;

[0043] Diabetic patients responded to voice information about age, sex, waist circumference, systolic blood pressure, and family history of diabetes;

[0044] The voice interaction unit sequentially collects voice feedback data of the diabetic patient in response to the voice information of age, gender, waist circumference, systolic blood pressure and family history of diabetes and forwards it to the controller, which then forwards it to the processor;

[0045] The processor analyzes the voice feedback data to obtain basic information of the diabetic patient, including age, gender, waist circumference, systolic blood pressure, and whether there is a family history of diabetes, and forwards it to the controller, which then forwards it to the CDRS evaluation module;

[0046] The CDRS evaluation module writes the basic information of the diabetic patient into a preset CDRS table, calculates the CDRS value of the diabetic patient, and feeds back the CDRS value of the diabetic patient to the controller, which then forwards it to the processor;

[0047] The processor receives and determines whether the CDRS value of the diabetic patient exceeds the preset value:

[0048] If it exceeds, a corresponding diabetes risk warning signal is generated and sent to the OGTT reminder module through the controller;

[0049] If it is not exceeded, a corresponding diabetes health reminder signal is generated and sent to the display screen through the controller;

[0050] The OGTT reminder module receives and responds to the diabetes risk warning signal, reminding the diabetic patient to go to the hospital for an OGTT test;

[0051] The display screen shows the height, weight and BMI value of the diabetic patient, as well as the monthly statistical log of the BMI value and / or the diabetes health reminder signal and BMI normal reminder information.

[0052] In another aspect, the present application further provides an electronic device, comprising:

[0053] processor;

[0054] a memory for storing processor-executable instructions;

[0055] Wherein, the processor is configured to implement the application method when executing the executable instructions.

[0056] Technical effects of the present invention:

[0057] This application optimizes and upgrades the functional architecture of existing electronic scales, so that the electronic scales not only have the measurement and calculation service functions of height, weight and BMI, but also have voice interaction functions. Through voice interaction, the age, gender, waist circumference, systolic blood pressure and family history of diabetes of diabetic patients can be collected based on various voice reminders of CDRS content, and written into the CDRS table after processing and calculation by the system, so as to obtain the CDRS value of diabetic patients and further determine whether they have high-risk diabetes. Therefore, the electronic scale can meet the measurement and evaluation of diabetic patients and realize rich health supervision and management.

[0058] Further features and aspects of the present disclosure will become apparent from the following detailed description of exemplary embodiments with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate exemplary embodiments, features, and aspects of the disclosure and, together with the description, serve to explain the principles of the disclosure.

[0060] Figure 1 Shown is a functional architecture diagram of an existing electronic scale unit;

[0061] Figure 2 Shown is a functional architecture diagram of the intelligent diabetes risk assessment scale based on voice interaction of the present invention;

[0062] Figure 3 The evaluation content of CDRS is shown;

[0063] Figure 4 Shown is a schematic diagram of an application system of an intelligent diabetes risk assessment scale based on voice interaction of the present invention;

[0064] Figure 5 Shown is a schematic diagram of the application of the electronic device of the present invention. DETAILED DESCRIPTION

[0065] Various exemplary embodiments, features and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise specified.

[0066] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0067] In addition, in order to better illustrate the present disclosure, numerous specific details are given in the following specific embodiments. It should be understood by those skilled in the art that the present disclosure can also be implemented without certain specific details. In some examples, means, components and circuits well known to those skilled in the art are not described in detail in order to highlight the main purpose of the present disclosure.

[0068] Example 1

[0069] like Figure 1 As shown, the present invention can be based on the existing electronic scale to upgrade the functional services. The electronic scale unit used has the function of measuring height and weight, calculating the BMI value according to the height and weight values, and displaying the height, weight and BMI value on the display screen, which can be specifically understood and operated in combination with the existing electronic scale.

[0070] The electronic scale unit is mainly composed of a power module, a processor, a controller, and a display screen. It also includes some main measuring devices and sensors, such as an infrared distance measurement module (for measuring height), a pressure sensor (for measuring weight), etc. (not marked in Figure 1 on the scale unit shown).

[0071] In this embodiment, the electronic scale unit may be an electronic scale for measuring height and weight as proposed in the invention patent publication number CN117490816A.

[0072] like Figure 2 As shown, on one hand, the present application proposes an intelligent diabetes risk assessment scale based on voice interaction, comprising:

[0073] An electronic scale unit, used to measure height and weight, calculate BMI value according to the height and weight values, and display the height, weight and BMI value on the display screen;

[0074] The memory is used to pre-store voice information about the age, gender, waist circumference, systolic blood pressure and family history of diabetes of the diabetic patient; a dynamic flash memory card can be used to pre-record and store the voice information about the age, gender, waist circumference, systolic blood pressure and family history of diabetes of each diabetic patient in the memory, and then the controller sequentially retrieves each voice information and forwards it to the voice interaction unit for playback, so as to remind the patient to answer the corresponding information;

[0075] A controller, which is used to retrieve the voice information about the age, gender, waist circumference, systolic blood pressure and family history of diabetes of the diabetic patient from the memory in sequence after calculating the BMI value of the diabetic patient, and send it to the voice interaction unit one by one; an MCU control chip, a PLC controller or a single-chip microcomputer can be used; preferably an STM32 single-chip microcomputer;

[0076] The voice interaction unit is used to broadcast the voice information about the age, gender, waist circumference, systolic blood pressure and family history of diabetes to the diabetic patient in sequence; and to collect the voice feedback data of the diabetic patient in response to the voice information about age, gender, waist circumference, systolic blood pressure and family history of diabetes in sequence and forward it to the controller, and then forward it to the processor by the controller; an AI voice system can be used for voice interaction, including voice collection, recognition, analysis and dialogue management; or the dialogue interface of the voice software of the background server can be used for voice interaction, and the background issues the corresponding voice interaction instructions, which are executed by the controller (including the corresponding type of voice playback); the specific voice interaction unit can be understood in combination with the existing voice interaction technology, such as the micro-module intelligent voice human-computer interaction module disclosed in patent CN219716465U, which can be connected by a single-chip microcomputer; or a system composed of a voice chip and a voice collection / player can be used;

[0077] The processor is used to analyze the voice feedback data to obtain basic information of the diabetic patient, including age, gender, waist circumference, systolic blood pressure and whether there is a family history of diabetes, and forward it to the controller, which then forwards it to the CDRS evaluation module; the CPU chip is used to process the data, and the processed data / signals are delivered to the controller for execution or forwarding;

[0078] The CDRS evaluation module is used to write the basic information of diabetic patients into the preset CDRS table (such as Figure 3As shown in the figure, the CDRS value of the diabetic patient is calculated, and the CDRS value of the diabetic patient is fed back to the controller, which is then forwarded to the processor by the controller; CDRS, namely the Chinese Diabetes Risk Score, is a scoring system developed using nationwide diabetes epidemiological survey data. The variables included in this scoring system include age, gender, waist circumference, BMI, systolic blood pressure and family history of diabetes, providing an optional modeling tool for diabetes screening and risk assessment; the CDRS table can be pre-embedded in the CDRS evaluation module, and the controller writes various data of the diabetic patient, and directly calculates and outputs the CDRS value of the diabetic patient;

[0079] The processor is further configured to:

[0080] Receive and determine whether the CDRS value of the diabetic patient exceeds the preset value (the preset value is set by the administrator, such as 25 points):

[0081] If it exceeds, a corresponding diabetes risk warning signal is generated and sent to the OGTT reminder module through the controller;

[0082] If it is not exceeded, a corresponding diabetes health reminder signal is generated and sent to the display screen through the controller; these signals can be alarm signals or voice signals, and the corresponding signal type is set by the administrator;

[0083] The OGTT reminder module is used to receive and respond to the diabetes risk warning signal, and remind the diabetic patient to go to the hospital for an OGTT test; the OGTT test is an oral glucose tolerance test; the OGTT reminder module can be an alarm or a signal display module specifically for high-risk diabetes, such as an LED screen, which can be used for risk warning, reminding the diabetic patient to go to the hospital for an OGTT test as soon as possible;

[0084] A display screen, used to receive and respond to the diabetes health reminder signal;

[0085] The power module, processor, display screen, memory, voice interaction unit, CDRS evaluation module, and OGTT reminder module are electrically connected to the controller respectively.

[0086] During specific implementation, the display interface will provide the normal range of BM, high and low warning reminders, and monthly target status.

[0087] When the Chinese Diabetes Risk Score Sheet is entered into the system, it will automatically communicate with the person through voice, automatically enter the data the person says into the system, and tell the specific score on the risk score sheet.

[0088] The total score range for the following six items is 0-51 points.

[0089] If your score is greater than or equal to 25 points, the system will remind you to go to the hospital for an oral glucose tolerance test (i.e. 0GTT test, which is a standard test used by hospitals to diagnose diabetes). The possibility of being diagnosed with diabetes is very high.

[0090] The above modules or units can be integrated on the original PCB board of the electronic scale unit. The corresponding integrated circuits and chips can be controlled and integrated in combination with the type of controller selected. This embodiment does not limit the specific hardware type of each module. The corresponding program can refer to the above interaction for embedded processing.

[0091] As an optional implementation scheme of the present application, optionally, the processor is further used for:

[0092] Determine whether the BMI value of a diabetic patient is within the normal range:

[0093] If it is, a corresponding BMI normal prompt message is generated and forwarded by the controller to the display for display;

[0094] If not, the corresponding BMI high / low risk prompt information is generated and forwarded by the controller to the display for display.

[0095] The normal range of BMI values ​​is pre-set by the system.

[0096] If the BMI value is no longer within the normal range, the controller can directly control the display to issue a corresponding type of prompt information.

[0097] As an optional embodiment of the present application, optionally, the controller is further used for:

[0098] Record the BMI values ​​of diabetic patients collected every month and generate a monthly statistical log of BMI values;

[0099] Saving the monthly statistical log of BMI values ​​to the memory;

[0100] During the preset time period, the monthly statistical log of the BMI values ​​of each month is sent to the display for display.

[0101] Each time the BMI calculation is performed, the controller can store the calculation result in the memory. A BMI monthly statistical form can be prepared in advance in the memory to record the monthly BMI measurement results and corresponding judgment information.

[0102] At a scheduled time each month, such as the end of each month, the controller retrieves the monthly statistical log of the BMI value of that month from the memory and displays it on the display, reminding the patient to check the monthly BMI changes.

[0103] like Figure 4 As shown, as an optional implementation scheme of the present application, optionally, it also includes:

[0104] A communication module is used to communicate data with a diabetes monitoring server, synchronize the assessment information of the diabetic patient to the diabetes monitoring server, and perform background monitoring;

[0105] The communication module is electrically connected to the controller.

[0106] In order to facilitate the management of the electronic scale, the electronic scale can be connected to the background server (diabetes monitoring server) through a communication module.

[0107] The communication module can adopt 5G communication, Bluetooth or WiFi and other communications, which can support the data / signal format of the controller and realize data interaction between the electronic scale and the background.

[0108] The specific communication module is determined according to the configured communication protocol and is not limited in this embodiment.

[0109] The electronic scale communicates with the background, which records the measurement results of each electronic scale to know the measurement status of each patient.

[0110] like Figure 4 The following is a schematic diagram of the data interaction system between the electronic scale and the background:

[0111] As an optional embodiment of the present application, optionally, the controller is further used for:

[0112] After generating the CDRS value of the diabetic patient, the controller synchronously sends the CDRS value of the diabetic patient to the communication module, and the communication module reports the CDRS value of the diabetic patient to the diabetes monitoring server;

[0113] The diabetes monitoring server records the CDRS value of the diabetic patient and binds the CDRS value of the diabetic patient to the identity ID of the diabetic patient.

[0114] The controller can report the CDRS value of each diabetic patient to the background through the communication module, so as to record the CDRS value of each diabetic patient in the background and realize background monitoring and early warning.

[0115] The background will bind each electronic scale with the corresponding patient's identity ID in advance to facilitate the management of the CDRS values ​​of diabetic patients.

[0116] The backend can interact with the patient's medical staff and send high-risk warning notifications and OGTT test notifications to the corresponding medical staff, so as to facilitate the medical staff to subsequently receive the corresponding diabetic patients and improve the efficiency of clinical diagnosis of diabetic patients.

[0117] As an optional embodiment of the present application, optionally, the controller is further used for:

[0118] After generating the corresponding diabetes risk warning signal, the controller synchronously sends the diabetes risk warning signal to the communication module, and the communication module reports the CDRS value of the diabetic patient to the diabetes monitoring server;

[0119] The diabetes monitoring server sends an OGTT test notification to the patient terminal of the diabetic patient and / or the medical terminal where the corresponding medical staff is located, notifying the diabetic patient to go to the hospital to receive the OGTT test.

[0120] For the communication link between the medical and nursing end, such as the doctor's PC and the nursing staff's EDA / PDA terminal and the backend server, please refer to the interaction method between doctors and nurses in existing hospitals and the backend system.

[0121] The patient side can be an APP or mini program on a smart terminal, which can communicate with the background server, enter the background, realize corresponding online data viewing and interaction, receive information sent by the background, etc.

[0122] The background monitors the CDRS value of the diabetic patient and determines whether the risk warning signal of the diabetic patient reported by the electronic scale unit is received. If received, a corresponding notification needs to be sent to the patient's attending physician or clinical nurse to remind the patient to go for the OGTT test. At the same time, a notification of the OGTT test can also be sent to the patient's smart terminal to notify the patient to go for the OGTT test.

[0123] Therefore, it is possible to monitor the overall condition of diabetic patients in real time, intervene in OGTT tests in a timely manner, and reduce the risks of diabetes to patients.

[0124] Obviously, those skilled in the art should understand that the implementation of all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above-mentioned embodiments. Those skilled in the art can understand that the implementation of all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above-mentioned embodiments. Among them, the storage medium can be a disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory (Flash Memory), a hard disk (Hard Disk Drive, abbreviated as: HDD) or a solid-state drive (SSD), etc.; the storage medium can also include a combination of the above-mentioned types of memory.

[0125] Example 2

[0126] Based on the implementation principle of Example 1, on the other hand, the present application proposes an application method of an intelligent diabetes risk assessment scale based on voice interaction, comprising the following steps:

[0127] The diabetic patient gets on the scale and starts measuring;

[0128] The electronic scale unit measures height and weight, and calculates the BMI value based on the height and weight values;

[0129] After calculating the BMI value of the diabetic patient, the controller sequentially retrieves voice information about the diabetic patient's age, gender, waist circumference, systolic blood pressure and family history of diabetes from the memory, and sends it to the voice interaction unit one by one;

[0130] The voice interaction unit broadcasts voice information about the diabetic patient's age, gender, waist circumference, systolic blood pressure and family history of diabetes to the diabetic patient in sequence;

[0131] Diabetic patients responded to voice information about age, sex, waist circumference, systolic blood pressure, and family history of diabetes;

[0132] The voice interaction unit sequentially collects voice feedback data of the diabetic patient in response to the voice information of age, gender, waist circumference, systolic blood pressure and family history of diabetes and forwards it to the controller, which then forwards it to the processor;

[0133] The processor analyzes the voice feedback data to obtain basic information of the diabetic patient, including age, gender, waist circumference, systolic blood pressure, and whether there is a family history of diabetes, and forwards it to the controller, which then forwards it to the CDRS evaluation module;

[0134] The CDRS evaluation module writes the basic information of the diabetic patient into a preset CDRS table, calculates the CDRS value of the diabetic patient, and feeds back the CDRS value of the diabetic patient to the controller, which then forwards it to the processor;

[0135] The processor receives and determines whether the CDRS value of the diabetic patient exceeds the preset value:

[0136] If it exceeds, a corresponding diabetes risk warning signal is generated and sent to the OGTT reminder module through the controller;

[0137] If it is not exceeded, a corresponding diabetes health reminder signal is generated and sent to the display screen through the controller;

[0138] The OGTT reminder module receives and responds to the diabetes risk warning signal, reminding the diabetic patient to go to the hospital for an OGTT test;

[0139] The display screen displays the height, weight and BMI value of the diabetic patient, as well as a monthly statistical log of the BMI value and / or a diabetes health reminder signal and a normal BMI reminder message.

[0140] Please understand the above steps in conjunction with the principles of Example 1, and will not be repeated in this example.

[0141] The modules or steps of the present invention described above can be implemented by a general-purpose computing system, they can be concentrated on a single computing system, or distributed on a network composed of multiple computing systems, and optionally, they can be implemented by a program code executable by a computing system, so that they can be stored in a storage system and executed by the computing system, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0142] Example 3

[0143] like Figure 5 As shown, further, in another aspect, the present application also proposes an electronic device, including:

[0144] processor;

[0145] a memory for storing processor-executable instructions;

[0146] Wherein, the processor is configured to implement the application method described in Example 2 when executing the executable instructions.

[0147] The electronic device of the embodiment of the present disclosure includes a processor and a memory for storing instructions executable by the processor, wherein the processor is configured to implement the application method described in the above embodiment 2 when executing the executable instructions.

[0148] Here, it should be noted that the number of processors can be one or more. At the same time, the electronic device of the embodiment of the present disclosure may also include an input system and an output system. Among them, the processor, memory, input system and output system may be connected through a bus or in other ways, which are not specifically limited here.

[0149] The memory is a computer-readable storage medium that can be used to store software programs, computer executable programs, and various modules, such as the program or module corresponding to the application method of the embodiment of the present disclosure. The processor executes various functional applications and data processing of the electronic device by running the software programs or modules stored in the memory.

[0150] The input system can be used to receive input numbers or signals. The signal can be a key signal related to user settings and function control of the device / terminal / server. The output system can include display devices such as display screens.

[0151] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. An intelligent diabetes risk assessment scale based on voice interaction, characterized in that: include: An electronic scale unit, used to measure height and weight, calculate BMI value according to the height and weight values, and display the height, weight and BMI values ​​on the display screen; A memory for pre-storing voice information about the age, gender, waist circumference, systolic blood pressure and family history of diabetes of the diabetic patient; The controller is used to retrieve the voice information about the age, gender, waist circumference, systolic blood pressure and family history of diabetes of the diabetic patient from the memory in sequence after calculating the BMI value of the diabetic patient, and send it to the voice interaction unit one by one; A voice interaction unit, used to sequentially broadcast voice information about the age, gender, waist circumference, systolic blood pressure and family history of diabetes to the diabetic patient; and, sequentially collecting voice feedback data of the diabetic patient in response to the voice information of age, gender, waist circumference, systolic blood pressure and family history of diabetes and forwarding it to the controller, which is then forwarded by the controller to the processor; A processor is used to parse the voice feedback data to obtain basic information of the diabetic patient, including age, gender, waist circumference, systolic blood pressure, and whether there is a family history of diabetes, and forward it to the controller, which then forwards it to the CDRS evaluation module; The CDRS evaluation module is used to write the basic information of the diabetic patient into the preset CDRS table, calculate the CDRS value of the diabetic patient, and feed back the CDRS value of the diabetic patient to the controller, which is then forwarded to the processor; CDRS, namely the Chinese Diabetes Risk Score; The processor is further configured to: Receive and determine whether the CDRS value of a diabetic patient exceeds the preset value: If it exceeds, a corresponding diabetes risk warning signal is generated and sent to the OGTT reminder module through the controller; If it is not exceeded, a corresponding diabetes health reminder signal is generated and sent to the display screen through the controller; An OGTT reminder module is used to receive and respond to the diabetes risk warning signal, and remind the diabetic patient to go to the hospital for an OGTT test; the OGTT test is an oral glucose tolerance test; A display screen, used to receive and respond to the diabetes health reminder signal; The power module, processor, display screen, memory, voice interaction unit, CDRS evaluation module, and OGTT reminder module are electrically connected to the controller respectively.

2. The intelligent diabetes risk assessment scale based on voice interaction according to claim 1, characterized in that: The processor is further configured to: Determine whether the BMI value of a diabetic patient is within the normal range: If it is, a corresponding BMI normal prompt message is generated and forwarded by the controller to the display for display; If not, the corresponding BMI high / low risk prompt information is generated and forwarded by the controller to the display for display.

3. The intelligent diabetes risk assessment scale based on voice interaction according to claim 1, characterized in that: The controller is further used for: Record the BMI values ​​of diabetic patients collected every month and generate a monthly statistical log of BMI values; Saving a monthly statistical log of BMI values ​​to the memory; During a preset time period, a monthly statistical log of BMI values ​​is sent to the display for display.

4. The intelligent diabetes risk assessment scale based on voice interaction according to claim 1, characterized in that: Also includes: A communication module is used to communicate data with a diabetes monitoring server, synchronize the assessment information of the diabetic patient to the diabetes monitoring server, and perform background monitoring; The communication module is electrically connected to the controller.

5. The intelligent diabetes risk assessment scale based on voice interaction according to claim 4, characterized in that: The controller is further configured to: After generating the CDRS value of the diabetic patient, the controller synchronously sends the CDRS value of the diabetic patient to the communication module, and the communication module reports the CDRS value of the diabetic patient to the diabetes monitoring server; The diabetes monitoring server records the CDRS value of the diabetic patient and binds the CDRS value of the diabetic patient to the identity ID of the diabetic patient.

6. The intelligent diabetes risk assessment scale based on voice interaction according to claim 4, characterized in that: The controller is further configured to: After generating the corresponding diabetes risk warning signal, the controller synchronously sends the diabetes risk warning signal to the communication module, and the communication module reports the CDRS value of the diabetic patient to the diabetes monitoring server; The diabetes monitoring server sends an OGTT test notification to the patient terminal of the diabetic patient and / or the medical terminal where the corresponding medical staff is located, notifying the diabetic patient to go to the hospital to receive the OGTT test.

7. An application method of the intelligent diabetes risk assessment scale based on voice interaction according to any one of claims 1 to 6, characterized in that: The steps include: The diabetic patient gets on the scale and starts measuring; The electronic scale unit measures height and weight, and calculates the BMI value based on the height and weight values; After calculating the BMI value of the diabetic patient, the controller sequentially retrieves voice information about the diabetic patient's age, gender, waist circumference, systolic blood pressure and family history of diabetes from the memory, and sends it to the voice interaction unit one by one; The voice interaction unit broadcasts voice information about the diabetic patient's age, gender, waist circumference, systolic blood pressure and family history of diabetes to the diabetic patient in sequence; Diabetic patients responded to voice information about age, sex, waist circumference, systolic blood pressure, and family history of diabetes; The voice interaction unit sequentially collects voice feedback data of the diabetic patient in response to the voice information of age, gender, waist circumference, systolic blood pressure and family history of diabetes and forwards it to the controller, which then forwards it to the processor; The processor analyzes the voice feedback data to obtain basic information of the diabetic patient, including age, gender, waist circumference, systolic blood pressure, and whether there is a family history of diabetes, and forwards it to the controller, which then forwards it to the CDRS evaluation module; The CDRS evaluation module writes the basic information of the diabetic patient into a preset CDRS table, calculates the CDRS value of the diabetic patient, and feeds back the CDRS value of the diabetic patient to the controller, which then forwards it to the processor; The processor receives and determines whether the CDRS value of the diabetic patient exceeds the preset value: If it exceeds, a corresponding diabetes risk warning signal is generated and sent to the OGTT reminder module through the controller; If it is not exceeded, a corresponding diabetes health reminder signal is generated and sent to the display screen through the controller; The OGTT reminder module receives and responds to the diabetes risk warning signal, reminding the diabetic patient to go to the hospital for an OGTT test; The display screen displays the height, weight and BMI value of the diabetic patient, as well as a monthly statistical log of the BMI value and / or a diabetes health reminder signal and a normal BMI reminder message.

8. An electronic device, characterized in that include: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to implement the application method described in claim 7 when executing the executable instructions.

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