KR20210075503A - System for providing dietetic therapy for diabetes management - Google Patents

Abstract

The dietetic therapy management server (300) comprises: an information collection module (321) which performs a membership registration procedure through data transmission/reception with the smart device (100) via the network (200) according to the execution of a diabetic manager app on the smart device (100) and stores a terminal identification number of the smart device (100), collected in the membership registration procedure, as metadata and a member ID, member password, and user personal information as a member information unit; and a diabetes management module (322) which calculate a ratio of carbohydrate, protein, fat for each individual carbohydrate requirement (calorie value) among daily calorie requirements for each person based on a glycated hemoglobin value included in user's personal information, and converts the calculated carbohydrate calories into points, and provides food and food combination information matching the converted points to the user device (100) through the network (200). Accordingly, the system provides a point dietetic therapy for the blood sugar management of a diabetic patient (including pre-diabetic patient), and artificial intelligence-based individualized coaching as major services, and additionally enables the integrated management of diabetes-related factors, such as weight, blood pressure, and exercise, through a single application, and thus increases the convenience of managing blood sugar and can prevent complications from diabetes.

Description

Diabetes management diet providing system {System for providing dietetic therapy for diabetes management}

The present invention relates to a system for providing a diet for managing diabetes, and more particularly, to a system for providing a diet for managing diabetes for professionally managing a diet for managing diabetes by controlling carbohydrate intake.

Conventionally, a lot of calorie calculations, personal training apps, etc. for diet, etc. have been released and provided to users.

In addition, about 425 million people (ages 20 to 79) of adults worldwide suffer from diabetes, and it is estimated that the number will increase to 629 million in 2045. In particular, the proportion of type 2 diabetes patients in the elderly is increasing with the increase in life expectancy.

However, as described above, in the case of a diet app targeting only total calorie control, there is a problem that it is insufficient to be applied to diabetic patients. This is because, in the case of diabetic patients, carbohydrate intake rather than total calories and the proportion of carbohydrates in total calories are major issues, whereas conventionally released calorie calculations and personal training apps perform only total calorie calculations.

Accordingly, in the technical field, there is a demand for technology development for professionally managing a diet for diabetes management by controlling carbohydrate intake.

Republic of Korea Patent Application No. 10-2007-0085165 (2007.08.23) "System and method for managing a dietetic therapy using the network"

The present invention is to solve the above problems, and provides a point diet and artificial intelligence individual coaching for blood sugar management of diabetic (including pre-diabetes) as main services, and additionally, diabetes and diabetes such as weight, blood pressure, and exercise. This is to provide a system for providing a diabetes management diet to improve the convenience of blood sugar management and prevent complications caused by diabetes by allowing related factors to be integrated and managed in one app.

In addition, the present invention is to provide a diabetes management diet system for providing a personalized AI diabetes management coaching service (1:1 online, wired, etc.) together with a regular report (weekly/monthly).

In addition, the present invention is to provide a diabetes management diet providing system by providing information based on the location of the diabetes evaluation excellent hospital (Health Insurance Review and Assessment Service).

However, the objects of the present invention are not limited to the above-mentioned objects, and other objects not mentioned will be clearly understood by those skilled in the art from the following description.

In order to achieve the above object, the diabetes management diet providing system according to an embodiment of the present invention is a diabetes management diet providing system including a smart device 100, a network 200, and a diet management server 300 ( In 1), the diet management server 300, through the smart device 100 and the signal and data transmission and reception through the network 200 according to the execution of the diabetes manager app on the smart device 100 an information collection module 321 for storing the collected terminal identification number of the smart device 100 as metadata, member ID, member password, and user personal information in "member information unit"; and a diabetes management module 322 that calculates a carbohydrate:protein:fat ratio for each individual carbohydrate requirement among individual daily calorie requirements based on the glycated hemoglobin value included in the user's personal information, and detects the calculated carbohydrate requirement characterized in that

In addition, the diabetes management module 322 converts the calculated carbohydrate requirement into points, and provides food and food combination information matching the converted points to the user device 100 through the network 200 characterized in that

In addition, the diabetes management module 322 performs carbohydrate point distribution for each meal, but extracts and compares the standard set blood sugar value and the fasting blood sugar value and the pre-bed blood sugar value from the "member information unit" stored in the database 330. characterized in that

In addition, the diabetes management module 322 calculates T1: T2: T3, which is the carbohydrate intake ratio of breakfast, lunch, and dinner in a normal state, as a reference value, and when the fasting blood glucose value exceeds the reference fasting glucose value, T3 It is characterized by setting the snack carbohydrate intake ratio after dinner and after dinner less than.

In addition, the diabetes management module 322 is characterized in that, when the pre-bedtime blood sugar value exceeds the reference pre-bedtime blood sugar value, the lunch and dinner carbohydrate intake ratios of less than T2 and less than T3 are set.

In addition, the diabetes management module 322, when the fasting blood glucose value exceeds the reference fasting blood glucose value and the pre-bed blood glucose value exceeds the reference pre-bed blood glucose value, the evening carbohydrate intake ratio of less than T3 and T2 or less It is characterized in that the lunch carbohydrate intake ratio is set at the same time.

The diabetes management diet providing system according to an embodiment of the present invention provides a point diet and artificial intelligence individual coaching for blood sugar management of diabetic (including pre-diabetes) as main services, and additionally includes weight, blood pressure, exercise and It provides the effect of improving the convenience of managing blood sugar and preventing complications due to diabetes by enabling the integrated management of factors related to diabetes in one app.

In addition, the diabetes management diet providing system according to another embodiment of the present invention can provide a personalized AI diabetes management coaching service (1:1 online, wired, etc.) along with a regular report (weekly/monthly) It works.

In addition, the diabetes management diet providing system according to another embodiment of the present invention has an effect of providing information about a diabetes evaluation excellent hospital (Health Insurance Review and Assessment Service) based on the user's location.

1 is a view showing a diabetes management diet providing system 1 according to an embodiment of the present invention.
2 is a block diagram showing the components of the diet management server 300 of the diabetes management diet providing system 1 according to an embodiment of the present invention.
3 is a block diagram showing the components of the diabetes management module 322 of the diet management server 300 according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, detailed description of preferred embodiments of the present invention will be described with reference to the accompanying drawings. In the following description of the present invention, if it is determined that a detailed description of a related known function or configuration may unnecessarily obscure the gist of the present invention, the detailed description thereof will be omitted.

In the present specification, when one component 'transmits' data or signal to another component, the component may directly transmit the data or signal to another component, and through at least one other component This means that data or signals can be transmitted to other components.

1 is a view showing a diabetes management diet providing system 1 according to an embodiment of the present invention. Referring to FIG. 1 , the diabetes management diet providing system 1 includes a smart device group 100g consisting of a plurality of smart devices 100 , a network 200 , a diet management server 300 , and a big data server 400 . ) may be included.

Here, the network 200 is a high-speed backbone network of a large-scale communication network capable of high-capacity, long-distance voice and data services, and may be a next-generation wired or wireless network for providing the Internet or high-speed multimedia services. When the network 200 is a mobile communication network, it may be a synchronous mobile communication network or an asynchronous mobile communication network. As an example of the asynchronous mobile communication network, there may be a wideband code division multiple access (WCDMA) type communication network. In this case, although not shown in the drawings, the mobile communication network 700 may include a Radio Network Controller (RNC). Meanwhile, although the WCDMA network is taken as an example, it may be a 3G LTE network, a 4G network, other next-generation communication networks such as 5G, and other IP-based IP networks. The network 200 serves to mutually transmit signals and data between the smart device group 100g, the diet management server 300 and the big data server 400, and other systems composed of a plurality of smart devices 100. do.

2 is a block diagram showing the components of the diet management server 300 of the diabetes management diet providing system 1 according to an embodiment of the present invention. 3 is a block diagram showing the components of the diabetes management module 322 of the diet management server 300 according to an embodiment of the present invention.

First, referring to FIG. 2 , the diet management server 300 includes a transceiver 310 , a control unit 320 and a database 330 , and the control unit 320 includes an information collection module 321 and a diabetes management module. 322 , a diabetes management coaching module 323 , a food-specific point providing module 324 , and a hospital information providing module 325 may be included.

Through this configuration, the diet management server 300 provides a point diet and artificial intelligence individual coaching service for blood sugar management of diabetic people (including pre-diabetes) as main services, and additionally, diabetes and diabetes such as weight, blood pressure, and exercise. By enabling the integrated management of related factors in one app, it improves the convenience of blood sugar management, prevents complications from diabetes, and provides personalized AI diabetes management with regular reports (weekly/monthly) on a 1:1 online basis. In addition to providing a coaching service, it is possible to provide information on diabetes evaluation excellent hospitals (Health Insurance Review and Assessment Service) based on the user's location.

Hereinafter, focusing on the components of the control unit 320, the diabetes management diet providing system 1 and the diet management server 300 will be described in detail.

The information collection module 321 transmits/receives unit 310 to transmit the diabetic manager app data to the smart device 100 according to the diabetic manager app data request according to the access of the smart device 100 through the network 200 By controlling the diabetic manager app can be installed on the smart device (100).

After that, the information collection module 321 proceeds with the membership registration procedure through signal and data transmission and reception with the smart device 100 through the network 200 according to the execution of the diabetic manager app on the smart device 100, and then the member The terminal identification number of the smart device 100 collected in the subscription procedure may be stored as metadata as a member ID, member password, and user personal information in "member information unit".

In addition, the information collection module 321 receives the HbA1c (glycated hemoglobin) value for a preset period from the smart device 100 through the network 200 , and is a blood glucose meter connected to the smart device 100 through short-range wireless communication. After controlling the transceiver 310 to receive the fasting blood glucose and pre-bed blood glucose values periodically received from the smart device 100 through the network 200, it may be stored together in the member information unit. Here, the glycated hemoglobin value may be a value reflecting the average blood glucose value for the last three months, the fasting blood glucose may be blood glucose after bedtime (measured in the morning), and the blood glucose before bedtime may be blood glucose before bedtime (measured in the evening).

Meanwhile, referring to FIG. 3 , the diabetes management module 322 includes an individual daily calorie calculation module 322a, a carbohydrate ratio calculation module 322b, a carbohydrate point calculation module 322c, a carbohydrate distribution module 322d, and a food recommendation module. (322e) may be included.

The individual daily calorie calculation module 322a is based on the AI platform, based on data such as meals, drugs, exercise and activity, body information (user age, gender), and body measurements (height, weight) included in the user's personal information. Individual daily calorie requirements, including individual daily carbohydrate requirements, can be calculated through an AI-based nutrition evaluation algorithm.

More specifically, the daily calorie calculation module 322a for each individual includes daily carbohydrate requirements for each individual based on meal, drug, exercise amount and activity amount, body information (user age, gender), and body measurement (height, weight) data. By calculating the calorie requirement through the AI-based nutritional evaluation algorithm, the smart device 100 user can easily understand the point by the food-specific point provision module 324, so that the user can obtain points for each food instead of the nutritional information table for each food. This allows you to conveniently implement a diet regimen.

That is, the individual daily calorie calculation module 322a may extract the user's age, gender, height, and weight from the member information unit and calculate the basic calorie value through a preset calorie calculation algorithm. Here, the calorie calculation algorithm may be a calorie calculation method provided by a scale according to the related art.

The carbohydrate ratio calculation module 322b may calculate the carbohydrate ratio using the calorie value calculated by the individual daily calorie calculation module 322a, the glycated hemoglobin value, the fasting blood glucose value, and the autologous total blood glucose value.

More specifically, the carbohydrate ratio calculation module 322b may calculate the carbohydrate:protein:fat ratio with respect to the calorie value calculated based on the glycated hemoglobin value.

Here, the carbohydrate ratio calculation module 322b sets the carbohydrate:protein:fat ratio to a1:b1:c1 when the measured glycated hemoglobin value is less than or equal to the reference glycated hemoglobin value compared with the preset reference glycated hemoglobin value If the glycated hemoglobin value is exceeded, the carbohydrate:protein:fat ratio can be set to a2:b2:c2.

The carbohydrate ratio calculation module 322b is preferably set so that a1 > P > a2, and P may be the carbohydrate ratio in the reference glycated hemoglobin value.

More specifically, the carbohydrate ratio calculation module 322b sets the carbohydrate:protein:fat ratio to 6:2:2 when the measured glycated hemoglobin value is less than or equal to the reference glycated hemoglobin value compared with the preset reference glycated hemoglobin value, and compares Therefore, if the standard glycated hemoglobin value is exceeded, the carbohydrate:protein:fat ratio can be set to 5:2.5:2.5. The higher the measured glycated hemoglobin value, the lower the carbohydrate ratio is set in proportion to the higher level, and the measured glycated hemoglobin value The lower the value, the higher the carbohydrate ratio can be set in proportion to the lower information.

The carbohydrate point calculation module 322c is, when the carbohydrate ratio is extracted for the carbohydrate ratio calculation module 322b with respect to the calorie value calculated by the individual daily calorie calculation module 322a, the carbohydrate point for the calorie value of the extracted carbohydrate ratio conversion can be performed. In summary, the carbohydrate point calculation module 322c calculates a calorie value corresponding to the proportion of carbohydrates in the individual daily calorie requirement, and then calculates as one point for the calculated carbohydrate calorie value and the preset unit calorie unit value. can do.

That is, the carbohydrate point calculation module 322c converts the preset unit calorie unit value of 60 kcal into 1 point when the ratio of carbohydrates in the individual daily calorie and calorie requirements corresponds to 6, and the calorie of the corresponding carbohydrate ratio is 600 kcal. By setting, 10 points can be calculated as carbohydrate points.

The carbohydrate distribution module 322d may distribute carbohydrate points for each meal. To this end, a fasting blood sugar value and a pre-bed blood sugar value may be extracted and compared with the reference set blood sugar value and the "member information unit" stored in the database 330 .

Basically, fasting blood glucose and pre-bed blood glucose values are short-term morning or evening blood glucose values. If fasting blood glucose is high, carbohydrate intake should be reduced from the evening before and after dinner (hereafter referred to as 'dinner'), and carbohydrate intake should be reduced. If it is high, you should reduce your lunch and dinner carbohydrate intake.

Accordingly, the carbohydrate distribution module 322d sets the standard value of T1: T2: T3, which is the carbohydrate intake ratio for breakfast, lunch, and dinner in the normal state, and when the fasting blood glucose value exceeds the reference fasting glucose value, the reference evening blood glucose value (T3) is less than Set the dinner intake ratio of , and if the pre-bed blood glucose value exceeds the reference pre-bed blood glucose value, set the lunch intake rate below the reference lunch blood glucose value (T2) and the dinner intake rate below the reference evening blood glucose value (T3). When the fasting blood glucose value exceeds the reference fasting blood glucose value and the pre-bed blood glucose value exceeds the reference pre-bed blood glucose value, the ratio of dinner intake below the reference fasting glucose value (T3) and lunch consumption below the reference lunch blood glucose value (T2) The ratio can be set at the same time.

That is, the carbohydrate distribution module 322d sets the breakfast, lunch, and dinner carbohydrate intake ratio of T1 : T2 : T3 = 1 : 1 : 1 in the normal state and 1 : 1 : 0.7 in the case of fasting blood glucose > reference fasting glucose. In the case of pre-bed blood glucose > reference pre-bed blood glucose, it may be set to 1: 0.8: 0.8, and in the case of fasting blood glucose > reference fasting glucose and pre-bed blood glucose > reference pre-bed blood glucose, it may be set to 0.9: 0.7: 0.7.

The food recommendation module 322e searches for the distributed carbohydrate point matching food based on the big data server 400 and transmits the searched matching food to the smart device 100 through the network 200 along with the point value. 310) can be controlled.

That is, the food recommendation module 322e converts carbohydrate-containing calories per food into a point conversion rate, and then creates a food or food combination suitable for each point for breakfast, lunch, and dinner, and then, through the network 200, the smart device 100 ) may control the transceiver 310 to transmit. For example, the diabetes management module 322 may convert to 1 point when carbohydrate calories among the total calories of one apple are 60 kcal and provide the food name corresponding to the converted point to the smart device 100 through the network 200 . .

In an embodiment of the present invention, as a result of the nutritional evaluation, the carbohydrate required per day is 9 points, and the user input 1 apple, 2/3 bowl of rice, bulgogi, ssam vegetables, kimchi, and 1/4 cup of stewed tofu. Assuming that the algorithm calculates 1 point for an apple, 2 points for 2/3 bowl of rice, 0.5 points for stewed tofu, and 0.5 points for bulgogi, it can be seen that 4 points were consumed through a meal (for reference, kimchi and Greens are counted as 0 points). Then, the user can predict that 5 points can be used through the rest of the meal, and by predicting the points of each food and food in advance by searching for food through the app, the user can implement a diet to control carbohydrate intake by himself. can help with management.

Next, the diabetes management coaching module 323 provides scientific and systematic personalized diabetes management coaching reports twice a month through continuous learning and data accumulation of blood sugar management methods for each user case based on the AI platform, and customized 1:1 The transceiver 310 may be controlled to provide diabetes management coaching to the user device 100 through the network 200 .

Here, the diabetes management coaching module 323 reports twice a month, which is provided as a personalized diabetes management coaching service, and records blood sugar level, blood pressure, weight, exercise amount and activity data data of various measurement devices connected to the smart device 100 and short-range wireless communication. It can be obtained from and can be provided to users in the form of a report by deriving problems based on big data for accumulated data.

The point providing module 324 for each food is a carbohydrate point from the user smart device 100 in order to enhance the convenience of the smart device 100 user by utilizing the influence ingredient table corresponding to the big data provided in the big data server 400. After transmitting the carbohydrate point to the big data server 400 through the network 200 according to the search request through the smart device 100, food or food combination information matching the carbohydrate point is returned from the big data server 400 It is possible to control the transceiver 310 to transmit to.

The hospital information providing module 325 may provide a search function for a diabetes evaluation excellent hospital based on the location information of the user smart device 100 . Here, the hospital information providing module 325 may utilize the information provided by the Health Insurance Review and Assessment Service stored in the big data server 400 for information on the diabetes evaluation excellent hospital.

The present invention can also be implemented as computer-readable codes on a computer-readable recording medium. The computer-readable recording medium includes all kinds of recording devices in which data readable by a computer system is stored.

Examples of the computer-readable recording medium include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, etc., and may also be implemented in the form of a carrier wave (eg, transmission through the Internet). also includes

In addition, the computer-readable recording medium is distributed in a computer system connected through a network, so that the computer-readable code can be stored and executed in a distributed manner. And functional programs, codes, and code segments for implementing the present invention can be easily inferred by programmers in the technical field to which the present invention pertains.

As described above, preferred embodiments of the present invention have been disclosed in the present specification and drawings, and although specific terms are used, these are only used in a general sense to easily explain the technical content of the present invention and help the understanding of the present invention. , it is not intended to limit the scope of the present invention. It will be apparent to those of ordinary skill in the art to which the present invention pertains that other modifications based on the technical spirit of the present invention can be implemented in addition to the embodiments disclosed herein.

1: Diabetes management diet provision system
100: smart device
100g: smart device group
200: network
300: diet management server
310: transceiver
320: control unit
321: information collection module
322: diabetes management module
322a: Individual Daily Calorie Calculation Module
322b: Carbohydrate Ratio Calculation Module
322c: Carbohydrate Point Calculation Module
322d : Carbohydrate Distribution Module
322e: Food Recommendation Module
323: Diabetes Management Coaching Module
324: Food-specific point provision module
325: hospital information provision module
330: database
400: big data server

Claims (6)

In the diabetes management diet providing system (1) comprising a smart device (100), a network (200) and a diet management server (300),
The diet management server 300,
The terminal identification number of the smart device 100 collected through signal and data transmission and reception with the smart device 100 through the network 200 according to the execution of the diabetic manager app on the smart device 100 as metadata an information collection module 321 that stores member ID, member password, and user personal information as "member information unit"; and
Diabetes management comprising a diabetes management module 322 that calculates a carbohydrate:protein:fat ratio for each individual carbohydrate requirement based on the glycated hemoglobin value included in the user's personal information, and detects the calculated carbohydrate requirement Dietary delivery system.
The method of claim 1,
The diabetes management module 322 is
converting the calculated carbohydrate requirement into points;
Diabetes management diet providing system, characterized in that providing food and food combination information matching the converted point to the user device (100) through the network (200).
3. The method of claim 2,
The diabetes management module 322,
Carbohydrate point distribution for each meal, but
A system for providing a diabetes management diet, comprising extracting and comparing a reference set blood sugar value and a fasting blood sugar value and a pre-bed blood sugar value from the “member information unit” stored in the database (330).
4. The method of claim 3,
The diabetes management module 322,
Under normal conditions, T1 : T2 : T3, which is the ratio of carbohydrate intake for breakfast, lunch and dinner, was calculated as the standard value,
When the fasting blood glucose value exceeds the reference fasting blood glucose value, a system for providing a diabetes management diet, characterized in that the evening carbohydrate intake rate is set below T3;
5. The method of claim 4,
The diabetes management module 322,
When the pre-bed blood sugar value exceeds the reference pre-bed blood sugar value, the diabetes management diet providing system, characterized in that setting the carbohydrate intake ratio for lunch less than T2 and dinner less than T3
6. The method of claim 5,
The diabetes management module 322,
When the fasting blood glucose value exceeds the reference fasting blood glucose value and the pre-bed blood glucose value exceeds the reference pre-bed blood glucose value,
Diabetes management diet providing system, characterized in that the dinner carbohydrate intake ratio of less than T3 and the lunch carbohydrate intake ratio of T2 or less are simultaneously set.

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