WO2021118002A1 - System and method for providing dietetic therapy for diabetes management - Google Patents

System and method for providing dietetic therapy for diabetes management Download PDF

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Publication number
WO2021118002A1
WO2021118002A1 PCT/KR2020/009662 KR2020009662W WO2021118002A1 WO 2021118002 A1 WO2021118002 A1 WO 2021118002A1 KR 2020009662 W KR2020009662 W KR 2020009662W WO 2021118002 A1 WO2021118002 A1 WO 2021118002A1
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carbohydrate
diabetes management
diabetes
blood sugar
smart device
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PCT/KR2020/009662
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French (fr)
Korean (ko)
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김은형
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주식회사 메디푸드랩
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Publication of WO2021118002A1 publication Critical patent/WO2021118002A1/en

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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
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
    • 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
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
    • 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
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • 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
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment

Definitions

  • the present disclosure relates to a system and method for providing a diabetes management diet, and more specifically, to a system and method for providing a diabetes management diet for professionally managing a diet for diabetes management by controlling carbohydrate intake it's about
  • One embodiment provides a point diet for blood sugar management of diabetic people (including pre-diabetes), and artificial intelligence individual coaching as main services, and additionally includes factors related to diabetes such as weight, blood pressure, and exercise in one app This is to increase the convenience of blood sugar management and prevent complications due to diabetes by allowing it to be managed in an integrated way.
  • one embodiment is to provide a personalized AI diabetes management coaching service (eg, 1:1 online, wired, etc.) together with a regular report (eg, weekly/monthly, etc.).
  • a personalized AI diabetes management coaching service eg, 1:1 online, wired, etc.
  • a regular report eg, weekly/monthly, etc.
  • an embodiment is to provide information about a diabetes evaluation excellent hospital (eg, stored by the Health Insurance Review and Assessment Service in Korea) based on the user's location.
  • a diabetes evaluation excellent hospital eg, stored by the Health Insurance Review and Assessment Service in Korea
  • Diabetes management diet providing system according to an embodiment, according to the execution of the diabetes manager app on the smart device, the smart device and the signal through the network, and the terminal identification number of the smart device collected through data transmission and reception as metadata members Calculating and calculating the carbohydrate:protein:fat ratio for each individual carbohydrate requirement based on the ID, member password, and information collection module that stores the user’s personal information as a “member information unit”, and the glycated hemoglobin value included in the user’s personal information. It has a diet management server including a diabetes management module for detecting the carbohydrate requirement.
  • the diabetes management module may convert the calculated carbohydrate requirement into points, and provide food and food combination information matching the converted points to the smart device through the network.
  • the diabetes management module may allocate carbohydrate points for each meal, and may extract and compare the reference blood sugar value and the fasting blood sugar value and the blood sugar value before bedtime from the “member information unit”.
  • the diabetes management module calculates T1: T2: T3, which is the carbohydrate intake ratio of breakfast, lunch, and dinner, as a reference value in the normal state, and when the fasting blood glucose value exceeds the preset reference fasting blood glucose value, the evening below T3 You can set the carbohydrate intake rate.
  • the diabetes management module may set the lunch and dinner carbohydrate intake ratios less than T2 and less than T3.
  • the dinner carbohydrate intake ratio of less than T3 and the lunch carbohydrate intake ratio of T2 or less simultaneously can be set.
  • Diabetes management diet providing method according to an embodiment, according to the execution of the diabetes manager app on the smart device, the smart device and the signal through the network, and the terminal identification number of the smart device collected through data transmission and reception as metadata member Storing ID, member password, and user personal information as a “member information unit”, and calculating the carbohydrate:protein:fat ratio for each individual carbohydrate requirement based on the glycated hemoglobin value included in the user’s personal information, and calculating the calculated carbohydrate detecting the demand.
  • One embodiment provides a point diet for blood sugar management of diabetic people (including pre-diabetes), and artificial intelligence individual coaching as main services, and additionally includes factors related to diabetes such as weight, blood pressure, and exercise in one app It is possible to improve the convenience of managing blood sugar and prevent complications due to diabetes by allowing it to be managed in an integrated way.
  • an embodiment may provide a personalized AI diabetes management coaching service (eg, 1:1 online, wired, etc.) together with a regular report (eg, weekly/monthly, etc.).
  • a personalized AI diabetes management coaching service eg, 1:1 online, wired, etc.
  • a regular report eg, weekly/monthly, etc.
  • one embodiment has an effect of providing information on diabetes evaluation excellent hospitals (eg, stored by the Health Insurance Review and Assessment Service in Korea) based on the user's location.
  • FIG. 1 is a view showing a diabetes management diet providing system 1 according to an embodiment.
  • FIG. 2 is a block diagram illustrating components of a diet management server 300 in the diabetes management diet providing system 1 according to an embodiment.
  • FIG. 3 is a block diagram illustrating components of the diabetes management module 322 of the diet management server 300 according to an embodiment.
  • the component when any one component 'transmits' data or signal to another component, the component may directly transmit data or signal to the other component, and data through at least one other component Or it means that the signal can be transmitted to other components.
  • 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.
  • the network 200 is a high-speed backbone network of a large-scale communication network capable of large-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.
  • the network 200 may be a mobile communication network, it may be a synchronous mobile communication network or an asynchronous mobile communication network.
  • the asynchronous mobile communication network there may be a wideband code division multiple access (WCDMA) type communication network.
  • WCDMA wideband code division multiple access
  • the mobile communication network 700 may include a Radio Network Controller (RNC).
  • RNC Radio Network Controller
  • the WCDMA network 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 transmits signals and data between the smart device group 100g, the diet management server 300, and the big data server 400, and other systems made up of a plurality of smart devices 100. .
  • FIG. 2 is a block diagram illustrating components of a diet management server 300 in the diabetes management diet providing system 1 according to an embodiment.
  • 3 is a block diagram illustrating components of the diabetes management module 322 of the diet management server 300 according to an embodiment.
  • 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 , diabetes management It may include a module 322 , a diabetes management coaching module 323 , a food-specific point providing module 324 , and a hospital information providing module 325 .
  • the diet management server 300 provides a point diet for blood sugar management of diabetic people (including pre-diabetes), and artificial intelligence individual coaching service as main services, and additionally, diabetes such as weight, blood pressure, and exercise. Enables integrated management of related factors in one app. Accordingly, it is possible to increase the convenience of blood sugar management and prevent complications due to diabetes, and provide personalized AI diabetes management coaching service along with regular reports (eg weekly/monthly, etc.) on a 1:1 online basis. In addition to providing, it is possible to provide information on diabetes evaluation excellent hospitals (eg, stored by the Health Insurance Review and Assessment Service in Korea) based on the user's location.
  • diabetes evaluation excellent hospitals eg, stored by the Health Insurance Review and Assessment Service in Korea
  • 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).
  • the information collection module 321 proceeds with the membership registration procedure through the smart device 100 through the network 200 according to the execution of the diabetic manager app on the smart device 100, signals, and data transmission and reception,
  • the terminal identification number of the smart device 100 collected in the membership registration procedure may be stored as metadata, and the member ID, member password, and user personal information may be stored as "member information unit".
  • 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.
  • the transceiver 310 After controlling the transceiver 310 to receive the fasting blood glucose and pre-bedtime blood glucose values periodically received from the smart device 100 through the network 200, it may be stored together in the member information unit.
  • 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)
  • the blood glucose before bedtime may be blood glucose before bedtime (measured in the evening).
  • 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.
  • the daily calorie calculation module 322a for each individual is based on the AI (Artificial Intelligence) platform, including meals, drugs, exercise amount, activity amount, body information (user age, gender), body measurements (height, weight), etc. included in the user's personal information. Based on the data, it is possible to calculate individual daily calorie requirements, including individual daily carbohydrate requirements, through an AI-based nutrition evaluation algorithm.
  • AI Artificial Intelligence
  • 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. Calorie requirements can be calculated through an AI-based nutrition evaluation algorithm. Accordingly, by giving points for easy understanding by the smart device 100 user by the food-specific point providing module 324, the user can conveniently conduct a diet through the food-specific point instead of the food-specific nutritional component table. have.
  • the individual daily calorie calculation module 322a may extract a user's age, gender, height, and weight from the member information unit and calculate a basic calorie value through a preset calorie calculation algorithm.
  • 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 blood glucose value before bedtime.
  • 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.
  • the carbohydrate ratio calculation module 322b may compare the measured glycated hemoglobin value with a preset reference glycated hemoglobin value and set the carbohydrate:protein:fat ratio as a1:b1:c1 when the measured glycated hemoglobin value is equal to or less than the reference glycated hemoglobin value. Alternatively, when the measured glycated hemoglobin value exceeds the reference glycated hemoglobin value, the carbohydrate ratio calculation module 322b may set the carbohydrate:protein:fat ratio as 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.
  • the carbohydrate ratio calculation module 322b may set 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.
  • the carbohydrate:protein:fat ratio may be set to 5:2.5:2.5, and the carbohydrate ratio calculation module 322b is configured to calculate the measured glycated hemoglobin value.
  • 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.
  • 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.
  • the carbohydrate point calculation module 322c sets a preset unit calorie unit value of 60 kcal to 1 point when the ratio of carbohydrates in the individual daily calorie requirement corresponds to 6, and the calorie of the corresponding carbohydrate ratio is 600 kcal, 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 blood sugar value before bedtime may be extracted and compared with the reference set blood sugar value and the "member information unit" stored in the database 330 .
  • fasting blood sugar and blood sugar before bedtime are short-term morning or evening blood sugar values. If fasting blood sugar is high, it is recommended to reduce carbohydrate intake the night before and after dinner (hereafter referred to as 'dinner'). If your blood sugar level before bedtime is high, it is recommended to reduce your carbohydrate intake at lunch and dinner.
  • the carbohydrate distribution module 322d sets the standard value of T1: T2: T3, which is the carbohydrate intake ratio of breakfast, lunch, and dinner in the normal state, and when the fasting blood glucose value exceeds the reference fasting blood glucose value, the reference evening blood glucose value (T3) is less than You can set the dinner intake ratio of When the pre-bedtime blood glucose value exceeds the reference pre-bedtime blood glucose value, the lunch meal intake ratio less than the reference lunch blood sugar value (T2) and the dinner intake ratio less than the reference dinner blood sugar value (T3) may be set.
  • the ratio of dinner intake below the reference fasting blood glucose value (T3) and the lunch intake rate below the reference lunch blood glucose value (T2) can be set at the same time.
  • blood sugar before bedtime > reference blood sugar before bedtime can be set to 1: 0.8: 0.8, and when fasting blood sugar > reference fasting blood sugar, and blood sugar before bed > reference blood sugar before bedtime can 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.
  • the food recommendation module 322e converts carbohydrate-containing calories per food into a point conversion ratio, and then creates a food or food combination suitable for each point for breakfast, lunch, and dinner, and then sends it to the smart device 100 through the network 200
  • the transceiver 310 may be controlled to transmit.
  • the diabetes management module 322 converts to 1 point when carbohydrate calories among the total calories of one apple are 60 kcal and provides the food name corresponding to the converted point to the smart device 100 through the network 200.
  • the carbohydrate required per day is 9 points
  • the user inputs 1 apple, 2/3 bowl of rice, bulgogi, ssam vegetables, kimchi, and 1/4 simmered tofu.
  • the algorithm calculates 1 point for one apple, 2 points for 2/3 bowl of rice, 0.5 points for stewed tofu, and 0.5 points for bulgogi, so you can see that you ate 4 points through your meal (for reference, kimchi and ssam vegetables) is counted as 0 points).
  • the user can predict that 5 points can be used through the rest of the meal, and by searching for food through the app, each food and the points of each food can be predicted in advance. Accordingly, since the user can implement a diet for controlling carbohydrate intake by himself/herself, the user may receive help in managing blood sugar.
  • 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 .
  • the diabetes management coaching module 323 reports twice a month that is provided as a personalized diabetes management coaching service. It connects the blood sugar level, blood pressure, weight, exercise amount, and activity data to the smart device 100 through short-distance wireless communication. It can be obtained from various measurement devices, and problems can be derived based on big data for accumulated data and provided to users in the form of a report.
  • the point providing module 324 for each food utilizes the nutritional information table corresponding to the big data provided in the big data server 400 to increase the convenience of the smart device 100 user, and the carbohydrate from the user smart device 100 According to the search request through the points, the carbohydrate points are transmitted to the big data server 400 through the network 200 . Thereafter, the food-specific point providing module 324 may control the transceiver 310 to receive food or food combination information matching the carbohydrate point from the big data server 400 and transmit it to the smart device 100 . have.
  • 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 .
  • the hospital information providing module 325 may utilize information provided by the Health Insurance Review and Assessment Service of the Republic of Korea stored in the big data server 400 for information on excellent diabetes evaluation hospitals.
  • Diabetes management diet providing method according to an embodiment, according to the execution of the diabetes manager app on the smart device, the smart device and the signal through the network, and the terminal identification number of the smart device collected through data transmission and reception as metadata member Storing ID, member password, and user personal information as a “member information unit”, and calculating the carbohydrate:protein:fat ratio for each individual carbohydrate requirement based on the glycated hemoglobin value included in the user’s personal information, and calculating the calculated carbohydrate detecting the demand.
  • the step of storing the "member information unit” is performed by the information collection module 321, and the description of the information collection module 321 is the same as described above.
  • the step of detecting the carbohydrate requirement is performed by the diabetes management module 322, and the description of the diabetes management module 322 is the same as described above.
  • 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. can do.
  • a method of providing a diabetes management diet is a scientific and systematic personalized diabetes management coaching report twice a month through continuous learning and data accumulation of blood sugar management methods for each user case based on an AI platform, and customized 1 It may include providing 1:1 diabetes management coaching to the user device 100 through the network 200 . These steps are performed by the diabetes management coaching module 323, and the description of the diabetes management coaching module 323 is the same as described above.
  • food or food combination information matching the carbohydrate point from the big data server 400 may include the step of receiving a return and transmitting it to the smart device 100 . These steps are performed by the food-specific point providing module 324, and the description of the food-specific point providing module 324 is the same as described above.
  • the method of providing a diabetes management diet may include providing a search function for a diabetes evaluation excellent hospital based on location information of the user's smart device 100 . These steps are performed by the hospital information providing module 325, and the description of the hospital information providing module 325 is the same as described above.
  • An embodiment may also be implemented as computer-readable code 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
  • 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.
  • functional programs, codes, and code segments for implementing an embodiment can be easily inferred by programmers in the technical field to which the present invention pertains.

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Abstract

This system for providing a dietetic therapy for diabetes management comprises an information collection module and a diabetes management module, and makes it possible to professionally manage a dietetic therapy for diabetes management by controlling carbohydrate intake. 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

당뇨 관리 식이요법 제공 시스템 및 방법Diabetes management diet delivery system and method
본 기재는 당뇨 관리 식이요법 제공 시스템 및 방법에 관한 것으로, 보다 구체적으로는, 탄수화물 섭취량 조절을 함으로써, 당뇨 관리를 위한 식이요법을 전문적으로 관리할 수 있도록 하기 위한 당뇨 관리 식이요법 제공 시스템 및 방법에 관한 것이다. The present disclosure relates to a system and method for providing a diabetes management diet, and more specifically, to a system and method for providing a diabetes management diet for professionally managing a diet for diabetes management by controlling carbohydrate intake it's about
종래 다이어트 등을 위한 칼로리 계산, 퍼스널 트레이닝 앱 등은 매우 많이 출시되어 사용자에게 제공되고 있다. Conventionally, a lot of calorie calculations, personal training apps, and the like for diet, etc. have been released and provided to users.
이와 더불어 세계 성인의 약 4억 2500만명(20세 내지 79세)이 당뇨병으로 고통받고 있으며, 실제로 2045년에는 6억 2900만명으로 늘어날 것으로 추정되고 있다. 특히, 수명 증가와 함께 노년층에서 제2형 당뇨환자의 비율이 증가하고 있는 실정이다. In addition, about 425 million people (ages 20 to 79) of the world's adults suffer from diabetes, and it is actually estimated that the number will increase to 629 million by 2045. In particular, the proportion of type 2 diabetes patients in the elderly is increasing with the increase in life expectancy.
그런데, 전체 칼로리 조절만을 목표로 한 다이어트 앱의 경우, 당뇨환자에게 적용되기 부족한 문제가 있다. 왜냐하면 당뇨환자의 경우, 총 칼로리보다 탄수화물 섭취량, 그리고 전체 칼로리에서 탄수화물이 차지하는 비율이 중요한데 반하여, 종래에 출시된 칼로리 계산, 퍼스널 트레이닝 앱 등은 전체 칼로리 계산만을 수행하기 때문이다. However, in the case of a diet app that aims only to control total calories, 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 important, whereas conventionally released calorie calculations and personal training apps perform only total calorie calculations.
이에 따라 해당 기술분야에 있어서는 탄수화물 섭취량을 조절함으로써, 당뇨 관리를 위한 식이요법을 전문적으로 관리할 수 있도록 하기 위한 기술 개발이 요구되고 있다. Accordingly, in the technical field, there is a demand for technology development for professionally managing a diet for diabetes management by controlling carbohydrate intake.
선행기술문헌은 대한민국 특허출원 출원번호 제10-2007-0085165(2007. 08. 23)호 "네트워크를 이용한 식이 요법 관리 시스템, 그리고 방법(System and method for managing a dietetic therapy using the network)"이 있다. In the prior art literature, there is Republic of Korea Patent Application No. 10-2007-0085165 (2007. 08. 23) No. "System and method for managing a dietetic therapy using the network". .
일 실시예는, 당뇨인(당뇨 전단계 포함)의 혈당관리를 위한 포인트 식이요법, 그리고 인공지능 개인별 코칭을 주요 서비스로 제공하며, 부가적으로 체중, 혈압, 운동과 같이 당뇨와 관련된 인자를 하나의 앱에서 통합 관리할 수 있도록 하여 혈당 관리의 편의성을 높이고 당뇨로 인한 합병증을 예방하기 위한 것이다. One embodiment provides a point diet for blood sugar management of diabetic people (including pre-diabetes), and artificial intelligence individual coaching as main services, and additionally includes factors related to diabetes such as weight, blood pressure, and exercise in one app This is to increase the convenience of blood sugar management and prevent complications due to diabetes by allowing it to be managed in an integrated way.
또한, 일 실시예는 정기적인 보고서(예를 들어, 주별/월별 등)와 함께 개인 맞춤형 인공지능 당뇨관리 코칭 서비스(예를 들어, 1:1 온라인, 유선 등)를 제공하기 위한 것이다. In addition, one embodiment is to provide a personalized AI diabetes management coaching service (eg, 1:1 online, wired, etc.) together with a regular report (eg, weekly/monthly, etc.).
또한, 일 실시예는 사용자 위치에 기반하여 당뇨 평가 우수 병원(예를 들어, 대한민국의 경우 건강보험심사평가원에 의해 저장됨) 정보를 제공하기 위한 것이다. In addition, an embodiment is to provide information about a diabetes evaluation excellent hospital (eg, stored by the Health Insurance Review and Assessment Service in Korea) based on the user's location.
그러나 본 발명의 일 실시예의 목적들은 상기에 언급된 목적으로 제한되지 않으며, 언급되지 않은 또 다른 목적들은 아래의 기재로부터 당업자에게 명확하게 이해될 수 있을 것이다. However, the objects of one embodiment 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.
일 실시예에 따른 당뇨 관리 식이요법 제공 시스템은, 스마트 디바이스 상에서 당뇨식 매니저 앱에 대한 실행에 따라 네트워크를 통해 스마트 디바이스와 신호, 그리고 데이터 송수신을 통해 수집된 스마트 디바이스의 단말식별번호를 메타데이터로 회원 ID, 회원 비밀번호, 사용자 개인정보를 "회원 정보 단위"로 저장하는 정보 수집 모듈, 그리고 사용자 개인정보에 포함된 당화혈색소 값을 기초로 개인별 탄수화물 요구량에 대한 탄수화물 : 단백질 : 지방 비율을 산정하고, 산정된 탄수화물 요구량을 검출하는 당뇨 관리 모듈을 포함하는 식이요법 관리 서버를 구비한다. Diabetes management diet providing system according to an embodiment, according to the execution of the diabetes manager app on the smart device, the smart device and the signal through the network, and the terminal identification number of the smart device collected through data transmission and reception as metadata members Calculating and calculating the carbohydrate:protein:fat ratio for each individual carbohydrate requirement based on the ID, member password, and information collection module that stores the user’s personal information as a “member information unit”, and the glycated hemoglobin value included in the user’s personal information. It has a diet management server including a diabetes management module for detecting the carbohydrate requirement.
당뇨 관리 모듈은, 산정된 탄수화물 요구량을 포인트로 전환하고, 전환된 포인트에 매칭되는 식품, 그리고 식품 조합 정보를 상기 네트워크를 통해 스마트 디바이스로 제공할 수 있다.The diabetes management module may convert the calculated carbohydrate requirement into points, and provide food and food combination information matching the converted points to the smart device through the network.
당뇨 관리 모듈은, 끼니별 탄수화물 포인트 배분을 수행하며, 기준 혈당값과 "회원 정보 단위"에서 공복 혈당값 및 취침전 혈당값을 추출하여 비교할 수 있다.The diabetes management module may allocate carbohydrate points for each meal, and may extract and compare the reference blood sugar value and the fasting blood sugar value and the blood sugar value before bedtime from the “member information unit”.
당뇨 관리 모듈은, 정상상태에서 아침, 점심, 그리고 저녁의 탄수화물 섭취비율인 T1 : T2 : T3을 기준 값으로 산정하고, 공복 혈당값이 미리 설정된 기준 공복 혈당값을 초과하는 경우, T3 미만의 저녁 탄수화물 섭취비율을 설정할 수 있다.The diabetes management module calculates T1: T2: T3, which is the carbohydrate intake ratio of breakfast, lunch, and dinner, as a reference value in the normal state, and when the fasting blood glucose value exceeds the preset reference fasting blood glucose value, the evening below T3 You can set the carbohydrate intake rate.
당뇨 관리 모듈은, 취침전 혈당값이 미리 설정된 기준 취침전 혈당값을 초과하는 경우, T2 미만의 점심, 그리고 T3 미만의 저녁 탄수화물 섭취비율을 설정할 수 있다. When the pre-bedtime blood sugar value exceeds a preset reference pre-bedtime blood sugar value, the diabetes management module may set the lunch and dinner carbohydrate intake ratios less than T2 and less than T3.
당뇨 관리 모듈은, 공복 혈당값이 기준 공복 혈당값을 초과하고 취침전 혈당값이 상기 기준 취침전 혈당값을 초과하는 경우, T3 미만의 저녁 탄수화물 섭취비율, 그리고 T2 이하의 점심 탄수화물 섭취비율을 동시에 설정할 수 있다.If the fasting blood glucose value exceeds the reference fasting blood glucose value and the pre-bedtime blood glucose value exceeds the reference pre-bedtime blood glucose value, the dinner carbohydrate intake ratio of less than T3 and the lunch carbohydrate intake ratio of T2 or less simultaneously can be set.
일 실시예에 따른 당뇨 관리 식이 요법 제공 방법은, 스마트 디바이스 상에서 당뇨식 매니저 앱에 대한 실행에 따라 네트워크를 통해 스마트 디바이스와 신호, 그리고 데이터 송수신을 통해 수집된 스마트 디바이스의 단말식별번호를 메타데이터로 회원 ID, 회원 비밀번호, 사용자 개인정보를 "회원 정보 단위"로 저장하는 단계, 그리고 사용자 개인정보에 포함된 당화혈색소 값을 기초로 개인별 탄수화물 요구량에 대한 탄수화물 : 단백질 : 지방 비율을 산정하고, 산정된 탄수화물 요구량을 검출하는 단계를 포함한다.Diabetes management diet providing method according to an embodiment, according to the execution of the diabetes manager app on the smart device, the smart device and the signal through the network, and the terminal identification number of the smart device collected through data transmission and reception as metadata member Storing ID, member password, and user personal information as a “member information unit”, and calculating the carbohydrate:protein:fat ratio for each individual carbohydrate requirement based on the glycated hemoglobin value included in the user’s personal information, and calculating the calculated carbohydrate detecting the demand.
일 실시예는, 당뇨인(당뇨 전단계 포함)의 혈당관리를 위한 포인트 식이요법, 그리고 인공지능 개인별 코칭을 주요 서비스로 제공하며, 부가적으로 체중, 혈압, 운동과 같이 당뇨와 관련된 인자를 하나의 앱에서 통합 관리할 수 있도록 하여 혈당을 관리의 편의성을 높이고 당뇨로 인한 합병증을 예방할 수 있다. One embodiment provides a point diet for blood sugar management of diabetic people (including pre-diabetes), and artificial intelligence individual coaching as main services, and additionally includes factors related to diabetes such as weight, blood pressure, and exercise in one app It is possible to improve the convenience of managing blood sugar and prevent complications due to diabetes by allowing it to be managed in an integrated way.
또한, 일 실시예는, 정기적인 보고서(예를 들어, 주별/월별 등)와 함께 개인 맞춤형 인공지능 당뇨관리 코칭 서비스(예를 들어, 1:1 온라인, 유선 등)를 제공할 수 있다. In addition, an embodiment may provide a personalized AI diabetes management coaching service (eg, 1:1 online, wired, etc.) together with a regular report (eg, weekly/monthly, etc.).
뿐만 아니라, 일 실시예는, 사용자 위치에 기반하여 당뇨 평가 우수 병원(예를 들어, 대한민국의 경우 건강보험심사평가원에 의해 저장됨) 정보를 제공하는 효과가 있다.In addition, one embodiment has an effect of providing information on diabetes evaluation excellent hospitals (eg, stored by the Health Insurance Review and Assessment Service in Korea) based on the user's location.
도 1은 일 의 실시예에 따른 당뇨 관리 식이요법 제공 시스템(1)을 나타내는 도면이다. 1 is a view showing a diabetes management diet providing system 1 according to an embodiment.
도 2는 일 실시예에 따른 당뇨 관리 식이요법 제공 시스템(1) 중 식이요법 관리 서버(300)의 구성요소를 나타내는 블록도이다. 2 is a block diagram illustrating components of a diet management server 300 in the diabetes management diet providing system 1 according to an embodiment.
도 3은 일 실시예에 따른 식이요법 관리 서버(300)의 당뇨 관리 모듈(322)의 구성요소를 나타내는 블록도이다. 3 is a block diagram illustrating components of the diabetes management module 322 of the diet management server 300 according to an embodiment.
이하, 본 발명의 바람직한 실시예의 상세한 설명은 첨부된 도면들을 참조하여 설명할 것이다. 하기에서 본 발명을 설명함에 있어서, 관련된 공지 기능 또는 구성에 대한 구체적인 설명이 본 발명의 요지를 불필요하게 흐릴 수 있다고 판단되는 경우에는 그 상세한 설명을 생략할 것이다. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a detailed description of a preferred embodiment 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.
본 명세서에 있어서는 어느 하나의 구성요소가 다른 구성요소로 데이터 또는 신호를 '전송'하는 경우에는 구성요소는 다른 구성요소로 직접 데이터 또는 신호를 전송할 수 있고, 적어도 하나의 또 다른 구성요소를 통하여 데이터 또는 신호를 다른 구성요소로 전송할 수 있음을 의미한다. In the present specification, when any one component 'transmits' data or signal to another component, the component may directly transmit data or signal to the other component, and data through at least one other component Or it means that the signal can be transmitted to other components.
도 1은 일 실시예에 따른 당뇨 관리 식이요법 제공 시스템(1)을 나타내는 도면이다. 도 1을 참조하면, 당뇨 관리 식이요법 제공 시스템(1)은 복수의 스마트 디바이스(100)로 이루어진 스마트 디바이스 그룹(100g), 네트워크(200), 식이요법 관리 서버(300), 그리고 빅데이터 서버(400)를 포함할 수 있다. 1 is a view showing a diabetes management diet providing system 1 according to an embodiment. 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.
여기서 네트워크(200)는 대용량, 장거리 음성, 그리고 데이터 서비스가 가능한 대형 통신망의 고속 기간 망인 통신망이며, 인터넷(Internet) 또는 고속의 멀티미디어 서비스를 제공하기 위한 차세대 유선, 그리고 무선 망일 수 있다. 네트워크(200)가 이동통신망일 경우 동기식 이동 통신망일 수도 있고, 비동기식 이동 통신망일 수도 있다. 비동기식 이동 통신망의 일 실시 예로서, WCDMA(Wideband Code Division Multiple Access) 방식의 통신망을 들 수 있다. 이 경우 도면에 도시되진 않았지만, 이동통신망(700)은 RNC(Radio Network Controller)을 포함할 수 있다. Here, the network 200 is a high-speed backbone network of a large-scale communication network capable of large-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).
한편, WCDMA망을 일 예로 들었지만, 3G LTE망, 4G망 그 밖의 5G 등 차세대 통신망, 그 밖의 IP를 기반으로 한 IP망일 수 있다. 네트워크(200)는 복수의 스마트 디바이스(100)로 이루어진 스마트 디바이스 그룹(100g), 식이요법 관리 서버(300), 그리고 빅데이터 서버(400), 그 밖의 시스템 상호 간의 신호, 그리고 데이터를 상호 전달한다. 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 transmits signals and data between the smart device group 100g, the diet management server 300, and the big data server 400, and other systems made up of a plurality of smart devices 100. .
도 2는 일 실시예에 따른 당뇨 관리 식이요법 제공 시스템(1) 중 식이요법 관리 서버(300)의 구성요소를 나타내는 블록도이다. 도 3은 일 실시예에 따른 식이요법 관리 서버(300)의 당뇨 관리 모듈(322)의 구성요소를 나타내는 블록도이다. 2 is a block diagram illustrating components of a diet management server 300 in the diabetes management diet providing system 1 according to an embodiment. 3 is a block diagram illustrating components of the diabetes management module 322 of the diet management server 300 according to an embodiment.
먼저, 도 2를 참조하면, 식이요법 관리 서버(300)는 송수신부(310), 제어부(320), 그리고 데이터베이스(330)를 포함하며, 제어부(320)는 정보 수집 모듈(321), 당뇨 관리 모듈(322), 당뇨 관리 코칭 모듈(323), 식품별 포인트 제공 모듈(324), 그리고 병원 정보 제공 모듈(325)을 포함할 수 있다. 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 , diabetes management It may include a module 322 , a diabetes management coaching module 323 , a food-specific point providing module 324 , and a hospital information providing module 325 .
이러한 구성을 통해 식이요법 관리 서버(300)는 당뇨인(당뇨 전단계 포함)의 혈당관리를 위한 포인트 식이요법, 그리고 인공지능 개인별 코칭 서비스를 주요 서비스로 하여, 부가적으로 체중, 혈압, 운동과 같이 당뇨와 관련된 인자를 하나의 앱에서 통합 관리할 수 있도록 한다. 이에 따라, 혈당 관리의 편의성을 높이고 당뇨로 인한 합병증 예방을 수행할 수 있고, 1:1 온라인 기반에 정기적인 보고서(예를 들어, 주별/월별 등)와 함께 개인 맞춤형 인공지능 당뇨관리 코칭 서비스를 제공할 뿐만 아니라, 사용자 위치에 기반하여 당뇨 평가 우수 병원(예를 들어, 대한민국의 경우 건강보험심사평가원에 의해 저장됨) 정보를 제공할 수 있다. Through this configuration, the diet management server 300 provides a point diet for blood sugar management of diabetic people (including pre-diabetes), and artificial intelligence individual coaching service as main services, and additionally, diabetes such as weight, blood pressure, and exercise. Enables integrated management of related factors in one app. Accordingly, it is possible to increase the convenience of blood sugar management and prevent complications due to diabetes, and provide personalized AI diabetes management coaching service along with regular reports (eg weekly/monthly, etc.) on a 1:1 online basis. In addition to providing, it is possible to provide information on diabetes evaluation excellent hospitals (eg, stored by the Health Insurance Review and Assessment Service in Korea) based on the user's location.
이하에서는 제어부(320)의 구성요소를 중심으로 당뇨 관리 식이요법 제공 시스템(1), 그리고 식이요법 관리 서버(300)에 대해서 구체적으로 살펴보도록 한다. 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.
정보 수집 모듈(321)은 네트워크(200)를 통해 스마트 디바이스(100)의 액세스(access)에 따라 당뇨식 매니저 앱 데이터 요청에 따라 당뇨식 매니저앱 데이터를 스마트 디바이스(100)로 전송하도록 송수신부(310)를 제어함으로써, 당뇨식 매니저 앱이 스마트 디바이스(100) 상에 설치되도록 할 수 있다. 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).
이후, 정보 수집 모듈(321)은 스마트 디바이스(100) 상에서 당뇨식 매니저 앱에 대한 실행에 따라 네트워크(200)를 통해 스마트 디바이스(100)와 신호, 그리고 데이터 송수신을 통해 회원 가입절차를 진행한 뒤, 회원 가입절차에서 수집된 스마트 디바이스(100)의 단말식별번호를 메타데이터로 회원 ID, 회원 비밀번호, 사용자 개인정보를 "회원 정보 단위"로 저장할 수 있다. Thereafter, the information collection module 321 proceeds with the membership registration procedure through the smart device 100 through the network 200 according to the execution of the diabetic manager app on the smart device 100, signals, and data transmission and reception, The terminal identification number of the smart device 100 collected in the membership registration procedure may be stored as metadata, and the member ID, member password, and user personal information may be stored as "member information unit".
또한, 정보 수집 모듈(321)은 네트워크(200)를 통해 스마트 디바이스(100)로부터 미리 설정된 기간 동안의 HbA1c(당화혈색소) 값을 수신하고, 스마트 디바이스(100)와 근거리 무선통신 방식으로 연결된 혈당측정기로부터 주기적으로 수신되는 공복 혈당, 취침전 혈당값을 스마트 디바이스(100)로부터 네트워크(200)를 통해 수신하도록 송수신부(310)를 제어한 뒤, 회원 정보 단위에 함께 저장할 수 있다. 여기서 당화혈색소 값은 최근 3개월 간의 평균 혈당값을 반영한 값일 수 있으며, 공복 혈당은 취침 후 혈당(아침에 측정한 값), 취침전 혈당은 취침전 혈당(저녁에 측정한 값)일 수 있다. 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-bedtime 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).
한편, 도 3을 참조하면, 당뇨 관리 모듈(322)은 개인별 일일 칼로리 산출 모듈(322a), 탄수화물 비율 산출 모듈(322b), 탄수화물 포인트 산출 모듈(322c), 탄수화물 분배 모듈(322d), 그리고 식품 추천 모듈(322e)을 포함할 수 있다. 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.
개인별 일일 칼로리 산출 모듈(322a)은 AI(Artificial Intelligence) 플랫폼을 기반으로 사용자 개인정보에 포함된 식사, 약물, 운동량, 활동량, 신체정보(사용자 나이, 성별), 신체계측(키, 몸무게) 등의 자료를 기반으로 개인별 일일 탄수화물 요구량을 포함한 개인별 일일 칼로리 요구량을 AI 기반 영양평가 알고리즘을 통해 산출할 수 있다. The daily calorie calculation module 322a for each individual is based on the AI (Artificial Intelligence) platform, including meals, drugs, exercise amount, activity amount, body information (user age, gender), body measurements (height, weight), etc. included in the user's personal information. Based on the data, it is possible to calculate individual daily calorie requirements, including individual daily carbohydrate requirements, through an AI-based nutrition evaluation algorithm.
보다 구체적으로, 개인별 일일 칼로리 산출 모듈(322a)은 식사, 약물, 운동량, 그리고 활동량, 신체정보(사용자 나이, 성별), 신체계측(키, 몸무게) 자료를 기반으로 개인별 일일 탄수화물 요구량을 포함한 개인별 일일 칼로리 요구량을 AI 기반 영양평가 알고리즘을 통해 산출할 수 있다. 이에 따라, 식품별 포인트 제공 모듈(324)에 의해 스마트 디바이스(100) 사용자가 이해하기 쉽도록 포인트를 부여함으로써, 사용자는 음식별 영양성분표 대신 식품별 포인트를 통해 편리하게 식이요법을 실시할 수 있다. 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. Calorie requirements can be calculated through an AI-based nutrition evaluation algorithm. Accordingly, by giving points for easy understanding by the smart device 100 user by the food-specific point providing module 324, the user can conveniently conduct a diet through the food-specific point instead of the food-specific nutritional component table. have.
개인별 일일 칼로리 산출 모듈(322a)은 회원 정보 단위에서 사용자 나이, 성별, 키, 몸무게를 추출하여 미리 설정된 칼로리 산출 알고리즘을 통해 기초 칼로리 값을 산출할 수 있다. 예를 들어, 칼로리 산출 알고리즘은 종래의 기술에 따른 체중계에서 제공하는 칼로리 산출 방식 등일 수 있다. The individual daily calorie calculation module 322a may extract a user's age, gender, height, and weight from the member information unit and calculate a basic calorie value through a preset calorie calculation algorithm. For example, the calorie calculation algorithm may be a calorie calculation method provided by a scale according to the related art.
탄수화물 비율 산출 모듈(322b)은 개인별 일일 칼로리 산출 모듈(322a)에 의해 산출된 칼로리 값과 당화혈색소 값, 공복 혈당값, 취침전 혈당값을 이용해서 탄수화물 비율을 산출할 수 있다. 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 blood glucose value before bedtime.
보다 구체적으로, 탄수화물 비율 산출 모듈(322b)은 당화혈색소 값을 기초로 산출된 칼로리 값에 대한 탄수화물 : 단백질 : 지방 비율을 산정할 수 있다. 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.
여기서, 탄수화물 비율 산출 모듈(322b)은 측정된 당화혈색소 값이 미리 설정된 기준 당화혈색소 값과 비교하여, 기준 당화혈색소 값 이하인 경우 탄수화물 : 단백질 :지방 비율을 a1 : b1 : c1로 설정할 수 있다. 또는 측정된 당화혈색소 값이 기준 당화혈색소 값을 초과하는 경우, 탄수화물 비율 산출 모듈(322b)은 탄수화물 : 단백질 : 지방 비율을 a2 : b2 : c2로 설정할 수 있다. Here, the carbohydrate ratio calculation module 322b may compare the measured glycated hemoglobin value with a preset reference glycated hemoglobin value and set the carbohydrate:protein:fat ratio as a1:b1:c1 when the measured glycated hemoglobin value is equal to or less than the reference glycated hemoglobin value. Alternatively, when the measured glycated hemoglobin value exceeds the reference glycated hemoglobin value, the carbohydrate ratio calculation module 322b may set the carbohydrate:protein:fat ratio as a2:b2:c2.
탄수화물 비율 산출 모듈(322b)은 a1 > P > a2에 해당하도록 설정하는 것이 바람직하며 P는 기준 당화혈색소 값에서 탄수화물 비율일 수 있다. 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.
보다 구체적으로, 탄수화물 비율 산출 모듈(322b)은 측정된 당화혈색소 값이 미리 설정된 기준 당화혈색소 값과 비교하여 기준 당화혈색소 값 이하인 경우 탄수화물 : 단백질 : 지방 비율을 6 : 2 : 2로 설정할 수 있다. 또는 측정된 당화혈색소 값이 기준 당화 혈색소 값을 초과하는 경우, 탄수화물 : 단백질 : 지방 비율을 5 : 2. 5 : 2. 5로 설정할 수 있으며, 탄수화물 비율 산출 모듈(322b)은 측정된 당화혈색소 값이 높을수록 높은 정도에 비례하여 탄수화물 비율을 낮게 설정할 수 있고, 측정된 당화혈색소 값이 낮을수록 낮은 정보에 비례하여 탄수화물 비율을 높게 설정할 수 있다. More specifically, the carbohydrate ratio calculation module 322b may set 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. Alternatively, when the measured glycated hemoglobin value exceeds the reference glycated hemoglobin value, the carbohydrate:protein:fat ratio may be set to 5:2.5:2.5, and the carbohydrate ratio calculation module 322b is configured to calculate the measured glycated hemoglobin value. The higher the value, the lower the carbohydrate ratio can be set in proportion to the high degree, and the lower the measured glycated hemoglobin value, the higher the carbohydrate ratio can be set in proportion to the lower information.
탄수화물 포인트 산출 모듈(322c)은 개인별 일일 칼로리 산출 모듈(322a)에 의해 산출된 칼로리 값에 대해서 탄수화물 비율 산출 모듈(322b)에 대해서 탄수화물 비율이 추출되면, 추출된 탄수화물 비율의 칼로리 값에 대해서 탄수화물 포인트로 전환을 수행할 수 있다. 요약하면, 탄수화물 포인트 산출 모듈(322c)은 개인별 일일 칼로리 요구량에서 탄수화물이 차지하는 비율에 해당하는 칼로리 값을 연산한 뒤, 연산된 탄수화물 칼로리 값에 대해서 미리 설정된 단위 칼로리 단위 값에 대해서 하나의 포인트로 연산할 수 있다. 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.
탄수화물 포인트 산출 모듈(322c)은 개인별 일일 칼로리 요구량에서 탄수화물이 차지하는 비율이 6에 해당하고, 해당된 탄수화물 비율의 칼로리가 600 kcal인 경우, 미리 설정된 단위 칼로리 단위 값인 60 kcal를 1 point로 설정함으로써, 10 포인트를 탄수화물 포인트로 연산할 수 있다. The carbohydrate point calculation module 322c sets a preset unit calorie unit value of 60 kcal to 1 point when the ratio of carbohydrates in the individual daily calorie requirement corresponds to 6, and the calorie of the corresponding carbohydrate ratio is 600 kcal, 10 points can be calculated as carbohydrate points.
탄수화물 분배 모듈(322d)은 끼니별 탄수화물 포인트 배분을 수행할 수 있다. 이를 위해 기준 설정혈당값과 데이터베이스(330)에 저장된 "회원 정보 단위"에서 공복 혈당값, 취침전 혈당값을 추출하여 비교할 수 있다. The carbohydrate distribution module 322d may distribute carbohydrate points for each meal. To this end, a fasting blood sugar value and a blood sugar value before bedtime may be extracted and compared with the reference set blood sugar value and the "member information unit" stored in the database 330 .
기본적으로 공복 혈당, 그리고 취침전 혈당값은 단기적인 아침 또는 저녁 혈당값이다. 공복 혈당이 높으면 전날 저녁식사, 그리고 저녁 후 간식(이하에서는 이를 ‘저녁식사’로 통합한다) 탄수화물 섭취를 줄이는 것이 좋다. 취침전 혈당값이 높으면 점심, 그리고 저녁식사 탄수화물 섭취를 줄이는 것이 좋다. Basically, fasting blood sugar and blood sugar before bedtime are short-term morning or evening blood sugar values. If fasting blood sugar is high, it is recommended to reduce carbohydrate intake the night before and after dinner (hereafter referred to as 'dinner'). If your blood sugar level before bedtime is high, it is recommended to reduce your carbohydrate intake at lunch and dinner.
이에 따라 탄수화물 분배 모듈(322d)은 정상상태에서 아침, 점심, 저녁의 탄수화물 섭취비율인 T1 : T2 : T3를 기준값으로 공복 혈당값이 기준 공복 혈당값을 초과하는 경우 기준 저녁혈당값(T3) 미만의 저녁식사 섭취비율을 설정할 수 있다. 취침전 혈당값이 기준 취침전 혈당값을 초과하는 경우 기준 점심혈당값(T2) 미만의 점심식사 섭취비율, 그리고 기준 저녁혈당값(T3) 미만의 저녁식사 섭취비율을 설정할 수 있다. 공복 혈당값이 기준 공복 혈당값을 초과하고 취침전 혈당값이 기준 취침전 혈당값을 초과하는 경우 기준 공복 혈당값(T3) 이하의 저녁 섭취비율과 기준 점심혈당값(T2) 이하의 점심 섭취비율을 동시에 설정할 수 있다. Accordingly, the carbohydrate distribution module 322d sets the standard value of T1: T2: T3, which is the carbohydrate intake ratio of breakfast, lunch, and dinner in the normal state, and when the fasting blood glucose value exceeds the reference fasting blood glucose value, the reference evening blood glucose value (T3) is less than You can set the dinner intake ratio of When the pre-bedtime blood glucose value exceeds the reference pre-bedtime blood glucose value, the lunch meal intake ratio less than the reference lunch blood sugar value (T2) and the dinner intake ratio less than the reference dinner blood sugar value (T3) may be set. When the fasting blood glucose value exceeds the reference fasting blood glucose value and the pre-bedtime blood glucose value exceeds the reference pre-bedtime blood glucose value, the ratio of dinner intake below the reference fasting blood glucose value (T3) and the lunch intake rate below the reference lunch blood glucose value (T2) can be set at the same time.
탄수화물 분배 모듈(322d)은 정상상태에서 아침, 점심, 저녁 탄수화물 섭취비율인 T1 : T2 : T3 = 1 : 1 : 1인 경우, 공복 혈당 > 기준 공복 혈당인 경우 1 : 1 : 0.7로 설정할 수 있으며, 취침전 혈당 > 기준 취침전 혈당인 경우 1 : 0.8 : 0.8로 설정할 수 있으며, 공복 혈당 > 기준 공복 혈당, 그리고 취침전 혈당 > 기준 취침전 혈당인 경우 0.9 : 0.7 : 0.7로 설정할 수 있다. The carbohydrate distribution module 322d can be set to 1: 1: 0.7 in the case of T1: T2: T3 = 1: 1: 1, which is the breakfast, lunch, and dinner carbohydrate intake ratio in the normal state, and when fasting blood sugar > standard fasting blood sugar. , blood sugar before bedtime > reference blood sugar before bedtime can be set to 1: 0.8: 0.8, and when fasting blood sugar > reference fasting blood sugar, and blood sugar before bed > reference blood sugar before bedtime can be set to 0.9: 0.7: 0.7.
식품 추천 모듈(322e)은 배분된 탄수화물 포인트 매칭 식품을 빅데이터 서버(400)를 기반으로 검색하여 검색된 매칭 식품을 포인트 값과 함께 네트워크(200)를 통해 스마트 디바이스(100)로 전송하도록 송수신부(310)를 제어할 수 있다. 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.
식품 추천 모듈(322e)은 식품당 탄수화물 포함 칼로리를 포인트 변환비율로 전환시킨 뒤, 아침, 점심, 저녁 별 포인트 적합한 식품 또는 식품 조합을 생성한 뒤, 네트워크(200)를 통해 스마트 디바이스(100)로 전송하도록 송수신부(310)를 제어할 수 있다. 예를 들어, 당뇨 관리 모듈(322)은 사과 1개의 전체 칼로리 중 탄수화물 칼로리가 60kcal인 경우 1 포인트로 전환하여 전환된 포인트에 해당하는 식품명을 네트워크(200)를 통해 스마트 디바이스(100)로 제공할 수 있다. The food recommendation module 322e converts carbohydrate-containing calories per food into a point conversion ratio, and then creates a food or food combination suitable for each point for breakfast, lunch, and dinner, and then sends it to the smart device 100 through the network 200 The transceiver 310 may be controlled to transmit. For example, the diabetes management module 322 converts to 1 point when carbohydrate calories among the total calories of one apple are 60 kcal and provides the food name corresponding to the converted point to the smart device 100 through the network 200. can
일 실시예로, 영양평가 결과 하루에 필요한 탄수화물이 9포인트이고, 사용자가 음식을 사과 1개, 밥 2/3공기, 불고기, 쌈채소, 김치, 두부 조림 1/4모 입력을 한다고 가정한다. 알고리즘을 통해 사과 1개는 1포인트, 밥 2/3공기는 2포인트, 두부조림 0.5포인트, 불고기 0.5포인트가 계산되므로, 식사를 통해 4포인트를 섭취한 것을 알 수 있다(참고로 김치와 쌈채소는 0 포인트로 산정한다). In one embodiment, as a result of the nutritional evaluation, it is assumed that the carbohydrate required per day is 9 points, and the user inputs 1 apple, 2/3 bowl of rice, bulgogi, ssam vegetables, kimchi, and 1/4 simmered tofu. The algorithm calculates 1 point for one apple, 2 points for 2/3 bowl of rice, 0.5 points for stewed tofu, and 0.5 points for bulgogi, so you can see that you ate 4 points through your meal (for reference, kimchi and ssam vegetables) is counted as 0 points).
그러면 사용자는 나머지 식사를 통해 5포인트를 사용할 수 있음을 예상할 수 있고 앱을 통해서 음식을 검색함으로써 각 식품, 그리고 음식의 포인트를 미리 예측할 수 있다. 이에 따라, 탄수화물 섭취를 조절하는 식이요법을 사용자 스스로 시행할 수 있으므로, 사용자는 혈당 관리에 도움을 받을 수 있다. Then, the user can predict that 5 points can be used through the rest of the meal, and by searching for food through the app, each food and the points of each food can be predicted in advance. Accordingly, since the user can implement a diet for controlling carbohydrate intake by himself/herself, the user may receive help in managing blood sugar.
다음으로, 당뇨 관리 코칭 모듈(323)은 AI 플랫폼을 기반으로 사용자 케이스별 혈당 관리 방법에 대한 지속적인 학습과 데이터 누적을 통해 과학적이고 체계적인 개인 맞춤형 당뇨관리 코칭을 월 2회 보고서, 그리고 맞춤형 1:1 당뇨 관리 코칭을 네트워크(200)를 통해 사용자 디바이스(100)로 제공하도록 송수신부(310)를 제어할 수 있다. 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 .
예를 들어, 당뇨 관리 코칭 모듈(323)은 개인 맞춤형 당뇨관리 코칭 서비스로 제공되는 월 2회의 보고서는 혈당수치, 혈압, 몸무게, 운동량, 그리고 활동량 데이터를 스마트 디바이스(100)와 근거리 무선통신으로 연결된 각종 측정 디바이스로부터 획득할 수 있으며, 누적된 데이터에 대해서 빅데이터 기반으로 문제점을 도출하여 보고서 형식으로 사용자에게 제공할 수 있다. For example, the diabetes management coaching module 323 reports twice a month that is provided as a personalized diabetes management coaching service. It connects the blood sugar level, blood pressure, weight, exercise amount, and activity data to the smart device 100 through short-distance wireless communication. It can be obtained from various measurement devices, and problems can be derived based on big data for accumulated data and provided to users in the form of a report.
식품별 포인트 제공 모듈(324)은 빅데이터 서버(400)에 구비된 빅데이터에 해당하는 영양성분표를 활용하여, 스마트 디바이스(100) 사용자의 편의성을 높이기 위해, 사용자 스마트 디바이스(100)로부터 탄수화물 포인트를 통한 검색 요청에 따라, 탄수화물 포인트를 네트워크(200)를 통해 빅데이터 서버(400)로 전송한다. 그 후, 식품별 포인트 제공 모듈(324)은 빅데이터 서버(400)로부터 탄수화물 포인트에 매칭되는 식품 또는 식품 조합 정보를 반환받아, 스마트 디바이스(100)로 전송하도록 송수신부(310)를 제어할 수 있다. The point providing module 324 for each food utilizes the nutritional information table corresponding to the big data provided in the big data server 400 to increase the convenience of the smart device 100 user, and the carbohydrate from the user smart device 100 According to the search request through the points, the carbohydrate points are transmitted to the big data server 400 through the network 200 . Thereafter, the food-specific point providing module 324 may control the transceiver 310 to receive food or food combination information matching the carbohydrate point from the big data server 400 and transmit it to the smart device 100 . have.
병원 정보 제공 모듈(325)은 사용자 스마트 디바이스(100)의 위치 정보를 기반으로 당뇨병 평가 우수 병원에 대한 검색 기능을 제공할 수 있다. 여기서, 병원 정보 제공 모듈(325)은 당뇨병 평가 우수 병원에 대한 정보에 대해서 빅데이터 서버(400)에 저장된 대한민국의 건강보험심사평가원에서 제공한 정보를 활용할 수 있다. 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 information provided by the Health Insurance Review and Assessment Service of the Republic of Korea stored in the big data server 400 for information on excellent diabetes evaluation hospitals.
일 실시예에 따른 당뇨 관리 식이 요법 제공 방법은, 스마트 디바이스 상에서 당뇨식 매니저 앱에 대한 실행에 따라 네트워크를 통해 스마트 디바이스와 신호, 그리고 데이터 송수신을 통해 수집된 스마트 디바이스의 단말식별번호를 메타데이터로 회원 ID, 회원 비밀번호, 사용자 개인정보를 "회원 정보 단위"로 저장하는 단계, 그리고 사용자 개인정보에 포함된 당화혈색소 값을 기초로 개인별 탄수화물 요구량에 대한 탄수화물 : 단백질 : 지방 비율을 산정하고, 산정된 탄수화물 요구량을 검출하는 단계를 포함한다.Diabetes management diet providing method according to an embodiment, according to the execution of the diabetes manager app on the smart device, the smart device and the signal through the network, and the terminal identification number of the smart device collected through data transmission and reception as metadata member Storing ID, member password, and user personal information as a “member information unit”, and calculating the carbohydrate:protein:fat ratio for each individual carbohydrate requirement based on the glycated hemoglobin value included in the user’s personal information, and calculating the calculated carbohydrate detecting the demand.
"회원 정보 단위"로 저장하는 단계는 정보 수집 모듈(321)에 의해 수행되며, 정보 수집 모듈(321)에 대한 설명은 전술한 것과 같다.The step of storing the "member information unit" is performed by the information collection module 321, and the description of the information collection module 321 is the same as described above.
탄수화물 요구량을 검출하는 단계는 당뇨 관리 모듈(322)에 의해 수행되며, 당뇨 관리 모듈(322)에 대한 설명은 전술한 것과 같다. 또한, 당뇨 관리 모듈(322)은 개인별 일일 칼로리 산출 모듈(322a), 탄수화물 비율 산출 모듈(322b), 탄수화물 포인트 산출 모듈(322c), 탄수화물 분배 모듈(322d), 그리고 식품 추천 모듈(322e)을 포함할 수 있다.The step of detecting the carbohydrate requirement is performed by the diabetes management module 322, and the description of the diabetes management module 322 is the same as described above. In addition, 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. can do.
일 실시예에 따른 당뇨 관리 식이 요법 제공 방법은, AI 플랫폼을 기반으로 사용자 케이스별 혈당 관리 방법에 대한 지속적인 학습과 데이터 누적을 통해 과학적이고 체계적인 개인 맞춤형 당뇨관리 코칭을 월 2회 보고서, 그리고 맞춤형 1:1 당뇨 관리 코칭을 네트워크(200)를 통해 사용자 디바이스(100)로 제공하는 단계를 포함할 수 있다. 이러한 단계는 당뇨 관리 코칭 모듈(323)에 의해 수행되며, 당뇨 관리 코칭 모듈(323)에 대한 설명은 전술한 것과 같다.A method of providing a diabetes management diet according to an embodiment is a scientific and systematic personalized diabetes management coaching report twice a month through continuous learning and data accumulation of blood sugar management methods for each user case based on an AI platform, and customized 1 It may include providing 1:1 diabetes management coaching to the user device 100 through the network 200 . These steps are performed by the diabetes management coaching module 323, and the description of the diabetes management coaching module 323 is the same as described above.
일 실시예에 따른 당뇨 관리 식이 요법 제공 방법은, 탄수화물 포인트를 네트워크(200)를 통해 빅데이터 서버(400)로 전송한 후, 빅데이터 서버(400)로부터 탄수화물 포인트에 매칭되는 식품 또는 식품 조합 정보를 반환받아, 스마트 디바이스(100)로 전송하는 단계를 포함할 수 있다. 이러한 단계는 식품별 포인트 제공 모듈(324)에 의해 수행되며, 식품별 포인트 제공 모듈(324)에 대한 설명은 전술한 것과 같다.Diabetes management diet providing method according to an embodiment, after transmitting the carbohydrate point to the big data server 400 through the network 200, food or food combination information matching the carbohydrate point from the big data server 400 may include the step of receiving a return and transmitting it to the smart device 100 . These steps are performed by the food-specific point providing module 324, and the description of the food-specific point providing module 324 is the same as described above.
일 실시예에 따른 당뇨 관리 식이 요법 제공 방법은, 사용자 스마트 디바이스(100)의 위치 정보를 기반으로 당뇨병 평가 우수 병원에 대한 검색 기능을 제공하는 단계를 포함할 수 있다. 이러한 단계는 병원 정보 제공 모듈(325)에 의해 수행되며, 병원 정보 제공 모듈(325)에 대한 설명은 전술한 것과 같다.The method of providing a diabetes management diet according to an embodiment may include providing a search function for a diabetes evaluation excellent hospital based on location information of the user's smart device 100 . These steps are performed by the hospital information providing module 325, and the description of the hospital information providing module 325 is the same as described above.
일 실시예는 또한 컴퓨터로 읽을 수 있는 기록매체에 컴퓨터가 읽을 수 있는 코드로서 구현하는 것이 가능하다. 컴퓨터가 읽을 수 있는 기록매체는 컴퓨터 시스템에 의하여 읽혀질 수 있는 데이터가 저장되는 모든 종류의 기록 장치를 포함한다. An embodiment may also be implemented as computer-readable code 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.
컴퓨터가 읽을 수 있는 기록매체의 예로는 ROM, RAM, CD-ROM, 자기테이프, 플로피 디스크, 광 데이터 저장장치 등이 있으며, 또한 캐리어 웨이브(예를 들어, 인터넷을 통한 전송)의 형태로 구현되는 것도 포함한다. 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
또한 컴퓨터가 읽을 수 있는 기록매체는 네트워크로 연결된 컴퓨터 시스템에 분산되어, 분산방식으로 컴퓨터가 읽을 수 있는 코드가 저장되고 실행될 수 있다. 그리고 일 실시예를 구현하기 위한 기능적인(functional) 프로그램, 코드, 그리고 코드 세그먼트들은 본 발명이 속하는 기술 분야의 프로그래머들에 의해 용이하게 추론될 수 있다. 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. In addition, functional programs, codes, and code segments for implementing an embodiment can be easily inferred by programmers in the technical field to which the present invention pertains.
이상과 같이, 본 명세서와 도면에는 본 발명의 바람직한 실시예에 대하여 개시하였으며, 비록 특정 용어들이 사용되었으나, 이는 단지 본 발명의 기술 내용을 쉽게 설명하고 발명의 이해를 돕기 위한 일반적인 의미에서 사용된 것이지, 본 발명의 범위를 한정하고자 하는 것은 아니다. 여기에 개시된 실시예 외에도 본 발명의 기술적 사상에 바탕을 둔 다른 변형 예들이 실시 가능하다는 것은 본 발명이 속하는 기술 분야에서 통상의 지식을 가진 자에게 자명한 것이다.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 contents of the present invention and to help the understanding of the present invention. , it is not intended to limit the scope of the present invention. It is 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.

Claims (7)

  1. 스마트 디바이스 상에서 당뇨식 매니저 앱에 대한 실행에 따라 네트워크를 통해 상기 스마트 디바이스와 신호, 그리고 데이터 송수신을 통해 수집된 상기 스마트 디바이스의 단말식별번호를 메타데이터로 회원 ID, 회원 비밀번호, 사용자 개인정보를 "회원 정보 단위"로 저장하는 정보 수집 모듈, 그리고According to the execution of the diabetes manager app on the smart device, the terminal identification number of the smart device collected through the transmission and reception of data and signals with the smart device through the network is converted to the member ID, member password, and user personal information as metadata. an information collection module that stores it in "information units; and
    상기 사용자 개인정보에 포함된 당화혈색소 값을 기초로 개인별 탄수화물 요구량에 대한 탄수화물 : 단백질 : 지방 비율을 산정하고, 산정된 탄수화물 요구량을 검출하는 당뇨 관리 모듈A diabetes management module that calculates the 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
    을 포함하는 식이요법 관리 서버를 구비한 당뇨 관리 식이 요법 제공 시스템. Diabetes management diet providing system having a diet management server comprising a.
  2. 제1항에서,In claim 1,
    상기 당뇨 관리 모듈은,The diabetes management module,
    상기 산정된 탄수화물 요구량을 포인트로 전환하고, 전환된 상기 포인트에 매칭되는 식품, 그리고 식품 조합 정보를 상기 네트워크를 통해 상기 스마트 디바이스로 제공하는 당뇨 관리 식이요법 제공 시스템. A diabetes management diet providing system that converts the calculated carbohydrate requirement into points, and provides food and food combination information matching the converted points to the smart device through the network.
  3. 제2항에서,In claim 2,
    상기 당뇨 관리 모듈은,The diabetes management module,
    끼니별 탄수화물 포인트 배분을 수행하며, 기준 혈당값과 "회원 정보 단위"에서 공복 혈당값 및 취침전 혈당값을 추출하여 비교하는 당뇨 관리 식이요법 제공 시스템. A diabetes management diet providing system that distributes carbohydrate points for each meal and extracts and compares standard blood sugar values and fasting blood sugar values and blood sugar values before bedtime from “member information unit”.
  4. 제3항에서,In claim 3,
    상기 당뇨 관리 모듈은,The diabetes management module,
    정상상태에서 아침, 점심, 그리고 저녁의 탄수화물 섭취비율인 T1 : T2 : T3을 기준 값으로 산정하고, 상기 공복 혈당값이 미리 설정된 기준 공복 혈당값을 초과하는 경우, T3 미만의 저녁 탄수화물 섭취비율을 설정하는 당뇨 관리 식이요법 제공 시스템. In the normal state, T1: T2: T3, which is the carbohydrate intake ratio for breakfast, lunch, and dinner, is calculated as a reference value, and when the fasting blood sugar value exceeds a preset reference fasting blood sugar value, the evening carbohydrate intake ratio less than T3 is calculated. Setting up a diabetes management diet delivery system.
  5. 제4항에서,In claim 4,
    상기 당뇨 관리 모듈은,The diabetes management module,
    상기 취침전 혈당값이 미리 설정된 기준 취침전 혈당값을 초과하는 경우, T2 미만의 점심, 그리고 T3 미만의 저녁 탄수화물 섭취비율을 설정하는 당뇨 관리 식이요법 제공 시스템When the pre-bedtime blood sugar value exceeds a preset reference pre-bedtime blood sugar value, a diabetes management diet providing system that sets the rate of carbohydrate intake for lunch less than T2 and dinner less than T3
  6. 제5항에서,In claim 5,
    상기 당뇨 관리 모듈은,The diabetes management module,
    상기 공복 혈당값이 상기 기준 공복 혈당값을 초과하고 상기 취침전 혈당값이 상기 기준 취침전 혈당값을 초과하는 경우, T3 미만의 저녁 탄수화물 섭취비율, 그리고 T2 이하의 점심 탄수화물 섭취비율을 동시에 설정하는 당뇨 관리 식이요법 제공 시스템. When the fasting blood glucose value exceeds the reference fasting blood glucose value and the pre-bedtime blood glucose value exceeds the reference pre-bedtime blood glucose value, a dinner carbohydrate intake ratio less than T3 and a lunch carbohydrate intake ratio less than or equal to T2 are simultaneously set Diabetes Management Dietary Delivery System.
  7. 스마트 디바이스 상에서 당뇨식 매니저 앱에 대한 실행에 따라 네트워크를 통해 상기 스마트 디바이스와 신호, 그리고 데이터 송수신을 통해 수집된 상기 스마트 디바이스의 단말식별번호를 메타데이터로 회원 ID, 회원 비밀번호, 사용자 개인정보를 "회원 정보 단위"로 저장하는 단계, 그리고According to the execution of the diabetic manager app on the smart device, the terminal identification number of the smart device collected through the transmission and reception of data and signals with the smart device through the network is converted to the member ID, member password and user personal information as metadata storing in "units of information"; and
    상기 사용자 개인정보에 포함된 당화혈색소 값을 기초로 개인별 탄수화물 요구량에 대한 탄수화물 : 단백질 : 지방 비율을 산정하고, 산정된 탄수화물 요구량을 검출하는 단계Calculating a carbohydrate:protein:fat ratio for each individual carbohydrate requirement based on the glycated hemoglobin value included in the user's personal information, and detecting the calculated carbohydrate requirement
    를 포함하는 당뇨 관리 식이 요법 제공 방법.A method of providing a diabetes management diet comprising:
PCT/KR2020/009662 2019-12-13 2020-07-22 System and method for providing dietetic therapy for diabetes management WO2021118002A1 (en)

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