WO2021118002A1 - Système et procédé permettant de fournir une thérapie diététique pour la gestion du diabète - Google Patents

Système et procédé permettant de fournir une thérapie diététique pour la gestion du diabète 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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WIPO (PCT)
Prior art keywords
carbohydrate
diabetes management
diabetes
blood sugar
smart device
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PCT/KR2020/009662
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English (en)
Korean (ko)
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김은형
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주식회사 메디푸드랩
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Publication of WO2021118002A1 publication Critical patent/WO2021118002A1/fr

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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

La présente invention concerne un système permettant de fournir une thérapie diététique pour la gestion du diabète, ledit système comprenant un module de collecte d'informations et un module de gestion du diabète, et permettant de gérer professionnellement une thérapie diététique pour la gestion du diabète par régulation de l'absorption des glucides. Le système fournit une thérapie diététique ponctuelle pour la gestion de la glycémie d'un patient diabétique (y compris un patient prédiabétique), et un accompagnement individualisé à base d'intelligence artificielle en tant que services majeurs, et permet en outre la gestion intégrée de facteurs liés au diabète, tels que le poids, la pression sanguine et l'exercice, par l'intermédiaire d'une seule application, et augmente donc la commodité de gestion de la glycémie et peut empêcher des complications du diabète.
PCT/KR2020/009662 2019-12-13 2020-07-22 Système et procédé permettant de fournir une thérapie diététique pour la gestion du diabète WO2021118002A1 (fr)

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KR20160061017A (ko) * 2014-11-21 2016-05-31 주식회사 메디플러스솔루션 환자 맞춤형 정보 제공 시스템
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KR20170109449A (ko) * 2016-03-21 2017-09-29 하나텍플러스 주식회사 애플리케이션 기반의 개인별 건강 분석에 따른 영양 관리 시스템 및 그 방법
KR20190069641A (ko) * 2017-11-30 2019-06-20 김슬기 사용자 식단 관리 서버 및 그것의 식단 정보 생성 방법

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Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2013097403A (ja) * 2011-10-27 2013-05-20 Rapix Laboratories Co Ltd 生活習慣解析システム及び生活習慣解析方法
KR20160061017A (ko) * 2014-11-21 2016-05-31 주식회사 메디플러스솔루션 환자 맞춤형 정보 제공 시스템
KR20160109510A (ko) * 2015-03-11 2016-09-21 에스디 바이오센서 주식회사 당뇨환자를 위한 혈당 관리 장치 및 혈당 관리 방법
KR20170109449A (ko) * 2016-03-21 2017-09-29 하나텍플러스 주식회사 애플리케이션 기반의 개인별 건강 분석에 따른 영양 관리 시스템 및 그 방법
KR20190069641A (ko) * 2017-11-30 2019-06-20 김슬기 사용자 식단 관리 서버 및 그것의 식단 정보 생성 방법

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