WO2017116003A1

WO2017116003A1 - Method for recommending, to user with diabetes symptoms, food personalized with consideration for amount of exercise

Info

Publication number: WO2017116003A1
Application number: PCT/KR2016/013164
Authority: WO
Inventors: 최승혁; 차근식; 남학현
Original assignee: 주식회사 아이센스
Priority date: 2015-12-30
Filing date: 2016-11-15
Publication date: 2017-07-06
Also published as: KR20170080867A; CN108352191A; KR101807853B1

Abstract

The present invention relates to a method for providing, to a user with diabetes symptoms, information on recommended food or food that should be avoided, and provides a food recommending method capable of: determining, on the basis of a user's food consumption amount, food type, blood sugar level, and amount of exercise, information on recommended food, or food that should be avoided, which is personalized to the user, so as to provide the same to the user; and providing information on recommended food, or food which should be avoided, which is personalized to the user, even from a menu comprising a plurality of foods.

Description

Personalized Food Recommendations Considering Exercise Level for Users with Diabetes Symptoms

The present invention relates to a method for providing information on recommended foods or foods to be avoided to a user with diabetic symptoms. The present invention relates to recommended foods or foods to be avoided that are personalized to the user based on the amount of meals, food types, blood sugar values, and exercise amount of the user. The information is determined and provided to the user, and even in a diet consisting of a plurality of foods, the food recommendation method may be provided to the user to provide information about personalized recommended foods or foods to be avoided.

Diabetes is an absolute or relative lack of insulin produced by the pancreas due to various causes, such as obesity, stress, poor eating habits, and hereditary inheritance, resulting in increased glucose levels in the blood and the detection of glucose in the urine, thereby causing acute and chronic It is a chronic degenerative disease that causes complications. Diabetes is rapidly increasing worldwide, and Korea is no exception, according to a 2013 report by the Korean Diabetes Association. It is estimated that 12.4% of the population over 30 years of age is diabetic and has about 4 million patients.

Diabetes is not a problem but a complication caused by it. Therefore, the goal of diabetes treatment is to control blood glucose as close to normal as possible to relieve symptoms caused by hyperglycemia and ultimately to prevent diabetic chronic complications and to delay the exacerbation. For successful glycemic control, it is necessary to know exactly the target level of glycemic control and frequently check how close your blood sugar level is to the target level, and accordingly, manage your lifestyle with proper diet, exercise and medication.

Currently, many medical device manufacturers provide various types of portable blood glucose meters to measure blood glucose levels at home, and diabetics can easily measure their own blood sugar on their own. On the other hand, life management such as meal therapy and exercise therapy for blood sugar management are mainly provided through educational programs of medical institutions, such as diabetes classes in hospitals, and the effectiveness of the management varies greatly depending on the understanding and skill of individual patients.

Especially in the case of the most important dietary therapy for blood sugar management, not only the variety of foods but also the same ingredients, depending on the degree of cooking and cooking method, since the difference in the effect of increasing blood sugar has a large difference in the amount of food and meal suitable for the early diabetics In addition, they have to spend a lot of time and trial and error before learning the proper amount of exercise according to their diet.

Existing efforts to remedy these difficulties include using food exchange tables first. The food exchange table categorizes the foods generally consumed into six food groups: cereal, fish, vegetable, fat, milk, and fruit, according to nutrients. It can be used freely in the same food group to help diabetics manage balanced nutrition and total calorie intake.

However, the food exchange table is defined mainly on food ingredients, and it is difficult to accurately consider the difference in cooking methods or the type and amount of sugar because only the total intake calories is taken into account, and it is difficult to control blood sugar according to the amount of exercise because the amount of exercise is not taken into account. .

As a way of supplementing the weak points of the food exchange table based on the total calories intake, there is a method of calculating the sugar. Glucose counting method calculates only the amount of sugar in the intake of the food has the advantage of allowing a meal plan that focuses on the intake of the sugar that determines the post-prandial blood sugar rather than the overall calories. However, this method also emphasizes only the total intake of the sugar, there is a limit that does not consider the absorption rate according to the type of sugar, this method also has a problem that it is difficult to control the blood sugar according to the exercise amount in consideration of the exercise amount.

Above all, all of the above-mentioned methods are common to many diabetic patients, and they are calculated from the viewpoint of ingredients or only some of the representative diets. Not only is it difficult, but also because the same food has a different effect on the blood sugar level according to the individual, there is a problem that does not provide a blood sugar control method considering the amount of information and exercise information about the good food and food to avoid to personalize to the user.

The present invention is to solve the problem of the method of recommending the type of food to the user with a conventional diabetic symptoms, the object of the present invention to be personalized to the user considering the amount of exercise of the user recommended food or food to avoid It is to provide a way to provide information about.

Another object of the present invention is to provide a method for providing a user with a personalized recommended food or information on foods to be avoided based on foods that meet or exceed a target blood sugar value based on the target blood sugar value. .

Another object of the present invention is to provide a method for determining a recommended or avoided food and providing information about a personalized recommended food type or a food to be avoided to the user even in a diet consisting of a plurality of foods.

In order to achieve the object of the present invention, the personalized food recommendation method according to the present invention comprises the steps of registering the user's blood sugar value, the user's food intake and food type, the amount of exercise mapping each other, the user's blood sugar value and target Comparing the blood sugar value and determining whether the blood sugar state is normal blood sugar state or abnormal blood sugar state based on whether the user's blood sugar value exceeds the target blood sugar value, and classifies the determined blood sugar state based on the amount of meal or exercise Generating information about the recommended food type or food type to be avoided, and providing the user with information about the personalized recommended food type or food type to be avoided.

Here, the blood sugar value of the user may be a difference between the pre-preparation blood sugar value and the post-prandial blood sugar value, or the blood sugar value measured by the user after meals.

The information on the amount of meal or information on the amount of exercise is divided into a meal amount level or exercise amount level is registered and stored, the meal amount level is characterized in that the user selects based on the subjective meal amount that the individual feels different for each user.

Preferably, the generating of the information on the recommended food type personalized to the user may include generating, as the information on the food type to be recommended to the user, a food type in which the meal amount is at a high level based on the meal amount and classified into a normal blood sugar state. It is done.

Preferably, the step of generating information about the recommended food type personalized to the user may include the food type divided by the normal blood sugar state and the meal amount and the exercise information of the corresponding food type divided by the normal blood sugar state. Characterized by generating information on the type of food.

Preferably, the step of generating information on the recommended type of food personalized to the user may be divided into normal blood glucose states from information on the blood sugar value of the user, the amount of meals of the user, the type of food, and the amount of exercise received for at least one unit period. Determining the highest exercise level from the meal level of the food type, and generating information about the food type to recommend to the user of the meal level and the highest exercise level from the meal level. It is done.

Preferably, the generating of the information on the recommended food type personalized to the user may include the amount of meals among the same food types from information on the blood sugar value of the user, the amount of meals of the user, the type of food, and the amount of exercise received for at least one unit period. The first step of judging the food types that are different from each other by the normal and abnormal blood glucose state, and the lowest level of the meal amount and exercise level of the meal type divided by the normal blood sugar state among the different food types Determining the meal amount level and the highest exercise level, and generating different types of food as information on the food types to be recommended to the user at the lowest meal level and the highest exercise level. do.

Personalized food like process according to the invention further comprises a step of calculating a food like value (R _i),

Create a number of food types set in the order of high food recommendation value as information about the food type to recommend to the user, or generate a number of food types set in the order of the lowest food recommendation value as information about the food type to be avoided by the user. It is characterized by.

Preferably, the food recommendation value Ri is calculated by the following Equation (1),

[Equation 1]

Where n is the total number of unit times of food (i), a _p is a weight assigned to the meal level of food (i) per unit time on the basis of the normal or abnormal blood sugar state, b _p is It is characterized in that the weight is assigned to the exercise level for each unit time ingesting the food (i) on the basis of the normal blood sugar state or abnormal blood sugar state.

In the personalized food recommendation method according to the present invention, when the information on the searched food type to be searched by the user is received, the searched food type is normal blood sugar state or abnormal blood sugar among at least one or more unit timed food types stored in the database unit. Determining whether there is a unit time divided by the state, and information about the user's meal level or exercise level for the searched food type and the blood sugar level at the unit time where the searched food type is divided into a normal blood sugar state or an abnormal blood sugar state. And extracting the status information and generating recommendation information of the searched food type based on the meal amount information or the exercise amount information in unit time divided into a normal blood sugar state or an abnormal blood sugar state.

Preferably, the step of generating information on the types of foods to be avoided personalized to the user includes foods that are classified as abnormal blood sugar states and foods to be avoided by the user, including meal amounts and exercise information of the corresponding food types classified as abnormal blood sugar states. It is characterized by generating information about the kind.

According to the present invention, a personalized food recommendation method for a user with diabetes symptoms has the following effects.

First, the personalized food recommendation method according to the present invention provides information on foods to be recommended or foods to be avoided to the user based on food information directly ingested by the user, exercise type and amount of exercise performed by the user, and blood glucose state information. In addition, a user with diabetes symptoms may be provided with personalized food information and exercise information.

Secondly, the personalized food recommendation method according to the present invention may avoid or recommend personalized foods to the user based on food type, exercise amount, exercise type, and exercise amount satisfying or exceeding the target blood glucose value based on the target blood glucose value. By determining the food, the user with diabetes symptoms may be provided with food information and exercise information satisfying the set target blood glucose value.

Third, the personalized food recommendation method according to the present invention determines a common food that damages or assists the user's blood sugar management in a food combination consisting of a plurality of foods, thereby avoiding the recommended food or avoiding the user from the diet actually ingested by the user. Provide information about food.

1 is a functional block diagram illustrating a device for recommending food to a user with diabetes symptoms according to the present invention.

2 is a flow chart illustrating a method of personalized food recommendation to a user with diabetes symptoms in accordance with the present invention.

FIG. 3 is a diagram for explaining an example of registering and storing blood sugar related information in a database unit when blood sugar related information such as food type, meal amount, blood sugar value, and exercise amount ingested by a user is received from a user terminal.

FIG. 4 is a diagram for explaining an example in which blood glucose related information associated with each other is mapped and stored in a database unit.

FIG. 5 is a diagram illustrating an example of an interface of a user terminal for inputting a type of food or a meal ingested from blood sugar related information.

6 is a flowchart illustrating an embodiment of a method of generating information on a type of food recommended for a user according to the present invention.

7 is a flowchart illustrating a method of generating information on a type of food to be recommended to a user when the same type of food is differently classified into an abnormal blood sugar state and a normal blood sugar state.

8 is a view for explaining an example of the blood sugar state for each unit time according to the type of food and the amount of meal.

9 is a flowchart illustrating a step of generating food recommendation information whether a particular food type is recommended food to a user or food to be avoided by the user.

10 is a flowchart illustrating an example of generating recommendation information of a searched food type based on meal amount information in a unit time divided into a normal blood sugar state or an abnormal blood sugar state.

Technical terms used in the present invention are merely used to describe specific embodiments, it should be noted that it is not intended to limit the present invention. In addition, the technical terms used in the present invention should be interpreted as meanings generally understood by those skilled in the art unless the present invention has a special meaning defined in the present invention, and is excessively comprehensive. It should not be interpreted in the sense of or in the sense of being excessively reduced. In addition, when a technical term used in the present invention is an incorrect technical term that does not accurately express the spirit of the present invention, it should be replaced with a technical term that can be properly understood by those skilled in the art.

Also, the singular forms used in the present invention include plural forms unless the context clearly indicates otherwise. In the present invention, terms such as “consisting of” or “comprising” are not to be construed as necessarily including all of the various components or steps described in the invention, and some of the components or some of the steps are included. It should be construed that it may not be, or may further include additional components or steps.

In addition, it should be noted that the accompanying drawings are only for easily understanding the spirit of the present invention and should not be construed as limiting the spirit of the present invention by the accompanying drawings.

Hereinafter, a method of recommending food to a user with diabetes symptoms according to the present invention will be described in more detail with reference to the accompanying drawings.

Referring to FIG. 1 in more detail, the transceiver 110 receives blood sugar related information such as blood sugar information of the user, amount of food ingested by the user, food type, exercise amount, exercise type, and the like. The blood sugar related information may be input through a user terminal possessed by the user, for example, a smartphone, and the input blood sugar related information may be received from the user terminal. Preferably, the user possesses a measuring device for measuring the exercise amount of the user, the information on the exercise amount of the user may be received directly from the measuring device or the exercise amount information measured by the measuring device may be received via a smartphone. The food recommendation apparatus according to the present invention is described as a server for receiving blood sugar related information from a user terminal and recommending personalized food to a user, but the food recommendation apparatus according to the present invention is registered in a user terminal according to the field to which the present invention is applied. It is possible to recommend a personalized food to the user in the user terminal itself through a program that is within the scope of the present invention.

The blood sugar information may be a target blood sugar value or a user's blood sugar value. The blood sugar value of the user may be a blood sugar value measured after a meal by a user, or a difference value between a blood sugar value measured by a user before a meal and a blood sugar value measured after a meal. In addition, the target blood sugar value defines a blood sugar value suitable for a user, and generally uses a single target blood sugar value, but may be set to have a plurality of target blood sugar values or a predetermined range. In the present invention, the target blood glucose value may be set by the user by directly inputting or modifying the user terminal. However, according to the field to which the present invention is applied, the target blood sugar value may be preset according to the user's physical state. Corresponds to the present invention.

The registration manager 130 may input the blood sugar information, the ingested food amount, the exercise amount, based on the blood sugar value, the ingested food amount, the food type, the target blood sugar value, the exercise amount, the exercise type, and the like. The information on the type of exercise is mapped to the user, and the blood glucose is measured and stored in the database unit 150 by mapping the date and time. Preferably, the intake of the meal amount can be registered and stored in a simple level such as the upper, middle, lower level according to the amount of meal or the user's exercise amount can be registered and stored in a simple level such as the upper, middle, lower level, etc. .

Here, the simple level classification for the meal amount may be input by the user through a user interface, or the amount of meals mapped to the intake calories converted from the information on the amount of meals input by the registration management unit 130 into quantified intake calories. Registration can be saved as a level. For example, when a user ingests 1 air of rice, the user may personalize the amount of meal subjectively felt by the user according to the user's eating habits or physical condition through the user interface and input the level into one of the upper, middle, and lower levels. have. As another example, the quantitative calories for the rice cooked in the registration management unit 130 and the amount of meals are mapped in advance and are registered in advance. When the user inputs the rice cooked air, the calorized calories for the rice cooked air (for example, , 100 kcal) and the amount of meal level 'middle' mapped thereto may be registered and stored.

Here, the simple level classification for the amount of exercise may be input by the user to select through the user interface, or change the information on the amount of exercise input from the registration management unit 130 into the quantified consumption calories and the amount of exercise mapped to the converted calories Registration can be saved as a level. For example, if the exercise type is walking, 20 minutes or less, 20 minutes or more, 40 minutes or less, 40 minutes or more are divided into 20 minutes or less, the exercise level is mapped to the lower level, 20 minutes or more, 40 minutes or less if the exercise level is medium The level is mapped to the level, and if it is 40 minutes or more, the exercise level is mapped to the upper level.

As an example, when the user walks for 60 minutes, the user may directly input the exercise amount information into upper, middle, and lower levels of the user through the user interface according to the user's physical condition. As another example, the quantitative consumption calories for 60 minutes of walking exercise and the amount of exercise level are mapped in advance and registered in the registration management unit 130. When the user inputs 60 minutes of walking exercise, the user quantifies 60 minutes of walking exercise. The information on the amount of exercise of the user may be registered and stored at the consumed calories (for example, 100 kcal) and the amount of exercise mapped thereto. As another example, the user may input the personalized exercise information that the user feels subjectively according to his / her physical condition to any one of the upper, middle, and lower levels.

In this way, the user directly inputs the user's meal level or exercise level, which is different for each user according to the user's physical condition, eating habits, and the like, and determines recommended foods or foods to avoid based on the input meal level or exercise level, thereby personalizing the user. Information about recommended foods or foods to be avoided can be easily and accurately generated.

In the present invention, the blood sugar-related information may be input together with a bundle of related information such as blood sugar value, meal amount, food type, exercise amount, exercise type, etc. Preferably, the time of eating food or the time of measuring blood sugar value, exercise Each of the times when the execution is completed may be divided and input together with date and time information. The registration manager 130 automatically maps and stores related information according to the date and time.

When the blood sugar value is received from the user terminal, the registration manager 130 compares the target blood sugar value registered with the received blood sugar value to determine the user's blood sugar state as either a normal blood sugar state or an abnormal blood sugar state. The information on the blood sugar state is mapped to the meal amount, the food type, and the exercise amount information and stored in the database unit 150.

When receiving a food recommendation request personalized to the user from the user terminal through the transceiver 110, the food information providing unit 170 registered and stored in the database unit 150, based on the amount of meal or exercise amount mapped blood sugar Based on the information about the status, information about the recommended food or food to be avoided personalized to the user is generated. In addition, when the food information providing unit 170 receives a request for inquiring whether a specific food type is a recommended food or a food to be avoided from the user terminal, the food information providing unit 170 generates the recommendation information for the specific food type as information on a personalized recommended food or food to be avoided. do.

The personalized recommendation food or information about the food to be avoided generated by the food information providing unit 170 is transmitted to the user terminal through the transceiver 110, the user personalized recommendation through the output unit provided in the user terminal Information about foods or foods to avoid can be queried.

Referring to Figure 2 in more detail, when receiving the blood sugar-related information such as food type, meal amount, blood sugar value, exercise amount, etc. the user ingested from the user terminal, the received blood sugar related information is registered and stored in the database unit (S100) ).

FIG. 3 illustrates an example of registering and storing blood sugar related information in a database unit when blood sugar related information such as food type, meal amount, blood sugar value, and exercise amount which a user ingests is received from the user terminal is illustrated in FIG. As such, the registration management unit receives blood sugar related information such as the type of food ingested at meal, the amount of meal, the blood sugar value measured after the meal, and the amount of exercise performed by the user after eating, when the user terminal receives the blood sugar related information by dividing by the received time or date. Information can be registered and stored in the database.

The blood sugar related information may be received from the user terminal at different times for each type. For example, information on the type or amount of food ingested by the user may be input immediately after a meal, and information on blood sugar values or exercise amount may be received after a meal. Two hours may be input at the time when blood glucose values are measured or when the exercise is completed, and the registration storage unit automatically maps the related blood sugar related information to each other and registers and stores them in the database unit. As shown in FIG. 4 (a), the information on blood glucose values and the amount of exercise received at 9:10 am on October 25, 2015 is the closest to the food type of the previously received 7:05 am breakfast. It is mapped and stored in the amount of meals and stored.

In the field to which the present invention is applied, a difference value between a pre-preparation blood sugar value and a post-prandial blood sugar value may be used as a blood sugar value. In this case, the registration management unit may directly receive a difference value between the pre-meal blood sugar value and the post-prandial blood sugar value from the user terminal. However, preferably, the pre-meal blood glucose value and the post-meal blood sugar value measured separately from the user terminal with measurement time information, respectively, and the registration management may automatically calculate and store the difference value in the process of mapping and storing the associated information. Figure 4 (b) is an example of blood sugar-related information stored in the database when the difference between the pre-preparation blood sugar value and post-prandial blood sugar value is used as the blood sugar value, the threshold time before and after the meal time, for example before meal time The measured blood glucose value received within 30 minutes and the measured blood sugar value received within 3 hours after mealtime are mapped to the pre-meal blood glucose value and the post-meal blood glucose value, respectively, to automatically calculate the difference between the pre-meal blood glucose value and the post-meal blood glucose value. Calculation is registered and stored.

Referring to FIG. 5, an example of an interface of a user terminal for inputting a food type or a meal amount of blood sugar related information is illustrated in FIG. 5A. For each type of food ingested, you can enter information about the amount of meal. In addition, as shown in FIG. 5 (b), the user may input all the combinations of food types eaten at a time.

Referring to FIG. 2 again, information about a recommended food type or a type of food to be avoided is generated from the information on the amount of registered meal, the amount of exercise, and the information on the blood sugar value of the user (S200). Here, by generating information on the type of food recommended to the user or the type of food to be avoided based on the information on the amount of meal and the amount of exercise, the user may consider both the amount of meal and the amount of exercise of the type of food ingested by the user, Create information about or create information about foods to avoid personalized to the user. In addition, instead of simply generating information about recommended foods or information about foods to be avoided based on simply the types of foods recommended or the types of foods to be avoided, specifically, the information on foods recommended, food levels of recommended foods, and foods of each recommended food should be performed. By generating information on the recommended food at the exercise amount level to be performed, the user may be provided with accurate and specific information about the amount of meal and the exercise amount according to the recommended food type.

In addition, since the food recommendation method personalized to the user according to the present invention generates information about recommended food or food to be avoided to the user based on the type of food directly ingested by the user or the amount of meal or exercise actually felt by the user, Information about recommended foods or foods to avoid, based on the amount of exercise and the amount of meals that the user mainly consumes, depending on the user's preferences, the amount of the user's meals, or the user's personal physical condition, or the exercise actually performed by the user. Can be obtained.

Preferably, based on the information on the amount of meals stored in the database unit, the amount of food is lower level and divided into abnormal blood sugar state is generated as food information to be avoided by the user irrespective of the amount of exercise.

Preferably, based on the information on the amount of the meal stored in the database unit, the amount of food is a high level and divided into normal blood sugar state is generated as food information to be recommended to the user regardless of the amount of exercise.

Preferably, based on the food recommendation value calculated from the blood sugar-related information stored in the database unit, the number of food types set in order of higher food recommendation values is generated as food type information to be recommended to the user, or the food recommendation value is low. The number of food types set in order may be generated as food type information to be avoided by the user.

Here, the food recommendation value Ri for the food i is calculated as in Equation 1 below.

[Equation 1]

Where n is the total number of times the food (i) is ingested, a _p is the weight assigned to the meal level when the food (i) is ingested based on the normal or abnormal blood glucose level, and b _p is the normal blood sugar level Or a weight assigned to an exercise amount level when the food (i) is ingested based on the abnormal blood glucose state.

Preferably, the blood sugar related information may be stored by dividing the blood sugar related information described in FIG. 4 again by unit time (for example, 1 day, 1 week, 1 month, etc.), and FIG. An example of related information is shown. In FIG. 9, the alphabet means food type.

Information about the recommended food type or the food type to be avoided personalized to the determined user is provided to the user terminal through the transceiver unit (S300).

Referring to FIG. 6, in more detail, blood glucose related information such as a user's meal amount, food type, blood sugar value, blood sugar state, and exercise amount is mapped and stored in the database unit, and blood sugar is stored among blood sugar related information stored in the database unit. Based on the state information, the food type associated with the normal blood sugar state is determined (S211).

A food type having a higher meal level is determined based on a meal amount among food types mapped to a normal blood sugar state (S213).

On the other hand, the highest amount of exercise level is determined at each meal level of the food type, rather than the upper level, based on the amount of meal among the food types mapped to the normal blood sugar state (S215). Food types with higher levels of food among the food types that are mapped to the normal blood glucose level are recommended for foods that are not related to exercise volume, and food types with medium or lower meals have the highest exercise level for each meal level. Generate information about (S217). That is, the information on the generated recommended food is provided to the user terminal and displayed. The food type mapped to normal blood sugar state recommends a food type having a higher level regardless of the exercise amount, or the food type mapped to normal blood sugar state. Food types with medium or low meals are recommended as the highest exercise level at each meal level.

The same food type may be determined to be a normal blood sugar state at some unit time in some unit time or to an abnormal blood sugar state at another unit time. In FIG. 7, the same food type is differently divided into an abnormal blood sugar state and a normal blood sugar state. If there is a flow chart for explaining how to generate information on the type of food to be recommended to the user.

Referring to Figure 7, from the information on the user's blood sugar value, the user's meal amount, food type, exercise amount received for at least one unit period from the same food type to the normal blood sugar state and abnormal blood glucose state based on the amount of meal First, the type of food that is different from each other is determined (S231). In FIG. 8, the food type H is divided into normal blood glucose states at unit times 2 and 3, but is classified as abnormal blood glucose states at unit times 1 and 4.

The lowest meal amount level and the highest exercise level are determined in the meal amount level and the exercise level of the food type divided into the normal blood sugar state among the food types having different blood sugar states (S233). Among the types of foods in which blood sugar levels are different from each other, the foods are generated as information on the types of foods to be recommended to the user at the lowest meal amount and the highest exercise level of the food types classified as normal blood sugar states (S235).

Referring to FIG. 9 in more detail, when information about a type of search food to be searched for by the user is received from the user terminal (S251), the searched food type is included in at least one or more unit time type foods stored in the database unit. It is determined whether there is a unit time divided into a normal blood sugar state or an abnormal blood sugar state (S253).

If there is a unit time in which the searched food type is divided into a normal blood sugar state or an abnormal blood glucose state, the user's meal level for the searched food type is determined in a unit time in which the searched food type is divided into a normal blood sugar state or an abnormal blood sugar state. Information on the activity level and information on the blood glucose level are extracted (S255).

The recommended information of the searched food type is generated based on the meal amount information or the exercise amount information in the unit time divided into the normal blood sugar state or the abnormal blood sugar state (S257).

Referring to FIG. 10, in more detail, it is determined whether the search food type has only a unit time divided by a normal blood sugar state (S271), and when there is only a unit time divided by a normal blood sugar state, The recommendation information is generated and provided to the user (S273). When the searched food type exists only in unit time divided into normal blood sugar states and is at a high level based on the amount of meals of the searched food type, the searched food type is generated as recommended food information regardless of the exercise amount. On the other hand, if the searched food type has only unit time divided into normal blood glucose states and is not a phase level based on the amount of food of the searched food type, the searched food at the meal level of the searched food type and the highest exercise level from the corresponding meal level The type is generated as food type information to be recommended to the user.

It is determined whether the search food type exists only in the unit time divided by the abnormal blood sugar state (S274), and when the search food type exists only in the unit time divided by the abnormal blood glucose state, the search food type is the food type information to be avoided by the user. It generates (S275).

On the other hand, it is determined whether there is a unit time in which the searched food type is divided into a normal blood sugar state and a unit time in which the searched food type is divided into an abnormal blood sugar state (S277). Unit time and unit time when the food type is classified as abnormal blood sugar state coexists Search for the lowest meal level and the highest exercise level at unit time classified as normal blood sugar state Food type to recommend to user Generate by type information (S279).

Meanwhile, the above-described embodiments of the present invention can be written as a program that can be executed in a computer, and can be implemented in a general-purpose digital computer which operates the program using a computer-readable recording medium.

The computer-readable recording medium may be a magnetic storage medium (for example, a ROM, a floppy disk, a hard disk, etc.), an optical reading medium (for example, a CD-ROM, DVD, etc.) and a carrier wave (for example, the Internet). Storage medium).

Although the present invention has been described with reference to the embodiments shown in the drawings, this is merely exemplary, and it will be understood by those skilled in the art that various modifications and equivalent other embodiments are possible. Therefore, the true technical protection scope of the present invention will be defined by the technical spirit of the appended claims.

Claims

Registering mapping information about blood sugar values of the user, food intake, food type, and exercise amount of the user;

Comparing the blood sugar value of the user with a target blood sugar value and determining whether the blood sugar state is a normal blood sugar state or an abnormal blood sugar state based on whether the blood sugar value of the user exceeds a target blood sugar value;

Generating information about a recommended food type or a food type to be avoided personalized to the user by dividing the determined blood sugar state based on the meal amount or the exercise amount; and

And providing the user with information about the type of recommended food or the type of food to be avoided.
The method of claim 1,

Wherein the blood sugar value of the user is a difference value between the pre-meal blood sugar value and the post-prandial blood sugar value of the user.
The method of claim 1,

The blood sugar value of the user is a personalized food recommendation method, characterized in that the user measured after meals.
The personalized food recommendation method of claim 2 or 3, wherein the information about the exercise amount is classified and stored in a subjective exercise level felt by the user.
The method of claim 4, wherein the generating of information on the type of recommended food personalized to the user is performed.

Personalized food recommendation method, characterized in that for generating a food type of the food level is divided into a normal blood sugar state based on the amount of the meal as information on the type of food to be recommended to the user.
The method of claim 5, wherein generating the personalized recommended food type information for the user

Personalized food recommendation method comprising generating information on the food type to be recommended to the user, including food type divided into normal blood sugar state, meal amount and exercise information of the corresponding food type divided into normal blood sugar state .
The method of claim 6, wherein generating the personalized recommended food type information for the user

Determining the highest exercise level at a meal level of a food type divided into normal blood glucose states from information on a user's blood sugar value, the user's meal amount, food type, and exercise amount received for at least one unit period; More,

Personalized food recommendation method, characterized in that for producing the food type information of the food type to recommend to the user at the meal amount level of the food type and the highest exercise amount level in the corresponding meal amount level.
The method of claim 4, wherein the generating of information on the type of recommended food personalized to the user is performed.

From the information on the blood sugar value of the user, the user's meal amount, food type, and exercise amount received for at least one unit period is different from each other in the normal blood sugar state and abnormal blood glucose state based on the meal amount of the same food type First determining the type of food;

Determining the lowest meal amount level and the highest exercise level level from the meal amount level and the exercise level of the meal type divided into normal blood sugar states among the food types that are differently divided; And

Personalized food recommendation method further comprises the step of generating the information on the food type to be recommended to the user at the lowest meal amount level and the highest exercise amount level.
The method of claim 4, wherein the personalized food recommendation method is

Calculating a food recommendation value R i ;

Create a set number of food types as information about food types to be recommended to the user, in order of the food recommendation value being high;

Personalized food recommendation method, characterized in that for generating the information of the type of food to be avoided by the user in the order of the food recommendation value is low.
The method of claim 9,

The food recommendation value Ri is calculated by the following Equation (1),

[Equation 1]

Where n is the total number of times the food (i) is ingested, a p is the weight assigned to the meal level when the food (i) is ingested based on the normal or abnormal blood glucose level, and b p is the normal blood sugar level Or a weight assigned to an exercise amount level when the food (i) is ingested based on the abnormal blood glucose state.
The method of claim 4, wherein the personalized food recommendation method is

When information about a search food type to be searched by a user is received, there is a unit time in which the search food type is divided into a normal blood sugar state or an abnormal blood sugar state among at least one or more unit time food types stored in a database unit. Judging;

Extracting information about a user's meal level or exercise level and blood sugar state information for the search food type at a unit time in which the searched food type is divided into a normal blood sugar state or an abnormal blood sugar state; And

And generating recommendation information of the searched food type based on the amount of meal information or the amount of exercise information in unit time divided into the normal blood sugar state or the abnormal blood sugar state.
The method of claim 4, wherein

Generating information on the type of food to be avoided personalized to the user

Personalized food recommendation method, characterized in that for generating information on the type of food to be avoided to the user, including information on the type of food is divided into abnormal blood sugar state, the amount of meals and exercise amount of the food type classified by abnormal blood sugar.