KR102428570B1 - Method for Predicting Changes of Blood-Sugar using Food Images - Google Patents

Abstract

The present invention relates to a blood sugar change prediction technique for managing the blood sugar of a diabetic patient or a user belonging to a diabetes risk group, which is suggested in terms of the fact that individuals have different blood sugar change trends even when consuming the same food. More specifically, the present invention relates to a method for predicting a blood sugar change by using a food image, capable of enabling a user requiring blood sugar management to check whether to eat food in the same state or make a request for special cooking excluding some ingredients of the food after pre-checking a risk level of a blood sugar change due to the intake of the food before consuming the food, and to check which type of exercise and how much of the exercise the user needs to do for safe blood sugar management after the consumption of the food. The method includes the following steps of: deriving a food name; predicting a blood sugar change due to the consumption of the food; and instructing a user about how to deal with a predicated blood sugar change exceeding a threshold value.

Description

Method for Predicting Changes of Blood-Sugar using Food Images

The present invention relates to a blood sugar change prediction technology for blood sugar management of a diabetic patient or a user belonging to a diabetic risk group, and has been proposed based on the fact that the trend of blood sugar change for each individual is different even if the same food is consumed. In more detail, the user who needs blood sugar control checks the risk of blood sugar changes due to the consumption of the food in advance before consuming the food, and then decides whether to eat the food as it is or to order it to be cooked excluding some ingredients of the food. , A method of predicting blood sugar changes using food images that provides convenience by recognizing the name and amount of food as a camera-photographed image, etc. is about

Diabetes mellitus refers to a group of metabolic diseases in which high blood sugar levels persist for a long period of time. Diabetes occurs when the pancreas does not produce enough insulin or the body's cells do not respond properly to the insulin produced.

Diabetes mellitus is one of the most important chronic diseases in modern times, and the incidence is particularly high in developed countries. Symptoms of high blood sugar include frequent urination and increased thirst and hunger.

Acute complications include diabetic ketoacidosis and hyperglycemic hyperosmolar non-ketotic coma, and serious long-term complications include cardiovascular disease, stroke, chronic renal failure, diabetic foot ulcer, diabetic retinopathy, and the like.

In order to effectively manage diabetes, it is necessary to track blood sugar levels. Since it is not realistic for a patient to visit a hospital to measure blood glucose every time, a personal blood glucose measurement device that can easily measure blood glucose by collecting blood by a user has recently been used. However, it is difficult to measure blood glucose at every meal because such a blood glucose measurement device cannot always be carried.

Also, even if you measure your blood sugar, you can only check the change in blood sugar caused by eating the food only after you eat it. Unless it is a very fatal food, there is a problem that it is impossible to know at all what follow-up measures are possible to control blood sugar.

Korean Patent Laid-Open No. 10-2016-0054320 (hereinafter, 'prior art') discloses a technology related to a blood sugar management system using a smartphone equipped with a blood sugar management application. However, even in the prior art, it is difficult to predict the blood sugar level to be changed from the food to be consumed before ingesting the food, so there is still a difficulty in actually managing the blood sugar appropriately.

Republic of Korea Patent Publication No. 10-2016-0054320 (2016.05.16)

The problem to be solved by the present invention is to learn a user-customized change in blood sugar for each food by measuring blood sugar after a user consumes food, and when the user cannot use the blood sugar measuring device or when the blood sugar measuring device is not provided It is to provide a blood sugar management method using a food image in which the user can stably control the blood sugar by predicting and providing the blood sugar level to be changed from the food to be consumed through the learned data even if the blood sugar is not measured.

The present invention provides a blood sugar management method by an application of a blood sugar management terminal as a means for solving the above problems.

The blood glucose management method of an embodiment includes the steps of: deriving, by the analysis module, a food name from the photographed food image; predicting, by the prediction module, a change in blood sugar of the user according to the intake of the food; and guiding the user how to respond if the change exceeds the user's preset risk threshold range.

In the blood glucose management method of an embodiment, a learning module periodically receives a blood glucose measurement value from a non-invasive wearable blood glucose measurement device connected through short-distance wireless communication for a predetermined time from the time of ingestion of the food, and The method may further include recording changes in blood sugar.

In the coping trick guide step of an embodiment, the analysis module derives the ingredients constituting the food using the derived food name, and the coaching module determines that the predicted change in blood sugar among the derived ingredients is the It may include presenting to the user at least one food material to be removed from the food in order not to exceed the risk threshold range.

The step of guiding the coping tips of an embodiment may include, by the coaching module, presenting, by the coaching module, at least one complementary food among beverages and side dishes, in which the predicted blood sugar change may not exceed the risk threshold range, to the user. can

The step of guiding how to respond in an embodiment may include, by the coaching module, presenting, by the coaching module, an instant exercise to be performed within a predetermined time after ingestion of the food so that the predicted change in blood sugar does not exceed the risk threshold range.

In an embodiment, the step of guiding a response tips may include, by the coaching module, presenting the amount of intake of the food so that the predicted blood sugar change does not exceed the risk threshold range.

The step of guiding the coping tips of an embodiment may include presenting the supplementary food based on the user's medical history information or preset food compatibility, which is input in advance by the coaching module.

According to an embodiment of the present invention, the user learns to learn a change in blood sugar for each food by measuring blood sugar after the user consumes food, and when the user cannot use the blood sugar measurement device or the blood sugar measurement device is not provided, the blood sugar Even if you do not measure the blood sugar level, the user can control the blood sugar stably by predicting and providing the blood sugar level to be changed from the food to be consumed through the learned data.

1A and 1B are block diagrams of an application or a blood sugar management system for executing a method for predicting a change in blood sugar of the present invention, and a blood sugar management terminal.
2 is a flowchart of a blood sugar management method using a food image according to Example 1. Referring to FIG.
3 is a flowchart of a blood sugar management method using a food image according to the second embodiment.
4 is a flowchart of a blood sugar management method using a food image according to a third embodiment.
5 is a flowchart of a blood sugar management method using a food image according to the fourth embodiment.
6 is a flowchart of a blood sugar management method using a food image according to Example 5;

Hereinafter, some embodiments of the present invention will be described in detail with reference to the drawings. However, this is not intended to limit the present invention to any specific embodiment, and it should be understood that all modifications, equivalents and substitutions including the technical spirit of the present invention are included in the scope of the present invention. do.

In this specification, the singular expression includes the plural expression unless the context clearly dictates otherwise.

In the present specification, when a component is described as having "have" or "comprise" a sub-component, other components are not excluded unless otherwise stated. This means that it may include

As used herein, the terms "...unit", "module" and "component" refer to a unit that processes at least one function or operation, and includes hardware, software or It may be implemented as a combination of hardware and software.

<Example 1>

Example 1 is focused on the fact that the change in blood sugar varies from person to person even if the same food is consumed, and how the change in blood sugar will occur when the user eats the food in front of his/her eyes without carrying the blood sugar measuring device every time. It relates to a technology that learns the trend of blood sugar change for each food in advance so that it can be predicted in advance.

1A and 1B are block diagrams of an application or a blood sugar management system for executing a method for predicting a change in blood sugar of the present invention, and a blood sugar management terminal.

The blood sugar management system according to the first embodiment includes the blood sugar management terminal 100 and the blood sugar measurement apparatus 200 .

The blood sugar management terminal 100 may operate in a learning mode and a blood sugar management mode.

In the blood sugar management mode, the blood sugar management terminal 100 captures a food to be eaten and predicts a change in blood sugar when the food is consumed by using the photographed food image. And when a dangerous situation is expected in view of the predicted blood sugar change trend, it guides the user with appropriate action tips.

In the learning mode, the blood sugar management terminal 100 learns a change in blood sugar for the user whenever food is eaten in conjunction with the blood sugar measurement device 200 . In other words, the blood sugar management terminal 100 photographs the food to be eaten, and specifies a corresponding food name from the photographed food image. In addition, the blood glucose measurement value after the user consumes food is periodically received from the blood glucose measurement apparatus 200 and recorded in the blood glucose change database DB2.

Hereinafter, the blood sugar management terminal 100 and the blood sugar measurement apparatus 200 will be sequentially described.

The blood sugar management terminal 100 includes a photographing module 110 , an analysis module 120 , a prediction module 130 , and a coaching module 140 , and may further include a learning module 150 .

First, the operation in the blood sugar management mode is as follows.

The photographing module 110 takes a picture of food by using a camera built in or separately provided in the blood sugar management terminal 100 according to a user's instruction. It is preferable that an external camera provided separately is wirelessly linked with the blood sugar management terminal 100 .

The analysis module 120 detects a food object from the food image photographed by the photographing module 110, and derives the food name by inquiring the detected object to the food database (DB1) built in advance.

Assuming that the user consumes the photographed food, the prediction module 130 inquires and predicts the user's blood sugar change according to the intake in the pre-built blood sugar change database DB2.

For example, when the name of the food derived from the photographed food image is kimbap, the prediction module 130 searches for the corresponding “user” and “gimbap” as keywords in the blood sugar change database (DB2) when consuming gimbap. predicts the change in blood sugar for each user's postprandial time period.

The coaching module 140 guides (or provides) a countermeasure to the user when the predicted blood glucose change exceeds a preset user's risk threshold range. Examples of countermeasures include removing specific ingredients from the corresponding food, reducing the intake of the corresponding food, taking supplemental food to be combined with the corresponding food, or performing a predetermined instant exercise immediately after a meal.

Next, the operation in the learning mode will be described.

The learning module 150 periodically receives a blood sugar measurement value from the blood sugar measurement device 200 through the communication module 160 for a predetermined time from the point of ingestion of the food, and monitors the change in blood sugar of the user according to the intake of the food. It is recorded in the blood glucose change database (DB2).

Specifically, the learning module 150 may receive the blood glucose measurement value every 30 minutes or every 60 minutes immediately after eating the food. In addition, the reception cycle of the blood glucose measurement value may be variably set, such as a 30-minute cycle within 1 hour after the start of the meal, and a 10-minute cycle after 1 hour.

The learning module 150 may further receive a blood glucose measurement value immediately before ingestion of food. This is to set a reference point of the user's blood sugar change when predicting the user's blood sugar change trend.

In addition, the learning module 150 may further receive from the analysis module 120 the food intake amount derived by the secondary image capturing after a meal in addition to the food name. That is, the learning module 150 may learn more specifically the blood sugar change trend according to the final intake amount of the corresponding food in addition to the blood sugar change trend according to the intake of a specific food.

On the other hand, although it is in the blood sugar management mode, there may be a case in which the learning module 150 operates as an exception.

Specifically, when the user consumes food while wearing the non-invasive blood sugar measurement apparatus 200 , the blood sugar management terminal 100 simultaneously activates the blood sugar management mode and the learning mode. In this case, the learning module 150 periodically receives the blood glucose measurement value from the blood glucose measurement device 200 through the communication module 160 for a predetermined time from the point of ingestion of the food, and changes the user's blood glucose according to the intake of the food. Temporarily save

The learning module 150 compares the change trend of the temporarily stored blood glucose measurement value with the pre-stored change trend when the blood sugar change information of the food currently being consumed is already stored in the blood sugar change database DB2, If the difference is greater than or equal to a preset error range, the previously stored information is updated with the change trend of the temporarily stored blood glucose measurement value.

In addition, if the difference between the two pieces of information is greater than or equal to the preset error range and health is improved, the coaching module 140 sends a message to the user, “Congratulations. Blood sugar control is getting better. You can also provide more congratulatory messages such as “Please continue to take care of your health in the future.” If the difference between the two pieces of information is more than the preset error range and the health is in a deteriorated state, the coaching module 140 tells the user, "The blood sugar is not being managed. You can also provide more warning messages such as “You need more careful health care.”

Next, the blood glucose measurement apparatus 200 measures the user's blood glucose in a blood collection method or a non-invasive method. In other words, the blood glucose measurement apparatus 200 of the blood collection method directly measures glucose contained in blood, and the non-invasive type blood glucose measurement apparatus 200 measures glucose contained in the user's sweat, not the blood, but sweat. Since the level of glucose in the body is proportional to the blood sugar, it is the principle of indirectly measuring the blood sugar by using the glucose in the sweat.

When the blood glucose measurement apparatus 200 is a blood sampling method, blood collection and blood glucose measurement may be intermittently performed by the user's manual button operation, and a predetermined measurement start command may be performed while the user is wearing (or wearing) the measurement apparatus. It is also possible to continuously perform blood sampling and blood glucose measurement by input.

When the blood glucose measurement apparatus 200 is a non-invasive method, the apparatus 200 may be provided in the form of a wearable device such as a patch-type sensor attached to the body, a wrist watch-type sensor, a clothing-type sensor, etc., and a predetermined measurement start command When this input or an operation of the photographing module 110 is detected, blood glucose measurement is started.

In addition, the blood glucose measurement apparatus 200 is preferably measured periodically and continuously for a predetermined time from the point of ingestion of food, whether in a manual method or an automatic method. , it is also possible to provide means such as a special alarm sound or vibration for the end time.

Meanwhile, the blood glucose measurement apparatus 200 is connected to the blood glucose management terminal 100 through short-range wireless communication such as Bluetooth, Wi-Fi, or Zigbee.

In the above, the blood glucose management terminal 100 and the blood glucose measurement apparatus 200 have been described separately from a functional point of view. However, the blood glucose measurement device 200 is built in the blood glucose management terminal 100 or By embedding a module, it may be implemented as a single product.

2 is a flowchart illustrating a blood sugar management method executed in the blood sugar management terminal according to the first embodiment.

The blood sugar management method according to the first embodiment includes a learning step (S10) including a step of deriving a food name (S101) and a step of recording a blood sugar change according to food intake (S102), a step of deriving a food name (S111), and a change in blood sugar It includes a blood sugar management step (S11) including a prediction step (S112) and a response method guide step (S113).

First, the learning step (S10) will be described in detail.

In the food name derivation step (S101), the analysis module 120 derives the food name by analyzing the food image provided to the photographing module 110. The name of the food to be consumed may be input as text or input by voice recognition.

In the blood glucose change recording step S102, the learning module 150 periodically receives the blood glucose measurement value from the blood glucose measurement device 200 connected through short-range wireless communication for a predetermined time from the time of ingestion of the food, and The user's blood sugar change is recorded in the blood sugar change database DB2.

Next, the blood sugar management step ( S11 ) will be described in detail.

In the food name derivation step (S111), the analysis module 120 derives the food name by analyzing the food image provided to the photographing module 110. The name of the food to be consumed may be input as text or input by voice recognition.

In the blood sugar change trend prediction step S112 , the prediction module 130 predicts the user's blood sugar change trend according to food intake.

In the coping technique guide step S113 , the coaching module 140 guides the user with an appropriate coping technique when the user's blood glucose change predicted by the prediction module 130 exceeds a preset user's risk threshold range.

The coaching module 140 may present at least one food material to be removed from the corresponding food to the user, may be a supplemental food that can control blood sugar so that the predicted blood sugar change does not exceed a threshold range, or measure the predicted blood sugar change amount. Instant exercise that can be reduced in a short time may be suggested, or if the amount of change in blood glucose when food is ingested is expected to exceed the threshold range, the intake amount may be presented so as not to exceed the threshold range.

Postprandial response tips for blood sugar management provided by the coaching module 140 will be described in detail in Examples 2 to 5 below.

<Example 2>

Embodiment 2 relates to a technique for informing a food material that can be removed from a corresponding food for blood sugar control before ingestion of food as one of the countermeasures provided by the coaching module.

3 is a flowchart illustrating a blood glucose management method according to the second embodiment.

Referring to FIG. 3 , the blood sugar management method of Example 2 includes a food name derivation step (S210), a blood sugar change trend prediction step according to food intake (S220), a food material derivation step (S230), and a guide step (S240). .

Here, the food name derivation step (S210) and the blood sugar change trend prediction step (S220) are the same as those of the first embodiment (S111, S112), and thus overlapping descriptions will be omitted.

In the food material derivation step (S230), the analysis module 120 derives the food materials constituting the corresponding food by using the derived food name. Specifically, food material information corresponding to the food name is further stored in the food database DB1, and the analysis module 120 queries the food database DB1 with the food object searched from the food image to find the name of the food and the food. The ingredients that make up the

Meanwhile, the user may further input additional ingredients directly to the ingredients of the corresponding food derived by the analysis module 120 . For example, squid delicacy is not used in normal gimbap, but if the user wants to consume kimbap containing squid delicacy, the user has a food name (“gimbap”) and ingredients derived from the gimbap image taken by the analysis module 120 You can also directly input “squid delicacy” as an additional ingredient in (“Nori, pickled radish, egg, spinach, burdock”).

In addition, when there is no food material information matching the food name in the food database DB1, the analysis module 120 may search the web for food material information corresponding to the food name using the Internet network.

In the guide step (S240), the coaching module 140 presents to the user at least one food material to be removed from the food so that the predicted blood sugar change does not exceed the risk threshold range among the food materials derived by the analysis module 120 .

Specifically, when it is predicted in the prediction module 130 that the blood sugar change exceeds the risk threshold range, the coaching module 140 must remove the blood sugar change based on the GI index (glycemic index) of the food material so as not to exceed the risk threshold range. Present food to the user. For example, when the risk threshold range is 140 or less and the predicted blood sugar change is 145, it is suggested to remove only one food material having the highest GI index. As another example, when the risk threshold range is 140 or less and the predicted blood sugar change is 160, it is guided to remove two or more food materials in the order of the highest GI index.

<Example 3>

Embodiment 3 relates to a technique for informing a supplementary food to be consumed together with the corresponding food for blood sugar management as one of the countermeasures provided by the coaching module.

4 is a flowchart illustrating a blood sugar management method according to the third embodiment.

The blood sugar management method of the third embodiment includes a food name deriving step (S310), a blood sugar change trend prediction step (S320), and a guiding step (S330).

Here, since the food name derivation step (S310) and the blood sugar change trend prediction step (S320) of Example 3 are the same as those (S111, S112) of Example 1, overlapping descriptions are omitted.

In the guide step (S330), the coaching module 140 presents the user with complementary foods such as beverages and side dishes, in which the predicted blood sugar change may not exceed the risk threshold range when consumed together with the main food in front of the user's eyes.

For example, since polyphenols contained in cinnamon powder are known to help control blood sugar, the coaching module 140 may present cinnamon powder as a complementary food. That is, the coaching module 140 may guide you by saying, “Spray cinnamon powder lightly on the food and eat it”.

The coaching module 140 may present supplementary food based on the user's medical history information input in advance. For example, cinnamon powder is a material that is not recommended for people with poor kidneys, and if the user has kidney disease in his/her medical history information, the coaching module 140 may suggest to consume with pork potato tea instead of cinnamon powder. For reference, the inulin component contained in pork potatoes is known to play a role in reducing blood sugar.

In addition, the coaching module 140 may present complementary food based on a preset food compatibility. For example, if a food ingredient contains honey, cinnamon, which is compatible with honey, is recommended as a complementary food.

<Example 4>

Embodiment 4 relates to a technique for notifying an instant exercise to be performed after ingestion of a corresponding food for blood sugar management as one of the countermeasures provided by the coaching module.

5 is a flowchart illustrating a blood sugar management method according to the third embodiment.

The blood sugar management method of the fourth embodiment includes a food name deriving step (S410), a blood sugar change trend prediction step (S420), and a guiding step (S430).

Here, since the food name derivation step (S410) and the blood sugar change trend prediction step (S420) of Example 4 are the same as those (S111, S112) of Example 1, overlapping descriptions are omitted.

In the guide step S430 , the coaching module 140 presents the user with an instant exercise to be performed within a predetermined time after ingestion of food so that the blood sugar change predicted by the prediction module 130 does not exceed the risk threshold range.

The coaching module 140 may present the exercise type, exercise intensity, and exercise time differently according to the degree of blood glucose change predicted by the prediction module 130 .

For example, if the risk threshold range is 140 or less and the blood sugar change predicted by the prediction module 130 is 145, the coaching module 140 suggests to the user to perform the squat motion for 5 minutes before 1 hour has elapsed after food intake can do.

Also, when the risk threshold range is 140 or less and the blood sugar change predicted by the prediction module 130 is 160, the coaching module 140 may suggest to the user to perform the push-up operation for 5 minutes and the squat operation for 10 minutes.

The learning module 150 may receive a blood sugar change after the user eats food and a blood sugar change after performing a suggested exercise, and may learn a blood sugar change amount according to the presented exercise. For example, the learning module 150 learns a blood sugar reduction amount that is changed when the user performs a squat for 10 minutes and a blood sugar reduction amount that changes when a user performs a squat for 5 minutes and a push-up for 5 minutes.

<Example 5>

Embodiment 5 relates to a technique of notifying an intake amount of a corresponding food for blood sugar management as one of the countermeasures provided by the coaching module.

6 is a flowchart illustrating a blood sugar management method according to the fifth embodiment.

The blood sugar management method of the fifth embodiment includes a food name deriving step ( S510 ), a blood sugar change trend prediction step ( S520 ), and a guiding step ( S530 ).

Here, the food name derivation step (S510) and the blood sugar change trend prediction step (S520) of Example 5 are the same as those (S111, S112) of Example 1, and thus overlapping descriptions will be omitted.

In the guide step S530 , the coaching module 140 presents the amount of food intake to prevent the blood sugar change predicted by the prediction module 130 from exceeding the risk threshold range.

For example, if the food derived from the food image is gimbap and the change in blood sugar predicted when the gimbap is consumed in the prediction module 130 is 150, exceeding the risk threshold range 140, the coaching module 140 tells the user “gimbap” Please eat only 5 pieces.”

In the above, the present invention has been described with reference to several embodiments related to the present invention, but those of ordinary skill in the art can use the present invention within the scope not departing from the spirit and scope of the present invention described in the claims below. It will be understood that various modifications and variations are possible.

In addition, the invention related to the method among the embodiments described above may be implemented as a program or a computer-readable recording medium storing the program.

That is, the blood glucose management method of the present invention may be implemented in the form of an application, and may be implemented as a software program executed in a mobile terminal such as a smartphone or tablet PC running on the basis of Google's Android or Apple's IOS, or Google Glass, It can be implemented as a software program running on wearable devices such as Apple Watch, Samsung Galaxy Watch, smart watch, etc. have.

In addition, the partial functions of the above-described device or system may be provided by being included in a recording medium that can be read through a computer by tangibly embodied a program of instructions for implementing the same. A computer-readable recording medium may include program instructions, data files, data structures, etc. alone or in combination. Examples of the computer-readable recording medium include magnetic media such as hard disks, floppy disks and magnetic tapes, optical media such as CD-ROMs and DVDs, and floppy disks. magneto-optical media, and hardware devices specially configured to store and carry out program instructions, such as ROM, RAM, flash memory, USB memory, and the like.

S111, S121, S210, S310, S410, S510: Food name derivation step
S120: Blood sugar change recording step
S130, S220, S320, S420, S520: Prediction of blood sugar change trend
S140, S230, S330, S430, S530: Guide step

Claims (6)

A method for managing blood sugar in a blood sugar management terminal, comprising:
Deriving a food name from the food image analysis module is taken;
predicting, by a prediction module, a blood sugar change trend of the user according to the intake of the food by inquiring a blood sugar change trend for the same food stored in a pre-built blood sugar change database;
guiding, by a coaching module, a response method to a user when the predicted blood glucose change exceeds a preset user's risk threshold range; and
receiving, by the learning module, a blood glucose measurement value periodically from a blood glucose measurement device connected through short-range wireless communication for a predetermined time from the time of ingestion of the food, and recording a change in blood glucose of the user according to the intake of the food in a blood glucose change database; including,
When the user consumes food while wearing the blood glucose measurement device of the non-invasive method, the learning module periodically receives the blood glucose measurement value from the blood glucose measurement device for a predetermined time from the point of ingestion of the food, and the food Temporarily recording a change in blood sugar of the user according to the intake of ; and
When the blood sugar change information for the same food as the currently consumed food is previously stored in the blood sugar change database, the learning module compares the change trend of the temporarily recorded blood sugar measurement value with the change trend of the previously stored blood sugar measurement value, If the difference between the information is greater than or equal to a preset error range, the method further comprising: updating the blood sugar change information previously stored in the blood sugar change database with the change trend of the temporarily recorded blood sugar measurement value;
The step of guiding the countermeasures is,
When the coaching module is ingested together, the user is presented with at least one supplementary food among beverages and side dishes in which the predicted blood sugar change may not exceed the risk threshold range, but in consideration of the user's medical history and food compatibility set in advance. characterized by providing complementary foods
How to manage blood sugar using food images. According to claim 1,
receiving, by the learning module, a blood glucose measurement value periodically from a blood glucose measurement device connected through short-range wireless communication for a predetermined time from the time of ingestion of the food, and recording a change in blood glucose of the user according to the intake of the food in a blood glucose change database;
A blood sugar management method using a food image further comprising a. delete According to claim 1,
The response tips guide step is,
deriving, by the analysis module, ingredients constituting the food using the derived food name; and
presenting, by the coaching module, at least one ingredient to be removed from the food to the user so that the predicted change in blood sugar among the derived ingredients does not exceed the risk threshold range
A method of managing blood sugar using a food image comprising a. delete According to claim 1,
The response tips guide step is,
and presenting, by the coaching module, an instant exercise to be performed within a predetermined time after ingestion of the food so that the predicted blood sugar change does not exceed the risk threshold range.

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