KR102661371B1 - Method for digital treatment for eating disorder and apparatus for digital treatment for eating disorder - Google Patents

Abstract

The present invention relates to eating disorder digital treatment methods and eating disorder digital treatment devices for performing such methods. The eating disorder digital treatment method may include the step of the eating disorder treatment device generating an eating diary based on a user input, and the eating disorder treatment device providing cognitive behavioral therapy and eating disorder training based on the eating diary.

Description

Digital treatment method for eating disorder and digital treatment device for eating disorder performing the method {Method for digital treatment for eating disorder and apparatus for digital treatment for eating disorder}

The present invention relates to eating disorder digital treatment methods and eating disorder digital treatment devices for performing such methods. More specifically, the present invention relates to an eating disorder digital treatment method for treating a user's eating disorder using an application on a user device and an eating disorder digital treatment device that performs the method.

An eating disorder is a disease that causes problems with food intake due to psychological problems. Eating disorders are characterized by an obsession with weight and can lead to damage to physical and mental health.

Eating disorders can be caused by a variety of causes.

Biological causes include genetics, changes in neurotransmitters, changes in substances involved in appetite and satiety, and changes in energy metabolism processes.

Psychological causes include social pressure that emphasizes thinness, conflict due to women's social roles, and information provided by the mass media that one can change one's body through advancements in medical technology or personal efforts.

Emotional causes include low self-esteem and uncertainty about oneself. This is due to the lack of ways to deal with negative emotions.

Eating disorders can be classified as follows:

Anorexia nervosa is characterized by persistent attempts to lose weight, weight loss, inappropriate preoccupation with food and weight, and bizarre behavior in handling food.

Bulimia nervosa is characterized by recurrent binge eating, eating faster than usual, and eating excessive amounts even when there is no feeling of hunger. After eating, you feel disgust and contempt for yourself.

Bulimia nervosa is a mental disorder in which people engage in compensatory behaviors such as inducing vomiting, using diuretics or laxatives, or exercising excessively to prevent weight gain after repeated binge eating.

Eating disorder types are not fixed, and in fact, many eating disorder patients often have both anorexia and bulimia. Additionally, it is estimated that 30% of patients who were initially anorexic have their diagnosis changed to bulimia over time. In this way, eating disorder types can be easily converted, and considering these disease characteristics, it is most important to approach the fundamental causes that trigger these eating disorders rather than treating specific eating disorder behaviors.

Adult eating disorders have many physical and mental co-morbidities, so they often require intensive medical services. In particular, patients with anorexia nervosa are often treated in the form of inpatient treatment because there is a possibility that they may transform into another eating disorder during the treatment process, and normalization of weight and management of concomitant diseases are also necessary at the beginning of treatment.

To date, there are no prescription applications that address eating disorders, and there is a need to develop prescription digital treatments to manage eating disorders in everyday life.
Prior art includes Publication Patent Publication No. 10-2020-0009595.

The purpose of the present invention is to solve all of the above-mentioned problems.

In addition, the present invention aims to provide a digital treatment for writing a meal diary based on an app on the user device and treating the user's eating disorder through cognitive behavioral therapy and eating disorder training.

In addition, the present invention provides cognitive behavioral therapy and eating disorder training adaptively to the user based on the user's meal diary data, and provides a method for treating eating disorders that minimizes unnecessary input from the user based on data acquired on the user device. The purpose is to provide digital therapeutics.

A representative configuration of the present invention to achieve the above object is as follows.

According to one embodiment of the present invention, the eating disorder digital treatment method includes the steps of generating a meal diary by an eating disorder treatment device based on a user input, and the eating disorder treatment device performing cognitive behavioral therapy and eating disorder based on the meal diary. It may include providing training.

Meanwhile, the meal diary may include at least one of information about the meal date, meal type, meal time, number of people who ate together, meal location, meal menu, and emotions after the meal.

Additionally, the user interface for selecting the type of meal may display context-specific text generated based on information about emotions after the meal.

According to another embodiment of the present invention, an eating disorder treatment device for digital treatment of eating disorders is implemented to generate a meal diary based on user input and provide cognitive behavioral therapy and eating disorder training based on the meal diary. You can.

Meanwhile, the meal diary may include at least one of information about the meal date, meal type, meal time, number of people who ate together, meal location, meal menu, and emotions after the meal.

Additionally, the user interface for selecting the type of meal may display context-specific text generated based on information about emotions after the meal.

According to the present invention, a digital therapeutic agent can be provided for writing a meal diary based on an app on the user's device and treating the user's eating disorder through cognitive behavioral therapy and eating disorder training.

In addition, according to the present invention, cognitive behavioral therapy and eating disorder training are adaptively provided to the user based on the user's meal diary data, and eating disorder treatment is provided by minimizing the user's unnecessary input based on data acquired on the user device. Digital therapeutics may be provided for

1 is a conceptual diagram showing an eating disorder treatment device according to an embodiment of the present invention.
Figure 2 is a conceptual diagram showing the operation of a meal diary according to an embodiment of the present invention.
3 and 4 are conceptual diagrams showing a user interface for a meal diary according to an embodiment of the present invention.
Figure 5 is a conceptual diagram showing the operation of the cognitive behavioral therapy unit according to an embodiment of the present invention.
Figure 6 is a conceptual diagram showing a user interface for cognitive behavioral therapy according to an embodiment of the present invention.
Figure 7 is a conceptual diagram showing the operation of the eating disorder training unit according to an embodiment of the present invention.
Figure 8 discloses a method for performing eating disorder training according to the user's condition according to an embodiment of the present invention.
Figure 9 is a conceptual diagram showing a method for determining user improvement in an eating disorder treatment device according to an embodiment of the present invention.

The detailed description of the present invention described below refers to the accompanying drawings, which show by way of example specific embodiments in which the present invention may be practiced. These embodiments are described in sufficient detail to enable those skilled in the art to practice the invention. It should be understood that the various embodiments of the present invention are different from one another but are not necessarily mutually exclusive. For example, specific shapes, structures and characteristics described herein may be implemented with changes from one embodiment to another without departing from the spirit and scope of the invention. Additionally, it should be understood that the location or arrangement of individual components within each embodiment may be changed without departing from the spirit and scope of the present invention. Accordingly, the detailed description described below is not intended to be limited, and the scope of the present invention should be taken to encompass the scope claimed by the claims and all equivalents thereof. Like reference numbers in the drawings indicate identical or similar elements throughout various aspects.

Hereinafter, several preferred embodiments of the present invention will be described in detail with reference to the attached drawings in order to enable those skilled in the art to easily practice the present invention.

1 is a conceptual diagram showing an eating disorder treatment device according to an embodiment of the present invention.

1 discloses an eating disorder treatment device for providing a digital treatment for a user's eating disorder.

Referring to FIG. 1, the eating disorder treatment device may include a meal diary 100, a cognitive behavioral treatment unit 110, an eating disorder training unit 120, and a processor 130.

The meal diary 100 may be implemented to allow the user to write a meal diary. The meal diary may include information about the food consumed by the user on a specific day. Information about food consumed at different times, such as breakfast, lunch, dinner, snacks, etc., can be included in the meal diary. Information about meal times entered by the user, people who ate together, meal location, menu, menu photos, etc. may be included in the meal diary.

Additionally, the meal diary 100 may additionally receive emotional information about the user's emotions while eating. For example, the meal diary 100 can receive information about how hungry you were before the meal, how full you were right after the meal, and how you felt at the end of the meal.

Additionally, the meal diary 100 can set a meal-related goal, check whether the goal has been completed, and record data on whether the goal has been completed.

The cognitive behavioral therapy unit 110 may be implemented to perform cognitive behavioral therapy to change the user's thoughts by analyzing the impact of the user's thoughts on emotions and behavior. The cognitive behavioral therapy unit 110 may receive information about the user's feelings and provide the user with specific reasons for the user's feelings so that the user can feel his or her feelings and change his or her thoughts and actions. The cognitive behavioral therapy unit 110 may perform cognitive behavioral therapy based on information about the user's emotions through the meal diary and/or the eating disorder training unit 120.

The eating disorder training unit 120 may be implemented to provide the user with information related to the eating disorder and provide information for treating the user's eating disorder in parallel with cognitive behavioral therapy.

The processor 130 may be implemented to control the operations of the meal diary 100, the cognitive behavioral therapy unit 110, and the eating disorder training unit 120.

Figure 2 is a conceptual diagram showing the operation of a meal diary according to an embodiment of the present invention.

In Figure 2, a method of creating a meal diary in a meal diary is disclosed.

Referring to Figure 2, the meal diary receives information about meal date, meal type (breakfast, lunch, dinner, snack), meal time, number of people who ate together, meal location, meal menu, and emotions after meal. You can keep a meal diary.

First, information about the meal date may be entered into the meal diary, and then information about the type of meal may be entered.

Afterwards, information about meal times according to meal types may be entered. The time at which information about meal time is first set may be determined differently depending on the type of meal. For example, if breakfast is selected, the time appropriate for breakfast (e.g., 7 a.m.) may be set as the initial set time, and if dinner is selected, the time appropriate for dinner (e.g., 7 PM) can be set as the initial setting time. Additionally, in the case of snacks, the initial setting time may be determined according to the time when the user attempts to input the type of meal.

Meal times can also be used to remind users to eat through notification settings. Through the meal diary, users can set alarms for the times to eat breakfast, lunch, dinner, and snacks and eat at set times.

Additionally, according to an embodiment of the present invention, separate comments can be set for breakfast, lunch, dinner, and snacks to help with the user's eating disorder. Taking the user's eating status into account, the user interface allows users to enter information about breakfast, lunch, dinner, and snacks, with comments tailored to the user's situation (e.g., There's no talent like courage, I'm proud of you, Stormy, etc.). It's time, but let's continue again, I know I'm trying, let's do better next time, etc.) You can display comments to motivate the user based on the situation.

Information about the number of people who ate may be entered in the meal diary. For example, information about the number of people who ate together with the user, such as alone, family, friends, coworkers, lovers, etc., may be entered.

Information about meal locations may be entered in the meal diary. For example, information about the place where the user ate, such as home, school/work, restaurant, etc., may be entered. Additionally, information on whether the meal was eaten at the table or somewhere other than the table can be additionally entered into the meal diary.

Additionally, if the user does not eat a meal, the user can check that the user did not eat a meal in the meal diary.

Additionally, information about meal menus may be uploaded to the meal diary. Information about the meal menu can be entered through text about the menu and photos of the menu.

Additionally, information about emotions after a meal may be entered into the meal diary. Information about feelings after a meal can include information about whether you were hungry right before the meal, whether you were full after the meal, and your feelings after the meal. For example, just before a meal, the degree of hunger can be entered in a slide-by-slide manner through a user interface. The degree of fullness after a meal can be entered in a slide format. The level of emotion after a meal can also be entered in a slide format. The level of emotion after a meal can be reflected in the user interface corresponding to the type of meal in the meal diary.

Additionally, the reason for the emotion immediately after the meal can be entered in the meal diary in multiple-choice or text form. Additionally, in the meal diary, you can select and enter the reason for the meal mistake (binge eating, eating and vomiting, spitting up, laxatives, drinking, body check, etc.). These meal sentiments can be expressed through contextual text on the user interface indicating the type of meal (e.g., There's no talent like courage. I'm proud of you. It was a whirlwind. But let's keep going. I know you're trying. Let's do better next time. etc.) can be changed.

Additionally, in the case of a meal diary, when a meal is consumed more than a set number of times, additional meals may be displayed separately on the user interface in addition to the meal type.

In addition, in an embodiment of the present invention, the user can set goals related to meals through a meal diary. For example, eating disorder-related goals such as 1) eating foods you have been avoiding, 2) not taking diet supplements, 3) skipping your exercise routine, 4) eating with family, 5) visiting a good restaurant, and 6) avoiding vomiting. Goals may be managed in the meal diary so that people can set and achieve their goals in the meal diary.

3 and 4 are conceptual diagrams showing a user interface for a meal diary according to an embodiment of the present invention.

3 and 4 show a user interface for inputting a meal diary.

Referring to Figure 3, screen A (310) is a screen for the date for the meal diary and the type of meal on that date. Users can enter information about a specific meal type on a specific date by selecting the date and set meal type (breakfast, lunch, dinner, snack). As shown in screen A (310), context-specific text information (e.g., I know you're trying. Let's do better next time, etc.) can be added under the meal type by considering the user's meal diary information.

Screen B (320) is a screen for selecting a specific meal type (for example, breakfast) and then entering information about meal time, number of people eating together, meal location, etc. Additionally, in case of skipping a meal, a user interface for selecting that the meal was skipped may also be implemented on screen B (320).

Referring to FIG. 4, screen C 410 and screen D 420 may be screens for inputting information about emotions after eating. Screen C (410) is a screen for entering the degree of hunger in a slide manner through a user interface regarding how hungry one is just before a meal, and for inputting the degree of fullness in a slide manner after a meal.

Screen D (420) is a screen for entering information about the mood at the end of the meal and the reasons for the mood.

Screen E 430 may be a screen for entering mistakes made during a meal. Users can select and record mistakes they made while eating (e.g. binge eating, eating, chewing, spitting up, excessive exercise, etc.).

Figure 5 is a conceptual diagram showing the operation of the cognitive behavioral therapy unit according to an embodiment of the present invention.

In Figure 5, a cognitive behavioral therapy method provided to the user by the cognitive behavioral therapy department is disclosed.

Referring to Figure 5, the cognitive behavioral therapy unit can receive information about sensations felt in the body and information about emotions that are the reason for the sensations felt in the body.

The cognitive behavioral therapy unit provides multiple causes for the user to feel emotions, and can make the user recognize the emotions he or she feels by considering the multiple causes selected by the user.

The cognitive behavioral therapy unit allows the user to recognize emotions more objectively, relieves the emotions, or makes the user aware that the emotions may be caused by the user's distorted perspective.

Through this method, the cognitive behavioral therapy department can analyze the impact of the user's thoughts on emotions and behavior and perform cognitive behavioral therapy to change the user's thoughts.

The cognitive behavioral therapy department is linked with the meal diary and eating disorder training department and can perform cognitive behavioral therapy for the user by considering the user's meal diary information and eating disorder training information. For example, the cognitive behavioral therapy department can consider the emotions felt through the user's meal diary information and provide a process to objectively recognize the cause and emotion of the emotion. Additionally, certain skills (e.g., lever guessing) can be implemented during eating disorder training to enable cognitive-behavioral therapy procedures.

Figure 6 is a conceptual diagram showing a user interface for cognitive behavioral therapy according to an embodiment of the present invention.

In Figure 6, a user interface for cognitive behavioral therapy is disclosed.

Referring to FIG. 6, screen F 610 is a screen for inputting information about the sensations the user feels in the body. Users can select and input the location where they feel the sensation and the type of sensation.

Screen G (620) may be a screen for receiving selections about emotions related to senses, and screen H (630) may be a screen for objectifying emotions and providing explanations to correct recognition of emotions.

Figure 7 is a conceptual diagram showing the operation of the eating disorder training unit according to an embodiment of the present invention.

In Figure 7, a method for providing training related to an eating disorder to a user in an eating disorder training department is disclosed.

Referring to FIG. 7, the eating disorder training department may provide stopping lever guessing (710), an eating disorder first aid kit (720), and weekly training (730) for users.

Stopping lever guessing (710) can be implemented in conjunction with the cognitive behavioral therapy department to treat the user's thoughts, emotions, and behavior.

The eating disorder first aid kit 720 is an area for providing recommended content related to eating disorders. Recommended content may be provided randomly on the eating disorder first aid kit 720, and content separately recommended to the user by a doctor may be provided.

Weekly training 730 can be implemented to provide content for treating eating disorders on a weekly basis with a plurality of sessions. Sessions are provided weekly, but content to be provided in the future can be marked as locked to prevent content from being provided in advance.

Screen I (750) is the screen for Stop Guessing the Lever (710), Eating Disorder First Aid (720), and Weekly Training (730).

Figure 8 discloses a method for performing eating disorder training according to the user's condition according to an embodiment of the present invention.

In Figure 8, a method for grouping users for eating disorder training and providing eating disorder training for each user group is disclosed.

Referring to FIG. 8, the eating disorder treatment device may group users based on the user's meal diary and provide different user disorder training for each user group.

Users may be set to a first user group and a second user group based on meal diary data obtained from the meal diary.

(1) User Group (Meal Pattern) (810)

A meal pattern may be extracted based on the user's meal diary data, and a user group (meal pattern) 810 may be determined based on the meal pattern. For example, the meal pattern may be determined based on the number of meals, meal menu, etc. included in the meal diary data. The more similar the number of meals and meal menus, the more similar meal patterns can be determined. For example, the average value of the user's daily number of meals may be set as one first vector value. The meal menu is divided into categories such as Korean food, Chinese food, Japanese food, snack food, etc., and vector coordinate values are set so that foods with similar categories, similar ingredients, and similar recipes are placed closer, and the average value of the food eaten between meals is set. It can be set to one second vector value.

The first vector value and the second vector value may be located on a first coordinate plane related to one meal pattern, and are clustered based on the first vector value and the second vector value to form a user group (meal pattern) 810. This can be decided.

(2) Setting of user group (emotions after meal) 820

Among the user's meal diary data, emotions after a meal may be extracted as vector values to determine the user group (emotions after a meal) 820. In relation to emotions after a meal, hunger before a meal, hunger after a meal, mood after a meal, and mistake after a meal may each be set as a third vector value, a fourth vector value, a fifth vector value, and a sixth vector value. {3 vector values, 4th vector values, 5th vector values, and 6th vector values} generated each time the user eats may be expressed on the second coordinate plane, and the user's {3 vector values, 4th vector values, and 6th vector values A user cluster may be formed by clustering a plurality of coordinates corresponding to the 5th vector value and the 6th vector value.

A user group (emotion after meal) 820 may be set in consideration of user cluster similarity.

User cluster similarity may be determined by considering the distance between the centers of at least one user cluster. For example, it may be assumed that user A has user cluster 1 and user cluster 2, and user B has user cluster 3 and user cluster 4. In this case, a decision may be made regarding user A's user cluster and user B's nearby cluster.

For example, if {User Cluster 1 of User A, User Cluster 3 of User B} are relatively close, and {User Cluster 2 of User A, User Cluster 4 of User B} are relatively close, the cluster of User Cluster 1 The user cluster similarity may be determined based on the sum of the first distance between the center and the cluster center of user cluster 3 and the second distance between the cluster center of user cluster 2 and the cluster center of user cluster 4.

In other words, the closer the emotions after a meal are, the closer the distance between user clusters is, so the user cluster similarity can be set to be relatively high. Additionally, even in the case of having complex post-meal emotions, the user cluster similarity may be set relatively high as the user has the same complex post-meal emotions.

In the present invention, the user group (emotion after meal) 820 is determined based on user cluster similarity, and more specifically, the first vector value and the second vector value on the first coordinate axis of the user group (emotion after meal) 820. Taking this into account, a smaller user group may be determined by performing sub-user grouping within the user group (emotion after meal) 820 that additionally takes meal patterns into consideration. The user group grouped by considering the first and second vector values on the first coordinate axis of the user group (emotion after meal) may be expressed in terms of the minimum user group 830.

According to an embodiment of the present invention, an eating disorder treatment device may provide weekly training based on user group (emotion after eating) 820. Weekly training may be provided as weekly training corresponding to the corresponding eating disorder problem for each user group (emotion after eating) 820 having similar eating disorder problems.

Additionally, the eating disorder treatment device may determine when to provide weekly training to the minimum user group 830. The minimum user group 830 may have a similar meal pattern, and weekly training is provided before and after a meal in consideration of the meal pattern of the minimum user group 830, so that the minimum user group 830 eats before and after a meal depending on the purpose of the training. Disability training can be provided.

Additionally, according to an embodiment of the present invention, comments on the meal diary may be provided considering the user group (emotion after meal) 820 and the minimum user group 830. As described above, separate comments are set for breakfast, lunch, dinner, and snacks in the meal diary, which can help with the user's eating disorder. Accordingly, taking into account the characteristics of the user group (post-meal emotions) 820 and the minimum user group 830, contextual comments may be provided in the meal diary after the meal.

Figure 9 is a conceptual diagram showing a method for determining user improvement in an eating disorder treatment device according to an embodiment of the present invention.

In Figure 9, a method for determining whether a user's eating disorder is improved according to changes in the user's eating pattern and user cluster is disclosed.

Referring to FIG. 9 , an improved meal pattern 920 for each user, which is determined as a default, is set, and it may be determined that the user's eating disorder is improved as the user meal pattern 910 changes to the improved meal pattern 920. The improved meal pattern 920 may be set differently depending on the current user meal pattern 910 and the eating disorder the user has. Considering the degree to which the user's eating pattern 910 approaches the improved eating pattern 920, the degree of improvement of the user's eating disorder may be quantified and provided.

In addition, based on changes in the user cluster, the improvement in the user's eating disorder can be quantified and judged as data.

A normal user cluster 980 is defined, and the center of the user cluster 950 is the center of the normal user cluster 960 based on the user cluster 950 created by periodically collecting information about the user's emotions after eating. Based on the degree to which the user is getting closer, improvement in the user's eating disorder can be quantified.

In addition, disappearance of the user cluster 950, such as a decrease in the user cluster 950 corresponding to the eating disorder, can also be used to quantify and determine improvement in the eating disorder. For example, there are existing two user clusters 950, and the two user clusters 950 correspond to complex eating disorders, and then the two user clusters 950 can be reduced to one user cluster 950. In this case, it can be judged as an improvement in the user's eating disorder and quantified.

In addition, changes in the width of the user cluster 950 can also be used to quantify improvement in the user's eating disorder. For example, the width of the user cluster 950 may mean the psychological fluctuation range of emotions after eating due to the current user's eating disorder. Accordingly, it may be determined that the user's eating disorder improves as the area of the user cluster 950 becomes smaller.

The embodiments according to the present invention described above can be implemented in the form of program instructions that can be executed through various computer components and recorded on a computer-readable recording medium. The computer-readable recording medium may include program instructions, data files, data structures, etc., singly or in combination. Program instructions recorded on the computer-readable recording medium may be specially designed and configured for the present invention, or may be known and usable by those skilled in the computer software field. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical recording media such as CD-ROMs and DVDs, and magneto-optical media such as floptical disks. medium), and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, flash memory, etc. Examples of program instructions include not only machine language code such as that created by a compiler, but also high-level language code that can be executed by a computer using an interpreter or the like. A hardware device can be converted into one or more software modules to perform processing according to the invention and vice versa.

In the above, the present invention has been described in terms of specific details, such as specific components, and limited embodiments and drawings, but this is only provided to facilitate a more general understanding of the present invention, and the present invention is not limited to the above embodiments. Anyone with ordinary knowledge in the technical field to which the invention pertains can make various modifications and changes from this description.

Therefore, the spirit of the present invention should not be limited to the above-described embodiments, and the scope of the patent claims described below as well as all scopes equivalent to or equivalently changed from the scope of the claims are within the scope of the spirit of the present invention. It will be said to belong to

Claims (6)

How to provide eating disorder digital treatment:
an eating disorder treatment device generating a meal diary based on user input; and
Including the step of the eating disorder treatment device providing cognitive behavioral therapy and eating disorder training based on the eating diary,
The meal diary includes at least one of the following information about meal date, meal type, meal time, number of people who ate together, meal location, meal menu, and feelings after the meal,
The user interface for selecting the type of meal displays contextual text generated based on information about emotions after the meal,
The cognitive behavioral therapy is performed by the user entering information about the sensation felt in the body, selecting an emotion related to the sensation, objectifying the emotion, and providing an explanation to correct the perception of the emotion,
The eating disorder treatment is carried out based on stopping guessing, eating disorder first aid kit, and weekly training,
The lever guessing stop is provided in conjunction with the cognitive behavioral therapy to perform treatment for the user's thoughts, emotions, and behavior,
The eating disorder first aid kit provides recommended content related to eating disorders,
The weekly training is a method characterized in that it provides content for treating eating disorders on a weekly basis based on a plurality of sessions. According to paragraph 1,
The eating disorder treatment device groups the user based on meal diary data included in the meal diary of the user and provides different user disorder training for each user group,
The user group includes a user group (meal pattern) and a user group (emotion after meal),
The user group (meal pattern) is determined based on the meal pattern determined based on the meal diary data,
The user group (emotion after meal) is determined based on the emotion after meal determined based on the meal diary data,
The minimum user group is determined by considering the vector value used to determine the user group (eating pattern) based on the user group (emotion after meal),
The weekly training is provided based on the user group (emotion after meal),
A method wherein the timing of providing the weekly training is determined based on the meal pattern of the minimum user group. According to paragraph 2,
The eating disorder treatment device sets an improved meal pattern for each user, and determines that the user's eating disorder improves as the user's meal pattern changes to the improved meal pattern,
The improved eating pattern is set differently depending on the current user eating pattern and the user's eating disorder,
The eating disorder treatment device provides quantification of the degree of improvement in the user's eating disorder by considering the degree to which the user's eating pattern approaches the improved eating pattern,
The eating disorder treatment device defines a normal user cluster, and the degree to which the center of the user cluster approaches the center of the normal user cluster based on the user cluster generated by periodically collecting information about the user's emotions after eating. A method characterized in that quantification of improvement in the eating disorder of the user based on . The eating disorder treatment device for eating disorder digital treatment is,
Create a meal diary based on user input,
Implemented to provide cognitive behavioral therapy and eating disorder training based on the food diary,
The meal diary includes at least one of the following information about meal date, meal type, meal time, number of people who ate together, meal location, meal menu, and feelings after the meal,
The user interface for selecting the type of meal displays contextual text generated based on information about emotions after the meal,
The cognitive behavioral therapy is performed by the user entering information about the sensation felt in the body, selecting an emotion related to the sensation, objectifying the emotion, and providing an explanation to correct the perception of the emotion,
The eating disorder treatment is carried out based on stopping guessing, eating disorder first aid kit, and weekly training,
The lever guessing stop is linked with the cognitive behavioral therapy to perform treatment on the user's thoughts, emotions, and behavior,
The eating disorder first aid kit provides recommended content related to eating disorders,
The weekly training is an eating disorder treatment device characterized in that it provides content for treating eating disorders on a weekly basis based on a plurality of sessions. According to paragraph 4,
The eating disorder treatment device groups the user based on meal diary data included in the meal diary of the user and provides different user disorder training for each user group,
The user group includes a user group (meal pattern) and a user group (emotion after meal),
The user group (meal pattern) is determined based on the meal pattern determined based on the meal diary data,
The user group (emotion after meal) is determined based on the emotion after meal determined based on the meal diary data,
The minimum user group is determined by considering the vector value used to determine the user group (eating pattern) based on the user group (emotion after meal),
The weekly training is provided based on the user group (emotion after meal),
An eating disorder treatment device, characterized in that the timing of providing the weekly training is determined based on the eating pattern of the minimum user group. According to clause 5,
The eating disorder treatment device sets an improved meal pattern for each user, and determines that the user's eating disorder improves as the user's meal pattern changes to the improved meal pattern,
The improved eating pattern is set differently depending on the current user eating pattern and the user's eating disorder,
The eating disorder treatment device provides quantification of the degree of improvement in the user's eating disorder by considering the degree to which the user's eating pattern approaches the improved eating pattern,
The eating disorder treatment device defines a normal user cluster, and the degree to which the center of the user cluster approaches the center of the normal user cluster based on the user cluster generated by periodically collecting information about the user's emotions after eating. An eating disorder treatment device, characterized in that quantifies the improvement of the user's eating disorder based on .

Images