KR102745815B1 - Personalized care service for Atopic Dermatitis - Google Patents

Abstract

An atopic care service providing system according to one embodiment of the disclosed invention may include a skin information receiving unit configured to receive a skin lesion image of a user from a camera; an atopic type determining unit configured to determine an atopic lesion type for the skin lesion image using a first artificial intelligence model based on the skin lesion image; an atopic severity determining unit configured to determine an atopic severity for the skin lesion image using a second artificial intelligence model based on the skin lesion image; and a display display screen generating unit configured to generate information of an analysis result screen to be displayed on a display of a user terminal based on the atopic lesion type for the skin lesion image and the atopic severity for the skin lesion image.

Description

{Personalized care service for Atopic Dermatitis}

The present invention relates to an atopic care service providing system that allows users to check analysis results on their own skin.

Changes in living environments due to socioeconomic growth are factors that cause and worsen allergic diseases, and the number of patients with allergic diseases has been steadily increasing since 2000. Atopic dermatitis is a representative allergic disease along with allergic rhinitis and asthma. According to disease statistics from the Health Insurance Review and Assessment Service, the number of patients with atopic dermatitis was estimated at approximately 970,000 in 2020. Of these, the proportion of infants under the age of 9 accounted for approximately 33.9%, and the proportion of patients in their teens and adolescence accounted for approximately 16.8%, showing that infants and children account for a significant proportion.

Meanwhile, the conventional method of providing analysis services for atopic symptoms only provides disease information, personal lifestyle habits, skin photos and hospital treatment history records, graphs/charts, and product recommendations, but there is a problem in that individual service users cannot easily receive customized analysis results for their affected area without being limited by location.
Meanwhile, related prior art includes Korean Patent Publication No. 10-2022-0018813 published on February 15, 2022.

The present invention provides an atopic care service providing system and a control method of the atopic care service providing system, which allows a user to take a picture of an atopic dermatitis area by himself or herself without the help of a specialist and to check the analysis results of his or her atopic dermatitis area remotely.

In addition, the present invention provides an atopic care service providing system and a control method of the atopic care service providing system that can assist a non-expert user to appropriately photograph an atopic dermatitis area.

In addition, the present invention provides an atopic care service providing system including an IoT device capable of appropriately photographing an atopic dermatitis area and a control method of the atopic care service providing system.

In addition, the present invention provides an atopic disease care service providing system capable of additionally providing a microbiome analysis service to a user who has analyzed an atopic dermatitis area, and a control method of the atopic care service providing system.

An atopic care service providing system according to one aspect of the disclosed invention may include: a skin information receiving unit configured to receive a skin lesion image of a user from a camera; an atopic type determining unit configured to determine an atopic lesion type for the skin lesion image using a first artificial intelligence model based on the skin lesion image; an atopic severity determining unit configured to determine an atopic severity for the skin lesion image using a second artificial intelligence model based on the skin lesion image; and a display display screen generating unit configured to generate information of an analysis result screen to be displayed on a display of a user terminal based on the atopic lesion type for the skin lesion image and the atopic severity for the skin lesion image.

In addition, the camera is provided and a skin information measuring device configured to transmit the skin lesion image to the skin information receiving unit is further included, and the skin information measuring device may include: an SCH sensor for obtaining skin moisture information and skin oil information of the user; and a TEWL sensor for obtaining transepidermal water loss information of the user.

In addition, the skin information measuring device may further include: a light-emitting element that generates light; and a measuring device processor that controls the light-emitting element to irradiate light toward the user's skin when the camera acquires a skin lesion image.

In addition, the skin information measuring device further includes a distance sensor configured to obtain distance information between the user's skin and the camera when the camera obtains a skin lesion image, and the measuring device processor can control the light emitting element so that the intensity of light generated by the light emitting element increases as the distance between the user's skin and the camera increases based on the distance information between the user's skin and the camera.

In addition, the skin information measuring device may further include a communication unit configured to transmit the skin affected area image, the skin moisture information, the skin oil information, and the transdermal moisture loss information to the skin information receiving unit using at least one of a Wi-Fi communication method and a Bluetooth communication method.

In addition, the device may further include an affected area extraction unit configured to extract an affected area image, which is an image of an area where atopic lesions are distributed, from the skin affected area image using a third artificial intelligence model based on the skin affected area image, the atopic type determination unit configured to determine an atopic lesion type for the skin affected area image using the first artificial intelligence model based on the affected area image, and the atopic severity determination unit configured to determine an atopic severity for the skin affected area image using the second artificial intelligence model based on the affected area image.

In addition, the method may further include a machine learning unit configured to generate the third artificial intelligence model through a machine learning method by using a plurality of learning skin lesion images as input variables and setting a learning lesion area image corresponding to each learning skin lesion image as an output variable.

In addition, the skin information receiving unit is configured to receive a skin affected area image acquired in real time by the camera, and the display display screen generating unit: generates information of an affected area photographing auxiliary screen that includes the skin affected area image acquired in real time and is displayed on the display of the user terminal; and generates information of the affected area photographing auxiliary screen so that information for inducing the camera to move to a position where an affected area image of an appropriate size can be acquired based on a relative size of the extracted affected area image to the skin affected area image is displayed on the display of the user terminal.

In addition, the display display screen generation unit may be configured to: generate information of the affected area photographing auxiliary screen so that information to indicate positioning the camera closer to the user's skin is displayed on the display of the user terminal when the relative size of the affected area image to the skin affected area image is less than a first reference ratio; and generate information of the affected area photographing auxiliary screen so that information to indicate positioning the camera further away from the user's skin is displayed on the display of the user terminal when the relative size of the affected area image to the skin affected area image is greater than or equal to a second reference ratio.

In addition, the method may further include a machine learning unit configured to generate the first artificial intelligence model through a machine learning method by using a plurality of learning skin lesion images as input variables and setting a learning atopic lesion type preset to correspond to each learning skin lesion image as an output variable.

In addition, the method may further include a machine learning unit configured to generate the second artificial intelligence model through a machine learning method by using a plurality of learning skin lesion images as input variables and setting a learning atopy severity level that is preset to correspond to each learning skin lesion image as an output variable.

In addition, the display screen generation unit may be configured to generate information on the analysis result screen such that information on whether a dermatological examination is necessary, recommended medicine information, recommended cosmetics information, and recommended food information corresponding to the atopic lesion type and the atopic dermatitis severity are displayed on the display of the user terminal.

In addition, the display screen generation unit may be configured to generate information on the analysis result screen so that information recommending microbiome analysis to the user is displayed on the display of the user terminal.

In addition, the display screen generation unit may be configured to generate information on the analysis result screen so that, if the atopic severity for the skin lesion image is higher than the standard severity, information recommending microbiome analysis for the user is displayed on the display of the user terminal.

In addition, the system may further include a user input receiving unit configured to receive input information input through the user terminal; and a fecal analysis result receiving unit configured to receive first fecal analysis result information generated based on the microbiome analysis result for the first feces for the user and input through the administrator terminal after the user input receiving unit receives the microbiome analysis request information.

In addition, the display display screen generation unit may be configured to generate information of a microbiome analysis result screen that includes the first fecal analysis result information and recommended medicine information, recommended cosmetic information, and recommended food information corresponding to the first fecal analysis result information, and is displayed on the display of the user terminal.

In addition, the fecal analysis result receiving unit may be configured to receive second fecal analysis result information generated based on the microbiome analysis result for second feces of the user and input through the administrator terminal after receiving the first fecal analysis result information.

In addition, the display display screen generation unit may be configured to generate information on a microbiome analysis result screen displayed on a display of the user terminal, including information on whether the user's health has improved between the time of acquisition of the first feces and the time of acquisition of the second feces, based on the first feces analysis result information and the second feces analysis result information.

A control method of an atopic care service providing system according to one aspect of the disclosed invention comprises the steps of: receiving a user's skin lesion image from a camera by a skin information receiving unit; extracting an area in which an atopic lesion is distributed from the skin lesion image as an lesion area image by a lesion area extracting unit based on the skin lesion image using a third artificial intelligence model; determining an atopic lesion type for the skin lesion image by an atopic type determining unit using a first artificial intelligence model based on the lesion area image; determining atopic severity for the skin lesion image by an atopic severity determining unit using a second artificial intelligence model based on the lesion area image; generating information of an analysis result screen displayed on a display of a user terminal based on the atopic lesion type for the skin lesion image and the atopic severity for the skin lesion image by a display display screen generating unit; receiving a skin lesion image acquired by the camera in real time by the skin information receiving unit; A step for generating, by the display display screen generating unit, information of an auxiliary screen for photographing a affected area, which includes the skin affected area image acquired in real time and is displayed on the display of the user terminal; A step for generating, by the display display screen generating unit, information of the auxiliary screen for photographing a affected area, so that information for inducing the camera to move to a position where an affected area image of an appropriate size can be acquired, based on the relative size of the extracted affected area image to the skin affected area image, is displayed on the display of the user terminal; A step for generating, by the display display screen generating unit, information of the auxiliary screen for photographing a affected area, so that information for instructing the camera to be positioned closer to the user's skin is displayed on the display of the user terminal if the relative size of the affected area image to the skin affected area image is less than a first reference ratio; A step for generating, by the display display screen generating unit, information of the auxiliary screen for photographing a affected area, so that information for instructing the camera to be positioned further away from the user's skin is displayed on the display of the user terminal if the relative size of the affected area image to the skin affected area image is greater than or equal to a second reference ratio; A step for generating information of the analysis result screen so that information on whether a dermatological examination is necessary, information on recommended medicines, information on recommended cosmetics, and information on recommended foods corresponding to the atopic lesion type and the atopic dermatitis severity, is displayed on the display of the user terminal by the display display screen generating unit; A step for generating information of the analysis result screen so that information recommending a microbiome analysis for the user is displayed on the display of the user terminal if the atopic dermatitis severity for the skin lesion image is higher than the reference severity level by the display display screen generating unit; A step for receiving input information input through the user terminal by the user input receiving unit; A step for receiving, after the user input receiving unit receives the microbiome analysis request information, first fecal analysis result information generated based on the microbiome analysis result for first feces for the user and input through the administrator terminal by the fecal analysis result receiving unit; The method may include: generating, by the display screen generating unit, information on a microbiome analysis result screen that includes the first fecal analysis result information and recommended medicine information, recommended cosmetic information, and recommended food information corresponding to the first fecal analysis result information, and that is displayed on the display of the user terminal; receiving, by the fecal analysis result receiving unit, second fecal analysis result information generated based on the microbiome analysis result for second feces for the user and input through the administrator terminal after receiving the first fecal analysis result information; and generating, by the display screen generating unit, information on a microbiome analysis result screen that includes information on whether the user's health has improved between the acquisition time of the first feces and the acquisition time of the second feces, and that is displayed on the display of the user terminal.

A computer program according to one aspect of the disclosed invention can be stored in a computer-readable, non-transitory recording medium to execute a control method of the atopic care service providing system.

According to one aspect of the disclosed invention, a user can take a picture of an atopic dermatitis area by himself or herself without the help of a professional, and check the analysis results of his or her atopic dermatitis area remotely.

In addition, according to an embodiment of the present invention, it is possible to assist non-expert users in properly photographing atopic dermatitis areas.

In addition, according to an embodiment of the present invention, an IoT device capable of appropriately photographing an atopic dermatitis area may be included.

In addition, according to an embodiment of the present invention, a microbiome analysis service can be additionally provided to a user who has analyzed an atopic dermatitis area.

Figure 1 is a control block diagram of an atopic care service providing system according to one embodiment.
FIG. 2 is a diagram illustrating a skin information measuring device according to one embodiment.
FIG. 3 is a diagram for explaining a process for performing analysis on an atopic dermatitis area according to one embodiment.
FIG. 4 is a drawing for explaining a refund photography assistance screen that displays information intended to guide a camera to approach a refund according to one embodiment.
FIG. 5 is a drawing for explaining a refund shooting assistance screen that displays information intended to induce the camera to move away from the refund according to one embodiment.
Figure 6 is a drawing for explaining an analysis result screen according to one embodiment.
FIG. 7 is a diagram illustrating a process for performing microbiome-based analysis according to one embodiment.
FIG. 8 is a diagram illustrating a screen of a microbiome-based analysis result according to one embodiment.
FIG. 9 is a diagram illustrating a process of displaying an analysis result screen by a healthcare app according to one embodiment.
FIG. 10 is a diagram illustrating a configuration displayed in an app of an atopic care service according to one embodiment.
FIG. 11 is a diagram illustrating an analysis result screen on which recommended food information is displayed according to one embodiment.
FIG. 12 is a diagram illustrating an analysis result screen providing stress care service according to one embodiment.
FIG. 13 is a diagram illustrating an analysis result screen that displays analysis results for beneficial bacteria according to one embodiment.
Figure 14 is a flowchart of a method for providing an atopic care service according to one embodiment.
Figure 15 is a flowchart of a method for providing a microbiome analysis service according to one embodiment.

Like reference numerals refer to like elements throughout the specification. This specification does not describe all elements of the embodiments, and general information within the technical field to which the disclosed invention pertains or information that is redundant between the embodiments is omitted.

Additionally, when a part is said to "include" a component, this does not mean that it excludes other components, but rather that it may include other components, unless otherwise specifically stated.

The '~ unit' used in this specification refers to a unit that processes at least one function or operation, and may mean, for example, a software, FPGA, or hardware component. The function provided by the '~ unit' may be performed separately by multiple components, or may be integrated with other additional components. The '~ unit' of this specification is not necessarily limited to software or hardware, and may be configured to be in an addressable storage medium, and may be configured to reproduce one or more processors. According to embodiments, multiple '~ units' may be implemented as one component, or one '~ unit' may include multiple components.

The terms first, second, etc. are used to distinguish one component from another, and the components are not limited by the aforementioned terms.

Singular expressions include plural expressions unless the context clearly indicates otherwise.

The identification codes in each step are used for convenience of explanation and do not describe the order of each step. Each step may be performed in a different order than specified unless the context clearly indicates a specific order.

The working principle and embodiments of the disclosed invention will be described with reference to the attached drawings below.

Figure 1 is a control block diagram of an atopic care service providing system according to one embodiment.

The atopic care service providing system (100) may be a system configured to allow a user to take a picture of his or her own or another user's skin, analyze the type or severity of atopic dermatitis for the taken skin image, and generate an analysis result screen (400) that may be displayed on a display or may include the analysis result. However, the type of atopy that the atopic care service providing system (100) can analyze is not necessarily limited to atopy.

The atopic care service provision system (100) is provided on a server and can communicate with at least one user terminal (500) and an administrator terminal via wired or wireless means.

The user terminal (500) may be a terminal used by a user who wishes to obtain analysis results for atopic symptoms using the atopic care service providing system (100). The user may check the analysis result screen (400) generated by the atopic care service providing system (100) through the display of the user terminal (500). The administrator terminal may be a terminal of an administrator who provides an atopic care service.

Meanwhile, the atopic care service providing system (100) according to one embodiment is not necessarily limited to being provided on a server and transmitting analysis result data or information of an analysis result screen (400) to a user terminal (500) through communication with the user terminal (500). For example, if the user terminal (500) downloads the atopic care service providing system (100) by downloading an application from a server, the atopic care service providing system (100) may be provided on the user terminal (500). That is, as long as the user can capture a skin affected area image (300) through a camera (210) and check an analysis result screen (400) for the skin affected area image (300) through the user terminal (500), the atopic care service providing system (100) does not matter on which terminal or server the atopic care service providing system (100) is provided and in what manner it is operated.

Referring to FIG. 1, an atopic care service providing system (100) may include a skin information receiving unit (111), a user input receiving unit (112), a fecal analysis result receiving unit (113), an affected area extracting unit (120), an atopic type determining unit (130), an atopic severity determining unit (140), a display screen generating unit (150), a memory (160), a machine learning unit (170), and a skin information measuring device (200).

The skin information receiving unit (111) can receive a skin affected area image (300) of the user from the camera (210). The skin affected area image (300) may be an image taken of the skin of the user suspected of having atopic symptoms.

When the atopic care service providing system (100) is provided on a server, the skin information receiving unit (111) can receive a skin affected area image (300) acquired by a camera (210) provided in the skin information measuring device (200) from the skin information measuring device (200). Alternatively, the skin information receiving unit (111) can receive a skin affected area image (300) acquired by a camera (210) provided in the user terminal (500) from the user terminal (500).

If the atopic care service providing system (100) is provided in the user terminal (500), the skin information receiving unit (111) can receive the skin affected area image (300) acquired by the camera (210) provided in the skin information measuring device (200) from the skin information measuring device (200). Alternatively, the skin information receiving unit (111) can directly receive the skin affected area image (300) acquired by the camera (210) provided in the user terminal (500) from the camera (210) of the user terminal (500) without going through another device or server. In other words, it does not matter how the image receiving unit (110) receives the skin affected area image (300).

The skin information receiving unit (111) can transmit the skin affected area image (300) to the affected area extraction unit (120), the atopic type determination unit (130), or the atopic severity determination unit (140).

The atopic type determination unit (130) can determine the atopic lesion type for the skin lesion image (300) using the first artificial intelligence model (161) based on the skin lesion image (300). The first artificial intelligence model (161) can be an artificial intelligence model used to determine the atopic lesion type corresponding to the input skin lesion image (300).

Atopic lesion types can be the types that are divided when atopic dermatitis is classified into four general types. For example, the atopic lesion type of a specific atopic dermatitis can be one of acute atopic dermatitis, chronic atopic dermatitis, infantile eczema, and non-atopic eczema. However, the types of atopic lesion types are not necessarily the four types or limited to the types mentioned above.

The atopic type determination unit (130) can transmit the determined atopic lesion type to the display screen generation unit (150).

The atopic severity judgment unit (140) can determine the atopic severity for the skin affected area image (300) using the second artificial intelligence model (162) based on the skin affected area image (300). The second artificial intelligence model (162) can be an artificial intelligence model used to determine the atopic severity corresponding to the input skin affected area image (300).

The severity of atopy can be the degree of symptoms that are divided when the severity of atopic dermatitis is classified into four general stages. For example, the severity of a specific atopic dermatitis can be one of the following: stage 1, which does not interfere with daily life; stage 2, which is severe itching and skin inflammation; stage 3, which is severe itching, dry skin, cracking of the skin, and the possibility of skin infection; and stage 4, which is severely dry and cracking of the skin, and severely restricts daily life. However, the severity of atopic lesion types is not necessarily limited to the four stages or the aforementioned stages.

The atopy severity judgment unit (140) can transmit the determined atopy severity to the display screen generation unit (150).

The display display screen generation unit (150) can generate information of the analysis result screen (400) based on the atopic lesion type for the skin lesion image (300) and the atopic lesion severity for the skin lesion image (300). Specifically, the display display screen generation unit (150) can generate signals or information necessary to generate the analysis result screen (400). The user terminal (500) can display the analysis result screen (400) on the display based on the information of the analysis result screen (400).

The analysis result screen (400) may be a screen displayed on the display of the user terminal (500). The analysis result screen (400) may be a screen including information on whether a dermatological examination is necessary corresponding to the atopic lesion type and atopic dermatitis severity corresponding to the skin lesion image (300) taken by the user, information on recommended medicines, information on recommended cosmetics, and information on recommended foods.

When the atopic care service system is provided on a server, the server can transmit information of the analysis result screen (400) to the user terminal (500) so that the analysis result screen (400) can be displayed on the display of the user terminal (500). When the atopic care service system is provided on the user terminal (500), the display display screen generation unit (150) can directly transmit information of the analysis result screen (400) to the processor that controls the display of the user terminal (500).

The artificial intelligence models, such as the first artificial intelligence model (161), the second artificial intelligence model (162), and the third artificial intelligence model (163), may be stored in the memory (160) of the atopic care service providing system (100). Meanwhile, the artificial intelligence models, such as the first artificial intelligence model (161), the second artificial intelligence model (162), and the third artificial intelligence model (163), are not necessarily separate artificial intelligence models that are distinct from each other. For example, the first artificial intelligence model (161), the second artificial intelligence model (162), and the third artificial intelligence model (163) may be completely the same artificial intelligence models, and the artificial intelligence models may only be expressed differently, and there is only one artificial intelligence model according to the present invention, and one artificial intelligence model may perform all deep learning operations of the present invention.

The machine learning unit (170) can create a first artificial intelligence model (161) through a machine learning method by using multiple learning skin lesion images as input variables and setting a learning atopic lesion type that is preset to correspond to each learning skin lesion image as an output variable.

The machine learning unit (170) can create a second artificial intelligence model (162) through a machine learning method by using multiple learning skin lesion images as input variables and setting a pre-set learning atopy severity level corresponding to each learning skin lesion image as an output variable.

Machine learning can mean using a model composed of multiple parameters and optimizing the parameters with given data. Machine learning can include supervised learning, unsupervised learning, and reinforcement learning depending on the type of learning problem. Supervised learning is learning the mapping between inputs and outputs, and can be applied when input and output pairs are given as data. Unsupervised learning is applied when there are only inputs and no outputs, and can find regularities between inputs, etc.

The machine learning unit (170) can generate an artificial intelligence model in various ways. For example, the machine learning unit (170) can learn features extracted from learning skin lesion images using a deep learning-based learning method. At this time, a CNN (Convolutional Neural Networks) structure that stacks several stages of convolution layers can be utilized to learn a method of extracting features from learning skin lesion images. However, the learning method of the machine learning unit (170) is not necessarily limited to a method utilizing the CNN structure. For example, the learning method of the machine learning unit (170) can be a method using a machine learning algorithm including an ANN (artificial neural network) or an RNN (recurrent neural network).

A user may capture an image (300) of a skin lesion for which an atopic dermatitis symptom is to be analyzed using his/her user terminal (500), but may also capture the image using a camera (210) provided in an IoT device specialized for capturing skin lesions.

FIG. 2 is a diagram illustrating a skin information measuring device according to one embodiment.

Referring to FIGS. 1 and 2, a skin information measuring device (200) may be provided with a camera (210) and may include a SCH sensor (220), a TEWL sensor (230), a distance sensor (240), and a light-emitting element (250).

The skin information measuring device (200) can transmit a skin affected area image (300) acquired through a camera (210) to a skin information receiving unit (111).

The SCH sensor (220) can obtain the user's skin moisture information and skin oil information. Specifically, the SCH sensor (220) can measure skin moisture information by measuring the electrical characteristics of the skin when the electrode comes into contact with the skin, and calculating the moisture content of the skin based on this. In addition, the SCH sensor (220) can measure skin oil information by measuring the amount of oil absorbed from the skin in contact with an oil absorbent paper for a certain period of time.

The TEWL sensor (230) can obtain the user's transepidermal water loss (TEWL) information. The transepidermal water loss information is not a parameter that directly indicates moisture in the stratum corneum, but is closely related to the barrier function and moisturizing function. The TEWL sensor (230) can measure the integrity of the skin barrier and the moisture protection function by measuring the rate at which moisture on the skin surface evaporates into the environment. For example, the TEWL sensor (230) can measure the amount of moisture evaporating from the epidermis by obtaining the vapor pressure for moisture diffusing into the air from the skin surface. In general, the TEWL value increases as the skin becomes drier, and the TEWL value may increase due to damage to the skin barrier or skin disease.

The light-emitting element (250) can generate light. The light-emitting element (250) can include a daylight LED (251) that generates light in the visible light range and a UV LED (252) that generates light in the ultraviolet light range.

The measuring device processor (270) can control the light emitting element (250) to irradiate light toward the user's skin when the camera (210) acquires a skin lesion image (300). The light in the visible light range or ultraviolet light range that is irradiated toward the skin can illuminate the skin so that the camera (210) can acquire an image of appropriate brightness when capturing the skin lesion.

The distance sensor (240) can obtain distance information between the user's skin and the camera (210) when the camera (210) obtains a skin target image (300). The distance sensor (240) can obtain distance information between the user's skin and the camera (210) when the camera (210) is turned on. The method by which the distance sensor (240) obtains distance information may be a method of measuring the time it takes for the ultrasonic waves or light generated by the distance sensor (240) to be reflected from the skin and return, but is not limited thereto.

It may be desirable for the camera (210) to obtain a skin lesion image (300) of consistent brightness regardless of the distance from the skin.

The measuring device processor (270) can control the light emitting element (250) so that the intensity of light generated by the light emitting element (250) increases as the distance between the user's skin and the camera (210) increases based on distance information between the user's skin and the camera (210). In addition, the measuring device processor (270) can control the light emitting element (250) so that the intensity of light generated by the light emitting element (250) decreases as the distance between the user's skin and the camera (210) decreases based on distance information between the user's skin and the camera (210).

The communication unit (260) provided in the skin information measuring device (200) can transmit skin affected area image (300), skin moisture information, skin oil information, and transdermal moisture loss information to the skin information receiving unit (111) using at least one of a Wi-Fi communication method and a Bluetooth communication method. However, the communication method by which the communication unit (260) transmits information is not limited thereto.

The display display screen generation unit (150) can generate information on an analysis result screen (400) including a skin affected area image (300), skin moisture information, skin oil information, and transdermal moisture loss information.

FIG. 3 is a diagram for explaining a process for performing analysis on an atopic dermatitis area according to one embodiment.

Referring to FIG. 3, it can be confirmed that a skin lesion image (300) acquired by the user through a camera (210) is displayed in real time on the display of the user terminal (500).

After completing the shooting of the affected area with the camera (210), the affected area image (301), which is an image of the area where the atopic affected area is distributed, may be displayed as a box in the acquired skin affected area image (300). The skin affected area image (300) is an image acquired by the user, and if it is acquired by shooting an appropriate affected area at an appropriate location, it may be appropriate as an analysis target. However, if an excessively large area is shot compared to the affected area, it may be problematic. The affected area image (301) may be an image of the area where the affected area is distributed that can be used as an analysis target in the skin affected area image (300).

Thereafter, the atopic care service providing system (100) can perform analysis on the skin affected area image (300) or affected area image (301) and display the analysis results on the display of the user terminal (500).

Specifically, the display display screen generation unit (150) can generate information on the analysis result screen (400) so that information on whether a dermatological examination is necessary, recommended medicine information, recommended cosmetics information, and recommended food information corresponding to the atopic lesion type and atopic dermatitis severity of the skin lesion image (300), is displayed on the display of the user terminal (500).

Referring to FIGS. 1 and 3, the affected area extraction unit (120) can extract an affected area image (301) from a skin affected area image (300) using a third artificial intelligence model (163) based on the skin affected area image (300).

The third artificial intelligence model (163) may be an artificial intelligence model used to extract an affected area image (301) corresponding to an input skin affected area image (300).

The machine learning unit (170) can generate a third artificial intelligence model (163) through a machine learning method by using multiple learning skin lesion images as input variables and setting learning lesion area images (301) corresponding to each learning skin lesion image as output variables.

The atopic type determination unit (130) can determine the atopic lesion type for the skin affected area image (300) using the first artificial intelligence model (161) based on the affected area image (301). The atopic severity determination unit (140) can determine the atopic severity for the skin affected area image (300) using the second artificial intelligence model (162) based on the affected area image (301).

Meanwhile, users who wish to perform atopic symptom analysis may be non-experts in atopic dermatitis. Such users may not know at which location to acquire the skin affected area image (300) through the camera (210) to be most appropriate for analysis.

FIG. 4 is a drawing for explaining a wound photography assistance screen (302) on which information for inducing a camera to approach a wound is displayed according to one embodiment, and FIG. 5 is a drawing for explaining a wound photography assistance screen (302) on which information for inducing a camera to move away from a wound is displayed according to one embodiment.

Referring to FIGS. 4 and 5, it can be seen that a camera photographing assistance screen (302) that assists the user in photographing the affected area is displayed on the display of the user terminal (500). At this time, the camera (210) used by the user may be provided in the user terminal (500) or may be provided in the skin information measuring device (200).

The skin information receiving unit (111) can receive a skin affected area image (300) acquired in real time by the camera (210).

The display display screen generation unit (150) can generate information of a skin lesion image (300) acquired in real time and displayed on the display of the user terminal (500) on the lesion photographing auxiliary screen (302). The user terminal (500) can display a skin lesion photographing auxiliary screen (302) on which a skin lesion image (300) being photographed by the user in real time through a camera (210) is displayed on the display based on the information of the skin lesion photographing auxiliary screen (302).

The display display screen generation unit (150) can generate information on the affected area shooting auxiliary screen (302) so that information for inducing the camera (210) to move to a position where an affected area image (301) of an appropriate size can be acquired based on the relative size of the extracted affected area image (301) to the skin affected area image (300) is displayed on the display of the user terminal (500).

The display display screen generation unit (150) can generate information of the affected area photographing auxiliary screen (302) so that information indicating that the camera (210) should be positioned closer to the user's skin is displayed on the display of the user terminal (500) when the relative size of the affected area image (301) to the skin affected area image (300) is less than the first reference ratio.

For example, if the relative size of the affected area image (301) to the affected area image (300) is less than the first reference ratio, the display display screen generation unit (150) can generate information on the affected area photographing auxiliary screen (302) that displays the message “Please bring the camera closer to the affected area.”

The relative size of the affected area image (301) to the affected area image (300) may be the area of the affected area image (300) relative to the area of the affected area image (301), or may be the horizontal or vertical length of the affected area image (300) relative to the horizontal or vertical length of the affected area image (301).

The first reference ratio may be a preset ratio that serves as a reference for determining whether the camera (210) acquires a skin lesion image (300) from too far away.

The display display screen generation unit (150) can generate information of the affected area photographing auxiliary screen (302) so that information indicating that the camera (210) should be positioned further from the user's skin is displayed on the display of the user terminal (500) when the relative size of the affected area image (301) to the affected area image (300) is greater than or equal to the second reference ratio.

For example, the display display screen generation unit (150) can generate information on a skin injury shooting auxiliary screen (302) that displays a message “Move the camera slightly away from the injury” when the relative size of the injury area image (301) to the skin injury image (300) is greater than or equal to the second reference ratio.

The second reference ratio may be a preset ratio that serves as a reference for determining whether the camera (210) is acquiring a skin lesion image (300) too close.

Figure 6 is a drawing for explaining an analysis result screen according to one embodiment.

Referring to FIGS. 1 and 6, the display display screen generation unit (150) can generate information on the analysis result screen (400) so that information recommending microbiome analysis to the user is displayed on the display of the user terminal (500).

For example, the display display screen generation unit (150) can generate information on an analysis result screen (400) that displays the message “We recommend microbiome analysis.”

Microbiome analysis is an analytical method that studies and analyzes the microbiome of an organism, that is, the microbial community that lives inside or on the surface of the organism. The microbiome can refer to a collection of various microorganisms such as bacteria, fungi, and viruses that exist in the human body. Microbiome analysis can be performed using various methods to understand and explain the composition, diversity, and functions of the microbiome. The commonly used analytical techniques include 16S ribosomal RNA gene sequencing, metagenomic sequencing, genome analysis, genome functional analysis, and protein analysis.

Meanwhile, microbiome analysis can be performed by analyzing human feces. For example, studying the microbiome by analyzing human feces can help analyze the health and disease, immune system, nutrient absorption, digestive process, etc. of the person.

A user inputs microbiome analysis request information requesting microbiome analysis through his/her user terminal (500), transmits his/her feces to an administrator of an atopic care service providing system (100), and then the administrator can check the microbiome analysis results entered through his/her user terminal (500).

The display display screen generation unit (150) can generate information on the analysis result screen (400) so that information recommending microbiome analysis to the user is displayed on the display of the user terminal (500) if the atopic severity for the skin lesion image (300) is higher than the reference severity. The reference severity may be a preset atopic severity that serves as a reference for recommending microbiome analysis.

For example, if the atopic severity for the skin lesion image (300) is stage 3 and the standard severity is stage 2, the display display screen generation unit (150) can generate information on the analysis result screen (400) that displays the message “We recommend microbiome analysis.”

FIG. 7 is a diagram illustrating a process for performing microbiome-based analysis according to one embodiment.

Referring to FIG. 1 and FIG. 7, the user input receiving unit (112) can receive input information entered through the user terminal (500).

The user input receiving unit (112) can transmit the received input information to the display screen generating unit (150) and the fecal analysis result receiving unit (113).

When the user input receiving unit (112) receives microbiome analysis request information, the atopic care service providing system (100) can transmit information or a message to the administrator terminal to perform microbiome-based analysis on the user's stool.

After the administrator confirms the information or message that requests a microbiome-based analysis, the administrator can analyze the user's stool received from the user. At this time, the stool first received by the administrator may be the first stool for the user.

The administrator can generate primary fecal analysis result information based on the microbiome analysis results for the primary feces of the user. The administrator terminal can receive primary fecal analysis result information through the administrator terminal.

Specifically, the fecal analysis result receiving unit (113) can receive the first fecal analysis result information from the administrator terminal after the user input receiving unit (112) receives the microbiome analysis request information.

The display display screen generation unit (150) can generate information of a microbiome analysis result screen (401) that includes first stool analysis result information and recommended medicine information, recommended cosmetics information, and recommended food information corresponding to the first stool analysis result information, and is displayed on the display of a user terminal (500).

After receiving the results of the first microbiome analysis and taking care of their health with the recommended products, users may want to perform a second microbiome analysis to see if there is any improvement.

The administrator can analyze the user's stool received from the user after a certain period of time after performing the microbiome-based analysis for the first time. At this time, the stool received by the administrator for the second time may be the user's secondary stool.

The administrator can generate secondary fecal analysis result information based on the microbiome analysis results for the secondary feces of the user. The administrator terminal can receive secondary fecal analysis result information through the administrator terminal.

Specifically, the fecal analysis result receiving unit (113) can receive secondary fecal analysis result information generated based on the microbiome analysis result for the second feces of the user and input through the administrator terminal after receiving the primary fecal analysis result information.

The display display screen generation unit (150) can generate information on a microbiome analysis result screen (401) displayed on a display of a user terminal (500) including information on whether the user's health has improved between the time of acquisition of the first feces and the time of acquisition of the second feces, based on the first feces analysis result information and the second feces analysis result information.

FIG. 8 is a diagram illustrating a screen of a microbiome-based analysis result according to one embodiment.

Referring to FIG. 8, the configuration of the microbiome analysis result screen (401) displayed on the display of the user terminal (500) can be confirmed.

For example, the display of the user terminal (500) may display the value of the harmful bacteria index for the user, information on whether the value is high compared to the average harmful bacteria index of a specific group, and risk information of the value.

When a user touches 'Check recommended lactic acid bacteria' displayed on the microbiome analysis results screen (401) and inputs it as input information, information such as the type and effectiveness of the recommended lactic acid bacteria product can be displayed on the microbiome analysis results screen (401).

In addition, when the user touches 'Purchase Product' on the microbiome analysis result screen (401) showing the recommended lactic acid bacteria product and inputs the information, a purchase service for the corresponding lactic acid bacteria product can be provided.

The microbiome analysis result screen (401) can display the improved effects after the user purchases and takes the probiotic product in the form of a report on harmful or beneficial bacteria.

FIG. 9 is a diagram illustrating a process of displaying an analysis result screen by a healthcare app according to one embodiment, and FIG. 10 is a diagram illustrating a configuration displayed in an app of an atopic care service according to one embodiment.

Referring to FIG. 9, a user can use the healthcare app service provided by the atopic care service providing system (100) through his/her user terminal (500).

The display screen generation unit (150) can generate information on a chatbot chat screen through which a user can exchange messages with a chatbot. The user terminal (500) can display the chatbot chat screen on the display based on the information on the chatbot chat screen.

A user can input a message of his/her intended content as input information while viewing the chatbot chat screen. The user input receiving unit (112) can receive input information input through the user terminal (500) from the user terminal (500).

The user input receiving unit (112) may be configured to receive input according to the user's intention to manipulate the screen displayed on the display of the user terminal (500). The user may input input information according to his/her intention into the user terminal (500) through the screen displayed on the display.

The user input receiving unit (112) may receive input information in a manner in which a keyboard, button, or mouse provided on a user terminal (500) equipped with a display receives physical force from the user, or may receive input information in a touch input manner on the display, but is not limited thereto. In addition, if the atopic care service providing system (100) is provided on a server, the user input receiving unit (112) may receive input in a manner in which the server's communication module receives an input signal from the user terminal (500), and the user input receiving unit (112) receives the signal from the server's communication module.

A user can input a message containing general information about his or her skin condition through the chatbot chat screen. The atopic care service provision system (100) can analyze the user's skin condition by analyzing the message input by the user through the chatbot chat screen.

The atopic care service provision system may further include a section for determining whether or not to perform an atopic analysis.

The atopy analysis decision unit can use a message analysis artificial intelligence model to determine whether an atopy analysis is necessary based on the message entered by the user through the chatbot chat screen.

The message analysis artificial intelligence model may be a pre-trained artificial intelligence model that sets a message related to atopy as an input variable and sets the necessity of a pre-set atopy analysis for the person who input the message as an output variable. The message analysis artificial intelligence model may be stored in memory (160).

If the atopy analysis decision unit determines that atopy analysis is necessary for a message entered through the chatbot chat screen, the display display screen generation unit (150) can generate information on the display display screen so that an image acquired through the camera (210) is displayed in real time on the display of the user terminal (500). For example, if the atopy analysis decision unit determines that atopy analysis is necessary for a message entered through the chatbot chat screen, the display display screen generation unit (150) can generate information on an affected area photographing auxiliary screen (302) that includes an affected area image (300) acquired in real time and is displayed on the display of the user terminal (500).

Thereafter, the atopic care service providing system (100) may perform an analysis on the skin affected area image (300) or affected area image (301) and display the analysis result on the display of the user terminal (500). For example, the information displayed on the display may include that the atopic severity of the user is 'moderate', the atopic type is 'atopic dermatitis', and the prescription for the user is 'apply a prescription moisturizer three times a day'.

In addition, the atopic care service providing system (100) can display information on recommended services for the user. At this time, the recommended services can include care programs, recommended products, microbiome analysis, and hospital treatment.

Referring to Figure 10, you can check the configurations displayed in the atopic care service app.

The atopic care service providing system (100) can control the app of the atopic care service so that the analysis results for each of the multiple skin affected area images (300) are displayed on the display. In addition, the app of the atopic care service can be controlled so that the analysis results, care guide, analysis report, recommended products, etc. for each skin affected area image (300) are displayed. At this time, the image, product name, and price of the recommended product for each skin affected area image (300) can be displayed on the display. In addition, the type of test recommended for each skin affected area image (300) and the description of the content of each test can be displayed on the display.

FIG. 11 is a drawing illustrating an analysis result screen on which recommended food information is displayed according to one embodiment, and FIG. 12 is a drawing illustrating an analysis result screen that provides a stress care service according to one embodiment.

Referring to Fig. 11, it can be confirmed that a recommended diet for a skin lesion image (300) is displayed on the analysis result screen (400). At this time, if the user touches 'Check alternative diet' displayed on the display and inputs it as input information, the recommended alternative diet can be displayed on the analysis result screen (400).

In addition, when the user touches 'Purchase Product' on the analysis results screen (400) showing the recommended alternative diet and inputs the information, a purchase service for the corresponding product can be provided.

Referring to Fig. 12, it can be confirmed that a stress relief program for a skin lesion image (300) is displayed on the analysis result screen (400). At this time, if the user touches 'Request for Stress Test' displayed on the display and inputs it as input information, a recommended stress relief program can be displayed on the analysis result screen (400). For example, if the user touches 'Request for Stress Test', 'Temple Stay' can be displayed on the display as a recommended stress relief program.

In addition, if a user inputs information indicating that he or she wishes to apply for a stress relief program on the analysis results screen (400) showing the recommended stress relief program, a purchase service for the program can be provided.

FIG. 13 is a diagram illustrating an analysis result screen that displays analysis results for beneficial bacteria according to one embodiment.

Referring to FIG. 13, the atopic care service providing system (100) can display information on non-face-to-face treatment services and doctor consultation services for skin lesion images (300) taken by the user.

For example, the display display screen generation unit (150) can generate screen information for a non-face-to-face medical consultation reservation for a skin lesion image (300) taken by a user, or generate screen information for a doctor consultation.

At least one component may be added or deleted in response to the performance of the components described above. In addition, it will be readily understood by those skilled in the art that the mutual positions of the components may be changed in response to the performance or structure of the system.

Fig. 14 is a flow chart of a method for providing an atopic care service according to one embodiment. This is only a preferred embodiment for achieving the purpose of the present invention, and it is obvious that some components may be added or deleted as needed.

Referring to Fig. 14, the skin information receiving unit (111) can receive a skin affected area image (300) of the user from the camera (210) (1001). The skin information receiving unit (111) can transmit the skin affected area image (300) to the affected area extraction unit (120).

The affected area extraction unit (120) can extract an area where an atopic dermatitis lesion is distributed from the skin affected area image (300) as an affected area image (301) using the third artificial intelligence model (163) based on the skin affected area image (300) (1002).

The display display screen generation unit (150) can generate a skin lesion image (300) acquired in real time and a skin lesion photographing auxiliary screen (302) displayed on the display of the user terminal (500) (1003). At this time, the display display screen generation unit (150) can generate a skin lesion photographing auxiliary screen (302) so that information for inducing the camera (210) to move to a position where an appropriately sized skin lesion image (301) can be acquired based on the relative size of the extracted skin lesion image (301) to the skin lesion image (300) is displayed on the display of the user terminal (500).

The atopic type determination unit (130) can determine the atopic lesion type for the skin lesion image (300) using the first artificial intelligence model (161) based on the skin lesion image (300) (1004).

The atopic dermatitis severity assessment unit (140) can determine the atopic dermatitis severity for the skin lesion image (300) using the second artificial intelligence model (162) based on the skin lesion image (300) (1005).

The display display screen generation unit (150) can generate information on the analysis result screen (400) based on the atopic lesion type for the skin lesion image (300) and the atopic lesion severity for the skin lesion image (300) (1006).

The user terminal (500) can display an analysis result screen on the display (1007).

Figure 15 is a flowchart of a method for providing a microbiome analysis service according to one embodiment.

Referring to FIG. 15, the user terminal (500) can display information on an analysis result screen (400) that displays information recommending microbiome analysis to the user (2001).

A user can input microbiome analysis request information to request microbiome analysis through his/her user terminal (500). The user input receiving unit (112) can receive the microbiome analysis request information (2002). When the user input receiving unit (112) receives the microbiome analysis request information, the atopic care service providing system (100) can transmit information or a message to the administrator terminal to perform a microbiome-based analysis on the user's stool.

The fecal analysis result receiving unit (113) can receive the first fecal analysis result information from the administrator terminal after the user input receiving unit (112) receives the microbiome analysis request information (2003).

The display of the user terminal (500) can display a microbiome analysis result screen (401) including the first fecal analysis result information and the recommended medicine information, recommended cosmetic information, and recommended food information corresponding to the first fecal analysis result information (2004).

The fecal analysis result receiving unit (113) can receive secondary fecal analysis result information generated based on the microbiome analysis result for the second feces of the user and input through the administrator terminal after receiving the primary fecal analysis result information (2005).

The display of the user terminal (500) can display a microbiome analysis result screen (401) including information on whether the user's health has improved between the time of obtaining the first stool and the time of obtaining the second stool (2006).

The skin information receiving unit (111), the user input receiving unit (112), the stool analysis result receiving unit (113), the affected area extracting unit (120), the atopic type determining unit (130), the atopic severity determining unit (140), the display screen generating unit (150), the machine learning unit (170), the communication unit (260), and the measuring device processor (270) may include any one of the multiple processors included in the atopic care service providing system (100). In addition, the atopic care service providing method according to the embodiments of the present invention described so far and the embodiments to be described hereinafter may be implemented in the form of a program that can be driven by a processor.

Here, the program may include program commands, data files, and data structures, either alone or in combination. The program may be designed and produced using machine language codes or high-level language codes. The program may be specifically designed to implement the above-described atopic care service providing method, or may be implemented using various functions or definitions that are known and available to those skilled in the art of computer software. The program for implementing the above-described atopic care service providing method may be recorded on a recording medium readable by a processor. In this case, the recording medium may be a memory (160).

The memory (160) can store a program that performs the operations described above and the operations described below, and the memory (160) can execute the stored program. In the case where there are a plurality of processors and memories (160), they can be integrated into a single chip or can be provided in physically separate locations. The memory (160) can include volatile memory such as S-RAM (Static Random Access Memory) and D-RAM (Dynamic Random Access Memory) for temporarily storing data. In addition, the memory (160) can include nonvolatile memory such as ROM (Read Only Memory), EPROM (Erasable Programmable Read Only Memory), and EEPROM (Electrically Erasable Programmable Read Only Memory) for long-term storage of control programs and control data.

The processor may include various logic circuits and operation circuits, process data according to a program provided from memory (160), and generate a control signal according to the processing result.

As described above, the disclosed embodiments have been described with reference to the attached drawings. Those skilled in the art to which the present invention pertains will understand that the present invention can be implemented in forms other than the disclosed embodiments without changing the technical idea or essential features of the present invention. The disclosed embodiments are exemplary and should not be construed as limiting.

100: Atopic care service provision system
111: Skin information receiving unit
112: User Input Reception Unit
113: Fecal analysis results receiving unit
120: Extraction of the refund area
130: Atopic type determination section
140: Atopic Severity Assessment Section
150: Display display screen generation section
160: Memory
161: The first artificial intelligence model
162: Second Artificial Intelligence Model
163: Third Artificial Intelligence Model
170: Machine Learning Department
200: Skin information measuring device
210: Camera
220: SCH sensor
230: TEWL sensor
240: Distance sensor
250: Light-emitting element
251: Daylight LED
252: UV LED
260: Communications Department
270: Measuring Device Processor
300: Skin lesion image
301: Image of the refund area
302: Refundable Photo Auxiliary Screen
400: Analysis Results Screen
401: Microbiome Analysis Results Screen
500: User Terminal

Claims (20)

A skin information receiving unit configured to receive an image of a user's skin area from a camera;
An atopic type determination unit configured to determine an atopic lesion type for the skin lesion image using a first artificial intelligence model based on the skin lesion image;
An atopic dermatitis severity determination unit configured to determine the atopic dermatitis severity for the skin lesion image using a second artificial intelligence model based on the skin lesion image;
A display screen generation unit configured to generate information on an analysis result screen displayed on a display of a user terminal based on the atopic lesion type for the above skin lesion image and the atopic lesion severity for the above skin lesion image; and
A skin information measuring device is provided with the above camera and configured to transmit the skin affected area image to the skin information receiving unit.
The above skin information measuring device:
SCH sensor for obtaining skin moisture information and skin oil information of the user;
A TEWL sensor for obtaining transepidermal water loss information of the user;
A light-emitting element that produces light;
A measuring device processor that controls the light-emitting element to irradiate light toward the user's skin when the camera acquires an image of the skin area; and
When the above camera acquires a skin area image, it includes a distance sensor configured to acquire distance information between the user's skin and the camera,
The above measuring device processor,
An atopic care service providing system, which controls a light-emitting element so that the intensity of light generated by the light-emitting element increases as the distance between the user's skin and the camera increases based on distance information between the user's skin and the camera. delete delete delete In the first paragraph,
The above skin information measuring device,
An atopic care service providing system further comprising a communication unit configured to transmit the skin lesion image, the skin moisture information, the skin oil information, and the transdermal moisture loss information to the skin information receiving unit using at least one of a Wi-Fi communication method and a Bluetooth communication method. A skin information receiving unit configured to receive an image of a user's skin area from a camera;
An atopic type determination unit configured to determine an atopic lesion type for the skin lesion image using a first artificial intelligence model based on the skin lesion image;
An atopic dermatitis severity determination unit configured to determine the atopic dermatitis severity for the skin lesion image using a second artificial intelligence model based on the skin lesion image;
A display screen generation unit configured to generate information on an analysis result screen displayed on a display of a user terminal based on the atopic lesion type for the above skin lesion image and the atopic lesion severity for the above skin lesion image; and
Based on the above skin lesion image, a lesion area extraction unit is configured to extract an lesion area image, which is an image of an area where atopic lesions are distributed, from the above skin lesion image using a third artificial intelligence model.
The above atopic type determination part is,
It is configured to determine the atopic lesion type for the skin affected area image using the first artificial intelligence model based on the affected area image,
The above atopic dermatitis severity assessment section is,
It is configured to determine the severity of atopy for the skin affected area image using the second artificial intelligence model based on the affected area image,
The above skin information receiving unit,
The above camera is configured to receive a skin affected area image acquired in real time,
The above display display screen generation unit:
Generating a skin injury shooting auxiliary screen displayed on the display of the user terminal while including the skin injury image acquired in real time; and
An atopic care service providing system configured to generate the affected area photographing auxiliary screen so that information for inducing the camera to move to a position where an affected area image of an appropriate size can be acquired based on the relative size of the extracted affected area image to the skin affected area image is displayed on the display of the user terminal. In Article 6,
An atopic care service providing system further comprising a machine learning unit configured to generate the third artificial intelligence model through a machine learning method by setting a plurality of learning skin lesion images as input variables and a learning lesion area image corresponding to each learning skin lesion image as an output variable. delete In Article 6,
The above display display screen generation unit:
If the relative size of the image of the affected area to the image of the affected skin is less than the first reference ratio, information indicating that the camera should be positioned closer to the user's skin is displayed on the display of the user terminal to generate the auxiliary screen for photographing the affected area; and
An atopic care service providing system configured to generate an auxiliary screen for photographing the affected area so that information indicating that the camera should be positioned further from the user's skin is displayed on the display of the user terminal when the relative size of the affected area image to the skin affected area image is greater than or equal to the second reference ratio. In the first paragraph,
An atopic care service providing system further comprising a machine learning unit configured to generate the first artificial intelligence model through a machine learning method by using a plurality of learning skin lesion images as input variables and setting a preset learning atopic lesion type corresponding to each learning skin lesion image as an output variable. In the first paragraph,
An atopic care service providing system further comprising a machine learning unit configured to generate the second artificial intelligence model through a machine learning method by using a plurality of learning skin lesion images as input variables and setting a learning atopic dermatitis severity level that is preset to correspond to each learning skin lesion image as an output variable. In the first paragraph,
The above display screen generation unit,
An atopic care service providing system configured to generate information on the analysis result screen such that information on whether a dermatological examination is necessary corresponding to the atopic lesion type and the atopic dermatitis severity, information on recommended medicines, information on recommended cosmetics, and information on recommended foods are displayed on the display of the user terminal. A skin information receiving unit configured to receive an image of a user's skin area from a camera;
An atopic type determination unit configured to determine an atopic lesion type for the skin lesion image using a first artificial intelligence model based on the skin lesion image;
An atopic severity determination unit configured to determine the atopic severity for the skin lesion image using a second artificial intelligence model based on the skin lesion image; and
A display screen generation unit configured to generate information on an analysis result screen displayed on a display of a user terminal based on an atopic lesion type for the above skin lesion image and an atopic lesion severity for the above skin lesion image,
The above display display screen generation unit:
Information recommending microbiome analysis for the user is configured to be generated on the analysis result screen so that the information is displayed on the display of the user terminal; and
An atopic care service providing system configured to generate information on the analysis result screen so that, if the atopic severity of the above skin lesion image is higher than the standard severity, information recommending microbiome analysis for the user is displayed on the display of the user terminal. delete In Article 13,
A user input receiving unit configured to receive input information entered through the user terminal; and
An atopic care service providing system further comprising a fecal analysis result receiving unit configured to receive, after the user input receiving unit receives microbiome analysis request information, first fecal analysis result information generated based on the microbiome analysis result for the first feces of the user and input through an administrator terminal. In Article 15,
The above display screen generation unit,
An atopic care service providing system configured to generate information on a microbiome analysis result screen displayed on a display of the user terminal, the information including the first fecal analysis result information and the recommended medicine information, recommended cosmetic information, and recommended food information corresponding to the first fecal analysis result information. In Article 16,
The receiving unit of the above fecal analysis results is,
An atopic care service providing system configured to receive, after receiving the first fecal analysis result information, second fecal analysis result information generated based on the microbiome analysis result for the second feces of the user and input through the administrator terminal. In Article 17,
The above display screen generation unit,
An atopic care service providing system configured to generate information on a microbiome analysis result screen displayed on a display of a user terminal, including information on whether the user's health has improved between the time of acquisition of the first feces and the time of acquisition of the second feces, based on the first feces analysis result information and the second feces analysis result information. A step of receiving an image of a user's skin affected area from a camera by a skin information receiving unit;
A step of extracting an area where an atopic dermatitis lesion is distributed from the skin lesion image as an lesion area image using a third artificial intelligence model based on the skin lesion image by the lesion area extraction unit;
A step of determining an atopic lesion type for the skin affected area image using a first artificial intelligence model based on the affected area image by an atopic type determination unit;
A step of determining the atopic severity for the skin affected area image using a second artificial intelligence model based on the affected area image by an atopic severity judgment unit;
A step of generating information of an analysis result screen displayed on a display of a user terminal based on the atopic lesion type for the skin lesion image and the atopic severity for the skin lesion image by a display display screen generating unit;
A step of receiving a skin affected area image acquired in real time by the camera by the skin information receiving unit;
A step of generating a skin area photographing auxiliary screen, which includes the skin area image acquired in real time by the display display screen generating unit, and is displayed on the display of the user terminal;
A step of generating the auxiliary screen for photographing the affected area so that information for inducing the camera to move to a position where an image of the affected area of an appropriate size can be obtained based on the relative size of the extracted affected area image to the skin affected area image is displayed on the display of the user terminal by the display display screen generating unit;
A step of generating the auxiliary screen for photographing the affected area so that information indicating to position the camera closer to the user's skin is displayed on the display of the user terminal when the relative size of the affected area image to the skin affected area image is less than a first reference ratio by the display display screen generating unit;
A step of generating the auxiliary screen for photographing the affected area so that information indicating to position the camera further from the user's skin is displayed on the display of the user terminal when the relative size of the affected area image to the skin affected area image is greater than or equal to a second reference ratio, by the display display screen generating unit;
A step of generating information on the analysis result screen so that information on whether a dermatological examination is necessary, information on recommended medicines, information on recommended cosmetics, and information on recommended foods corresponding to the atopic lesion type and the atopic dermatitis severity are displayed on the display of the user terminal by the display display screen generating unit;
A step of generating information on the analysis result screen so that, if the atopic severity of the skin lesion image is higher than the standard severity, information recommending microbiome analysis for the user is displayed on the display of the user terminal by the display display screen generating unit;
A step of receiving input information input through the user terminal by a user input receiving unit;
A step of receiving, by the user input receiving unit, microbiome analysis request information, and then receiving, by the fecal analysis result receiving unit, first fecal analysis result information generated based on the microbiome analysis result for the first feces of the user and input through the administrator terminal;
A step of generating information of a microbiome analysis result screen that includes the first fecal analysis result information and recommended medicine information, recommended cosmetic information, and recommended food information corresponding to the first fecal analysis result information, by the display display screen generating unit, and displayed on the display of the user terminal;
After receiving the first fecal analysis result information, a step of receiving second fecal analysis result information generated based on the microbiome analysis result for the second feces of the user and input through the administrator terminal by the fecal analysis result receiving unit; and
A control method for an atopic care service providing system, comprising the step of generating information on a microbiome analysis result screen displayed on a display of the user terminal, the information including information on whether the user's health has improved between the time of acquiring the first feces and the time of acquiring the second feces, based on the first feces analysis result information and the second feces analysis result information, by the display display screen generating unit. A computer program stored in a computer-readable, non-transitory recording medium to execute the control method of the atopic care service provision system of Article 19.