KR20220105718A - Ai-based ersonalized prediction service that links physical and patent information - Google Patents

Abstract

The present invention relates to an artificial intelligence-based healthcare service providing device including: a user health information management unit that receives user health information including user information input from a user and user condition information including at least one actually measured biometric information; a user exercise information management unit configured to receive user exercise information obtained by measuring the user's exercise amount; an external environmental information management unit that collects environmental harmful information outside the user according to the user's current location; an information analysis processing unit that analyzes the user's health information, the user's exercise information, and the environmental harmful information to predict a disease likely to occur to the user; and a healthcare service providing unit that presents a healthcare role model to the user according to the predicted disease of the user and guides alleviation of the disease of the user by providing the eating and exercise habits of the role model. It is possible to provide information and services related to the alleviation of possible diseases and improvement in user's physical functions.

Description

AI-based personalized prediction service linking body information and patent information {AI-BASED ERSONALIZED PREDICTION SERVICE THAT LINKS PHYSICAL AND PATENT INFORMATION}

The present invention relates to an artificial intelligence-based health care service providing technology, and more particularly, to an artificial intelligence-based system that can provide information and services related to improvement of a user's physical function and possible diseases based on the user's daily exercise amount. It relates to a device for providing health care services.

Recently, as many people are interested in health, they consume health functional supplements or exercise at a sports center. As more and more people visit sports centers, the sports center-related market is growing rapidly, and artificial intelligence (AI), big data, cloud computing, and the Internet of things (IoT) are The development of the 4th industrial technology is causing many changes in the healthcare market and products.

On the other hand, heart disease, chronic lung disease, kidney disease, diabetes, high blood pressure, arthritis, etc., including cancer, are called chronic diseases because they do not occur instantly but are chronic degenerative diseases over a long period of time. Chronic diseases are diseases caused by improper lifestyle and refer to a group of diseases that are affected by lifestyle habits such as eating habits, exercise habits, recreation, smoking, and drinking on the onset and progression of diseases. Accordingly, recently, health care technologies capable of predicting and managing a user's health state by introducing an artificial intelligence element have been developed.

Korea Patent Registration No. 10-1927669 (2018.12.04) relates to a method of providing a customized health care service algorithm linked to a mobile terminal, the subject evaluation step of evaluating the subject's lifestyle according to a predetermined criterion, and the subject Content provision step of providing customized contents determined through the target classification step and the target evaluation step, and after providing the customized contents for a preset period, reevaluate the target person's lifestyle or new data collected from the National Health Insurance Corporation server It includes a monitoring step that compares it with the health checkup data. Korean Patent Registration No. 10-1381520 (2014.03.28) relates to a ubiquitous healthcare service system and method using an in-house communication network, which measures the biometric information of a user who is a health care target and uses an access point (AP) through wireless communication. ), but when a transmission error occurs due to a communication failure, a biometric information measuring means for storing the measured biometric information in the storage unit and retransmitting it when the communication failure is resolved, and a biometric information measuring means receiving the By including the access point (AP) for delivery to the ubiquitous healthcare service server system through the telephone network (PSTN), the biometric information of a chronically ill patient requiring continuous management is periodically measured and delivered to the server through the home network, The server collects and analyzes it, provides it to users through individual homepages on the web, and also connects with medical institutions or health clubs, so that users' health can be managed comprehensively and systematically.

An embodiment of the present invention is to provide an artificial intelligence-based health care service providing apparatus capable of providing information and services related to improvement of a user's physical function and disease that may occur based on the user's daily exercise amount.

An embodiment of the present invention analyzes the user's questionnaire, exercise amount, various living body and external environment-related sensing information.

We aim to provide an artificial intelligence-based health care service providing device that allows users to improve their eating and exercise habits and manage their health by following the role model by presenting the most suitable health care role model for users.

An embodiment of the present invention provides an artificial intelligence-based health care service providing device that provides customized health coaching services to users through role models and can provide health analysis and counseling services based on artificial intelligence (AI).

In embodiments, an artificial intelligence-based healthcare service providing apparatus includes a user health information management unit configured to receive user health information including user information input from a user and user state information including at least one measured biometric information, the user health information management unit, the A user exercise information management unit that receives user exercise information obtained by measuring the user's exercise amount, an external environment information management unit that collects harmful environmental information outside the user according to the current location of the user, the user health information and the user exercise information and the An information analysis processing unit that analyzes environmental harmful information to predict a disease likely to develop in the user, and a health care role model to the user according to the user's predicted disease It includes a health care service provider to guide the improvement of the user's disease by providing.

The user exercise information management unit is measured through a sensor worn on the user or mounted on the exercise equipment used by the user, one or more of the exercise amount information including the number of times of exercise of the user, the exercise item, the number of steps or an estimated amount of calories consumed It can be included as exercise information. The information analysis processing unit selects a disease likely to develop by associating relevant user health information with user exercise information and environmental harmful information, calculates an onset prediction index of the disease by the following equation, and calculates the onset prediction index by the following equation It can be calculated by multiplying the weight for the main information related to the disease.

[Equation]

Here, P is an outbreak prediction index, U is user health information, U0 is a preset reference value for user health information, C is user exercise information, C0 is a preset reference value for user exercise information, E is environmental harmful information, and E0 is The preset reference value for environmental hazardous information, T, represents the exposure time.

The information analysis processing unit generates a disease prediction model by modeling user health information and user exercise information through machine learning based on national health statistical data, and generates the user health information and the user exercise information based on the disease prediction model. By analyzing it, it is possible to predict the possibility of developing a disease of the corresponding user.

The healthcare service provider may provide a role model for providing customized health coaching and artificial intelligence (AI)-based health analysis counseling for the user's potential health risks.

The healthcare service provider may display the role model on a smart mirror or a hologram virtual space and coach exercise and diet management for user health through the role model.

The health care service provider provides the user terminal with a percentile along with a color-coded bar image according to the level of the user's disease risk rate, and recommends a diet for the disease at the risk level to provide a disease improvement service. have.

The healthcare service providing unit provides a role model for each disease to the user terminal, and when a role model is set by the user, the role model's daily life menu is provided as a notification message to induce the user to eat according to the role model's diet. can

The disclosed technology may have the following effects. However, this does not mean that a specific embodiment should include all of the following effects or only the following effects, so the scope of the disclosed technology should not be construed as being limited thereby.

The artificial intelligence-based healthcare service providing apparatus according to an embodiment of the present invention may provide information and services related to improvement of a user's physical function and possible diseases based on the user's daily exercise amount.

The artificial intelligence-based healthcare service providing apparatus according to an embodiment of the present invention analyzes the user's questionnaire, exercise amount, and various biological and external environment-related sensing information and presents the most suitable health care role model for the user, allowing the user to become a role model. By following this, you can improve your eating and exercise habits and manage your health.

The artificial intelligence-based health care service providing apparatus according to an embodiment of the present invention can provide a customized health coaching and analysis counseling service to a potential health risk group of a user by using a cyber model or a trainer of a sports center as a model

1 is a diagram illustrating an artificial intelligence-based healthcare service providing system according to an embodiment of the present invention.
FIG. 2 is a block diagram illustrating an apparatus for providing a healthcare service in FIG. 1 .
3 is a block diagram illustrating functional elements of the processor in FIG. 2 ;
4 is a flowchart illustrating an AI-based healthcare service provision process according to an embodiment of the present invention.
FIG. 5 is an exemplary diagram illustrating a user's disease onset prediction analysis report provided to the user terminal of FIG. 1 .
FIG. 6 is an exemplary view illustrating a role model selection screen for each possible disease that is provided to the user terminal of FIG. 1 .

Since the description of the present invention is merely an embodiment for structural or functional description, the scope of the present invention should not be construed as being limited by the embodiment described in the text. That is, since the embodiment is capable of various changes and may have various forms, it should be understood that the scope of the present invention includes equivalents capable of realizing the technical idea. In addition, since the object or effect presented in the present invention does not mean that a specific embodiment should include all of them or only such effects, it should not be understood that the scope of the present invention is limited thereby.

On the other hand, the meaning of the terms described in the present application should be understood as follows.

Terms such as “first” and “second” are for distinguishing one component from another, and the scope of rights should not be limited by these terms. For example, a first component may be termed a second component, and similarly, a second component may also be termed a first component.

When a component is referred to as being “connected” to another component, it may be directly connected to the other component, but it should be understood that other components may exist in between. On the other hand, when it is mentioned that a certain element is "directly connected" to another element, it should be understood that the other element does not exist in the middle. Meanwhile, other expressions describing the relationship between elements, that is, “between” and “between” or “neighboring to” and “directly adjacent to”, etc., should be interpreted similarly.

The singular expression is to be understood to include the plural expression unless the context clearly dictates otherwise, and terms such as "comprises" or "have" refer to the embodied feature, number, step, action, component, part or these It is intended to indicate that a combination exists, and it should be understood that it does not preclude the possibility of the existence or addition of one or more other features or numbers, steps, operations, components, parts, or combinations thereof.

Identifiers (eg, a, b, c, etc.) in each step are used for convenience of description, and the identification code does not describe the order of each step, and each step clearly indicates a specific order in context. Unless otherwise specified, it may occur in a different order from the specified order. That is, each step may occur in the same order as specified, may be performed substantially simultaneously, or may be performed in the reverse order.

The present invention can be embodied as computer-readable codes on a computer-readable recording medium, and the computer-readable recording medium includes all types of recording devices in which data readable by a computer system is stored. Examples of the computer-readable recording medium include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, hard disk storage device, and the like.

All terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present invention belongs, unless otherwise defined. Terms defined in the dictionary should be interpreted as being consistent with the meaning of the context of the related art, and cannot be interpreted as having an ideal or excessively formal meaning unless explicitly defined in the present application.

1 is a diagram illustrating an artificial intelligence-based healthcare service providing system according to an embodiment of the present invention.

Referring to FIG. 1 , an artificial intelligence-based healthcare service providing system 100 includes a healthcare service providing device 110 , at least one sensor 120 , a wearable device 130 , a user terminal 140 , and a smart mirror. (150).

The healthcare service providing device 110 corresponds to a computing device that can be connected to at least one sensor 120 , the wearable device 130 , the user terminal 140 , and the smart mirror 150 through a network.

At least one sensor 120 may be connected to the healthcare service providing device 110 through a network based on IoT. In an embodiment, the at least one sensor 120 is at least one first sensor 120a that measures or senses the user's bio-related information within a specific sensing area to generate the measured value, and the user's external environment. Alternatively, it may include a second sensor 120b for generating harmful environment information by sensing harmful substances, and a third sensor 120c for generating a measurement value by measuring user's exercise-related information. Here, the first sensor 120a may be worn on the user's body or set in a space where the user stays. The second sensor 120b may be repeatedly disposed for each specific unit area over one or more wide areas. The third sensor 120c may be worn on the user's body or mounted on at least one exercise device that the user exercises.

For example, the first sensor 120a may be implemented as a blood pressure monitor, a blood glucose meter, or a body composition meter for measuring the height/weight/body mass of the user. The second sensor 120b is a temperature-humidity sensor that measures the temperature and humidity in the sensing area, a harmful substance sensor that senses the amount of harmful substances such as environmental hormone substances or carcinogens, and fine particles of environmental pollutants in the air, fine/ultra-fine dust, etc. It may be implemented as an atmospheric environment sensor that senses the amount of particles. The third sensor 120c may output the user's exercise data to the outside and may be implemented as a treadmill or the like. Here, in the case of an exercise equipment used by a large number of people, it may be implemented to distinguish it from measurement of an exercise amount of other users through user identification. For example, user biometric information such as facial recognition or fingerprint recognition may be used to identify a user and measure an exercise amount for each user.

The wearable device 130 is a computing device that can be connected to the healthcare service providing device 110 through a network. In one embodiment, the wearable device 130 is an accessory type, a fabric/clothing integrated type, a body attached type, or a bioimplantation type. It is implemented as a wearable device of a type to measure the user's bio data periodically or aperiodically, but is not limited thereto, and it is implemented as a portable device to measure bio data under the control of the user. there is also In an embodiment, the wearable device 130 may come into contact with the user's body or penetrate a specific body to generate bio data including at least one of sleep time, pulse, activity amount, high blood pressure, and diabetes, and sensing for each. It can be implemented by including sensor modules.

The user terminal 140 corresponds to a computing device that can be connected to the healthcare service providing device 110 through a network, and may be implemented as, for example, a desktop, a laptop computer, a tablet PC, or a smart phone.

In one embodiment, the at least one sensor 120 , the wearable device 130 , and the user terminal 140 may be implemented as a computing device independent of each other, and in another embodiment, at least some of them are one computing device. It can be implemented integrally in the device.

The smart mirror 150 corresponds to a display device that can be connected to the healthcare service providing device 110 through a network, and is usually a mirror, but when the user approaches, it can be implemented as a display that provides customized healthcare information to the user. have.

FIG. 2 is a block diagram illustrating an apparatus for providing a healthcare service in FIG. 1 .

Referring to FIG. 2 , the healthcare service providing apparatus 110 may include a processor 210 , a memory 220 , a user input/output unit 230 , and a network input/output unit 240 .

The processor 210 may execute the health care service providing procedure shown in FIG. 4 , and manage the memory 220 read or written in this process, and between the volatile memory and the non-volatile memory in the memory 220 . Synchronization time can be scheduled. The processor 210 may control the overall operation of the healthcare service providing device 110 , and is electrically connected to the memory 220 , the user input/output unit 230 , and the network input/output unit 240 to control the data flow between them. can be controlled The processor 210 may be implemented as a central processing unit (CPU) of the healthcare service providing apparatus 110 .

The memory 220 is implemented as a non-volatile memory, such as a solid state disk (SSD) or a hard disk drive (HDD), and may include an auxiliary storage device used to store overall data required for the healthcare service providing device 110 . and may include a main memory implemented as a volatile memory such as random access memory (RAM). [0055] The user input/output unit 230 includes an environment for receiving a user input and an environment for outputting specific information to the user, for example, a mouse, a trackball, a touch pad, a graphic tablet, a scanner, a touch screen, It may include an input device including an adapter such as a keyboard or pointing device, and an output device including an adapter such as a monitor. In an embodiment, the user input/output unit 230 may correspond to a computing device accessed through a remote connection.

The network input/output unit 240 includes an environment for connecting with at least one of the at least one sensor 120 , the wearable device 130 , and the user terminal 140 , and, for example, performs local area network (LAN) communication. may include an adapter for

3 is a block diagram illustrating functional elements of the processor in FIG. 2 ;

Referring to FIG. 3 , the processor 210 includes a user health information management unit 310 , a user exercise information management unit 320 , an external environment information management unit 330 , an information analysis processing unit 340 , and a healthcare service providing unit 350 . may include.

The user health information management unit 310 may receive and manage user health information input or measured from the user. The user health information may include user information directly input by the user and user state information measured through a measurement tool.

User information is one of membership registration information (age, gender, region, marriage, childbirth, region, etc.) created by the user when registering as a member, medical questionnaire, food intake, usual diet, medical history, family history, treatment history, surgery history, and allergies. It may include the above information. Such user information may be information that the user fills in while signing up as a member to use the health care service, or may be information added and supplemented from time to time after membership registration.

In addition, the user information may be medical and health-related records held by the National Health Insurance Corporation for the user. Alternatively, the user information may include health checkup result data, various prescription and medication data for the user, and long-term care data for the elderly.

In addition, when registering as a member or operating a health care service providing system, the health care service providing device may provide and fill out a health-related questionnaire to the user, and then use the answers of the questionnaire as user information.

Other user information may include health-related information personally created and entered by the user. User information may include everything from relatively simple basic information such as height, weight, and body fat to more detailed information such as past medical history, family history, allergies, diet, lifestyle, and exercise habits.

In an embodiment, the user health information management unit 310 may manage personal health records for each user. The user health information management unit 310 may receive specific disease data designated by the user from the user terminal 140 and reflect it in the user's personal health record. The user health information management unit 310 may update the user's personal health record by interworking with a medical institution server (not shown) under the approval of the user.

The user health information management unit 310 may receive and manage user state information obtained by measuring the user's physical state through at least one sensor 120 or the wearable device 130 .

The user status information may be biometric information including at least one of a user's blood sugar, blood pressure, cholesterol, and body fat, but is not limited thereto, and the user's heart rate, respiration rate, and sleep time (which may include bedtime and wake-up time) , body temperature, etc. may include all measurable body information related to the user's physical function and chronic disease prediction. Measurement of user status information may be performed automatically or manually.

When the user's biometric information is measured by the sensor 120 , the biometric information may be transmitted to the user's health information manager 310 in the memory 220 or the healthcare service providing device 110 through a network. If biometric information measured by an external sensor and stored in an external server is used, the healthcare service providing apparatus 110 may receive the biometric information through the network input/output unit 240 .

And here, the sensor may be an external sensor connected to an external server, rather than a sensor included in the healthcare service providing system. However, if the external server and the healthcare service providing device can be connected and data can be shared, data measured by a sensor connected to the external server can also be utilized as user biometric information according to an embodiment of the present invention.

When the sensor measures the user's biometric information, the user's biometric information may be transmitted to the healthcare service providing device through the network.

In an embodiment, the user health information management unit 310 may generate and update user status information by collecting the user's biometric information before, during, or after the user exercises or during a specific time period.

The user exercise information management unit 320 measures the exercise amount of the user to obtain and manage the user exercise information. The user exercise information is information measured by the wearable device 130 worn by the user or the sensor 120 located in the exercise equipment used by the user, and includes exercise amount information such as the number of times of exercise, the type of exercise, the number of steps or an estimate of consumed calories. can do.

In one embodiment, the user exercise information management unit 320 receives the user's bio-data from the wearable device 130, classifies the user's sleep amount and activity amount, and calculates the number of steps and calories consumed based on the amount of activity as the user's daily exercise amount. can manage

The external environmental information management unit 330 collects and manages environmental harmful information outside the user according to the current location of the user.

Environmental hazardous information may also be measured by the sensor 120 . In this case, the sensor for measuring environmental harmful information is a sensor for measuring the numerical value of the user's external environmental factors, unlike the sensor for measuring the user's biometric information. The numerical value can be sensed and the result can be provided to the health care service providing device as environmental harmful information. As another example, the external environmental information management unit 330 through the sensor 120, temperature and humidity, carbon monoxide (CO), carbon dioxide (CO2), ozone, carcinogens such as formaldehyde or bisphenol or environmental hormone substances, radon, etc. It is possible to obtain environmental hazard information by sensing.

As described above, the environmental harmful information may be measured by one or more sensors 120 that are physically separated from the healthcare service providing device 110 but connectable through a wired/wireless communication network.

Since the environmental hazard information indicates the environmental hazard factors of the location where the user is located, it can be measured by the device installed on the user. Alternatively, after the sensors are evenly distributed over a wide area, the measurement value of the sensor 120 or measuring station closest to the current user's location may be used as environmental harmful information near the user.

Therefore, the environmental hazardous information stored in the external environmental information management unit 330 may include temperature and humidity information, daily temperature information, air quality information, pollutant information, hazardous material information, UV index, and radioactivity values of the location where the user is located, and the user may include the salinity level of the food eaten by

In addition, the external environmental information management unit 330 may subdivide the above-described environmental harmful information according to the degree of harmfulness. That is, the external environmental information management unit 330 may display the environmental hazardous information as an environmental hazard index within a specific numerical range, for example, 0 to 10 or -10 to 10, 0 to 100 according to the degree of risk, severity, pollution, etc.

Here, temperature and humidity information, air quality information, pollutant information, hazardous material information, UV index, radiation level, etc. may be merged and quantified as one or more comprehensive numerical values, or each factor may be calculated as separate environmental hazardous information and environmental hazardous index. have.

In an embodiment, the external environmental information management unit 330 receives the salinity measurement value of the food consumed by the user from the first sensor 120a and receives the fine dust measurement value from the second sensor 120b to provide environmental harmful information. can be included In the above, the environmental hazardous information has been described as an embodiment including salinity and fine dust measurement values, but is not limited thereto, and various other substances or atmospheric environment that can be classified as hazardous substances corresponding to the onset factors of chronic diseases. It may include measurement values for various other gases or particles that can be classified as contamination measurement targets.

The information analysis processing unit 340 may analyze the user's health information, exercise information, and environmental harmful information to predict the user's physical function and disease likely to occur. In an embodiment, the information analysis processing unit 340 may relate the user's health information and exercise information in consideration of the importance of each user in a specific aspect and the relevance of the external environment, ie, environmental harmful information. For example, it can be used to derive the lung disease incidence index in association with environmental harmful information about air pollution and the amount of respiration or exercise. Alternatively, temperature and humidity, sleep time, exercise amount, etc. may be used in connection with deriving the onset index of heart disease.

Here, the information analysis processing unit 340 may generate a disease prediction model by modeling user health information and user exercise information through case learning. For example, the information analysis processing unit 340 obtains health information and exercise information for each disease as learning data from national health statistics, and calculates the possibility of the user's disease (eg, hypertension, diabetes, hyperlipidemia, obesity, etc.) on the basis of the learning data. You can learn through learning. The information analysis processing unit 340 may analyze the user's health information and exercise information based on the machine learning result to predict the possibility of the user's disease onset.

In an embodiment, the information analysis processing unit 340 determines the number of steps in the user exercise information as the reference number of steps (eg, 5000) or the average number of user steps during a specific time period (eg, during the last 3 months). It is possible to generate physical fitness data indicating the relative size of the user's physical strength based on the difference between the comparison values by comparing and analyzing the . Here, the information analysis processing unit 340 may express the physical fitness data as a grade constant that corresponds to a fitness grade and is calculated as a natural number within a specific range.

In an embodiment, the information analysis processing unit 340 may analyze the personal health record to detect the user's disease data and generate a health safety factor related to the disease data as a user-dependent health safety factor. For example, the information analysis processing unit 340 reads the personal health record associated with the user managed by the user health information management unit 310 to detect the presence or absence of disease data of the user, and specific disease data (eg, [mild] of diabetes]) is detected, a health safety factor (eg, diabetes) associated with the disease data may be generated as a user-dependent health safety factor. Here, the association between the disease data and the health and safety factors may be preset and changed by a designer or a user.

In one embodiment, the information analysis processing unit 340 is based on the user's health information, the user's exercise information, and the environmental harmful information, the user's body function and lifestyle (eg, eating habits, exercise habits, etc.) related to the disease risk rate can be calculated. Here, the lifestyle-related diseases may include six chronic diseases of hypertension, diabetes, obesity, hyperlipidemia, stomach cancer, and colorectal cancer, and may additionally include diseases affected by the environment according to environmental harmful information.

The information analysis processing unit 340 may calculate a selection and onset prediction index of a disease that is likely to develop by associating relevant user health information, user exercise information, and environmental harmful information. For example, the prediction of the onset of hypertension may be calculated by correlating user health information, such as age, weight, family history, eating habits, smoking status, blood pressure, and the like, with user exercise information, such as the amount of exercise of the user.

First, the onset prediction index (P) may be calculated by Equation 1 below.

[Equation 1].

P is an outbreak prediction index, U is user health information, U0 is a preset reference value for user health information, C is user exercise information, C0 is a preset reference value for user exercise information, E is environmental harmful information, E0 is environmental harmful information A preset reference value for information, and T is the exposure time (hour).

The information analysis processing unit 340 may set user health information having relatively high importance to the user as a fixed main factor by reflecting the user's disease information. For example, user health information or environmental harmful information related to a previous medical history or family history may be set as a major factor. That is, in the case of a user with a previous or family history of colorectal cancer, the total calorie intake or amount of exercise may be set as a major factor. Information set as the main factor may be calculated by adding a weight (w) when calculating the disease onset prediction index. If the number of steps in the exercise amount for the user is set as the main factor, it can be calculated by multiplying the number of steps by the weight w. This can be expressed by Equation 2 below.

[Equation 2]

The information analysis processing unit 340 may calculate the onset prediction stage by subdividing the disease onset prediction index from the first stage to the tenth stage according to an increase in the onset probability. That is, the onset prediction index of 1 to 10 is the first stage, 11 to 20 is the second stage, 21 to 30 is the third stage, etc., and the healthcare service providing device 110 generates the onset prediction stage information according to the calculated value of the onset prediction index. It can be provided together with the disease name and/or information on the disease to be predicted.

The healthcare service provider 350 derives and provides healthcare information for health improvement recommended to the user according to the predicted disease and the predictive index of the disease. In an embodiment, the healthcare service provider 350 may provide guide information for improving a habit of a user based on a possible disease of the user. Here, the user habit improvement guide information may be implemented in a form that allows the user to set a role model and informs the lifestyle of the set role model. For example, the healthcare service provider 350 presents a healthcare role model to the user according to the user's onset predicted disease, and when the role model is set by the user, provides the role model's eating habits and exercise habits so that the user eats according to the role model and may be encouraged to exercise.

The health care service providing unit 350 may provide a customized health care service for each disease that can be developed by the user through a role model. Here, the role model refers to a sample for user-customized self-care, and a cyber model or a trainer at a sports center can be set as a model, but is not limited thereto, and the self-care of a celebrity or user with a healthy image is stimulated You can model various people who can do it.

The healthcare service provider 350 may provide a user-customized health coaching service through a role model. In an embodiment, the healthcare service provider 350 may provide a user-customized exercise through the smart mirror 150 and induce the user to manage health through exercise habits. Here, the healthcare service provider 350 displays the role model on the smart mirror 150 so that the user can exercise along the role model displayed on the smart mirror 150 . For example, the smart mirror may be implemented using a glass mirror of a sports center, a bathroom mirror of a home, or the like.

The healthcare service provider 350 may provide a service so that a user can receive a customized health coaching role model through a mirror in a sports center or home based on the cloud. In one embodiment, the healthcare service provider 350 displays a role model on the smart mirror 150 when a user approach is detected on the smart mirror 150, and at least one sensor 120 and a wearable device 130 through the role model. ) and information collected through the user terminal 140 may provide voice and video health coaching including customized exercise or diet management to users who have been authenticated. Here, the health care service provider 350 may provide a customized health consultation service to the user by interactively performing with the user through a role model based on artificial intelligence (AI).

The healthcare service provider 350 may provide customized health coaching and health counseling activities for role models in cyberspace using holograms.

In addition, the health care service provider 350 may recommend a customized diet for each disease and manage health through eating habits.

For example, the health care service provider 350 may provide a recommended diet tailored to the recommended calorie (1,600 kcal) for obesity prevention as shown in the example of [Table 1] below.

Table 1

When a disease suspected or concerned is selected by the information analysis processing unit 340, the healthcare service provider 350 provides a recommended food corresponding to the disease, a place to purchase the recommended food, and a recommended diet or corresponding recommended food using the recommended food. It is possible to derive user-customized healthcare information, which is additional information optimized for users, such as a medical center recommended for a disease, and provide it to the user. In addition, when the onset prediction index is relatively low, customized healthcare information such as behavioral guidelines, recommended diet, recommended food, and exercise method is provided. , it is a method of providing information on available drugs and places of purchase, and differential information may be provided according to the size of the outbreak prediction index. A reference value may be set in advance for the magnitude of the incidence prediction index. For example, when the user is at a risk level for developing diabetes, the health care service provider 350 transmits health care information including at least one of recommended exercise information, recommended meal information, and recommended activity information for the user's blood sugar control to the user terminal ( 140) can be provided. For example, when the user's blood glucose level is at a hypoglycemic level less than a preset level, the healthcare service provider 350 provides a service for requesting emergency rescue to a nearby medical institution based on the location of the user terminal 140 . may be

4 is a flowchart illustrating an AI-based healthcare service provision process according to an embodiment of the present invention.

First, the healthcare service providing apparatus 110 according to an embodiment of the present invention receives user information input through the user terminal 140 and user status information obtained by measuring the user's biometric as user health information (step S410 ). ). The user information may correspond to information input by a user through the user terminal 140 . User information includes user membership registration information (age, gender, height, weight, etc.), health checkup information from the Health Insurance Corporation, and user health questionnaire and questionnaire information (drinking, smoking, lifestyle, disease, etc.) can The user state information may correspond to user biometric information measured automatically or manually through at least one sensor 120 or a measurement tool such as the wearable device 130 . The user status information may include In-Body (BMI) information, blood pressure, blood sugar, and the like. The healthcare service providing apparatus 110 may be connected to the sensor 120 or the wearable device 130 through a network through wired or wireless. The user state information is measured by an external sensor outside the health care service providing system 100, and when the user state information is stored in an external server connected to the sensor, the health care service providing device 110 communicates with the external server. It is also possible to receive user status information from an external server by attempting a connection.

And the healthcare service providing device 110 receives the user's exercise information obtained by measuring the user's exercise amount (step S420). The user exercise information may correspond to information measured during the user's exercise through various IoT-based sensors 120 installed in the exercise equipment used by the user or the user's wearable device 130 . The user exercise information may include the number of exercise times, exercise items, exercise quantity, and the like, and the exercise quantity may be obtained by measuring the number of steps and calorie consumption.

In addition, the healthcare service providing apparatus 110 may collect environmental harmful information outside the user according to the current user's location (step S430). Here, the harmful environmental information outside the user may be measured by the sensor 120 or the user wearable device 130 . Since the harmful environmental information is only information about the surrounding environment where the user is currently located, the healthcare service providing apparatus 110 may reset the measurement location in real time based on the location-based service of the user terminal 140 . .

Environmental harmful information may also be measured by the sensor 120 or the user wearable device 130 and then transmitted to the healthcare service providing device 110 . To this end, the healthcare service providing apparatus 110 may use a wired/wireless communication network with the sensor 120 or the wearable device 130 .

The healthcare service providing device 110 analyzes user health information, user exercise information, and environmental harmful information (step S440). And as a result of the analysis, a disease determined to be likely to develop in the user and a risk rate of the disease are calculated (step S450).

As the basis for determining that a specific disease is likely to develop in the user, information entered by the user through the user terminal 140 such as the user's medical history, family history, eating habits, and lifestyle, and the user's current blood pressure, pulse rate, respiration rate, etc. By using the information on the amount of exercise of the information user and the environmental harmful information as an environmental factor, the healthcare service providing apparatus 110 may derive a disease that may occur in the user. In addition, quantified data, that is, the incidence risk rate is calculated as a percentile (%) of how high the risk of contracting the disease is and provided to the user terminal 140 . The health care service providing device 110 provides information on the user's basic constitution, medical history, and characteristics that may affect the onset of a specific disease, the user's current biometric information, and environmental factors affecting the onset of the disease Considering these factors, it is possible to calculate the risk of disease by quantifying it. In particular, in this process, Equation 1 or Equation 2 described above may be used.

In addition, the health care service providing apparatus 110 may perform a role model service that provides customized health care information for a disease having an onset risk according to the calculation result of the onset risk rate (S460). The role model service means to provide a role model that provides customized health coaching and health counseling service through a mirror or hologram cyberspace, along with a warning about the user's potential health risks. Customized health coaching may include information on exercise, diet management, and the like. For health counseling, based on artificial intelligence (AI), interactive counseling between role models and users can be performed to provide analytical counseling services.

5 is an exemplary diagram illustrating a user's disease onset prediction analysis report provided to the user terminal of FIG. 1 .

In FIG. 5 , the user terminal 140 interworks with the healthcare service providing device 110 through the healthcare service providing agent installed by the user to analyze the onset prediction of the disease from the healthcare service providing device 110 . can be provided. In the user's analysis report, the user's disease risk rate may be converted into a percentile (%) and displayed together with a bar image. In this case, the bar image may be displayed with different colors according to the risk level of the disease incidence. For example, the disease incidence rate may be divided into four levels of normal, caution, warning, and risk, and a bar image and a risk rate value may be displayed by classifying the color into blue, yellow, orange, and red according to each level. The user's analysis report may also provide a disease improvement service by recommending a diet for a disease at a risk level.

FIG. 6 is an exemplary view illustrating a role model selection screen for each possible disease that is provided to the user terminal of FIG. 1 .

In FIG. 6 , the healthcare service providing apparatus 110 may provide a role model for each disease, and when the user sets a role model for the disease, the user terminal 140 informs the user of the role model's diet, so that the user can choose the role model's diet. Make sure you follow it every day. For example, it is possible to induce the user to eat a low-sodium meal by notifying the user that the role model set by the user ate a low-sodium meal with natto tofu salad and milk between 7 and 9 a.m. in the morning.

Although the above has been described with reference to preferred embodiments of the present invention, those skilled in the art can variously modify and change the present invention within the scope without departing from the spirit and scope of the present invention as set forth in the claims below. You will understand that it can be done.

100: AI-based healthcare service provision system
110: health care service providing device
120: at least one sensor 130: wearable device
140: user terminal 150: smart mirror
210: processor
310: user health information management unit 320: user exercise information management unit
330: external environmental information management unit 140: information analysis processing unit
350: health care service provider

Claims (7)

a user health information management unit for receiving user health information including user information input from the user and user status information including at least one measured biometric information;
One or more of the exercise amount information including the number of times of exercise of the user, the exercise item, the number of steps or an estimated calorie consumption obtained by measuring the exercise quantity of the user through a sensor worn by the user or mounted on the exercise equipment used by the user a user exercise information management unit for receiving user exercise information including;
an external environmental information management unit that collects environmental harmful information outside the user according to the current user's location;
an information analysis processing unit that analyzes the user health information, the user exercise information, and the environmental harmful information to predict a disease that is likely to develop in the user; and
According to the disease predicted onset of the user, a health care role model is presented to the user, and a health care service providing unit for guiding the improvement of the user's disease by providing the role model's eating habits and exercise habits, wherein the user exercise information management unit When a plurality of users use the exercise equipment, the user is identified through the biometric information and the amount of exercise for each user is divided and measured, and the healthcare service provider displays the role model in a smart mirror or a hologram virtual space, An artificial intelligence-based healthcare service providing device, characterized in that it provides voice and video health coaching including exercise and diet management for user health. According to claim 1, wherein the information analysis processing unit
By associating relevant user health information with user exercise information and environmental harmful information, a disease with a potential for onset is selected, the onset prediction index of the disease is calculated by the following equation, and main information related to the disease when the onset prediction index is calculated Artificial intelligence-based healthcare service providing device, characterized in that for calculating by multiplying the weight.
[Equation]

Here, P is an outbreak prediction index, U is user health information, U0 is a preset reference value for user health information, C is user exercise information, C0 is a preset reference value for user exercise information, E is environmental harmful information, and E0 is The preset reference value for environmental hazardous information, T, represents the exposure time.
According to claim 1, wherein the information analysis processing unit
Based on the national health statistical data, the user health information and user exercise information are modeled through machine learning to generate a disease prediction model, and based on the disease prediction model, the user health information and the user exercise information are analyzed and the user's An artificial intelligence-based healthcare service providing device, characterized in that it predicts the possibility of disease onset. According to claim 1, wherein the health care service providing unit
Artificial intelligence-based healthcare service providing apparatus, characterized in that it provides a role model for providing customized health coaching and AI-based health analysis counseling for the user's potential health risks. The method of claim 5, wherein the health care service providing unit
A cyber model or a sports center trainer, a celebrity with a healthy image, or a person who can emotionally stimulate the user's self-care as a role model, and interactively with the user through the role model to provide a customized health consultation service to the user AI-based healthcare service providing device. According to claim 1, wherein the health care service providing unit
Artificial intelligence-based, characterized in that the user's disease risk rate is provided to the user terminal as a percentile along with a color-coded bar image according to the level, and a diet is recommended for the disease at the risk level to provide a disease improvement service A device for providing healthcare services. The method of claim 6, wherein the health care service providing unit
Artificial intelligence, characterized in that by providing a role model for each disease to the user terminal, and when the role model is set by the user, the role model's daily life menu is provided as a notification message to induce the user to eat according to the role model's diet based healthcare service provider.

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