KR102554826B1 - Server for managing health and mehtod thereof - Google Patents

Abstract

A method of operating a health management server according to an embodiment of the present invention, comprising: collecting user data and open data; classifying and storing the user data and the open data; setting a health management index reference value based on the user data and the open data; calculating a health management index based on the user data and the open data; Comparing the health management index reference value and the health management index; and generating feedback data when the health management index is smaller than the health management index reference value. It may include; providing the feedback data to the first electronic device.

Description

Health management server and its operating method {SERVER FOR MANAGING HEALTH AND MEHTOD THEREOF}

Embodiments of the present invention relate to a health management server and its operating method.

With the development of wearable devices and communication technology, services using Internet of Things (IoT) technology are expanding. As for wearable devices, innovative products are being launched in various industries, including leading IT companies such as Samsung Electronics, Apple, and Google, as well as companies specializing in sports goods such as Nike and Adidas. Devices are mainly focused on healthcare products for health care and wellness purposes.

On the other hand, quantification of personal activity data has become possible through developed smart device and sensor technology, and as the paradigm of medical service changes from treatment-centered to personal fitness/wellness-centered, the application and spread of wearable devices in the healthcare field is increasing. It can be said that this is the fastest growing area.

With the expansion of the U-healthcare market, the self-quantification market is rapidly growing. In addition, recently, the number of apps that collect personal biometric data in real time and use them for healthcare is increasing, and the trend of self-digitization is creating an environment where self-healthcare can be easily done, while promoting market activation at the same time. Apart from the development of technologies for the Internet of Things, products implementing IoT services using conventional Internet communication technologies and sensor technologies are being released in various fields, but most of the technologies are still in their early stages.

As the rapidly aging society progresses, continuous management of chronic diseases such as diabetes and high blood pressure is required. .

Korean Patent Publication No. 10-2018-0126911 (2017.05.19)

Embodiments of the present invention are aimed at providing a server and its operating method that can manage health in a customized manner by utilizing various data provided by users.

A method of operating a health management server according to an embodiment of the present invention, comprising: collecting user data and open data; classifying and storing the user data and the open data; setting a health management index reference value based on the user data and the open data; calculating a health management index based on the user data and the open data; Comparing the health management index reference value and the health management index; and generating feedback data when the health management index is smaller than the health management index reference value. Providing the feedback data to the first electronic device; may be provided.

According to embodiments of the present invention, it is possible to suggest a user-customized real life habit by continuously monitoring and managing the user's health condition.

In addition, according to the embodiments of the present invention, the user's compliance with medications taken by the user can be determined to give the user a customized prescription, and at the same time, the user's lifestyle, particularly the amount of exercise, can be identified.

1 is an exemplary view showing a system including a health management server according to an embodiment of the present invention.
2 is a diagram showing the configuration of a health management server according to an embodiment of the present invention.
3 is a flow-chart showing the operation of a health management server according to an embodiment of the present invention.
4A is a sequence-chart illustrating operations of a server and a first electronic device that calculate medication compliance according to an embodiment of the present invention.
4b to 4c are conceptual diagrams illustrating the operation of a server for calculating adherence to medication according to an embodiment of the present invention.
4D is a flow chart showing the operation of the server 150 according to an embodiment of the present invention.
5A is a sequence-chart showing operations of a server and a first electronic device that calculates a living index according to an embodiment of the present invention.
5B is a conceptual diagram illustrating the operation of a server calculating a living index according to an embodiment of the present invention.
5C is a flow-chart showing the operation of a server according to an embodiment of the present invention.

Hereinafter, various embodiments of the present invention will be described with reference to the accompanying drawings. It should be understood that the present invention is not limited to specific embodiments, and includes various modifications, equivalents, and/or alternatives of the embodiments of the present invention. In connection with the description of the drawings, like reference numerals may be used for like elements.

In this document, expressions such as "has", "may have", "includes", or "may include" refer to the presence of a corresponding feature (eg, numerical value, function, operation, or component such as a part). , which does not preclude the existence of additional features.

In this document, expressions such as "A or B", "at least one of A and/and B", or "one or more of A or/and B" may include all possible combinations of the items listed together. . For example, "A or B", "at least one of A and B", or "at least one of A or B" includes (1) at least one A, (2) at least one B, Or (3) may refer to all cases including at least one A and at least one B.

Expressions such as "first", "second", "first", or "second" as used herein may modify various elements, in any order and/or importance, and may refer to one element as another. It is used to distinguish from components, but does not limit the components. For example, without departing from the scope of rights described in this document, a first element may be called a second element, and similarly, the second element may also be renamed to the first element.

As used in this document, the expression "configured to" means "suitable for", "having the capacity to", depending on the situation. ", "designed to", "adapted to", "made to", or "capable of" can be used interchangeably. The term "configured (or set) to" does not necessarily mean "specifically designed to."

In this document, for example, “command”, “instruction”, “control information”, “message”, “messages” transmitted and received between the first electronic device(s) and the second electronic device(s). "Information", "data", "packet", "data packet", "intent" and/or "signal" means any human-perceivable idea or specific electrical representation (e.g., digital code/analog physical quantity) or may refer to itself. It will be apparent to those skilled in the art that the above-listed exemplary expressions can be interpreted in various ways depending on the context in which they are used. In this document, “A is greater than B” means not only “A is greater than B”, but also “A is greater than or equal to B”.

Terms used in this document are only used to describe a specific embodiment, and may not be intended to limit the scope of other embodiments. Singular expressions may include plural expressions unless the context clearly dictates otherwise. Terms used herein, including technical or scientific terms, may have the same meaning as commonly understood by a person of ordinary skill in the technical field described in this document. Among the terms used in this document, the terms defined in general dictionaries may be interpreted as having the same or similar meaning to the meaning in the context of the related art, and unless explicitly defined in this document, in an ideal or excessively formal meaning. not interpreted In some cases, even terms defined in this document cannot be interpreted to exclude the embodiments of this document.

1 is a diagram illustrating an environment in which a system for providing health care services according to an embodiment of the present invention is implemented.

As shown in FIG. 1 , a system for providing health management services according to an embodiment of the present invention includes a first electronic device 110, a second electronic device 130, and a health management server 150 (hereinafter referred to as 'server'). referred to as). The first electronic device 110 and the second electronic device 130 and the server 150 may be connected through a network.

The first electronic device 110 may be a terminal of a user using a health management service. For example, the first electronic device 110 may be a terminal for a patient suffering from a chronic disease or taking medication.

The first electronic device 110 may acquire user data and provide it to the server 150 through a network.

According to an embodiment of the present invention, user data includes information related to the user's health, such as disease, blood sugar, meal amount, exercise amount, sleep time, medication time, medication cycle, etc., as well as the user's current location, real-time location, exercise status, It may include user location information that can be acquired from location-based services, such as moving speed.

According to an embodiment of the present invention, the first electronic device 110 may acquire user data directly input by the user. For example, the user utilizes the first electronic device 110 to obtain basic personal information such as gender, age, height, weight, ID, address, etc., as well as information on medical records received at medical institutions, health checkup data, and the like. and can be entered directly. In addition, the user may input various information such as genetic information, family history, disease, diet, exercise amount, and lifestyle by using the first electronic device 110 .

According to an embodiment of the present invention, the first electronic device 110 may acquire user data by detecting various user biometric information. For example, the first electronic device 110 may be an app for checking health information or a terminal (eg, a smartphone) to which a sensor for detecting bio information is added. For example, the first electronic device 110 may be attached to the user's body and detect various biometric information. The first electronic device 110 may detect various information such as blood pressure, blood sugar level, weight, pulse rate, electrocardiogram, etc., and if the user agrees to the location-based service, the user's motion is detected to determine the user's exercise amount, You can also check whether or not you exercised.

The second electronic device 130 may be a terminal of a company providing open data. Open data may refer to information related to users. For example, the open data may include weather information about the user's location, health information of the user, and the like.

According to an embodiment of the present invention, the second electronic device 130 is a terminal of the Korea Meteorological Administration, and transmits information on the weather, temperature, etc. of the user's current location and weather forecast information on the future weather, temperature, etc. to the server 150. can provide According to an embodiment of the present invention, the second electronic device 130 is a terminal of a healthcare platform, and with the consent of the user of the first electronic device 110, the user's blood sugar level, high blood pressure level, etc. Health information related to the user being managed may be provided to the server 150 . According to an embodiment of the present invention, the second electronic device 130 is a terminal of a hospital, and provides health information related to the user managed by the hospital, such as disease information and prescription information received by the user of the first electronic device 110. Information may be provided to server 150 .

The first electronic device 110 and the second electronic device 130 may be implemented as a computer capable of accessing a remote server or terminal through a network. For example, the computer may include a laptop, a desktop, a laptop, and the like equipped with a web browser. In addition, the first electronic device 110 and the second electronic device 130 may be implemented as terminals capable of accessing a remote server or terminal through a network. For example, the first electronic device 110 and the second electronic device 130 are wireless communication devices that ensure portability and mobility, and include navigation, personal communication system (PCS), global system for mobile communication (GSM), and PDC. (Personal Digital Cellular), PHS (Personal Handphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access) , Wibro (Wireless Broadband Internet) terminal, smart phone (smartphone), smart pad (smartpad), tablet PC (Table PC), such as all kinds of handheld (Handheld) based wireless communication devices can be included.

The server 150 receives user data and open data from the first electronic device 110 and the second electronic device 130, and based on the user data and open data, sets a health management index reference value corresponding to the user. .

The health management index may include medication compliance and/or lifestyle index. According to an embodiment of the present invention, the server 150 may calculate medication compliance by utilizing user data and open data. According to an embodiment of the present invention, the server 150 may calculate a living index by utilizing user data and open data.

The server 150 may calculate a health management index corresponding to the user based on the user data and open data, compare the calculated health management index with a set health management index reference value, and provide feedback data to the user. The health management index, health management index reference value, and feedback data corresponding to the user may be generated based on user data provided from the first electronic device 110 and open data provided from the second electronic device 130, It may be modified based on at least one of continuously updated user data and open data.

According to an embodiment of the present invention, the server 150 may provide a health management service with respect to the user's lifestyle, in particular, the amount of exercise and the user's medicine-taking habit, through feedback data.

The server 150 uses user data provided from the first electronic device 110 and open data provided from the second electronic device 130 as well as big data and AI (Artificial Intelligence) to obtain health management index and health management index. The reference value and feedback data of can be created or modified. For example, the server 150 may provide a health management service to a new user based on the previously accumulated data by referring to the health management index, health management index reference value, and feedback data accumulated from a plurality of users.

2 is a diagram showing the configuration of a server 150 according to an embodiment of the present invention.

Referring to FIG. 2 , a server 150 according to an embodiment of the present invention includes a bus 210, a display 220, a communication circuit 230, a database 240, a memory 250, and an I/O interface 260. ) and a processor 270. In another embodiment, the server 150 may omit at least one of the above components or may additionally include other components.

The bus 210 may electrically connect the components 220 to 270 to each other. Bus 210 may include circuitry for communication (eg, control messages and/or data) between components 220-270.

The display 220 may display text, images, videos, icons, or symbols constituting various contents. The display 220 may include a touch screen and may receive a touch, gesture, proximity, or hovering input using an electronic pen or a part of the user's body.

For example, the display 220 may be a liquid crystal display (LCD), a light emitting diode (LED) display, an organic light emitting diode (organic LED) display, or a microelectromechanical systems (MEMS) display, or electronic paper. may include a display. The display 220 may be included in the server 150 or implemented separately from the server 150 but operatively connected to the server 150 .

The communication circuit 230 may establish a communication channel between the server 150 and external devices (eg, the buyer's electronic device 110 and the seller's electronic device 130). For example, the communication circuit 230 may communicate with external devices by accessing the network 280 through wireless or wired communication.

Network 280 may correspond to the network shown in FIG. 1 . The network 280 may include at least one of a telecommunications network, a computer network, the Internet, or a telephone network. Wireless communication protocols for accessing the network 280 include, for example, Long-Term Evolution (LTE), LTE Advanced (LTE-A), Code Division Multiple Access (CDMA), Wideband CDMA (WCDMA), Universal At least one of Mobile Telecommunications System), WiBro (Wireless Broadband), GSM (Global System for Mobile communications), or 5G standard communication protocol may be used.

The database 240 may be implemented on the memory 250 or may be implemented on a separate storage medium. The database 240 may store all contents and details of data transmitted and received with the first electronic device 110 and the second electronic device 130 . For example, the database 240 may store user data and open data. According to various embodiments, since the data stored in the database 240 is sensitive customer information, it may be distributed and stored in a blockchain network to improve security regarding the use of the information. If the database 240 is distributed and stored in the blockchain network, the history of transmission, modification, deletion, addition, etc. of the information included in the database 240 can be more safely managed in the blockchain network.

Memory 250 may include volatile and/or non-volatile memory. The memory 250 may store instructions or data related to at least one other component of the server 150 . For example, memory 250 may store instructions that, when executed, cause processor 270 to perform various operations described herein. For example, the command may be included in a package file of an application program.

The I/O interface 260 may serve to transfer commands or data input from a user or other external device to other components of the server 150. The I/O interface 260 may be implemented in hardware or software, and may be used as a concept encompassing a user interface (UI) and terminals for communication with other external devices.

The processor 270 may include at least one of a central processing unit (CPU), an application processor (AP), and a communication processor (CP). The processor 270 is electrically connected to the memory 250, the display 220, and the communication circuit 230 through the bus 210, and has different configurations according to instructions, programs, or software stored in the memory 250 during operation. It may perform calculations or data processing related to control and/or communication of the elements. Accordingly, execution of the command, application program, or software may be understood as an operation of the processor 270 .

The operations of the processor 270 are representative examples, and the technical idea of the present invention is not limited thereto. For example, the operation of the “server 150” described directly or indirectly in this specification may be understood as the operation of the processor 270 included in the corresponding “server 150”. In addition, it will be apparent to those skilled in the art that at least some of the operations performed by the server 150 can be performed by a third device through a server-client architecture, cloud computing, and/or parallel computing. .

The processor 270 may generate a health management index, a reference value of the health management index, and feedback data based on user data provided from the first electronic device 110 and open data provided from the second electronic device 130. . According to an embodiment of the present invention, the processor 270 may generate medication compliance, a reference value for medication compliance, and feedback data on medication based on user data and open data. According to an embodiment of the present invention, the processor 270 may generate life index, reference values of the life index, and feedback data on life patterns based on user data and open data.

Hereinafter, various embodiments of the present invention implemented in an environment including individual subjects as described above will be described.

3 is a flow-chart showing the operation of the server 150 according to an embodiment of the present invention.

In step S301, the server 150 may collect user data and open data. According to an embodiment of the present invention, the server 150 may receive user data from the first electronic device 110 and open data from the second electronic device 130 .

User data includes the user's disease, meal amount, exercise amount, exercise status, sleep time, medication taking time, medication response time, medication cycle, blood pressure, blood sugar, pulse, electrocardiogram, user's gender, age, height, weight, ID, address, duty It may include health information about the user, such as record data, health examination data, genetic information, family history, current location of disease, personal information, medical treatment information, and the like. User data may be input by a user using the first electronic device 110 . Also, user data may be measured by the first electronic device 110 .

Open data may include time information related to date and time, non-working days, weather information such as weather at the current location of the user, temperature, future weather, and health information such as blood sugar levels and high blood pressure levels managed by other platforms. In the case of time information, data managed by the server 150 itself may be utilized.

In step S303, the server 150 may classify and store user data provided from the first electronic device 110 and open data provided from the second electronic device 130.

According to an embodiment of the present invention, the server 150 may store a user's ID in correspondence with a disease. According to an embodiment of the present invention, the server 150 may store the user's ID in correspondence with the disease and medication time. According to an embodiment of the present invention, the server 150 may store a user's ID in correspondence with a disease, medication time, and medication response time. According to various embodiments of the present disclosure, the server 150 may store the user's ID, disease, numerical value related to the disease, day of the week, exercise status, amount of exercise, and weather in correspondence with each other.

As such, the server 150 may classify and store user data and open data in the database 240 in correspondence with the user's ID, disease, and other information. The above disclosure is only an example, and the present invention is not limited thereto.

In step S305, the server 150 may set a health management index reference value corresponding to the user based on the user data provided from the first electronic device 110 and the open data provided from the second electronic device 130. The health management index reference value refers to a target value that guides the user's disease level to reach a good level without worsening.

According to an embodiment of the present invention, the reference value of the health management index may refer to a medication compliance reference value corresponding to the user. Medication compliance refers to the degree to which a patient's medication behavior conforms to the guidance of a healthcare provider. In addition, the medication compliance reference value refers to a medication target value that guides the user's disease level to reach a satisfactory level.

The server 150 may set a medication compliance reference value corresponding to the user based on the user's disease, disease level, medication medication time, medication medication interval, diet, and the like. For example, if the fasting blood glucose level of the user is '400 (mg/dL)', since it is a very dangerous situation, the server 150 may set the medication compliance reference value corresponding to the user as high as 95%. For another example, if the fasting blood sugar level of the user is '150 (mg/dL)', the user has diabetes but is less dangerous than the previous example, so the server 150 determines the medication compliance reference value corresponding to the user. It can be set as low as 60%.

According to an embodiment of the present invention, when the fasting blood glucose level of the user is lowered from '400 (mg/dL)' to '150 (mg/dL)', the server 150 sets the medication compliance reference value corresponding to the user to 95%. It can be updated to 60% from .

According to an embodiment of the present invention, the health management index may refer to a reference value of a living index corresponding to a user. Life index refers to the amount of exercise instructed by health care service providers or the amount of exercise to overcome the disease according to big data. The life index reference value refers to a target value of exercise amount that guides the user's disease level to reach a satisfactory level.

The server 150 may set a reference value of the living index corresponding to the user based on the user's disease, disease level, exercise status, exercise intensity, exercise duration, diet, and the like. For example, if the fasting blood sugar level of the user is '400 (mg/dL)', since it is a very dangerous situation, the server 150 may set the reference value of the life index corresponding to the user as high as 95%. For another example, if the fasting blood sugar level of the user is '150 (mg/dL)', the user has diabetes but is less dangerous than the previous example, so the server 150 sets the reference value of the living index corresponding to the user to 60%. can be set lower. According to an embodiment of the present invention, when the fasting blood glucose level of the user is lowered from '400 (mg/dL)' to '150 (mg/dL)', the server 150 sets the standard value of the living index corresponding to the user to 95%. It can be updated to 60% from . The information described above is only an example, and is not limited thereto.

In step S307, the server 150 may calculate a health management index corresponding to the user based on the user data and the open data.

According to an embodiment of the present invention, the server 150 may calculate the medication compliance corresponding to the user based on user data and open data. The medication compliance may be calculated by the server 150 using the user's disease, disease value (eg, blood sugar level, high blood pressure level, etc.), medication taking time, medication taking interval, diet, and the like.

According to an embodiment of the present invention, the server 150 may calculate a living index corresponding to a user based on user data and open data. The life index may be calculated by the server 150 using the user's disease, disease level (eg, blood sugar level, high blood pressure level, etc.), exercise status, exercise intensity, exercise duration, diet, and the like.

According to an embodiment of the present invention, the server 150 may calculate a health management index at each predetermined time point. According to various embodiments of the present disclosure, the server 150 may calculate a health management index whenever user data and open data are updated.

In step S309, the server 150 may generate feedback data by comparing the health management index reference value set in step S305 and the health management index calculated in step S307. The server 150 may provide the generated feedback data to the first electronic device 110 . The user can check the feedback data using the first electronic device 110 .

FIG. 4A is a sequence-chart showing operations of the server 150 and the first electronic device 110 for calculating medication compliance according to an embodiment of the present invention. The operation of the server 150 disclosed in FIG. 4A represents the detailed operation of step S307 disclosed in FIG. 3 .

In step S401, the server 150 may provide the first electronic device 110 with a notification message (hereinafter referred to as a medication notification message) for notifying a medication-taking action. The medicine-taking notification message may include medicine information, information about the timing of taking medicine, and the like.

According to an embodiment of the present invention, the server 150 may provide a medication reminder message to the first electronic device 110 at a time set by the user.

According to another embodiment of the present invention, the server 150 may provide a medication reminder message to the first electronic device 110 at a time set by user data and open data. For example, the server 150 may provide a medication reminder message to the first electronic device 110 according to a recommended intake time by a doctor in charge. For another example, the server 150 may provide the first electronic device 110 with a medication reminder message according to a medication cycle of another user suffering from symptoms similar to the user's. For another example, the server 150 may provide a medication reminder message to the first electronic device 110 according to a medication cycle of a person who has improved among a plurality of other users suffering from symptoms similar to the user's.

In step S403, the server 150 may receive a confirmation message (hereinafter, a medication confirmation message) from the first electronic device 110 as to whether or not the user has taken the medicine. The medication confirmation message may include information about whether or not to take the medication, information about when to take the medication, and the like.

The user may directly input whether or not to take the medicine by using the first electronic device 110 . For example, when the user has taken medicine, the user may directly input the fact of taking the medicine using the first electronic device 110 . In addition, the user may directly input the timing of taking the medicine by using the first electronic device 110 . For another example, when the user has not taken the medicine, the user may directly input the fact that he or she has not taken the medicine by using the first electronic device 110 .

The first electronic device 110 may provide a medication confirmation message to the server 150 in response to the medication notification message provided by the server 150 .

According to various embodiments of the present disclosure, the server 150 refers to the data collected (sensed) by the first electronic device 110 without receiving a separate medication confirmation message so that the user can take the medicine according to the medication reminder message. You can predict whether you've taken it. For example, the server 150 may predict whether the user has taken medicine by integrating the user's blood sugar level, blood pressure, real-time location, and past accumulated data provided from the first electronic device 110 .

In step S405, the server 150 may generate medication data based on the medication confirmation message. The taking data includes a medication notification message, a medication confirmation message, and information related to whether or not the user responds to the medication notification message.

According to an embodiment of the present invention, the server 150 may generate medication data by responding to the user's response to the medication notification message, the medication confirmation message, and the medication notification message.

For example, when a user takes a medicine and responds to a medication reminder message, the server 150 matches the time of providing the medication reminder message to the first electronic device 110, the time of taking the medicine, and the fact of taking the medicine. Dosage data can be generated.

For another example, when the user responds to the medication notification message without taking the medicine, the medication notification message is provided to the first electronic device 110, and the medication confirmation message is sent from the first electronic device 110. It is possible to generate dose data corresponding to the time of receipt and the fact of non-taking.

According to various embodiments of the present disclosure, when a medication confirmation message is not provided from the first electronic device 110, the server 150 may generate medication data by correlating the medication reminder message with the fact of 'non-response'. .

According to various embodiments of the present invention, the server 150 generates taking data by matching open data such as days of the week, non-working days, weather, temperature, etc. with a medication notification message, a medication confirmation message, and whether or not a user responds to the medication notification message. can do. Through this, the server 150 may determine the characteristics of the user regarding medication taking, such as a low response rate for taking medication on a rainy day, a high response rate for taking medication on a sunny day, or a low response rate for taking medication on a holiday day.

On the other hand, according to an embodiment of the present invention, the server 150 corresponds to the medication response time, medication score, and medication compliance extracted and calculated after this step with the medication reminder message, medication confirmation message, response status, and open data. Dosage data can be updated.

In step S407, the server 150 may extract the medication response time from the medication data. According to an embodiment of the present invention, the medication response time refers to a time difference from the time when the medication notification message is provided to the first electronic device 110 to the time when the user takes the medicine. According to another embodiment of the present invention, the medication response time refers to a time difference between a predetermined taking time point (eg, a dosage time recommended by a doctor in charge) and a time point when the user takes the medicine.

According to various embodiments of the present disclosure, even if there is no medication confirmation message, the server 150 may extract the medication completion time and medication response time by referring to the medication data collected (sensed) by the first electronic device 110. there is. For example, the server 150 may predict the user's medication completion time and medication response time by integrating the user's blood sugar level, blood pressure, real-time location, and past accumulated data provided from the first electronic device 110 .

In step S409, the server 150 may calculate a medication score based on the extracted medication response time.

According to an embodiment of the present invention, the server 150 may calculate the medication score according to a preset criterion. According to an embodiment of the present invention, the server 150 divides the user's medication response time into five time zones such as 'non-response', 'on time', 'within 10 minutes', 'within 1 hour', and 'other'. A medication score for the medication response time may be calculated by classifying and assigning a score for each time slot. For example, the server 150 gives '0 point' for 'non-response', '1 point' for 'on time', '0.7 point' for 'within 10 minutes', and '0.5 point' for 'within 1 hour'. ', for responses within 24 hours, points can be assigned for each response time point, such as '0.2 point'. This is just one example, and is not limited thereto.

According to an embodiment of the present invention, the server 150 may calculate the medication score based on the medication response time extracted for a certain period of time. For example, if the user responds to the medication as "'non-response' 1 time, 'on time' 3 times, 'within 10 minutes' 1 time" during the day, the server 150 calculates the medication-taking score for the day as 3.7 points. can do.

In step S411, the server 150 may check the necessary number of times the user has to take the medicine during a certain period of time (hereinafter, the number of times necessary to take the medicine). The server 150 may check the required number of medications based on user data and/or open data.

According to an embodiment of the present invention, the user may directly input the required number of medications by using the first electronic device 110 . For example, the user may directly input the required number of times to take the medicine in the form of 'five times a day' by using the first electronic device 110 . For another example, the user may directly input the required number of times to take the medicine, 'three times a week' by using the first electronic device 110 . The first electronic device 110 may provide the server 150 with the 'required number of medications' input by the user. The server 150 may check information on the 'required number of medications' provided from the first electronic device 110 .

According to another embodiment of the present invention, the server 150 may check the required number of medications corresponding to the user based on the open data. For example, the server 150 may check the required number of medications corresponding to the user based on prescription information provided by the hospital where the user was treated.

According to various embodiments of the present invention, the server 150 may recommend the required number of medications based on information about other users having similar symptoms to the user. For example, the server 150 may recommend the number of times required to take medication of a user whose medication compliance and life index are close to those of a plurality of other users suffering from symptoms similar to the user's.

In step S413, the server 150 may calculate the medication compliance corresponding to the user based on the number of medication points extracted during a certain period of time and the number of times required to take the medication.

According to an embodiment of the present invention, medication compliance may be defined as a ratio of medication scores to the number of times required to take medication. The server 150 may calculate the medication compliance by utilizing the medication score extracted in step S409 and the number of required medications confirmed in step S411. Specifically, the server 150 may calculate medication compliance as in Equation 1 below.

[Equation 1]

The operation of the server 150 for calculating adherence to medication will be described in detail with reference to FIGS. 4B to 4C.

According to various embodiments of the present disclosure, the server 150 may predict the user's medication compliance based on the accumulated medication data. Specifically, the server 150 may predict the user's medication compliance by utilizing at least one of the accumulated location information, weather information, time information, medication information, day of the week information, and past medication compliance of the user. For example, the server 150 may predict the user's medication compliance on a rainy day. For another example, the server 150 may predict the medication compliance of the user on a holiday day. For another example, the server 150 may predict the user's medication compliance when the user is located in the home. For another example, the server 150 may predict the user's medication compliance for a specific time period. However, this is only an example, and is not limited thereto.

4B to 4C are conceptual diagrams illustrating operations of the server 150 for calculating adherence to medication according to an embodiment of the present invention. Hereinafter, an operation process of the server 150 for calculating medication compliance for users 'A', 'B', 'C', 'D', and 'E' will be disclosed.

In the table shown in FIG. 4B, 'User', 'Number of Medication Required', and 'First Time Point' to 'Fifth Time Point' are fields, and the 'User' field includes health management provided by the health management server An ID for a service that uses a service is set as a value, and 'number of medications required' is a value corresponding to the user's required number of medications during the day. The server 150 determines the number of times user 'A' needs to take medicine is '5 times', the number of times user 'B' needs to take medicine is '2 times', the number of times user 'C' needs to take medicine is '6 times', and user 'D' It can be confirmed that the required number of times of medication of ' is '3 times' and the number of times that user 'E' needs to take medicine is '5 times'.

On the other hand, the first time point refers to the time between 05:00 and 07:00 when the user is in an empty state, the second time point refers to the time between 07:00 and 09:00 when the user finishes breakfast, and the third time point refers to the time when the user finishes eating breakfast. The fourth time point refers to the time between 17:00 and 20:00 after the user finishes dinner, and the fifth time point refers to the time from 21:00 immediately before the user goes to bed to the next day. It can refer to the time between 02:00. However, this is only an example, and is not limited thereto.

A value of '1' in the 'first time' to 'fifth time' fields means that the user took the medicine at that time, '0' means that he did not take the medicine at that time, and '- 1' means that the medication notification message was not responded to at that time. Also, '*' signifies that the server 150 has provided the medication notification message to the first electronic device 110 at that time.

The server 150 may provide a total of five medication notification messages to the first electronic device 110 of user 'A' at each of the first to fifth time points. User 'A' has completed taking the medication at the first time point, and has responded to the medication notification message. User 'A' did not take medicine at the second time point, but responded to the medication notification message. User 'A' has completed taking the medication at the third point in time and has responded to the medication notification message. Meanwhile, user 'A' did not respond to the medication notification message at the fourth time point. User 'A' has completed taking the medication at the fifth time point, and has responded to the medication reminder message.

The first electronic device 110 may provide a medication confirmation message to the server 150 a total of four times in response to the medication reminder message according to the user 'A' input. The server 150 may generate taking data based on the received medication confirmation message. Specifically, the server 150 may generate medication data corresponding to user 'A' with respect to the fact that user 'A' took all of the medicines during the time when each of the medication confirmation messages were received 4 times and during the 4 times. can

Meanwhile, the server 150 may provide a total of two medication reminder messages to the first electronic device 110 of user 'B' at each of the second and fourth time points. User 'B' has completed taking the medication at the second time point, and has responded to the medication reminder message. User 'B' did not take medicine at the fourth time point, but responded to the medication notification message.

The first electronic device 110 may provide a medication confirmation message to the server 150 a total of two times in response to the medication notification message according to user 'B' input. The server 150 may generate taking data based on the received medication confirmation message. Specifically, the server 150 transmits taking data corresponding to user 'B' with respect to the fact that user 'B' took the medicine only once during the time when each of the medication confirmation messages were provided twice and during the two times. can create

Meanwhile, the server 150 may provide a total of five medication notification messages to the first electronic device 110 of user 'C' at each of the first to fifth time points. User 'C' did not respond to the medication reminder message at the first time point. User 'C' has completed taking the medication at the second time point, and has responded to the medication reminder message. User 'C' has completed taking the medication at the third point in time and has responded to the medication reminder message. Meanwhile, user 'C' has completed taking the medication at the fourth time point and responded to the medication reminder message. User 'C' did not take the medicine at the fifth time point, but responded to the medication reminder message.

The first electronic device 110 may provide a medication confirmation message to the server 150 a total of four times in response to the medication reminder message according to user 'C' input. The server 150 may generate taking data based on the received medication confirmation message. Specifically, the server 150 takes the medicine corresponding to user 'C' with respect to the fact that user 'C' did not take the medicine once during the time when each of the four medication confirmation messages were provided and during the four times. data can be generated.

Meanwhile, the server 150 may provide the medication reminder message to the first electronic device 110 of user 'D' a total of three times at each of the first, third, and fifth time points. User 'D' has completed taking medication at all time points of the first, third and fifth time points, and has responded to the medication reminder message.

The first electronic device 110 may provide a medication confirmation message to the server 150 a total of three times in response to the medication notification message according to the user 'D' input. The server 150 may generate taking data based on the received medication confirmation message. Specifically, the server 150 generates medication data corresponding to the user 'D' with respect to the fact that the user 'D' has completed taking all medications during the three times when each of the three medication confirmation messages is provided and the fact that the user 'D' has taken all medications. can

Meanwhile, the server 150 may provide a total of five medication notification messages to the first electronic device 110 of user 'E' at each of the first to fifth time points. User 'E' did not respond to the medication notification message at any of the first to fifth time points.

The server 150 may generate medication data corresponding to user 'E' in response to the fact that user 'E' has not responded to the medication notification message. The server 150 may extract a medication response time from the generated medication data and calculate a medication score based on the medication response time. Furthermore, the server 150 may calculate medication compliance based on the medication score and the required number of medications.

In the table shown in FIG. 4C, 'user', 'number of medications required', 'number of responses', 'non-response (0)', and 'first period (1)' to 'fourth time point (0.2)' field, and in the 'user' field, the ID for the service using the health management service provided by this health management server is set as a value, and 'the number of times required to take medication' corresponds to the user count as a value. The 'number of responses' is the number of times the user responds to the medication reminder message, that is, the number of times the first electronic device 110 provides the server 150 with a medication confirmation message.

Meanwhile, the first interval may refer to a time within 5 minutes from immediately after the medication reminder message is sent to the first electronic device 110 . The second interval may refer to a time within 15 minutes from 5 minutes after the medication reminder message is sent to the first electronic device 110 . The third interval may refer to a time from 15 minutes after the medication reminder message is sent to the first electronic device 110 to within 60 minutes. The fourth interval may refer to a time within 24 hours from 60 minutes after the medication reminder message is sent to the first electronic device 110 . '0 point' for 'non-response', '1 point' for responses within the 'first period', '0.7 points' for responses within the 'second period', and '0.5 point' for responses within the 'third period' Points' and '4th section' are assigned points for each response time, such as '0.2 points'. However, this is only an example, and is not limited thereto.

In the 'non-response' field, the number of times the user did not respond to the medication notification message, that is, the number of times the first electronic device 110 did not provide the medication confirmation message to the server 150 in response to the medication notification message is set as a value do. In the 'first interval' field, the number of times the user responds to the medication notification message within 5 minutes is set as a value. In the 'second interval' field, the number of times the user responds to the medication notification message within 15 minutes from 5 minutes later is set as a value. In the 'third interval' field, the value of the number of times the user responds to the medication notification message within 60 minutes from 15 minutes later is set. In the 'fourth interval' field, the number of times the user responds to the medication reminder message within 24 hours from 60 minutes later is set as a value.

Referring to FIG. 4C , user 'A' responded to the medication reminder message 'once' within the first interval, 'once' within the second interval, and 'once' within the third interval. 1 time' was answered within the 4th section. Meanwhile, user 'A' did not respond to the medication reminder message once.

The server 150 may calculate the medication score corresponding to user 'A' as '2.4 (1 + 0.7 + 0.5 + 0.2) points'. Meanwhile, the server 150 may confirm that the required number of medications corresponding to user 'A' is '5 times'. Based on this, the server 150 may calculate the medication compliance of user 'A' as 48%.

The server 150 may calculate the medication score corresponding to user 'B' as '0.7 (0.5+0.2) points'. Meanwhile, the server 150 may confirm that the required number of medications corresponding to user 'B' is 'twice'. Based on this, the server 150 may calculate the medication compliance of user 'B' as 35%.

The server 150 may calculate the medication score corresponding to user 'C' as '1.7 (1+0.7) points'. Meanwhile, the server 150 may confirm that the required number of medications corresponding to user 'C' is '5 times'. Based on this, the server 150 may calculate the medication compliance of user 'C' as 34%.

The server 150 may calculate the medication score corresponding to user 'D' as '3(1+1+1) points'. Meanwhile, the server 150 may confirm that the required number of medications corresponding to the user 'D' is 'three times'. Based on this, the server 150 may calculate the medication compliance of user 'D' as 100%.

The server 150 may calculate the medication score corresponding to user 'E' as '0'. Meanwhile, the server 150 may confirm that the required number of medications corresponding to user 'E' is '5 times'. Based on this, the server 150 may calculate the medication compliance of user 'E' as 0%.

4D is a flow chart showing the operation of the server 150 according to an embodiment of the present invention. In FIG. 4d, the operation of the server 150 in step S309 disclosed in FIG. 3 is disclosed in detail. Also, in FIG. 4D, the operation of the server 150 starts after step S413 of FIG. 4A.

In step S415, the server 150 may compare the medication compliance calculated in step S413 with a preset medication compliance reference value. According to an embodiment of the present invention, the server 150 may compare medication compliance with a medication compliance reference value for each weather. According to another embodiment of the present invention, the server 150 may compare medication compliance with a medication compliance reference value for each day of the week. According to another embodiment of the present invention, the server 150 may compare medication compliance with reference values for medication compliance for each location.

If the medication compliance calculated in step S413 is smaller than the preset medication compliance reference value, in step S417, the server 150 may generate feedback data. For example, the server 150 'adherence to medication is less than the reference value. Take your medicines well.' Feedback data can be generated. As another example, the server 150 says, 'You don't take your medicine well on Saturdays. Please be extra careful.' Feedback data can be created. For another example, the server 150 'There is no response to the medication reminder. Please make sure to enter whether or not to take it.' Feedback data can be created. For another example, for a user whose calculated adherence to medication on Wednesday is smaller than a preset reference value for medication compliance, the server 150 may generate feedback data saying 'Please take your medicine well on Wednesday.' This is only one example, and is not limited thereto.

Meanwhile, the server 150 according to an embodiment of the present invention performs natural language processing such as natural language generation and natural language understanding, machine learning, and artificial neural networks. network), deep learning, etc., to generate feedback data. According to an embodiment of the present invention, the server 150 may generate user-customized feedback data by utilizing at least one analysis method among natural language processing (NLP)-based related word analysis, emotional word analysis, and issue analysis. .

In step S419, the server 150 may provide the generated feedback data to the first electronic device 110. According to an embodiment of the present invention, the server 150 may provide feedback data to the first electronic device 110 until the user's medication compliance exceeds the medication compliance reference value. According to another embodiment of the present invention, the server 150 may provide the first electronic device 110 with feedback data from the previous day of the corresponding day when the medication compliance of a specific day is less than a reference value. Alternatively, the server 150 may provide feedback data to the first electronic device 110 together with the first medication reminder message of the corresponding day.

On the other hand, if the medication compliance calculated in step S413 is greater than or equal to the preset medication compliance reference value, the server 150 may return to step S301 to collect user data and open data.

FIG. 5A is a sequence-chart showing operations of the server 150 and the first electronic device 110 that calculates a living index according to an embodiment of the present invention. The operation of the server 150 disclosed in FIG. 5A represents the detailed operation of step S307 disclosed in FIG. 3 .

In step S501, the server 150 may provide an exercise notification message (hereinafter, an exercise notification message) to the first electronic device 110. The exercise notification message may include information on a guide through which the user can efficiently exercise, such as a recommended amount of exercise, an exercise method, and a type of exercise.

According to an embodiment of the present invention, the server 150 may provide an exercise notification message to the first electronic device 110 at a time set by the user.

According to another embodiment of the present invention, the server 150 may provide an exercise notification message to the first electronic device 110 at a time set by user data and open data. For example, the server 150 may provide an exercise notification message to the first electronic device 110 according to the user's exercise pattern identified by user data and open data. For another example, the server 150 may provide an exercise notification message to the first electronic device 110 according to an exercise cycle of another user suffering from symptoms similar to that of the user. For another example, the server 150 may provide an exercise notification message to the first electronic device 110 according to an exercise period of a person who has improved from among a plurality of other users suffering from symptoms similar to the user's.

In step S503, the first electronic device 110 may provide living data to the server 150. The living data may include information related to the user's lifestyle, such as the user's moving distance, means of movement, moving speed, diet, exercise status, exercise item, exercise time, and amount of calories consumed.

According to an embodiment of the present invention, the user may directly input a moving distance, a means of movement, a moving speed, a diet, whether or not to exercise, an exercise item, and an exercise time into the first electronic device 110 . Based on the input information, the first electronic device 110 may provide living data to the server 150 .

According to another embodiment of the present invention, the first electronic device 110 collects moving distance, means of movement, moving speed, diet, exercise status, exercise event, exercise time, blood sugar level, blood pressure, etc. without a user's separate input ( sensing). The first electronic device 110 may provide life data to the server 150 based on the collected (sensed) information.

In step S505, the server 150 may generate exercise data based on the living data provided from the first electronic device 110. Specifically, the server 150 matches open data such as movement distance, means of movement, movement speed, diet, exercise status, exercise item, exercise time and weather, day of the week, time, place, etc. included in living data to obtain exercise data. can create For example, the exercise data may include information such as "the user maintained a walking exercise for 1 hour on a rainy day and moved 5 km." As another example, the exercise data may include information such as "The user maintained running exercise at an average speed of 5 km/h for 2 hours on a sunny day."

In step S507, the server 150 may check the amount of exercise that the user needs to exercise for a certain period of time (hereinafter, the required amount of exercise) and the number of days that the user needs to exercise for a certain period of time (hereinafter, the number of days that the user needs to exercise). According to an embodiment of the present invention, the required amount of exercise may refer to the amount of calories that the user should consume for a week. According to an embodiment of the present invention, the number of days a user needs to exercise may refer to the number of days a user needs to exercise in a week. The server 150 may check the user's required amount of exercise and the number of days required for exercise based on user data and/or open data.

According to an embodiment of the present invention, the user may directly input the required amount of exercise using the first electronic device 110 . For example, the user may directly input the required amount of exercise as 'calorie consumption: 1,500 kcal' for a week using the first electronic device 110 . The first electronic device 110 may provide the required amount of exercise input by the user to the server 150 . The server 150 may check information on the required amount of exercise provided from the first electronic device 110 .

According to another embodiment of the present invention, the server 150 may check the required amount of exercise corresponding to the user based on the open data. For example, the server 150 may check the required amount of exercise corresponding to the user based on prescription information given by the hospital where the user was treated.

According to various embodiments of the present disclosure, the server 150 may recommend a required amount of exercise based on information about other users having similar symptoms to the user.

Meanwhile, according to an embodiment of the present invention, the server 150 may extract the unit required exercise amount. The unit required exercise amount means the amount of exercise required by the user during the day. That is, the required unit exercise amount means the amount of calories that the user needs to consume during the day. For example, if the user's required exercise amount for one week is '1,400 kcal', the server 150 may extract the unit required exercise amount as '200 kcal'.

Meanwhile, according to an embodiment of the present invention, the user may directly input the number of days required for exercise using the first electronic device 110 . For example, the user may directly input the number of days required for exercise as 'required exercise days: 5 days' for a week by using the first electronic device 110 . The first electronic device 110 may provide the server 150 with the number of days required for exercise input by the user. The server 150 may check information on the number of days required for exercise provided from the first electronic device 110 .

According to another embodiment of the present invention, the server 150 may check the number of days required for exercise corresponding to the user based on the open data. For example, the server 150 may check the number of days required for exercise corresponding to the user based on prescription information given down by the hospital where the user was treated.

According to various embodiments of the present disclosure, the server 150 may recommend the number of days required for exercise based on information about other users having similar symptoms to the user.

Meanwhile, according to an embodiment of the present invention, the server 150 may extract the number of days required for unit exercise.

In step S509, the server 150 may extract the amount of exercise from the exercise data. According to an embodiment of the present invention, the amount of exercise may refer to the amount of calories consumed by the user.

In step S511, the server 150 may calculate an exercise index based on the exercise data. Specifically, the server 150 may calculate an exercise index based on information on whether or not to exercise.

According to an embodiment of the present invention, the server 150 may calculate the exercise index by utilizing the number of exercise days performed by the user during a week. Specifically, the server 150 may calculate the exercise index as in Equation 2 below.

[Equation 2]

The exercise index may be an index indicating the number of days of exercise actually performed compared to the number of days the user needs to exercise. The operation of the server 150 for calculating the exercise index is described in detail in FIG. 5B.

In step S513, the server 150 may calculate the momentum index based on the extracted momentum.

According to an embodiment of the present invention, the server 150 may calculate the exercise quantity index by utilizing the exercise quantity performed by the user for a week. Specifically, the server 150 may calculate the momentum index as shown in Equation 3 below.

[Equation 3]

The momentum index may be an indicator representing the amount of exercise actually performed compared to the amount of exercise required by the user. The operation of the server 150 for calculating the momentum index is described in detail in FIG. 5B.

In step S515, the server 150 may calculate a life index corresponding to the user based on the exercise index and the momentum index.

According to an embodiment of the present invention, the life index may be defined as the product of the exercise index and the exercise quantity index. Specifically, the server 150 may calculate the living index as shown in Equation 4 below.

[Equation 4]

The operation of the server 150 for calculating the living index will be described in detail with reference to FIG. 5C.

According to various embodiments of the present disclosure, the server 150 may predict a user's life index based on accumulated exercise data. Specifically, the server 150 may predict the user's living index by utilizing at least one of the accumulated user's location information, weather information, time information, medication information, day of the week information, and past living index. For example, the server 150 may predict the life index of the user on a rainy day. As another example, the server 150 may predict the life index of the user on a non-working day. As another example, the server 150 may predict the user's living index when the user is located in a house. As another example, the server 150 may predict a user's living index in a specific time period. However, this is only an example, and is not limited thereto.

5B is a conceptual diagram illustrating the operation of the server 150 for calculating an exercise index and a momentum index according to an embodiment of the present invention. Hereinafter, the number of days required for exercise during Monday to Friday of users 'A', 'B', 'C', 'D', and 'E' is '5 days', the required amount of exercise is all 1,000 kcal, and the required amount of exercise per unit is 200 kcal Assume that

User 'A' exercised every day from Monday to Friday, consuming 200 kcal per day for a total of 1,000 kcal. Since user 'A' has done a mail exercise, the server 150 may calculate the exercise index corresponding to user 'A' as '1' by using Equation 2. Since user 'A' exercises 200 kcal every day, the server 150 may calculate the momentum index corresponding to user 'A' as '1' by using Equation 3. Furthermore, the server 150 may calculate the living index corresponding to user 'A' as '100%' by using Equation 4.

User 'B' exercised every day from Monday to Friday, consuming 100 kcal per day for a total of 1,000 kcal. Since user 'B' exercises every day, the server 150 may calculate the exercise index corresponding to user 'B' as '1' by using Equation 2. However, since user 'B' exercises 100 kcal every day unlike user 'A', the server 150 may calculate the momentum index corresponding to user 'B' as '0.5' by using Equation 3. Furthermore, the server 150 may calculate the living index corresponding to user 'B' as '50%' by using Equation 4.

User 'C' performed the exercise only from Wednesday to Friday, consumed 200 kcal a day from Wednesday to Friday, and consumed 600 kcal for a week. Since user 'C' exercised for only 3 days out of 5 days, the server 150 may calculate the exercise index corresponding to user 'C' as '0.6' by using Equation 2. Since user 'C' has a higher momentum than user 'B', the server 150 may calculate the momentum index corresponding to user 'C' as '0.6' by using Equation 3. Furthermore, the server 150 may calculate the living index corresponding to user 'C' as '36%' by using Equation 4. Although user 'C' actually performed more exercise than user 'B', user 'C''s fitness index may be set lower than user 'B''s fitness index because she did not exercise daily.

User 'D' performed exercise only on Friday, and consumed 500 kcal a day on Friday, consuming only 500 kcal for a week. Since user 'D' has exercised for only 1 day out of 5 days, the server 150 may calculate the exercise index corresponding to user 'D' as '0.2' by using Equation 2. Since user 'D' has the same momentum as user 'B', the server 150 may calculate the momentum index corresponding to user 'D' as '0.5' by using Equation 3. Furthermore, the server 150 may calculate the living index corresponding to user 'D' as '10%' by using Equation 4. Although the amount of exercise actually performed by user 'D' is the same as that of user 'B', the life index of user 'D' can be set much lower than that of user 'B' because he performed the exercise for only one day. .

User 'E' performed daily exercise from Monday to Friday and consumed 1250 kcal for a week while consuming different calories from Monday to Friday. Since user 'E' continues to exercise every day, the server 150 may calculate the exercise index corresponding to user 'E' as '1' by using Equation 2. Since the momentum of user 'E' is higher than that of user 'B', the server 150 may calculate the momentum index corresponding to user 'E' as '1.25' by using Equation 3. Furthermore, the server 150 may calculate the living index corresponding to user 'E' as '125%' by using Equation 4.

According to various embodiments of the present invention, when the living index is calculated to exceed 100%, the server 150 may set the living index of the corresponding user as 100%. According to various embodiments of the present disclosure, the server 150 may deliver a message about exercise moderation to a user whose life index is greater than a preset value.

5C is a flow-chart illustrating the operation of the server 150 according to an embodiment of the present invention. In FIG. 5C, the operation of the server 150 in step S309 disclosed in FIG. 3 is disclosed in detail. Also, in FIG. 5C, the operation of the server 150 starts after step S515 shown in FIG. 5A.

In step S517, the server 150 may compare the living index calculated in step S515 with a preset living index reference value. According to an embodiment of the present invention, the server 150 may compare the living index with the living index reference value for each weather. According to another embodiment of the present invention, the server 150 may compare the living index with the living index reference value for each day of the week. According to another embodiment of the present invention, the server 150 may compare the living index with the living index reference value for each location.

When the living index calculated in step S517 is smaller than the preset living index reference value, in step S519, the server 150 may generate feedback data. For example, the server 150 'The living index is smaller than the reference value. Please exercise.' As another example, the server 150 says, 'There is less exercise on Saturday. Please be extra careful.' Feedback data can be created. For another example, the server 150 'There is no response to the exercise notification. Please make sure to enter whether or not you exercised.' Feedback data can be created. As another example, the server 150 may generate feedback data saying 'Please exercise on Wednesday' to a user whose calculated Wednesday lifestyle index is smaller than a preset lifestyle index reference value. According to another embodiment of the present invention, if there is a precipitation forecast at the location of the user whose living index is smaller than the living index reference value on a rainy day, the server 150 sends a message saying 'It's going to rain, so it would be nice to exercise indoors!' Feedback data can be generated. This is only one example, and is not limited thereto.

Meanwhile, the server 150 according to an embodiment of the present invention performs natural language processing such as natural language generation and natural language understanding, machine learning, and artificial neural networks. network), deep learning, etc., to generate feedback data. According to an embodiment of the present invention, the server 150 may generate user-customized feedback data by utilizing at least one analysis method among natural language processing (NLP)-based related word analysis, emotional word analysis, and issue analysis. .

In step S521, the server 150 may provide the generated feedback data to the first electronic device 110. According to an embodiment of the present invention, the server 150 may provide feedback data to the first electronic device 110 until the user's living index exceeds the standard value for living index. According to another embodiment of the present invention, when the life index of a specific day is smaller than the reference value of the life index, the server 150 may provide feedback data of the previous day of the week to the first electronic device 110 . Alternatively, the server 150 may provide feedback data to the first electronic device 110 together with the first exercise notification message of the corresponding day. According to another embodiment of the present invention, when there is a precipitation forecast at the location of the user whose living index on a rainy day is smaller than the living index reference value, the server 150 transmits feedback data to the first electronic device on the previous day when the corresponding rainfall forecast is present ( 110) can be provided.

On the other hand, if the living index calculated in step S517 is greater than or equal to the preset living index reference value, the server 150 may return to step S301 to collect user data and open data.

An electronic device, server, or external device according to various embodiments of the present document described above is, for example, a smart phone, a tablet PC, a mobile phone, a video phone, a desktop PC, a laptop PC, a personal digital assistant (PDA), It may include at least one of a portable multimedia player (PMP), an MP3 player, a mobile medical device, a camera, or a wearable device.

According to various embodiments, the wearable device is an accessory type (eg, watch, ring, bracelet, anklet, necklace, glasses, contact lens, or head-mounted-device (HMD)), fabric or clothing integral type ( For example, it may include at least one of an electronic clothing), a body attachment type (eg, a skin pad or tattoo), or a body implant type (eg, an implantable circuit).

In some embodiments, the electronic device or external device may be a home appliance. Home appliances include, for example, televisions, DVD players (Digital Video Disk players), audio systems, refrigerators, air conditioners, vacuum cleaners, ovens, microwave ovens, washing machines, air purifiers, set-top boxes, and home automation. It may include at least one of a home automation control panel, a security control panel, a TV box, a game console, an electronic dictionary, an electronic key, a camcorder, or an electronic picture frame.

In another embodiment, the electronic device, the external device, and the wearable device may include various medical devices (eg, various portable medical measuring devices (blood glucose meter, heart rate monitor, blood pressure monitor, or body temperature monitor), MRA (magnetic resonance angiography), MRI (magnetic resonance imaging), CT (computed tomography), camera, or ultrasonic device, etc.), navigation device, satellite navigation system (GNSS (Global Navigation Satellite System)), EDR (event data recorder), FDR (flight data recorder) ), automotive infotainment devices, home robots, or internet of things (e.g. light bulbs, various sensors, electricity or gas meters, sprinkler devices, fire alarms, thermostats, street lights, exercise equipment) , hot water tank, heater, boiler, etc.) may include at least one.

The embodiments disclosed in this document are presented for explanation and understanding of the disclosed technical content, and do not limit the scope of the present invention. Therefore, the scope of this document should be construed to include all changes or various other embodiments based on the technical spirit of the present invention.

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Claims (6)

In the operating method of the health management server,
Collecting user data and open data;
classifying and storing the user data and the open data;
setting a reference value for medication compliance - a first reference value - and a reference value for a lifestyle index - a second reference value - based on the user data and the open data;
calculating the medication compliance and the life index based on the user data and the open data;
generating feedback data by comparing the first reference value with the medication compliance and comparing the second reference value with the life index;
providing the feedback data to a first electronic device;
providing a medication reminder message to the first electronic device;
receiving a medication confirmation message corresponding to the medication reminder message from the first electronic device;
generating medication data based on the medication confirmation message;
extracting a medication response time from the medication data;
generating a table consisting of a user, the number of times required to take medication, and first to fifth time points as fields and corresponding values for each field;
Calculating a medication score based on the table;
checking the required number of times of taking the medicine corresponding to the user;
calculating the medication compliance based on the medication scores extracted for a predetermined period of time and the required number of medication medications;
receiving living data from the first electronic device;
generating exercise data based on the living data;
Checking the required amount of exercise and the number of days required for exercise corresponding to the user;
Extracting whether or not exercise and the amount of exercise are performed from the exercise data;
Calculating an exercise index according to Equation 2 below based on the information on whether or not the exercise is performed;
Calculating a momentum index according to Equation 3 based on the information on the momentum; and
Calculating the life index based on the exercise index and the momentum index,
The step of calculating the medication compliance
Calculate the medication compliance according to Equation 1 below,
The step of calculating the living index is
Calculating the living index according to Equation 4 below
How to operate the health management server.
[Equation 1]

[Equation 2]

[Equation 3]

[Equation 4]

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