KR20160125543A - User-oriented healthcare big data service method, computer program and system - Google Patents

Abstract

A user-centric health care big data service method and system for performing the method of the present invention, comprising the steps of: a) measuring personal health information in a wearable device; (b) obtaining raw (RAW) data related to the personal health information measured at the mobile terminal and transmitting the obtained raw data to a big data server; (c) converting raw data received at the big data server into data of big data; (d) converting the data converted by the big data server into personalized healthcare data and storing the personalized healthcare data; And (e) retrieving from the personalized healthcare data stored in the big data server at the mobile terminal and obtaining and displaying information selected by the user.
The present invention provides a high-quality user-centered healthcare service more conveniently by processing large-capacity data measured from a wearable device into big data and processing and processing the data more efficiently.

Description

USER-ORIENTED HEALTHCARE BIG DATA SERVICE METHOD, COMPUTER PROGRAM AND SYSTEM BACKGROUND OF THE INVENTION 1. Field of the Invention < RTI ID = 0.0 >

The present invention relates to a healthcare big data service method, a computer program and a system for carrying out the method, and more particularly, to a health care big data service method in which personal health information generated from a wearable device is converted into big data, A service method, a program and a system thereof.

Currently, various IT products and care services (such as child protection and growth care, care for the elderly, mental healing care of the general public, and financial forecasting management in a rapidly changing situation) , Psychology, physiology, emotion, etc.) are difficult to understand, express and quantify, there is a fundamental limitation in application and advancement.

In particular, there is a lack of consideration of the factors that determine 'I' represented by lifestyle, and it faces the difficulty of tools or methods that characteristically express human beings with complex and diverse characteristics.

To overcome this problem, various studies using lifelog data have been conducted worldwide, but the lack of innovative devices for lifelog collection and semantic analysis of vast amounts of data have not yet been solved .

However, in recent years, as devices for collecting such life logs, various sensors built in a smart phone have been used, or wearable devices that measure various health-related information or exercise-related information by wearing the device, Although a device capable of collecting log information has been developed and marketed, there is still a very limited technology for efficiently analyzing and extracting large amounts of data obtained therefrom and converting the data into meaningful information.

In addition, although many manufacturers currently produce and sell wearable devices, they are only focusing on personal health measurement based on healthcare. In addition, it is urgently required to construct a dedicated system that can utilize the generated data, but there is no system or method for a healthcare-related big data service that can be constructed and systemized.

Korean Patent Laid-Open Publication No. 10-2014-0146748 (public date: December 29, 2014)

A user-oriented health care big data service method according to the present invention, a computer program and a system for performing the method have the following problems.

First, a method and system for efficiently storing and processing large-capacity data measured from a wearable device.

Second, it is intended to provide a user-oriented health care service more conveniently by processing a large amount of data measured from a wearable device into big data and processing and processing the data more efficiently.

The solution of the present invention is not limited to those mentioned above, and other solutions not mentioned can be clearly understood by those skilled in the art from the following description.

According to a first aspect of the present invention, there is provided a method of measuring personal health information, comprising the steps of: (a) measuring personal health information in a wearable device; (b) obtaining raw (RAW) data related to the personal health information measured at the mobile terminal and transmitting the obtained raw data to a big data server; (c) converting raw data received at the big data server into data of big data; (d) converting the data converted by the big data server into personalized healthcare data and storing the personalized healthcare data; And (e) retrieving from the personalized healthcare data stored in the big data server at the mobile terminal and obtaining and displaying information selected by the user.

Here, the personal health information includes personal record information including a recording message using a wearable device by a user and personal health information measured through a sensor of the wearable device.

In the step (b), RAW data relating to the personal health information measured in the wearable device is acquired and stored in real time in the mobile terminal, and the acquired RO data is transmitted to the big data server in real time (RAW) data related to the personal health information measured in the wearable device is periodically acquired and stored in the mobile terminal, and the obtained raw data is stored at a predetermined cycle To the big data server.

In addition, in the step (c), it is preferable to convert the raw data into big data using a file distribution system, a parallel data processing technique, and a big table technique, Health care information including personal medical data, health state data based on the personal health information, and health prevention information, treatment and management information of the user based on the health data and the health state data In the step (a), the personal health information may include user voice information measured in the wearable device.

And, a second aspect of the present invention is a computer program stored in a medium in combination with hardware for executing the above-described service method.

A third aspect of the present invention is summarized as a wearable device worn by a user for measuring a user's personal health information; A big data server for converting the measured personal health information into data of big data and converting the converted data into personalized health care data; And a mobile terminal for acquiring the measured personal health information as raw data and transmitting the measured personal health information to the big data server, wherein the mobile terminal retrieves from the personalized healthcare data and acquires information selected by the user .

Preferably, the big data server includes a personal health record (PHR) server, the big data server is connected to the PACS server of the medical institution to acquire the medical information of the user, It is desirable to include a NoSQL database.

Preferably, the big data server is equipped with an Elasticsearch search engine, and the wearable device preferably includes a voice recognition device capable of recognizing the user's voice.

The user-oriented health care big data service method according to the present invention, a computer program and a system for carrying out the method have the following effects.

First, a method of efficiently storing and processing massive data measured from a wearable device, a service method and system capable of contributing to the improvement of personal health by providing better quality healthcare information and updated information in real time or periodically .

Second, a large amount of data measured from a wearable device is converted into big data and then processed and processed more efficiently, thereby providing a user-oriented health care service conveniently.

Third, it provides a service that enables user-oriented personalized care by establishing a real-time database of preventive medicine and providing reliable data to users (general, patient, doctor, etc.).

The effects of the present invention are not limited to those mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the following description.

FIG. 1 is a flowchart illustrating a method for a user-centered healthcare big data service according to an embodiment of the present invention.
2 is a flowchart illustrating a method for a user to retrieve information and obtain a result in a user-centered healthcare big data service method according to an embodiment of the present invention.
3 is a block diagram illustrating a configuration of a user-centric health care big data service system according to another embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings so that those skilled in the art can easily carry out the present invention. It will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the spirit or scope of the invention. Wherever possible, the same or similar parts are denoted using the same reference numerals in the drawings.

The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The singular forms as used herein include plural forms as long as the phrases do not expressly express the opposite meaning thereto.

Means that a particular feature, region, integer, step, operation, element and / or component is specified and that other specific features, regions, integers, steps, operations, elements, components, and / It does not exclude the existence or addition of a group.

All terms including technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Predefined terms are further interpreted as having a meaning consistent with the relevant technical literature and the present disclosure, and are not to be construed as ideal or very formal meanings unless defined otherwise.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the drawings.

FIG. 1 is a flowchart illustrating a method for a user-centered healthcare big data service according to an embodiment of the present invention. As shown in FIG. 1, the user-oriented health care big data service method according to an embodiment of the present invention includes: a) measuring (S100) personal health information in a wearable device 100; (b) obtaining raw data related to the personal health information measured at the mobile terminal 200 and transmitting the obtained raw data to the big data server 300 (S200); (c) converting raw data (RAW) received from the big data server 300 into big data (S300); (d) converting (S400) the converted data into personalized healthcare data and storing the personalized healthcare data; And (e) retrieving from the personalized healthcare data stored in the big data server 300 at the mobile terminal 200 and acquiring and displaying information selected by the user (S500).

As described above, the embodiment of the present invention collects and stores health related information and exercise related information collected from various wearable devices 100 as RAW data from the user's mobile terminal 200, The data server 300 switches and processes the data of the big data and proposes a service system that can easily acquire and confirm user-customized health care information from the mobile terminal 200 of the user.

As described above, conventionally, various health and exercise measurement sensors or wearable devices 100 measure specific information, display it through a mobile device or the like through brief analysis and processing based on the measured information, The information quality and application were limited in that it provided a degree of system.

Accordingly, in the embodiment of the present invention, in addition to the health and exercise information of the user acquired from the various wearable devices 100 used by the user, the health and exercise information of the user, which is collected by the user through the wearable device 100, Personalized health care information is generated by using a big data processing method such as a file distribution processing system such as Hadoop or NoSQL and a parallel data processing method and the user can conveniently use the large data processing method, So that it is possible to provide a service system capable of contributing to the improvement of individual health by providing healthcare information of higher quality and information updated in real time or every time.

Hereinafter, a service method that is progressed step by step will be described in detail with reference to the drawings.

(a) Step (S100) is a step of measuring personal health information in the wearable device 100. Here, the wearable device 100 is a device worn by a user such as a watch, a glasses, a patch, etc., and stores therein health information such as the blood pressure of the user, blood glucose, etc. and the health information such as the heart rate, And a wireless communication device for transmitting data measured through a sensor to the outside. As the wireless communication device, it is possible to use a Bluetooth or Zigbee device capable of communicating in a short distance, or it may be equipped with an apparatus for Internet communication.

In addition, the wearable device 100 is a portable device that not only measures the health and exercise information of the user but also records various personal information related to the privacy of the user through voice or text messages. It is also possible to acquire lifglog information of the user.

That is, the above-described personal health information includes personal health information or exercise information of a user measured through a sensor built in the wearable device 100, and voice and text messages recorded or stored through the wearable device 100 Information such as life log information. This is a method of analyzing information that is mixed with physical information measured by a sensor, such as an individual's health state or exercise state, together with life log information expressing the current user's thoughts or feelings, etc., using a big data analysis method , It is possible to generate or provide more accurate personal healthcare information for the user.

Since the life log information of the individual user is personal privacy information related to privacy, it is needless to say that the information communication should have security and confidentiality through encryption and the like. In addition, the measurement of the personal health information can be performed in real time through the wearable device 100, or can be measured at a specific time period.

(b) Step (S200) is a step of acquiring raw data (RAW) related to the personal health information measured by the mobile terminal 200 and transmitting the obtained raw data to the big data server 300 . Here, the mobile terminal 200 may be a portable computing device having a wireless communication device such as a smart phone, a tablet PC, and a PDA. That is, in step (b), the mobile terminal 200 such as a smart phone acquires raw (RAW) data measured at a real time or a specific time period in the wearable device 100, And transmits it to the big data server 300.

In the embodiment of the present invention, the open API is used to externally utilize the personal health information measured in the wearable device 100. That is, the mobile terminal 200 obtains RAW data related to personal health information by using the open API and transmits it to the big data server 300 connected to the network.

(c) Step S300 is a step of converting the raw data received from the big data server 300 into big data. That is, a large amount of raw data (RAW) data for personal health information accumulated in real time is processed and analyzed into desired data by a file distribution and parallel processing technique, so that the user can easily receive high quality health and care information through the mobile terminal 200 And the data is processed so that it can be provided.

Big data refers to large-scale data generated in a digital environment, which is large in size, has a short generation cycle, and includes not only numeric data but also text and image data. As the amount of data is increased, the kinds of data are also diversified. It is possible to analyze and predict the opinions and opinions through the location information and SNS as well as the behavior of the people.

The characteristic of big data is generally summarized as 3V. (O'Reilly Radar Team, 2012), which means the volume of data, the velocity of data generation, and the varieties of the form. In recent years, we have added value and complexity.

Software and hardware that analyze and process these data in accordance with the characteristics of such big data also use open source Hadoop or NoSQL or R (open source statistical solution) analysis package, distributed parallel processing technology, and cloud computing. Enables efficient system operation without building expensive data warehouses based on existing expensive storage and databases.

In the user-oriented healthcare big data service method according to the embodiment of the present invention, the large data (RAW) data measured in the wearable device 100 is stored in the big data server 300 In the step of converting data into data, it is preferable to convert the raw data into big data using a file distribution system, a parallel data processing technique, and a big table technique.

Here, the distributed file system (GFS) is a technique for creating large-scale storage by combining a plurality of computers. In general, in the case of a web search engine, it is necessary to store a huge amount of web pages existing all over the world, or data on the Internet is very rapidly growing. Therefore, in order to securely store and efficiently process large- It is desirable to use such a distributed file system as a system for storing and processing big data.

Distributed file systems always copy and store multiple files for this purpose. It also saves multiple copies of information about the file's contents and location. Because the contents and information of the files are distributed and stored on several computers, the search time is shortened. Also, even if one computer fails, the information contained therein is not lost because there is a copy elsewhere.

The parallel data processing technique is a distributed data processing technique of the big data used in the embodiment of the present invention. In the embodiment of the present invention, MapReduce, which is a parallel data processor of distributed data, is used.

MapReduce is a distributed data processing technology that utilizes multiple computers for efficient data processing (Dean & Ghemawat, 2004). As the name implies, MapReduce consists of two processes: Map and Reduce. First, in the map phase, large data is distributed to several computers in parallel to produce new data (intermediate results), and in the redist step, the intermediate results thus generated are finally combined to produce desired results. The redistribution process also applies a distributed processing method that uses several computers at the same time.

That is, in the embodiment of the present invention, the data processing step of the big data server 300 distributes a large amount of raw data to a plurality of computers constituting the big data server 300 in the map step, To intermediate results, combining the intermediate results generated in the redesing step, and finally generating the desired result by the user. The Reduce step is also dedicated to a distributed processing approach that utilizes multiple computers simultaneously.

Bigtable is a distributed storage system for reading and writing large amounts of data. Bigtable is a distributed storage system for processing structured data (Fay Chang, 2006). In order to efficiently read and write large-scale complex data structures such as web search, BigTable has a complex structure unlike existing relational databases, but has advantages in that it can process faster and more accurately than existing RDBs in terms of data processing.

(d) Step (S400) is a step of converting the data converted by the big data server 300 into personalized healthcare data and storing the personalized healthcare data. Here, the personalized healthcare data is processed by the big data server 300 to measure the RAW data of the collected personal health information, and provides exercise, health, and care information most suitable for the individual . That is, in the step (d), the large data measured in real time in the wearable device 100 and the recorded personal recorded message information are collected and processed by the big data server 300 to provide personalized health care information to be.

In addition, the personalized health care information or each data processed in the big data server 300 can be provided as customized data to a user (general user, patient, doctor), and the content of each data can be provided to the user It is desirable to provide the information only when it is encrypted or registered or authenticated so as to have the nature of "

Here, the personalized healthcare data may include health care data based on individual medical data, personal health information, and disease prevention, treatment, and management information of the user based on the health data and the health state data It is preferable to include health care information.

(e) Step S500 is a step of retrieving from the personalized healthcare data stored in the big data server 300 at the mobile terminal 200 and acquiring and displaying information selected by the user. This step refers to a step in which a user connects to the big data server through the mobile terminal 200 to retrieve desired data or information and displays the retrieved result on the display window of the mobile terminal 200. [

That is, in order to execute the user-oriented health care big data service method according to the embodiment of the present invention in a smart phone as the mobile terminal 200, various menu bars, search windows The user can easily access the big data server 300 through a user interface such as category classification to acquire and confirm high-quality customized health care information.

2 is a flowchart illustrating a method for a user to retrieve information and obtain a result in a user-centered healthcare big data service method according to an embodiment of the present invention. 2, when the user performs a search through the mobile terminal 200 (Search request), the mobile terminal 200 accesses the big data server 300 or the personal health record (PHR) server, The Big Data Server 300 generates a result through the Big Data Analysis process and transmits the result to the mobile terminal 200. Result Then the terminal in the hair displays the result page on the display window Thus, the user can easily check the result of the retrieved information. (Result Page)

2, the wearable device 100 worn by the user recognizes the voice of the user, and the mobile terminal 200 then transmits the user's voice to the big data server 300 Not only the search request but also the voice data of the recognized user is included in one piece of personal health information and transmitted to the big data and the big data server 300 analyzes the voice data to be used as the judgment of the abnormal symptom or the remote medical data It is possible to feed back processing and analysis results to the mobile terminal 200 again.

Here, the mobile terminal 200 can classify the voice recognition information received from the wearable device 100 by voice recognition algorithm in consideration of the date, time, and past voice information, and record and store the voice recognition information. It can also be used as remote medical data by connecting to an external remote medical server. As described above, in the case of a general user, personal health record data or healthcare information constructed with big data can be easily obtained by using a voice recognition function, and data of a specific situation (abnormality, etc.) It is of course also possible to receive messages using the message function.

3 is a block diagram illustrating a configuration of a user-centric health care big data service system according to another embodiment of the present invention. 3, the healthcare big data service system according to the embodiment of the present invention is a system that performs the above-described method, and is a wearable device 100 that is worn by a user and measures a user's personal health information, ; A big data server 300 for converting the measured personal health information into big data and converting the converted data into personalized healthcare data; And a mobile terminal (200) for acquiring the measured personal health information as RAW data and transmitting the measured personal health information to the big data server (300), wherein the mobile terminal (200) And acquires and displays information selected by the user.

As described above, the embodiment of the present invention is a system for performing a user-oriented healthcare big data service method of the embodiment of FIG. 1, including a wearable device 100, a mobile terminal 200 and a big data server 300 .

Here, the wearable device 100 is also referred to as a wearable computer, and refers to a computer or a device that can be worn like a pair of glasses, a watch, clothes, etc., and can be worn by the user at all times, The mobile terminal 200 refers to a computing device that is portable and portable, such as a smart phone, a tablet PC, and a PDA, and is equipped with a wireless communication device and is capable of short-range wireless communication and network communication such as the Internet.

As shown in FIG. 3, the big data server is formed as a Hadoop cluster group capable of distributing and parallelizing a large amount of data into a group of computing devices capable of network communication or a group thereof. In other words, the large data server 300 is composed of a plurality of NoSQL databases and a cluster of Hadoop format composed of a master node and a plurality of slave nodes. The big data server 300 is equipped with an Elastics search search engine, Can be enhanced.

Also, the big data server 300 preferably includes a personal health record (PHR) server or is connected to a medical image information system (PACS) server of a medical institution to acquire medical information of the user. Personal Health Record (PHR) servers can be used as data for telemedicine and preventive medicine data collection, acquisition and processing in real-time in health centers or hospitals, and have the advantage of enhancing security and confidentiality.

In addition, by linking with medical-related servers such as PACS servers of external medical institutions, medical information can be used more abundantly and more accurately, so that the information generated through the big data service provides high quality service with higher security, accuracy and predictability can do.

As described above, by using the system according to the embodiment of the present invention, personal health information is acquired from the wearable device 100 and transmitted to the server, and it is stored in a large data system (Hadoop, MongoDB, etc.) instead of a conventional relational database ), And then stores and processes the data, thereby providing a big data healthcare service centered on the general user.

The embodiments and the accompanying drawings described in the present specification are merely illustrative of some of the technical ideas included in the present invention. Accordingly, the embodiments disclosed herein are for the purpose of describing rather than limiting the technical spirit of the present invention, and it is apparent that the scope of the technical idea of the present invention is not limited by these embodiments. It will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

100: wearable device 200: mobile terminal 300: big data server

Claims (14)

(a) measuring personal health information in a wearable device;
(b) obtaining raw (RAW) data related to the personal health information measured at the mobile terminal and transmitting the obtained raw data to a big data server;
(c) converting raw data received at the big data server into data of big data;
(d) converting the data converted by the big data server into personalized healthcare data and storing the personalized healthcare data; And
(e) retrieving from the personalized healthcare data stored in the big data server at the mobile terminal and acquiring and displaying information selected by the user, and displaying the personalized healthcare data. The method according to claim 1,
The personal health information may include:
The personal record information including the recording message using the wearable device by the user,
And the personal health information measured through the sensor of the wearable device. The method of claim 2,
The step (b)
(RAW) data related to personal health information measured in the wearable device is acquired and stored in real time in the mobile terminal, and the acquired raw data is transmitted to a big data server in real time. Healthcare Big Data Service Method. The method of claim 2,
The step (b)
(RAW) data relating to personal health information measured in the wearable device is periodically acquired and stored in the mobile terminal, and the acquired raw data is transmitted to the big data server at regular intervals. Centralized healthcare Big data service method. The method according to claim 1,
The step (c)
(RAW) data into data of a big data using a file distribution system, a parallel data processing technique, and a big table technique. The method according to claim 1,
The personalized healthcare data includes personal medical data of a user,
Health status data based on the personal dry -ness information,
And health care information including disease prevention, treatment, and management information based on the health data and the health state data between the user and the health care provider. The method according to any one of claims 1 to 6,
In the step (a)
Wherein the personal health information includes user voice information measured in the wearable device. A computer program stored on a medium for execution in accordance with claim 1 in combination with hardware. A wearable device for measuring a user's personal health information by being worn by a user;
A big data server for converting the measured personal health information into data of big data and converting the converted data into personalized health care data; And
And a mobile terminal for acquiring the measured personal health information as raw data and transmitting the personal health information to the big data server,
Wherein the mobile terminal retrieves from the personalized healthcare data and acquires and displays information selected by the user. The method of claim 9,
The big data server,
A personal health record (PHR) server. The method of claim 9,
Wherein the big data server is connected to the PACS server of the medical institution to acquire the medical information of the user. The method of claim 9,
Wherein the Big Data Server includes a NoSQL database. The method of claim 9,
Wherein the big data server is equipped with an Elastics search search engine. The method of claim 9,
Wherein the wearable device comprises a voice recognition device capable of recognizing a voice of a user.

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