JP2014026411A - Health care system and server therefor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To lighten a user's workload.SOLUTION: A health care system comprises: a user terminal 30 for photographing a health care device 40 and transmit the image data to a server 10; and the server 10 for detecting feature points of a shape of the health care device 40 by analyzing the image data received from the user terminal 30, identifying the health care device 40 by comparing the detected feature points with shape data on the health care device 40 previously stored in a DBMS (database management system), and managing measurement data for each identified health care device 40.

Description

  The present invention relates to a health care system that manages measurement data of a health care device and a server thereof.

  In recent years, various health care systems have been proposed while health consciousness is increasing. For example, Patent Document 1 discloses a system in which medical examination data output with a QR code (registered trademark) is read by a camera-equipped mobile phone and the medical examination data is registered in a database of a server via the Internet. According to such a system, since manual input of medical examination data becomes unnecessary, a user's work burden can be reduced.

JP 2008-269304 A

  By the way, there are various types of health care devices such as a weight scale (body composition meter), an activity meter, a blood pressure meter, and a blood glucose meter, and a plurality of health care devices may be used in combination. According to the prior art, when a new healthcare device is used, it is necessary for the user to manually input information on the healthcare device and register it in the system. Such work is necessary every time a new health care device is used, and is troublesome for the user.

  In view of the above-described conventional technology, an object of the present invention is to provide a health care system and a server thereof that can reduce a user's work burden.

  In order to achieve the above object, the invention according to the first aspect is a healthcare system for managing measurement data of a healthcare device, wherein the user terminal captures the healthcare device and transmits the image data to a server. And detecting feature points of the shape of the healthcare device by analyzing image data received from the user terminal, and detecting the detected feature points and shape data of the healthcare device stored in advance in a storage unit. The gist of the invention is to provide a server that identifies the healthcare device by comparison and manages the measurement data for each identified healthcare device.

  The invention according to the second aspect is the shape data of the health care device used by the user of the user terminal when the server compares the feature point with the shape data in the invention according to the first aspect. The gist is to make only the comparison object.

  The invention according to a third aspect is the invention according to the first or second aspect, wherein the server detects character information representing the color or manufacturer of the healthcare device as the feature point, and detects the detected color or manufacturer. The gist is to digitize the character information that represents.

  The invention according to a fourth aspect is the invention according to any one of the first to third aspects, wherein the server automatically cuts out the screen portion of the healthcare device from the image data, and cut out the screen portion. The gist is to perform character identification only for.

  The invention according to a fifth aspect is characterized in that, in the invention according to the fourth aspect, the server identifies a part of the image data in which a large dot difference has occurred as a screen part of the healthcare device. To do.

  The invention according to a sixth aspect is characterized in that, in the invention according to the fourth aspect, the server identifies a boundary between an outer shape of the healthcare device and a screen portion by binarizing the image data. And

  The invention according to a seventh aspect is the invention according to any one of the first to sixth aspects, wherein the user terminal caches shape data of a health care device used for a user of the own terminal, and the cached shape The gist is to identify the healthcare device based on the data.

  In order to achieve the above object, the invention according to the eighth aspect is a health care system server that manages measurement data of a health care device, and a storage unit that preliminarily stores the shape data of the health care device; A receiving unit that receives image data obtained by photographing the healthcare device, an analysis unit that detects feature points of the shape of the healthcare device by analyzing the image data received by the receiving unit, and the analysis unit An identification unit that identifies the healthcare device by comparing the feature points detected by the shape data of the healthcare device stored in advance in the storage unit, and the healthcare identified by the identification unit The gist is to provide a management unit for managing the measurement data for each device.

  ADVANTAGE OF THE INVENTION According to this invention, it is possible to provide the health care system which can reduce a user's work burden, and its server.

It is a network block diagram of the health care system in the embodiment of the present invention. It is explanatory drawing of the function outline | summary of the health care system in embodiment of this invention. 1 is an overall configuration diagram of a health care system in an embodiment of the present invention. It is a functional block diagram of a server in an embodiment of the invention. It is an internal block diagram of the management table in the embodiment of the present invention. It is an internal block diagram of the management table in the embodiment of the present invention. It is an internal block diagram of the management table in the embodiment of the present invention. It is a screen transition diagram of the smart phone in the embodiment of the present invention. It is a figure which shows an example of the image data of the active mass meter in embodiment of this invention. It is a figure which shows an example of the image data of the weight scale in embodiment of this invention. It is a figure which shows an example of the device identification in embodiment of this invention. It is a figure for demonstrating in detail the device identification in embodiment of this invention, Comprising: (a) Comparative example, (b) Example. It is a figure for demonstrating in detail the character identification in embodiment of this invention, Comprising: (a) Comparative example, (b) Example. It is a figure for demonstrating in detail the character identification in embodiment of this invention, Comprising: (a) Comparative example 1, (b) Comparative example 2, (c) Example. It is a flowchart of the health care system in the embodiment of the present invention. It is a sequence diagram of the health care system in the embodiment of the present invention. It is a sequence diagram of the health care system in the embodiment of the present invention.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. The following embodiment exemplifies a health care system for embodying the technical idea of the present invention, and the configuration of the apparatus and the data structure are limited to the following embodiment. It is not a thing.

(Network configuration example)
FIG. 1 is a network configuration diagram of a health care system according to an embodiment of the present invention. As shown in this figure, the server 10 is installed on the IP network 20. The user terminal 30 is a terminal operated by the user, and specifically, is a smart phone 30a or a PC 30b. It is assumed that the user owns a health care device 40 such as an activity meter 40a or a weight scale 40b. Health data measured by the health care device 40 (hereinafter referred to as “measurement data”) is registered in the server 10 via the user terminal 30.

(Functional overview)
FIG. 2 is an explanatory diagram of a functional outline of the health care system according to the embodiment of the present invention. As shown in this figure, a web application (base) 10c is constructed on the web server 10d, and further a DBMS 10a and a server application 10b are constructed thereon. The DBMS 10a is a database management system for managing various data. The server application 10b is for realizing functions such as (1) data acquisition by a camera, (2) shape management of the healthcare device 40, measurement data management, (3) individual identification, and (4) alarm. These functions (1) to (4) will be described in detail later. If such a plurality of functions are implemented as the server application 10b, it is possible to flexibly cope with a change in function and to reduce costs.

(System overall configuration example)
FIG. 3 is an overall configuration diagram of the health care system according to the embodiment of the present invention. As shown in FIG. 3, the health care system includes a server 10, a communication network 21, a smart phone 30 a, a PC 30 b, and a health care device 40. The PC 30b is connected to a communication network 21 such as an IP network 20 via a home GW 22. The smart phone 30a has a camera function 31a as an application. The PC 30b can acquire image data taken by the camera 31b. The user can photograph the healthcare device 40 using the camera function 31a and the camera 31b (hereinafter collectively referred to as “imaging device 31”). The user terminal 30 such as the smart phone 30 a or the PC 30 b transmits the image data captured by the imaging device 31 to the server 10. The server 10 detects the feature point of the shape of the healthcare device 40 by analyzing the image data received from the user terminal 30, and the detected feature point and the shape data of the healthcare device 40 stored in advance in the DBMS 10a Are identified, and the measurement data is managed for each identified healthcare device 40.

(Server configuration example)
FIG. 4 is a functional block diagram of the server 10. For example, the DBMS 10a includes management tables T1 to T5. The management table T1 is a table for managing line IDs, user terminal IDs, and user IDs. The management table T2 is a table for managing healthcare device IDs. The management table T3 is a table for managing the measurement data of the healthcare device 40. The management table T4 is a table for managing healthcare device shape IDs. The management table T5 is a table for managing control data such as threshold values.

  The GUI program 10c refers to and updates data in the management tables T1 to T5 as necessary. For example, when the line used by the PC 30b for the first connection and the healthcare device 40 used are registered, the management tables T1 and T2 are updated. When the threshold value managed by the management table T5 is exceeded, an alarm is sent to the user to notify that. In addition, various functions such as performing authentication processing based on the account data D1 are provided.

(Internal configuration example of management table)
Next, an internal configuration example of the management table will be described. It goes without saying that the internal structure of the management table is not limited and can be changed as appropriate. For example, in the management table T1, not only the line ID, user terminal ID, and user ID but also the health care device ID can be managed. In the management table T3, not only the measurement data of the healthcare device 40 but also the shape data of the healthcare device can be managed.

  FIG. 5 is an internal configuration diagram of the management table T3. In the management table T3, the measurement value (measurement data) of the healthcare device 40 is bundled with various data. “User ID” is an ID for uniquely identifying a user. The “line ID / user terminal ID” is an ID for uniquely identifying the line / user terminal 30 to be registered. The “health care device ID” is an ID that uniquely identifies the health care device 40. “Date” is the date when the measurement value of the healthcare device 40 is measured. “Time” is the time when the measurement value of the healthcare device 40 is measured. “Sensor type” is a classification of a weight scale (body composition meter), an activity meter, and a blood pressure monitor. “Health care device 1 measurement value” is a measurement value of the health care device 1. The same applies to “health care device 2 measurement value” and “health care device 3 measurement value”. “Health care device 1 information” is shape data of the health care device 1. The same applies to “healthcare device 2 information” and “healthcare device 3 information”. “Health care device 1 time stamp” is the time when the health care device 1 information is acquired. The same applies to “health care device 2 time stamp” and “health care device 3 time stamp”.

  FIG. 6 is an internal configuration diagram of the management table T5. In the management table T5, the control data is bundled with various data. The “user ID”, “line ID / user terminal ID”, and “health care device ID” are as described above. “Health care device 1 control” represents the control content of the health care device 1. The same applies to “health care device 2 control” and “health care device 3 control”.

  FIG. 7 is an internal configuration diagram of the management table T1. In the management table T1, the health care device ID is associated with various data. The “user ID”, “line ID / user terminal ID”, “health care device ID”, and “sensor type” are as described above. “Date” is the date when the measured value of the healthcare device 40 is registered in the DBMS 10a. “Time” is the time when the measured value of the healthcare device 40 is registered in the DBMS 10a.

(Screen transition example)
FIG. 8 is a screen transition diagram of the smart phone 30a. Such a screen transition is realized by cooperation between the Web server 10d and the application on the smart phone 30a. First, when an application is launched on the initial screen M1 of the smart phone 30a, the user logs in to the system. In the TOP menu M2, various menus M3 to M9 can be selected. When the data display menu M3 for each device is selected, measurement data for each healthcare device 40 is displayed. When the device data reading menu M4 is selected, the camera function 31a is activated, and the measurement data of the healthcare device 40 is read and stored in the smartphone 30a. When the device data registration menu M5 is selected, the measurement data stored in the smart phone 30a is registered in the server 10. When the registered health care device setting menu M6 is selected, various settings can be made for the health care device 40 registered in the server 10. When the alarm setting menu M7 is selected, the alarm can be set to be transmitted in a predetermined case such as when the measurement data of the health care device 40 is an abnormal value or when it is not registered. When the user information registration menu M8 is selected, user information can be registered in the server 10. When the shape registration menu M9 is selected, the shape of the health care device 40 can be registered in the server 10. On these screens, a graph M10, a wizard M11, and the like can be displayed.

(Device registration)
Next, registration (device registration) of the health care device 40 will be described in detail. The term “device” simply means the health care device 40. The server 10 includes (a) an OCR function, (b) a shape storage function, (c) a registrant, and a registered device storage function. Device registration is performed based on these functions to facilitate device identification described later. (A) The OCR function is a function for reading numbers, characters (steps, mmHg, kg,%, etc.) and pointers. (B) The shape storage function is a function for storing shape data based on the shape feature points (color, shape, number position, screen position, etc.) of the health care device 40. For example, FIG. 9 shows an example of activity meter image data I1 photographed by the photographing device 31, and FIG. 10 shows an example of weight scale image data I2 photographed by the photographing device 31. The area E1 is an area for identifying an outer shape, and the area E2 is an area for identifying a character. Here, as shown in FIG. 9, when the outer shape is substantially elliptical and a number is identified at a predetermined position near the center of the ellipse, the health care device 40 may be recognized as an activity meter. . In addition, as shown in FIG. 10, when the outer shape is substantially rectangular and the pointer is identified at a predetermined position close to one side of the square, the health care device 40 may be recognized as a scale. (C) The registrant / registered device storage function is a function for facilitating information management by binding the registered line and user terminal 30 information with the registrant and registered device.

(Device identification)
Next, identification (device identification) of the health care device 40 will be described in detail. The server 10 includes (a) an OCR identification function and (b) a shape identification function, and performs device identification based on these functions. (A) The OCR identification function is a function that reads and identifies numbers, characters (steps, mmHg, kg,%, etc.), and pointers. (B) The shape identification function is a function for acquiring feature points (color, shape, numerical position, screen position, etc.) of the shape of the health care device 40 as binary data. Similarities between the acquired binary data and the already registered shape data are compared, and those having similar feature vectors are identified.

  FIG. 11 shows an example of device identification. As shown in this figure, the server 10 detects the feature point E3 of the shape of the healthcare device 40 by analyzing the image data I3. Specifically, the data of the feature point E3 is X coordinate, Y coordinate, size, Laplacian, vector, color, character information representing a manufacturer, and the like. The technique for detecting the feature point E3 may be a known technique such as an ORB feature quantity detector. Character information representing colors and manufacturers is digitized. By comparing the detected feature point E3 with the shape data of the health care device 40 stored in advance in the DBMS 10a, it can be identified that the health care device 40 is an activity meter.

  FIG. 12 is a diagram for explaining the device identification in detail. First, as shown in FIG. 12A, when performing device identification, a method of performing matching processing with a large number of device data (for example, image data for several million units) registered in the server 10 can be considered. However, according to this method, a large machine specification is necessary on the device identification side, and it is necessary to inquire the server 10 every time to perform such heavy processing. Accordingly, as shown in FIG. 12B, the user terminal 30 caches the shape data of the health care device 40 used by the user of the user terminal in the storage unit C1, and the health care device based on the cached shape data. 40 may be identified. Specifically, matching processing is performed between the device data (for example, binary data for several units) of the user of the terminal registered in the storage unit C1 and the feature point E3 that is numerical data. In this way, since the processing is lightened, the machine specification of the user terminal 30 that performs device identification can be dealt with even with cheap. Further, if the processing becomes lighter, not only device identification based only on data such as Laplacian and the total amount of change but also device identification based on color and character information (slightly heavy processing) can be performed at the user terminal 30 at the same time. It is possible to improve the accuracy of identification. Furthermore, if device identification is performed at the user terminal 30, the number of inquiries to the server 10 can be reduced, and device identification can be completed early. Of course, when device identification on the user terminal 30 side fails, device identification may be performed on the server 10 side. Even in this case, the matching process can be performed only on binary data for several units linked with the user of the terminal.

(Character identification)
Next, character identification will be described in detail. First, as shown in FIG. 13A, a method is conceivable in which device identification for the area E1 and character identification for the area E2 are performed separately. However, according to this method, separate processing time is required for device identification and character identification. In addition, since many areas such as the area E4 that are not necessary for character identification are read, the accuracy of character identification decreases. Therefore, as illustrated in FIG. 13B, when performing device identification, the server 10 identifies a portion (region E2) where a large difference in dots has occurred as a liquid crystal screen portion. Then, the identified liquid crystal screen portion is automatically cut out, and character identification is performed only on the cut out liquid crystal screen portion.

  FIG. 14 is a diagram for explaining the character identification in more detail. First, as shown in FIG. 14A, there is a method in which a healthcare device 40 is photographed, device identification is performed on the entire image data, and character identification is performed on the entire image data. Conceivable. However, according to this method, many areas that are not necessary for character identification are read, and the accuracy of character identification is reduced. Further, as shown in FIG. 14 (b), the healthcare device 40 is photographed, device identification is performed on the entire image data, and then a preset part is manually cut out, and the cut out part is targeted. A method of performing character identification can be considered. However, according to this method, it is difficult to manually cut out an appropriate portion, and the accuracy of character identification is reduced when the manually cut out portion is not photographed well. Therefore, as illustrated in FIG. 14C, the server 10 captures the health care device 40 and binarizes the image data to identify the boundary between the outer shape of the health care device 40 and the liquid crystal screen portion. . Then, a portion where a difference from the background is generated is automatically cut out as a liquid crystal screen portion, and character identification is performed on the cut out portion as a target. According to the method of FIG. 14C, the time required for character identification can be reduced by about 40% and the accuracy of character identification is improved by about 20% compared to the method of FIG. It is possible to make it. Further, compared with the method of FIG. 14B, it is possible to improve the accuracy of character identification by about 30%.

(Operation example)
FIG. 15 is a flowchart of the healthcare system in the embodiment of the present invention. Here, the operation of device identification, automatic cutting, and character identification will be mainly described.

  First, the health care device 40 is photographed, feature points of the image data are detected, and the detected feature points are acquired as binary data (S1 → S2 → S3). The similarities between the acquired binary data and the already registered shape data are compared, and those having similar feature vectors are identified (S4), and the type of the health care device 40 is specified. Further, the image data is binarized several times, a point where the boundary between the outer shape and the liquid crystal screen part becomes clear is detected, and the liquid crystal screen part is cut out (S5 → S6 → S7). Further, reading from the digital number dictionary is performed, and character identification is performed on the liquid crystal screen portion (S8 → S9). Finally, referring to the threshold value for each device, various information such as a device name and a measured value is output to the smart phone 30a (S10 → S11).

  FIG. 16 is a sequence diagram at the time of initial registration.

  First, when a user, a line, and a user terminal 30 are requested to be grouped on the WEB GUI of the PC 30b, user information is transmitted to the server 10 and registered in the DBMS 10a (S21 → S22 → S23). Next, the line ID and MAC address are transmitted from the smart phone 30a to the server 10 and registered in the DBMS 10a (S24 → S25). Next, the DBMS 10a is referred to, and a report for linking the user, the line, and the user terminal 30 is transmitted to the smart phone 30a (S26 → S27). Next, when the user joins the healthcare device 40 and the user on the WEB GUI of the PC 30b, an application on the smartphone 30a is activated and the healthcare device 40 is photographed by the camera function 31a (S28 → S29 → S30 → S31). Next, when image data is transmitted from the smart phone 30a to the server 10, confirmation of the image data (shape analysis / image reading position confirmation / registration device confirmation) is performed (S32 → S33). Normally, a lot of device information is registered in the DBMS 10a. Here, however, device identification is performed only by analyzing the difference with the healthcare device 40 owned by the DBMS 10a. Next, the analysis data is transmitted from the server 10 to the smart phone 30a, and the analysis result is displayed (S34 → S35). Next, when an alarm setting is requested on the WEB GUI of the PC 30b, the threshold value is transmitted to the server 10 and registered in the DBMS 10a (S38 → S39 → S40). As a result, the threshold is determined, and an alarm is transmitted from the server 10 to the PC 30b (S50 → S51). For example, an alarm is transmitted when the measured blood pressure or weight is far from the threshold value or when the measurement data is not updated for a certain period. It is possible to determine whether or not the measurement data is appropriate from the threshold value, check whether or not the user is an individual, and check data to be registered, thereby preventing reading errors and the like.

  FIG. 17 is a sequence diagram when registering daily measurement data.

  First, when registration of measurement data and user binding are requested on the WEB GUI of the PC 30b, an application on the smartphone 30a is activated and the healthcare device 40 is photographed by the camera function 31a (S61 → S62 → S63 → S64). Next, when the image data is transmitted from the smart phone 30a to the server 10, the image data is confirmed (S65 → S66). It is possible to respond flexibly even when device addition or function addition occurs. Next, the numerical analysis data is transmitted from the server 10 to the smart phone 30a, and the numerical result is displayed (S67 → S68). As already described, if the device information is cached in the user terminal 30, device identification can be completed early. Numerical analysis data can be predicted from threshold values and time-series data, and it is possible to save time and effort for device identification and data input each time. Further, the feature point analysis data is transmitted from the server 10 to the smart phone 30a, and the device confirmation result is displayed (S69 → S70). The liquid crystal screen portion is identified by the OCR function, and the outer shape of the device is identified by the shape identification function (learned in advance when registering as background processing). The OCR function and the shape identification function are linked, and the character identification portion is cut out at the timing when the feature point is identified by the shape identification function, thereby simplifying the processing. Finally, when the registration date / time, registration device, measurement result, and the like are confirmed on the smart phone 30a, the measurement data of the healthcare device 40 is transmitted from the smart phone 30a to the server 10 and registered in the DBMS 10a (S72 → S73). ).

  As described above, in the healthcare system according to the embodiment of the present invention, the feature point of the shape of the healthcare device 40 is detected by photographing the healthcare device 40 and analyzing the image data, and the detected feature point Is compared with the shape data of the health care device 40 stored in advance in the DBMS 10a, the health care device 40 is identified, and the measurement data is managed for each identified health care device 40. As a result, even when a new healthcare device 40 is used, it is not necessary for the user to manually input information on the healthcare device 40, so that the user's workload can be reduced.

  Moreover, when comparing the feature point and the shape data, the server 10 sets only the shape data of the health care device 40 used by the user of the user terminal 30 as a comparison target. Thereby, since a comparison object is narrowed down, a processing burden can be reduced.

  Further, the server 10 detects character information representing the color or manufacturer of the health care device 40 as a feature point, and digitizes the character information representing the detected color or manufacturer. Thereby, since device identification is performed based on color and character information, the accuracy of device identification can be improved.

  Further, the server 10 automatically cuts out the screen portion of the healthcare device 40 from the image data, and performs character identification only for the cut-out screen portion. Thereby, since character recognition is performed only for a necessary portion, the accuracy of character identification can be improved.

  In addition, the server 10 identifies a portion in which a large dot difference has occurred in the image data as a screen portion of the healthcare device 40. Thereby, since the screen portion is automatically identified with high accuracy, the accuracy of character identification can be improved.

  Further, the server 10 binarizes the image data to identify the boundary between the outer shape of the healthcare device 40 and the screen portion. Thereby, since the screen portion is automatically identified with high accuracy, the accuracy of character identification can be improved.

  Further, the user terminal 30 caches the shape data of the health care device 40 used by the user of the terminal itself, and identifies the health care device 40 based on the cached shape data. Thereby, since device identification is performed on the user terminal 30 side, the number of inquiries to the server 10 can be reduced, and device identification can be completed early.

  The server 10 is received by a storage unit (DBMS 10a) that stores shape data of the healthcare device 40 in advance, a reception unit (GUI program 10c) that receives image data obtained by capturing the healthcare device 40, and a reception unit. The analysis unit (server application 10b) that detects the feature point of the shape of the healthcare device 40 by analyzing the image data, the feature point detected by the analysis unit and the healthcare device 40 stored in advance in the storage unit An identification unit (server application 10b) that identifies the healthcare device 40 by comparing the shape data of each and a management unit (DBMS 10a) that manages the measurement data for each healthcare device 40 identified by the identification unit Prepare. As a result, even when a new healthcare device 40 is used, it is not necessary for the user to manually input information on the healthcare device 40, so that the user's workload can be reduced.

  In addition, according to the health care system in the embodiment of the present invention, various effects can be obtained. For example, since the learning function is provided, the shape identification of the health care device 40 and the numerical prediction from the measurement data (weight, blood pressure, etc.) so far can be made easy to input data. Further, since the control logic is shared by the server 10 deployed on the network, not the health care device 40, man-hours for adding new functions can be reduced. If function development is performed on the server 10 side, it is possible to improve user convenience without changing the user terminal 30. Furthermore, the control logic can be converted into APIs to make various functions easy to use, and settings for the control logic can be performed on the network. Furthermore, data can be easily managed even with a non-NW compatible healthcare device. Furthermore, since the data is managed by the network, the log information can be viewed by any terminal.

  Note that the present invention can be realized not only as a healthcare system, but also as a healthcare method that uses a characteristic processing unit included in such a healthcare system as a step, or executes these steps on a computer. It can also be realized as a program to be executed. It goes without saying that such a program can be distributed via a recording medium such as a CD-ROM or a transmission medium such as the Internet.

10 ... Server 10a ... DBMS (storage unit, management unit)
10c: GUI program (receiving unit, analyzing unit, identifying unit)
30 ... User terminal 30b ... PC
30a ... Smartphone 40 ... Healthcare device

Claims (8)

A health care system for managing measurement data of a health care device,
A user terminal that photographs the healthcare device and transmits the image data to a server;
By analyzing the image data received from the user terminal, the feature point of the shape of the health care device is detected, and the detected feature point is compared with the shape data of the health care device stored in the storage unit in advance. And a server that manages the measurement data for each identified health care device.   2. The health according to claim 1, wherein when comparing the feature point and the shape data, the server sets only the shape data of a health care device used by a user of the user terminal as a comparison target. Care system.   The said server detects the character information showing the color or manufacturer of the said health care device as the said feature point, and quantifies the character information showing the detected color or manufacturer. Health care system.   4. The server according to claim 1, wherein the server automatically cuts out a screen portion of the healthcare device from the image data, and performs character identification only on the cut-out screen portion. 5. Health care system.   The healthcare system according to claim 4, wherein the server identifies a portion of the image data where a large dot difference has occurred as a screen portion of the healthcare device.   The health care system according to claim 4, wherein the server identifies a boundary between an outer shape of the health care device and a screen portion by binarizing the image data.   The said user terminal caches the shape data of the health care device used for the user of a self-terminal, and identifies the said health care device based on the cached shape data. The health care system according to one item. A healthcare system server for managing measurement data of healthcare devices,
A storage unit for storing in advance the shape data of the healthcare device;
A receiving unit for receiving image data obtained by photographing the health care device;
An analysis unit for detecting feature points of the shape of the healthcare device by analyzing the image data received by the reception unit;
An identification unit for identifying the healthcare device by comparing the feature point detected by the analysis unit and the shape data of the healthcare device stored in advance in the storage unit;
A management unit that manages measurement data for each of the healthcare devices identified by the identification unit.

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