Health condition estimation system, method, program, storage medium, server and user terminal

Abstract

To estimate the health condition of a user from an image of urine without presenting the image of urine to the user.SOLUTION: A health condition estimation system that estimates a health condition of a user from an image of urine, comprises: an image acquisition unit that acquires an image of urine; an extraction unit that extracts a feature quantity which is characteristic of the image of urine from the image acquired by the image acquisition unit; an estimation unit that estimates the health condition of the user from the image acquired by the image acquisition unit using an estimation model which has been trained by machine learning with biological information for the user and the feature quantity extracted by the extraction unit as learning data; a display control unit that displays, on a display unit, information on the health condition of the user estimated by the estimation unit; and an inhibition unit that inhibits display of the image of urine acquired by the image acquisition unit on the display unit.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to a health condition estimation system, a method, a program, a storage medium, a server, and a user terminal. [Background technology]

[0002] BACKGROUND ART Conventionally, there is known a technique for displaying various health information calculated based on the color of urine photographed by an imaging module (see Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Special Publication No. 2023-517305 Summary of the Invention [Problem to be solved by the invention]

[0004] However, some users (subjects) may be reluctant to view an image of their own urine.

[0005] The problem to be solved by the present invention is to estimate a user's health condition from an image of urine without presenting the image of urine to the user. [Means for solving the problem]

[0006] [1] A health condition estimation system according to one embodiment includes: A health condition estimation system that estimates a user's health condition from a urine image, comprising: an image acquisition unit for acquiring an image of urine; an extraction unit that extracts a feature amount that is characteristic of a urine image from the image acquired by the image acquisition unit; an estimation unit that estimates a health condition of the user from the image acquired by the image acquisition unit using an estimation model that has been machine-learned using the user's biometric information and the feature amount extracted by the extraction unit as learning data; a display control unit that displays information about the user's health condition estimated by the estimation unit on a display unit; and a prohibition unit that prohibits the display of the urine image acquired by the image acquisition unit on the display unit; Equipped with.

[0007] [2] A health condition estimation system according to one aspect is the health condition estimation system described in [1] above, The extraction unit extracts color information of urine as a feature characteristic of the urine image.

[0008] [3] A health condition estimation system according to one aspect is the health condition estimation system according to [1] or [2] above, the biological information is a blood glucose level of the user, The information on the health condition is the degree of diabetes.

[0009] [4] A health condition estimation system according to one aspect is the health condition estimation system according to any one of [1] to [3] above, the biological information includes at least one of a blood hematocrit value, a blood urea nitrogen / creatinine ratio, and a blood uric acid value; The health condition information includes the degree of dehydration.

[0010] [5] A health condition estimation system according to one aspect is the health condition estimation system according to any one of [1] to [4] above, The device further includes a notification unit that notifies a user when the estimation unit has not performed the estimation for a predetermined period of time.

[0011] [6] In one embodiment, the method comprises: A method for estimating a user's health condition from a urine image, comprising: an image acquisition step of acquiring an image of urine; an extraction step of extracting a feature amount characteristic of a urine image; an estimation step of estimating the user's health condition from the urine image using an estimation model that has been machine-learned using the user's biometric information and features extracted from the urine image as learning data; a display step of displaying information about the estimated health condition of the user on a display unit; a prohibition step of prohibiting the display of an image of urine on the display unit; Includes:

[0012] [7] A program according to one aspect includes: A program for causing a computer to execute a method for estimating a user's health condition from a urine image, the method comprising: A method for estimating a user's health condition from a urine image, comprising: an image acquisition step of acquiring an image of urine; an extraction step of extracting a feature amount characteristic of a urine image; an estimation step of estimating the user's health condition from the urine image using an estimation model that has been machine-learned using the user's biometric information and features extracted from the urine image as learning data; a display step of displaying information about the estimated health condition of the user on a display unit; a prohibition step of prohibiting the display of an image of urine on the display unit; Includes:

[0013] [8] A storage medium according to one aspect includes: A computer-readable storage medium storing the program described in [7] above.

[0014] [9] In one aspect, a server includes: A server used in a health condition estimation system that estimates a user's health condition from a urine image, comprising: a receiving unit that receives an image of urine from a user terminal; an image acquisition unit that acquires an image of the urine received by the receiving unit; an extraction unit that extracts a feature amount that is characteristic of a urine image from the image acquired by the image acquisition unit; an estimation unit that estimates a health condition of the user from the image acquired by the image acquisition unit using an estimation model that has been machine-learned using the user's biometric information and the feature amount extracted by the extraction unit as learning data; a transmission unit that transmits information about the user's health condition estimated by the estimation unit to the user terminal; Equipped with.

[0015]

[10] A user terminal according to one aspect includes: A user terminal used in a health condition estimation system that estimates a user's health condition from a urine image, comprising: a transmitting unit that transmits the urine image to a server that includes an image acquiring unit that acquires a urine image, an extracting unit that extracts feature amounts characteristic of the urine image from the image acquired by the image acquiring unit, and an estimating unit that estimates the user's health condition from the image acquired by the image acquiring unit using an estimation model that has been machine-learned using the user's biometric information and the feature amounts extracted by the extracting unit as learning data; a receiving unit that receives information about the user's health condition estimated by the estimation unit of the server; a display control unit that displays the information about the user's health condition received by the receiving unit on a display unit; a prohibition unit that prohibits the display of the urine image acquired by the image acquisition unit of the server on the display unit; Equipped with. [Effects of the Invention]

[0016] According to the present invention, it is possible to estimate a user's health condition from an image of urine without presenting the image of urine to the user. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a diagram showing an example of the system configuration of a health state estimation system 1 according to the present embodiment. [Figure 2] 1 is a block diagram showing an example of a hardware configuration of a health state estimation system 1 according to the present embodiment. [Figure 3] 1 is a block diagram showing an example of the functional configuration of a health condition estimation system 1 according to the present embodiment. [Figure 4] 4 is a flowchart showing an example of the operation of the health state estimation system 1 according to the present embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0018] Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. In each drawing, components having equivalent functions are designated by the same reference numerals, and detailed description of the components having the same reference numerals will not be repeated.

[0019] (Overview of the health status estimation system) The health condition estimation system 1 according to this embodiment is a system that estimates the health condition of a user from image data of the user's urine. Details of the health condition estimation system according to this embodiment will be described below.

[0020] (Configuration of health status estimation system) 1 is a diagram showing a schematic configuration of a health condition estimation system 1 according to this embodiment. As shown in FIG. 1, the health condition estimation system 1 according to this embodiment includes a user terminal 2 (terminal device) used by a user, and a server 3.

[0021] The user terminal 2 and the server 3 are connected to each other so that they can communicate with each other via a network 4 such as the Internet. The network 4 may be either a wired line or a wireless line, and the type and form of the line do not matter. At least a portion of the user terminal 2 and the server 3 are realized by a computer (information processing device). The user terminal 2 is, for example, a terminal device such as a personal computer, smartphone, or tablet terminal. There are assumed to be a large number of user terminals 2, depending on the number of users who use the health condition estimation system 1.

[0022] After urinating, a user of the health condition estimation system 1 takes an image of their own urine using the user terminal 2 and sends the taken urine image to the server 3 via the network 4. The server 3 receives the urine image from the user terminal 2, estimates the user's health condition from the received urine image, and returns the estimation result (information about the user's health condition) to the user terminal 2.

[0023] (Hardware configuration) Next, a description will be given of the hardware configuration of the health state estimation system 1 according to this embodiment. Fig. 2 is a block diagram showing an example of the hardware configuration of the user terminal 2 and server 3 included in the health state estimation system 1 according to this embodiment.

[0024] In the user terminal 2, the CPU 201 is a processing device that controls the overall operation of the user terminal 2. The ROM 202 is a non-volatile memory that stores control programs executed by the CPU 201 and various data. The RAM 203 is a volatile memory used as a load area and work area for programs executed by the CPU 201. The storage device 204 is a storage means for storing various types of information, and may be built into the user terminal 2 itself or may have a removable storage medium. The input device 205 is a device through which a user of the user terminal 2 inputs information, and may be, for example, a keyboard, mouse, touch panel, microphone, etc. The display 206 is a display device that displays various types of information (user interface, etc.). The image sensor 207 is a photoelectric conversion element that captures an image of a subject. The communication I / F (interface) 208 is an interface for connecting to the network 4. The bus 209 is a bus line that interconnects the above components.

[0025] In the server 3, the CPU 301 is a processing device that controls the overall operation of the server 3. The ROM 302 is a non-volatile memory that stores the control programs executed by the CPU 301 and various data. The RAM 303 is a volatile memory that is used as a load area and work area for the programs executed by the CPU 301. The storage device 304 is a storage means for storing various information, and may be built into the server 3 main body or may have a removable storage medium. The communication I / F (interface) 305 is an interface for connecting to the network 4. The bus 306 is a bus line that connects the above components to each other.

[0026] (Functional configuration) Next, a functional configuration of the health condition estimation system 1 according to this embodiment will be described. Fig. 3 is a diagram showing an example of the functional configuration of the health condition estimation system 1 according to this embodiment.

[0027] First, we will explain the functional configuration of the user terminal 2. As shown in Fig. 3, the user terminal 2 has a communication unit 21, a control unit 22 that controls the overall operation of the user terminal 2, an input unit 23 through which the user inputs various information, an output unit 24 that outputs various information, an imaging unit 25 that captures an image of a subject, and a storage unit 26 that stores various information.

[0028] The communication unit 21 is a communication interface between the user terminal 2 and the network 4. The communication unit 21 transmits and receives information between the user terminal 2 and the server 3 via the network 4. The information that the communication unit 21 sends to the server 3 via the network 4 includes information about the user of the health state estimation system 1 (user attribute information) and image data of the user's urine. The information that the communication unit 21 receives from the server 3 via the network 4 includes information about the user's health state estimated by an estimation unit 32c (described later) from the image data of the user's urine.

[0029] The control unit 22 includes a display control unit 22a, a prohibition unit 22b, and a notification unit 22c.

[0030] Display control unit 22a displays, on output unit 24 (display unit) described below, various types of information related to health state estimation system 1. This various information includes information related to the user's health state estimated by estimation unit 32c described below.

[0031] The prohibition unit 22b prohibits the display control unit 22a from displaying (outputting) on ​​the display unit (output unit 24) an image of the user's urine captured by the imaging unit 25 (described later). As a result, the image of the user's urine is not displayed (output) on the display unit (output unit 24), and the user can check information about the health condition estimated from the image of the urine without seeing the image of their own urine.

[0032] Notification unit 22c notifies the user of health state estimation system 1 of various information via output unit 24. For example, if estimation unit 32c, which will be described later, has not estimated the user's health state for a predetermined period of time, notification unit 22c notifies the user via output unit 24 of a notification urging the user to perform the estimation. The notification may be in the form of a voice message such as "Let's estimate your health state," or the message may be displayed on the display of the user terminal.

[0033] The input unit 23 is an element for allowing the user of the user terminal 2 to input information, and is, for example, a keyboard, a mouse, a touch panel, a microphone, a gesture input device, etc. The information input by the input unit 23 includes user attribute information such as the user's age, sex, medical history, favorite foods, blood glucose level, hematocrit level in blood, urea nitrogen / creatinine ratio, and uric acid level.

[0034] The output unit 24 is an interface that outputs various information (images and sounds) from the user terminal 2 to the user, and is, for example, a video display device (display unit) such as a liquid crystal display, or a speaker. When the output unit 24 is configured as a display unit, a GUI for receiving operations from the user is displayed on this display unit by the display control unit 22a.

[0035] The imaging unit 25 captures an image of a subject (particularly urine) using a camera module including an imaging element of the user terminal 2. The image captured by the imaging unit 25 is output to the control unit 22, where it is subjected to various image processing, and is displayed on the display unit (output unit 24) by the display control unit 22a, or transmitted to the server 3 via the network 4 by the communication unit 21.

[0036] The storage unit 26 is, for example, a data storage such as an internal memory or an external memory (such as an SD memory card). The storage unit 26 stores various data handled by the control unit 22, various information downloaded by the communication unit 21 from the server 3 via the network 4, images (urine images) captured by the imaging unit 25, and the like. Note that the storage unit 26 does not necessarily have to be provided within the user terminal 2, and a part or all of the storage unit 26 may be provided in another device communicatively connected to the user terminal 2 via the network 4. Furthermore, the prohibition unit 22b prohibits the image of the user's urine stored in the storage unit 26 from being displayed (output) on the display unit (output unit 24), so the user does not see the image of their own urine.

[0037] Next, a description will be given of the functional configuration of the server 3. As shown in FIG.

[0038] The communication unit 31 is a communication interface between the server 3 and the network 4. The communication unit 31 transmits and receives information between the server 3 and the user terminal 2 via the network 4. Information transmitted and received between the communication unit 31 and the user terminal 2 via the network 4 includes user attribute information and urine image data transmitted from the user terminal 2 to the server 3, and information related to the user's health condition transmitted from the server 3 to the user terminal 2 (the estimation result of the user's health condition by the estimation unit 32c).

[0039] The control unit 32 controls the overall operation of the server 3. The control unit 32 has an image acquisition unit 32a, an extraction unit 32b, and an estimation unit 32c.

[0040] The image acquisition unit 32a acquires urine image data for use by the estimation unit 32c (described later) to estimate the user's health condition. The image acquisition unit 32a also acquires urine image data to be used as learning data when generating an estimation model used by the estimation unit 32c. The image acquisition unit 32a acquires the urine image data via the network 4 using the communication unit 31, for example.

[0041] The extraction unit 32b extracts a feature quantity characteristic of the urine image from the image acquired by the image acquisition unit 32a. The feature quantity characteristic of the urine image is, for example, urine color information.

[0042] The estimation unit 32c estimates the user's health condition from the image (urine image) acquired by the image acquisition unit 32a using an estimation model (trained model) that has been machine-learned using the user's biometric information (blood glucose level, blood hematocrit level, urea nitrogen / creatinine ratio, uric acid level, etc.) and the features extracted by the extraction unit 32b (e.g., urine color information) as learning data.

[0043] Here, the biological information used in machine learning to generate an estimation model does not necessarily need to be the biological information itself, but may be a degree of health state corresponding to the biological information. For example, as the degree of health state, blood glucose levels such as hypoglycemia, slightly hypoglycemia, healthy, slightly hyperglycemia, and hyperglycemia may be used according to the numerical range of blood glucose levels, or dehydration levels such as slightly dehydrated, slightly dehydrated, healthy, slightly overhydrated, and overhydrated may be used according to the numerical range of at least one of blood hematocrit, urea nitrogen / creatinine ratio, and uric acid level.

[0044] Furthermore, the user's health condition estimated by the estimation unit 32c may be specific numerical values ​​of physiochemical data such as blood glucose level, blood hematocrit level, urea nitrogen / creatinine ratio, and uric acid level, or may be the degree of health condition corresponding to these physiochemical data (blood glucose level, dehydration level, etc.).

[0045] The storage unit 33 is, for example, a data storage such as an internal memory or an external memory (such as an SD memory card). The storage unit 33 stores various data handled by the control unit 32, various information received by the communication unit 31 from the user terminal 2 via the network 4, various databases (DBs), and the like. The databases include training data for generating an estimation model that estimates the user's health condition from a urine image. Specifically, the databases include information such as a set of urine image data and biological information corresponding to the urine image data (blood glucose level, blood hematocrit level, urea nitrogen / creatinine ratio, uric acid level, etc.).

[0046] In addition, the memory unit 33 does not necessarily have to be provided within the server 3, and part or all of the memory unit 33 may be provided within another device that is communicatively connected to the server 3 via the network 4.

[0047] (Example of operation) Next, a description will be given of an example of the operation of the health condition estimation system 1. Fig. 4 is a diagram showing the flow of the operation of using the health condition estimation system 1 to estimate a user's health condition from an image of the user's urine.

[0048] First, the image acquiring unit 32a of the server 3 acquires an image of the user's urine (step S1). For example, the image acquiring unit 32a acquires the image of the user's urine from the user terminal 2 via the communication unit 31 over the network 4.

[0049] Next, the extraction unit 32b of the server 3 extracts a feature amount characteristic of the urine image (for example, urine color information) from the image acquired by the image acquisition unit 32a (step S2).

[0050] Next, the estimation unit 32c of the server 3 estimates the user's health condition from the image acquired by the image acquisition unit 32a using an estimation model that has been machine-learned using the user's biometric information and the features extracted by the extraction unit 32b as learning data (step S3).

[0051] Next, the display control unit 22a of the user terminal 2 displays the information about the user's health condition estimated by the estimation unit 32c on the display unit (output unit 24) (step S4).

[0052] Then, prohibition unit 22b of user terminal 2 prohibits the display (output) of the urine image acquired by image acquisition unit 32a on the display unit (output unit 24) (step S5). Note that the prohibition control by prohibition unit 22b may be performed before step S4.

[0053] As described above, according to this embodiment, the health condition estimation system 1 includes an image acquisition unit 32a that acquires an image of urine, an extraction unit 32b that extracts features characteristic of the urine image from the image acquired by the image acquisition unit 32a, an estimation unit 32c that estimates the user's health condition from the image acquired by the image acquisition unit 32a using an estimation model that has been machine-learned using the user's biometric information and the features extracted by the extraction unit 32b as learning data, a display control unit 22a that displays (outputs) information about the user's health condition estimated by the estimation unit 32c on a display unit (output unit 24), and a prohibition unit 22b that prohibits the display (output) of the urine image acquired by the image acquisition unit 32a on the display unit (output unit 24).Therefore, the health condition of the user can be estimated from the urine image without presenting the urine image to the user.

[0054] Any part or all of the functional units described in this specification may be realized by a program. The program mentioned in this specification may be distributed by being non-temporarily recorded on a computer-readable recording medium, or may be distributed via a communication line (including wireless communication) such as the Internet, or may be distributed in a state where it is installed on any terminal.

[0055] Based on the above description, a person skilled in the art may be able to conceive additional effects and various modifications of the present invention, but the aspects of the present invention are not limited to the individual embodiments described above. Various additions, modifications, and partial deletions are possible within the scope of the conceptual idea and spirit of the present invention, which is derived from the content defined in the claims and their equivalents.

[0056] For example, what is described in this specification as a single device (or component, the same applies hereinafter) (including what is depicted as a single device in the drawings) may be realized by multiple devices. Conversely, what is described in this specification as multiple devices (including what is depicted as multiple devices in the drawings) may be realized by a single device. Alternatively, some or all of the means and functions included in a certain device (e.g., a server / user terminal) may be included in another device (e.g., a user terminal / server).

[0057] Furthermore, not all of the features described in this specification are essential requirements, and in particular, features described in this specification but not included in the claims can be considered optional additional features.

[0058] It should be noted that the applicant is merely aware of the inventions disclosed in the documents listed in the "Prior Art Documents" section of this specification, and the present invention does not necessarily aim to solve the problems of the disclosed inventions. The problem that the present invention aims to solve should be determined by taking into consideration the entire specification. For example, if this specification states that a specific configuration achieves a certain effect, it can also be said that the present invention solves a problem that is the reverse of that effect. However, it is not necessarily intended that such a specific configuration be an essential requirement. [Explanation of symbols]

[0059] 1. Health status estimation system 2. User terminal 21 Communications Department 22 Control Unit 22a Display control unit 22b Prohibited part 22c Notification Department 23 Input section 24 Output section (display section) 25 Imaging unit 26 Memory section 3 Server 31 Communications Department 32 Control section 32a Image acquisition unit 32b Extraction part 32c Estimation part 33 Storage section

Claims

1. A health condition estimation system that estimates a user's health condition from a urine image, comprising: an image acquisition unit for acquiring an image of urine; an extraction unit that extracts a feature amount that is characteristic of a urine image from the image acquired by the image acquisition unit; an estimation unit that estimates a health condition of the user from the image acquired by the image acquisition unit using an estimation model that has been machine-learned using the user's biometric information and the feature amount extracted by the extraction unit as learning data; a display control unit that displays information about the user's health condition estimated by the estimation unit on a display unit; and a prohibition unit that prohibits the display of the urine image acquired by the image acquisition unit on the display unit; A health condition estimation system comprising:

2. The health condition estimation system according to claim 1 , wherein the extraction unit extracts color information of urine as a characteristic feature of the urine image.

3. the biological information is a blood glucose level of the user, The health condition estimation system according to claim 2 , wherein the information relating to the health condition is a degree of diabetes.

4. the biological information includes at least one of a blood hematocrit value, a blood urea nitrogen / creatinine ratio, and a blood uric acid value; The health condition estimation system according to claim 2 , wherein the information relating to the health condition is a degree of dehydration.

5. The health state estimation system according to claim 3 , further comprising a notification unit that notifies a user when the estimation unit has not performed the estimation for a predetermined period of time.

6. A method for estimating a user's health condition from a urine image, comprising: an image acquisition step of acquiring an image of urine; an extraction step of extracting a feature amount characteristic of a urine image; an estimation step of estimating the user's health condition from the urine image using an estimation model that has been machine-learned using the user's biometric information and features extracted from the urine image as learning data; a display step of displaying information about the estimated health condition of the user on a display unit; a prohibition step of prohibiting the display of an image of urine on the display unit; A method comprising:

7. A program for causing a computer to execute a method for estimating a user's health condition from a urine image, the method comprising: A method for estimating a user's health condition from a urine image, comprising: an image acquisition step of acquiring an image of urine; an extraction step of extracting a feature amount characteristic of a urine image; an estimation step of estimating the user's health condition from the urine image using an estimation model that has been machine-learned using the user's biometric information and features extracted from the urine image as learning data; a display step of displaying information about the estimated health condition of the user on a display unit; a prohibition step of prohibiting the display of an image of urine on the display unit; Including, the program.

8. A computer-readable storage medium storing the program according to claim 7.

9. A server used in a health condition estimation system that estimates a user's health condition from a urine image, comprising: a receiving unit that receives an image of urine from a user terminal; an image acquisition unit that acquires an image of the urine received by the receiving unit; an extraction unit that extracts a feature amount that is characteristic of a urine image from the image acquired by the image acquisition unit; an estimation unit that estimates a health condition of the user from the image acquired by the image acquisition unit using an estimation model that has been machine-learned using the user's biometric information and the feature amount extracted by the extraction unit as learning data; a transmission unit that transmits information about the user's health condition estimated by the estimation unit to the user terminal; A server comprising:

10. A user terminal used in a health condition estimation system that estimates a user's health condition from a urine image, comprising: a transmitting unit that transmits the urine image to a server that includes an image acquiring unit that acquires a urine image, an extracting unit that extracts feature amounts characteristic of the urine image from the image acquired by the image acquiring unit, and an estimating unit that estimates the user's health condition from the image acquired by the image acquiring unit using an estimation model that has been machine-learned using the user's biometric information and the feature amounts extracted by the extracting unit as learning data; a receiving unit that receives information about the user's health condition estimated by the estimation unit of the server; a display control unit that displays the information about the user's health condition received by the receiving unit on a display unit; a prohibition unit that prohibits the display of the urine image acquired by the image acquisition unit of the server on the display unit; A user terminal comprising:

Images