WO2022225037A1 - 検査システム、検査装置、検査方法、および検査プログラム - Google Patents

検査システム、検査装置、検査方法、および検査プログラム Download PDF

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Publication number
WO2022225037A1
WO2022225037A1 PCT/JP2022/018515 JP2022018515W WO2022225037A1 WO 2022225037 A1 WO2022225037 A1 WO 2022225037A1 JP 2022018515 W JP2022018515 W JP 2022018515W WO 2022225037 A1 WO2022225037 A1 WO 2022225037A1
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Prior art keywords
eye
inspection
image
camera
display
Prior art date
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Ceased
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PCT/JP2022/018515
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English (en)
French (fr)
Japanese (ja)
Inventor
大治郎 竹
善弘 大下
和夫 白石
真由巳 岸本
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Santen Pharmaceutical Co Ltd
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Santen Pharmaceutical Co Ltd
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Priority to CN202280029134.9A priority Critical patent/CN117177703A/zh
Priority to JP2023515530A priority patent/JPWO2022225037A1/ja
Publication of WO2022225037A1 publication Critical patent/WO2022225037A1/ja
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
    • A61B3/10—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis

Definitions

  • the present disclosure relates to an inspection system, an inspection apparatus, an inspection method, and an inspection program for inspecting the moisture level of eyes.
  • the present disclosure also relates to a testing system, testing device, testing method, and testing program for testing the stability of the tear film.
  • the present disclosure relates to an inspection system, an inspection apparatus, an inspection method, and an inspection program for inspecting for the presence or absence of dry eye.
  • Dry eye is a disease in which tears are not evenly distributed over the surface of the eye (for example, the cornea) due to insufficient tear volume or an imbalance in tear quality. Patients with dry eye may experience eye discomfort, impaired visual function, and damage to the surface of the eye.
  • Patent Document 1 discloses an ophthalmologic apparatus capable of diagnosing dry eye.
  • the ophthalmologic apparatus disclosed in Japanese Patent Application Laid-Open No. 7-136120 captures an interference pattern formed by light reflected on the surface of the eye with a camera. A user can examine the presence or absence of dry eye by observing the interference pattern captured by the camera of the ophthalmologic apparatus.
  • the ophthalmologic apparatus disclosed in Japanese Patent Application Laid-Open No. 7-136120 is an apparatus specialized for users such as ophthalmologists who have enough knowledge to determine the presence or absence of dry eye.
  • ophthalmologists who have enough knowledge to determine the presence or absence of dry eye.
  • the present disclosure has been made to solve the above problems, and aims to provide an inspection system, an inspection apparatus, an inspection method, and an inspection program that enable self-checking of the eyes.
  • the present disclosure relates to an inspection system that inspects the moisture level of eyes.
  • the inspection system includes an inspection unit that inspects the degree of moisture in the eye based on a camera, a photographed image obtained by photographing the eye by the camera, and an estimation model including a neural network, and displays the inspection result by the inspection unit. and a display.
  • the estimation model is trained to test the moisture level of the eye from the captured image, based on learning data including the captured image and test results of the moisture level of the eye.
  • the captured images include a first still image immediately after blinking and a second still image after a predetermined time has passed since blinking.
  • each of the first still image and the second still image is extracted from a moving image obtained by photographing the eye with a camera.
  • each of the first still image and the second still image is an image of a face including at least eyes.
  • the eye image is extracted from the face image included in each of the first still image and the second still image.
  • the inspection unit inspects the moisture level of the eye based on the degree of fluctuation of the eye image extracted from the first still image and the degree of fluctuation of the eye image extracted from the second still image. do.
  • the display further displays an eye image included in the captured image.
  • the display further displays information regarding recommended eye drops.
  • the display also outputs information about the eye clinic.
  • the information about the ophthalmological clinic includes at least one of information prompting medical care by the ophthalmic clinic, information about medical care at the ophthalmic clinic, and information about the recommended ophthalmic clinic.
  • the display displays test results based on the check result of at least one of the subjective symptoms related to the eye and the possibility that the eye has an ophthalmic disease, and the test by the test unit.
  • the inspection system further includes an inspection device and a server device capable of communicating with the inspection device.
  • the inspection device includes a camera and a display.
  • the server device includes an inspection unit.
  • the present disclosure relates to an inspection device that inspects the moisture level of eyes.
  • the inspection device has an inspection unit that inspects the degree of moisture in the eye based on a camera, a photographed image obtained by photographing the eye by the camera, and an estimation model including a neural network, and displays the inspection result by the inspection unit. and a display.
  • the present disclosure relates to an inspection device that inspects the moisture level of eyes.
  • the inspection device comprises a camera, a communication device for communicating with a server device comprising an estimation model including a neural network, and a display.
  • the communication device transmits a captured moving image obtained by capturing an image of the eye with the camera to the server device.
  • the communication device receives the test result of the moisture level of the eye obtained by the server device based on the captured image of the eye extracted from the captured moving image and the estimated model.
  • a display shows the test results.
  • the present disclosure relates to an inspection method for inspecting the degree of moisture in eyes by computer.
  • the inspection method includes steps of inputting a photographed image obtained by photographing the eye with a camera, inspecting the moisture level of the eye based on the photographed image and an estimation model including a neural network, and inspecting and outputting an inspection result obtained by the step.
  • the present disclosure relates to an inspection program for inspecting the degree of moisture in the eyes.
  • the inspection program includes a step of inputting a photographed image obtained by photographing the eye with a camera into a computer, and a step of examining the moisture level of the eye based on the photographed image and an estimation model including a neural network. , and a step of outputting the result of inspection by the step of inspecting.
  • the present disclosure relates to an inspection system that inspects the stability of the tear film.
  • the inspection system includes an inspection unit that inspects the stability of the tear film based on a camera, a photographed image obtained by photographing the eye by the camera, and an estimation model including a neural network, and an inspection result by the inspection unit. and a display for displaying.
  • the present disclosure relates to an inspection system that inspects for the presence or absence of dry eye.
  • the inspection system includes an inspection unit that inspects for the presence or absence of dry eye based on a camera, a photographed image obtained by photographing the eye by the camera, and an estimation model including a neural network, and displays the inspection result by the inspection unit. and a display.
  • the user can perform an eye self-check.
  • FIG. 10 is a diagram showing a user interface screen displayed on the display of the inspection device during self-check;
  • FIG. 10 is a diagram showing a user interface screen displayed on the display of the inspection device during self-check;
  • FIG. 10 is a diagram showing a user interface screen displayed on the display of the inspection device during self-check;
  • FIG. 10 is a diagram showing a user interface screen displayed on the display of the inspection device during self-check;
  • FIG. 10 is a diagram showing a user interface screen displayed on the display of the inspection device during self-check;
  • FIG. 10 is a diagram showing a user interface screen displayed on the display of the inspection device during self-check;
  • FIG. 10 is a diagram showing a user interface screen displayed on the display of the inspection device during self-check;
  • FIG. 10 is a diagram showing a user interface screen displayed on the display of the inspection device during self-check;
  • FIG. 10 is a diagram showing a user interface screen displayed on the display of the inspection device during self-check;
  • FIG. 10 is a diagram showing a user interface screen displayed on the display of the inspection device during self-check;
  • FIG. 10 is a diagram showing a user interface screen displayed on the display of the inspection device during self-check;
  • FIG. 10 is a diagram showing a user interface screen displayed on the display of the inspection device during self-check;
  • FIG. 10 is a diagram showing a user interface screen displayed on the display of the inspection device during self-check;
  • FIG. 10 is a diagram showing a user interface screen displayed on the display of the inspection device during self-check;
  • FIG. 10 is a diagram showing a user interface screen displayed on the display of the inspection device during self-check;
  • FIG. 10 is a diagram showing a user interface screen displayed on the display of the inspection device during self-check;
  • FIG. 10 is a diagram showing a user interface screen displayed on the display of the inspection device during self-check;
  • FIG. 10 is a diagram showing a user interface screen displayed on the display of the inspection device during self-check;
  • FIG. 10 is a flowchart related to eye moisture degree inspection processing executed by a server device;
  • FIG. It is a figure for demonstrating the test
  • the term “eye” is used as a term that includes not only the eyeball but also tissues around the eyeball, such as the eyelid, inner corner, and outer corner of the eye.
  • the term “eye” is primarily used to describe the human eyeball.
  • the term “pupil” is mainly used as a term to describe the iris of the human eye.
  • the “moisture level of the eye” is not limited to the “moisture level of the eyeball”, but also includes the “moisture level of the pupil” or the “moisture level of the iris”.
  • FIG. 1 is a diagram for explaining an eye moisture level test using the test apparatus 1 according to the present embodiment.
  • Eyes with dry eye disease may have poorer tear production than normal eyes, or may produce adequate tear quality but may evaporate more quickly due to poor tear quality. Unstable. Therefore, in the case of dry eye, even if the state of tears is stable immediately after blinking, the state of tears becomes unstable after a lapse of time without blinking.
  • the user 10 starts an application program (hereinafter also referred to as a "self-check application”) for performing an eye self-check using the examination apparatus 1, and conducts an examination according to the self-check application.
  • an application program hereinafter also referred to as a "self-check application”
  • self-check application for performing an eye self-check using the examination apparatus 1, and conducts an examination according to the self-check application.
  • the inspection apparatus 1 includes a camera 16 as shown in FIG.
  • the lens of the camera 16 is arranged on the back side of the inspection device 1 (the side opposite to the side where the display 15 is arranged).
  • the inspection device 1 captures a moving image of the face of the user 10 with the camera 16 .
  • a moving image obtained by shooting with the camera 16 (hereinafter also referred to as a “shot moving image”) includes a plurality of face still images obtained in time series.
  • the inspection device 1 is communicably connected to a server device 2, which will be described later.
  • the inspection device 1 transmits data of the moving image obtained by the camera 16 to the server device 2 .
  • the server device 2 extracts a plurality of still images from the captured moving image acquired from the inspection device 1 .
  • the server device 2 uses image recognition by AI (Artificial Intelligence) to extract eye parts from each of the plurality of still images, and specifies changes in the time series of the extracted eye images. By doing so, the moisture level of the eyes of the user 10 is inspected.
  • the server device 2 transmits the inspection result to the inspection device 1 .
  • the inspection device 1 displays the inspection results acquired from the server device 2 on the display 15 .
  • the user 10 can objectively inspect the moisture level of his or her own eyes by inspecting the state (stability) of tears in his/her own eyes using the inspection device 1 . In this manner, the user 10 can easily perform an eye self-check using the examination apparatus 1 without depending on his or her level of knowledge.
  • test results output by the test device 1 are not limited to the determination results of the moisture level of the eye, and include the determination results of the stability of the tear layer (tear film) that covers the surface of the eye. Furthermore, the test results output by the test apparatus 1 include the presence or absence of dry eye, that is, the determination result of dry eye or not, or the determination result of suspicion of dry eye.
  • the eye (pupil) moisture level means the degree to which the surface of the eye is moistened with tears. The lower the moisture level, the more unstable the tear condition and the unevenness of the tear film.
  • the lens of the camera 16 may be arranged on the side where the display 15 of the inspection device 1 is arranged. In this case, the user 10 should turn the display 15 side of the inspection device 1 toward the front of the user 10 and photograph the moving image of the face.
  • FIG. 2 is a diagram showing the configuration of an inspection system 1000 according to this embodiment.
  • the inspection system 1000 can communicate with a plurality of inspection devices 1 (in the example of FIG. 2, inspection device 1A, inspection device 1B, and inspection device 1C) and each of the plurality of inspection devices 1. and a connected server device 2 .
  • the inspection device 1 is configured according to a general-purpose computer architecture.
  • a portable terminal such as a smart phone that can be carried by the user 10 is exemplified as the inspection device 1 .
  • the inspection device 1 may be a device other than a smart phone, such as a desktop computer, a laptop computer, and a tablet computer.
  • the inspection device 1 includes a processor 11, a communication device 12, a memory 13, an input interface 14, a display 15, and a camera 16.
  • the processor 11 is a computing entity (computer) that executes various processes according to various programs.
  • the processor 11 is composed of, for example, at least one of a CPU (Central Processing Unit), FPGA (Field Programmable Gate Array), GPU (Graphics Processing Unit), and MPU (Multi Processing Unit). Note that the processor 11 may be configured by a processing circuit.
  • the communication device 12 transmits and receives data (information) to and from the server device 2 through wired connection or wireless connection.
  • the communication device 12 transmits and receives data (information) to and from the communication device 22 of the server device 2 by wireless communication via the network 5 .
  • the communication device 12 transmits a captured moving image including the captured image of the eye acquired by the camera 16 to the server device 2 via the network 5 during the self-check.
  • the communication device 12 receives data including the test result of the degree of moisture in the eyes from the server device 2 via the network 5 during the self-check.
  • the memory 13 is composed of volatile memory such as DRAM (Dynamic Random Access Memory) and SRAM (Static Random Access Memory), or non-volatile memory such as ROM (Read Only Memory).
  • the memory 13 stores various programs and data such as a self-check application 131 for performing an eye self-check.
  • the self-check application 131 is an application program for the user 10 to personally check the moisture level of his or her eyes, and includes a program for photographing the eyes with the camera 16 .
  • the input interface 14 is an interface that accepts input from the user 10, such as buttons and a touch panel.
  • the input interface 14 outputs signals to the processor 11 based on user input.
  • the display 15 is a display device such as a liquid crystal display, a plasma display, an organic EL (Electro Luminescence) display, etc., and displays a predetermined screen based on the control of the processor 11 .
  • a display device such as a liquid crystal display, a plasma display, an organic EL (Electro Luminescence) display, etc.
  • the camera 16 shoots a moving image of the shooting target.
  • Moving image data 236 of the captured moving image obtained by the camera 16 is transmitted to the server device 2 via the network 5 .
  • the server device 2 is configured according to a general-purpose computer architecture.
  • the server device 2 is owned by a manufacturer that provides the user 10 with a self-check application 131 for testing the degree of moisture in the eyes.
  • the server device 2 includes a processor 21 , a communication device 22 and a memory 23 .
  • the processor 21 is an example of an "inspection unit".
  • the processor 21 is a computing entity that executes various processes (for example, an inspection process to be described later) according to various programs (for example, an inspection program 231 to be described later).
  • the processor 21 is composed of, for example, at least one of a CPU, FPGA, GPU, and MPU. Note that the processor 21 may be configured by an arithmetic circuit.
  • the communication device 22 transmits and receives data (information) to and from each of the plurality of inspection devices 1 through wired connection or wireless connection.
  • the communication device 22 transmits and receives data (information) to and from the communication device 12 of the inspection device 1 by wireless communication via the network 5 .
  • the communication device 22 receives, from the inspection device 1 via the network 5, the captured moving image including the captured image of the eye acquired by the camera 16 during the self-check.
  • the communication device 22 transmits data including the test results of the degree of moisture in the eyes to the test device 1 via the network 5 during the self-check.
  • the memory 23 is composed of volatile memory such as DRAM and SRAM, or non-volatile memory such as ROM.
  • the memory 23 stores an inspection program 231 for inspecting the moisture level of the eye, an estimation model 232 used for inspecting the moisture level of the eye, eye drop information 233 including information on eye drops, and eye clinic information including information on an eye clinic. 234, user information 235 including information about each user 10 of a plurality of inspection devices 1, moving image data 236 of captured moving images acquired by the camera 16 of the inspection device, and calculating the score used when determining the result of the self-check.
  • Various programs and data such as a calculation table 237 for
  • the inspection program is a program for inspecting the moisturizing degree of the eye by analyzing the photographed moving image of the eye acquired from the inspection apparatus 1 by AI.
  • FIG. 3 is a diagram for explaining learning of the estimation model 232 in the learning phase.
  • the learning phase is a pre-learning phase in which the estimation model 232 is trained before the self-check application 131 is provided to the inspection device 1 of the user 10 .
  • the estimation model 232 is trained by the learning device 31 to test the moisture level of the eye from the photographed image of the eye.
  • the learning device 31 makes the estimation model 232 learn by supervised learning using the learning data 4 .
  • the learning data 4 is prepared in advance for learning the estimation model 232, and includes a captured video of the eye and test results of the moisture level of the eye.
  • the designer of the inspection program 231 shoots a video of the eyes of a plurality of people with different eye moisture levels, and prepares the obtained captured images of the eyes and the inspection results (correct data) of the moisture levels of the eyes.
  • Data 4 for learning is associated with these data.
  • a designer prepares a plurality of such learning data 4 in advance.
  • the estimation model 232 includes a neural network 2321 and parameters 2322 used by the neural network 2321.
  • the neural network 2321 is a convolution neural network (CNN: Convolution Neural Network), a recurrent neural network (RNN: Recurrent Neural Network), or an LSTM network (Long Short Term Memory Network) for image recognition by deep learning.
  • CNN Convolution Neural Network
  • RNN Recurrent Neural Network
  • LSTM Long Short Term Memory Network
  • the estimation model 232 performs deep learning by using the neural network 2321 as described above.
  • Parameters 2322 include weighting factors and the like used in calculations by neural network 2321 . Note that the estimation model 232 is not limited to learning by deep learning using a neural network, and may be learned by other machine learning.
  • the learning device 31 accepts an input of the photographed image of the eye from the learning data 4 .
  • the learning device 31 executes processing for examining the moisture level of the eye represented by the captured eye image based on the input captured image of the eye and the estimation model 232 including the neural network 2321 .
  • the learning device 31 acquires a still image immediately after blinking and a still image after a predetermined time (for example, 5 seconds) has passed since blinking.
  • Each of the two acquired still images is a still image including at least an eye image.
  • the learning device 31 inputs the acquired two still images to the estimation model 232 .
  • the estimation model 232 estimates the moisture level of the eyes of the user 10 by identifying changes in the time series of the two eye images through image recognition.
  • the learning device 31 acquires the estimation result of the eye moisture level obtained by the estimation model 232 .
  • the learning device 31 may estimate the degree of moisture in the eyes based on a plurality of still images obtained from immediately after blinking until a predetermined time (for example, 5 seconds) has elapsed. For example, the learning device 31 acquires all still images obtained for each frame from immediately after blinking until a predetermined time (for example, 5 seconds) elapses, and changes the acquired eye images in time series. By specifying, the user's 10 eye moisture level may be estimated.
  • the learning device 31 learns the estimation model 232 based on the result of estimating the moisturizing degree of the eye and the correct data included in the learning data 4 (the result of pre-measuring the moisturizing degree of the eye represented by the photographed image). . Specifically, the learning device 31 adjusts the parameter 2322 (for example, the weighting factor) so that the estimation result of the eye moisture degree obtained by the estimation model 232 approaches the correct data. to learn
  • FIG. 4 is a diagram showing the configuration of the inspection device 1 in the operation phase.
  • the operation phase is a phase in which the eye moisture level is estimated using the estimation model 232 after the self-check application 131 is provided to the examination apparatus 1 of the user 10 .
  • the server device 2 stores the estimation model 232 learned by the learning device 31 shown in FIG.
  • the server device 2 acquires the estimated model 232 from the learning device 31 and stores the acquired estimated model 232 in the memory 23 .
  • the learning device 31 may be the server device 2
  • the functions of the learning device 31 described above may be functions of the processor 21 of the server device 2 .
  • the processor 21 of the server device 2 includes an input section 211 , a processing section 212 and an output section 213 .
  • the input unit 211 receives an input of a captured moving image including a captured image obtained by capturing the eye of the user 10 with the camera 16 of the inspection device 1 .
  • the processing unit 212 performs processing for inspecting the moisture level of the eye represented by the captured image based on the captured image extracted from the captured moving image input from the input unit 211 and the estimation model 232 including the neural network 2321. to run.
  • the estimation model 232 is not limited to learning by deep learning using a neural network, and may be learned by other machine learning.
  • the processing unit 212 acquires a still image of the eye immediately after blinking and a still image of the eye after a predetermined time (for example, 5 seconds) has passed since the blink.
  • a still image of an eye immediately after blinking is an example of a "first still image.”
  • a still image of the eye after a predetermined period of time (for example, 5 seconds) has elapsed since blinking is an example of a "second still image.”
  • Each of the two acquired still images is a still image including at least an eye image.
  • the processing unit 212 inputs the two acquired still images to the estimation model 232 .
  • the estimation model 232 estimates the moisture level of the eyes of the user 10 by identifying changes in the time series of the two eye images through image recognition.
  • the processing unit 212 acquires the estimation result of the eye moisture level obtained by the estimation model 232 .
  • the processing unit 212 may estimate the moisture level of the eye based on a plurality of still images obtained from immediately after blinking until a predetermined time (for example, 5 seconds) has elapsed. For example, the processing unit 212 acquires all still images obtained for each frame from immediately after blinking until a predetermined time (for example, 5 seconds) has elapsed, and changes the acquired eye images in time series. By specifying, the user's 10 eye moisture level may be estimated.
  • the output unit 213 outputs the inspection results obtained by the processing unit 212 to the inspection device 1 .
  • the display 15 of the inspection device 1 provides the user 10 with the test results of the moisture level of the eyes by displaying a screen showing the obtained test results of the moisture level of the eyes.
  • FIG. 5 to 15 are diagrams showing user interface screens displayed on the display 15 of the inspection apparatus 1 during self-check.
  • the user can operate icons displayed on the display 15 by using the input interface 14 .
  • the user interface screens shown in FIGS. 5 to 15 are examples, and can be changed as appropriate by the designer of the self-check application 131 or the like.
  • the self-examination of the eyes by the user 10 using the self-check application 131 is also referred to as "self-check.”
  • a login screen is displayed on the display 15. As shown in FIG. 5A, when the user 10 activates the self-check application 131 using the inspection device 1, a login screen is displayed on the display 15. As shown in FIG. 5A, when the user 10 activates the self-check application 131 using the inspection device 1, a login screen is displayed on the display 15. As shown in FIG. 5A, when the user 10 activates the self-check application 131 using the inspection device 1, a login screen is displayed on the display 15. As shown in FIG.
  • the login screen includes fields for entering an ID and a password for identifying the user 10.
  • User 10 acquires an ID and a password from server device 2 by registering information (for example, name, gender, age, telephone number, e-mail address, etc.) of user 10 on server device 2 . Note that the user 10 may be able to set a desired ID and password.
  • Information registered in the server device 2 by the user 10 is stored in the memory 23 as user information 235 .
  • the inspection device 1 transmits the ID and password to the server device 2 .
  • the inspection device 1 displays a menu screen on the display 15 as shown in FIG. 5(B).
  • the menu screen includes an icon 151 for starting a self-check, an icon 152 for browsing the history of past self-checks, and an icon 153 for making various settings.
  • the inspection apparatus 1 displays a risk check screen for the user 10 to perform a risk check on the display 15, as shown in FIGS. 5(C) and 5(D).
  • a risk check is a check for examining the possibility that the user 10 has an ophthalmic disease.
  • the risk check includes the sex, age, usage time of a PC and smartphone per day, presence or absence of stiff shoulders, presence or absence of headache, wearing contact lenses, use of eye drops, and past Includes multiple check items such as whether or not dry eye is diagnosed.
  • the inspection device 1 displays a selection screen on the display 15 as shown in FIG. 6(E).
  • the selection screen includes an icon 148 for browsing tutorials and an icon 149 for shooting.
  • the inspection apparatus 1 displays a tutorial screen on the display 15 as shown in FIGS. 6(F1) to 7(F6).
  • the tutorial screen includes images for explaining to the user 10 how to photograph the eyes for self-check.
  • the inspection apparatus 1 displays on the display 15 a message such as "Look outside and rest your eyes.” to display. Furthermore, the inspection apparatus 1 displays a message on the display 15 to inform the user 10 that natural light will be used for moving image shooting, such as "Photographing will be performed using natural light during the daytime.”
  • the inspection apparatus 1 displays a moving image such as "Please stand in front of the window, approach the distance of one arm, face the window, and shoot.”
  • a message is displayed on the display 15 to notify the user 10 of the standing position at the time of photographing.
  • the inspection apparatus 1 communicates with the user 10 during video shooting such as "Please check the shooting distance. Make a good mark with your hand and hold your thumb as straight as possible.”
  • a message for notifying the user 10 of the positional relationship with the camera 16 is displayed on the display 15. - ⁇
  • the inspection apparatus 1 makes a motion between the user 10 and the camera 16 at the time of shooting a moving image, such as "Put your thumb lightly on your cheekbone and put your little finger on the back of the terminal.”
  • a message is displayed on the display 15 to notify the user 10 of the positional relationship.
  • the inspection device 1 displays on the display 15 an image diagram when the thumb is lightly placed correctly on the cheekbone.
  • the inspection apparatus 1 displays on the display 15 an image diagram when the thumb is lightly placed on the cheekbone by mistake.
  • the display 15 displays an example in which the lower eyelid is pulled by the thumb placed on the cheekbone.
  • the inspection apparatus 1 displays a self-check screen on the display 15 as shown in FIGS. 8(G1) to 9(G8).
  • the self-check screen includes an image for allowing the user 10 to shoot a moving image of the eye using the camera 16 and for measuring the moisture level of the eye based on the obtained shot moving image.
  • the inspection apparatus 1 says, "Blink slowly and shoot a video for about 5 seconds immediately after that. Please refrain from blinking during shooting.”
  • a message is displayed on the display 15 prompting the user 10 to photograph the face with the thumb lightly on the cheekbone.
  • the user 10 uses the camera 16 to shoot a moving image of his/her face including his/her eyes for 5 seconds while viewing the scenery outside using natural light during the day.
  • the inspection apparatus 1 displays an image being captured by the camera 16 on the display 15.
  • the inspection apparatus 1 displays a message such as "imaging completed” on the display 15 to notify the user 10 that the imaging is completed, as shown in FIG. 8 (G3).
  • the inspection apparatus 1 displays an image immediately after the start of imaging on the display 15 after the imaging is completed.
  • the inspection apparatus 1 detects the pupil (black eye) based on the still image immediately after the start of photography, and extracts an image of the peripheral portion of the eye (for example, the eye portion) including the pupil.
  • the inspection device 1 indicates the extracted image portion by a framework.
  • the user 10 can adjust so that at least the image portion of the eye is within the frame by moving or enlarging or reducing the frame.
  • the icon 147 the user 10 can cut out the portion of the image within the framework and extract at least the captured image of the eye.
  • the user 10 can retake the image by selecting the icon 146 .
  • the inspection apparatus 1 displays on the display 15 the message "Please confirm whether the image is suitable for inspection.”
  • the inspection apparatus 1 displays on the display 15 the photographed image of the eye when 5 seconds have passed since the photographing.
  • the inspection apparatus 1 provides an example of a photographed image of the eye when the detection and focusing of the pupil (black eye) is appropriate, and an example of a photographed image of the eye when the detection and focusing of the pupil (black eye) are not appropriate. is displayed on the display 15.
  • the inspection apparatus 1 sends a message asking the user 10 whether an image suitable for inspection has been acquired, such as "Is the image suitable for inspection?"
  • the display 15 displays an icon 154 indicating that an image suitable for the examination has been acquired, and an icon 155 indicating that the moving image of the eye should be retaken.
  • the inspection apparatus 1 displays on the display 15 a message such as "AI determination in progress” to inform the user 10 that the determination is in progress. Furthermore, the examination apparatus 1 displays on the display 15 an icon 156 for the user 10 to check the subjective symptoms along with a message such as "click here for the subjective symptom check” prompting the user 10 to check the subjective symptoms related to the eyes. .
  • the examination apparatus 1 displays a plurality of subjective symptom check screens on the display 15 step by step, as shown in FIGS. 10(H1) and (H2).
  • the examination apparatus 1 checks the subjective symptoms of the user 10 related to eyes, such as "my eyes feel dry” and "my eyes tend to get tired", as a subjective symptom check. 12 items of questions are displayed on the display 15. The user 10 can input a subjective symptom check result by checking items with subjective symptoms. In addition, as shown in FIG. 10 (H1), the user 10 can also take over the subjective symptom check results input in the past.
  • the examination apparatus 1 displays a message such as "Thank you for your reply! Image examination results have been obtained.”
  • an icon 157 for viewing the test results is displayed on the display 15 together with a message informing the user 10 that the test results of the self-check have been obtained.
  • the inspection device 1 displays a plurality of inspection result screens showing the inspection results of the self-check step by step on the display 15, as shown in FIGS.
  • FIG. 12 shows test results when the user 10 has a low eye moisture level.
  • the examination apparatus 1 displays an image 1511 showing the comprehensive evaluation of the examination result, an image 1521 showing the check result of the tear quality, and an image 1531 showing the enlarged eye portion. is displayed on the display 15.
  • the image 1511 displays a message indicating that the user 10 has a low level of moisturization in the eye, such as "Your eye's moisturizing level is low”. You may find out the 'true' cause of the decrease in the moisture level of the pupil.”
  • Image 1521 includes a diagram that informs user 10 that the quality of user's tears is unstable.
  • An image 1531 includes a magnified image of the eye of the user 10 used for self-check. Furthermore, in this magnified image, the part of the eye that was subject to image recognition in the self-check is shown. Thereby, the user 10 can confirm the image of his own eye used for the self-check on the display 15 .
  • the inspection device 1 displays on the display 15 an image 1541 showing the inspection results of the self-check based on the subjective symptom check shown in FIG. 12 (J2)
  • the image 1541 includes a message that informs the user 10 of the result of the subjective symptom check, such as "You have 5 or more items and your tears may be unstable.”
  • FIG. 13 shows the test results when the user 10 has a moderate level of moisture in the eyes.
  • the examination apparatus 1 displays an image 1512 showing the comprehensive evaluation of the examination result, an image 1522 showing the tear quality check result, and an image 1532 showing the enlarged eye portion. is displayed on the display 15.
  • the image 1512 displays a message indicating that the user 10's eye moisture level is moderate, such as "your eye moisture level is moderate", and an overall evaluation of "care with drug store eye drops". If you are concerned about your symptoms, please consult an ophthalmologist.”, which prompts the user 10 to perform self-care including the use of eye drops.
  • Image 1522 includes a diagram that informs user 10 that the quality of user's tears is generally normal.
  • An image 1532 includes a magnified image of the eye of the user 10 used for self-check. Furthermore, in this magnified image, the part of the eye that was subject to image recognition in the self-check is shown. Thereby, the user 10 can confirm the image of his own eye used for the self-check on the display 15 .
  • the inspection device 1 displays on the display 15 an image 1542 showing the inspection results of the self-check based on the subjective symptom check shown in FIG.
  • the image 1542 includes a message that informs the user 10 of the result of the subjective symptom check, such as "You have two items and your tears may be unstable.”
  • the inspection apparatus 1 displays on the display 15 an image 1543 showing the inspection results of the self-check based on the risk checks shown in FIGS. 5(C) and 5(D).
  • An image 1543 shows that the risk of dry eye increases when the risk of dry eye falls among the items subject to the risk check, such as "If the following items are met, the risk of dry eye is high, so be careful.” Contains a message that informs the user 10 of the item.
  • the inspection apparatus 1 displays an icon 158 on the display 15 for viewing measures based on the inspection result on the inspection result screen.
  • test apparatus 1 When the user 10 operates the icon 158 on the test result screen (the test result screen of FIG. 12 (J1)) when the user 10 has low eye moisture level, the test apparatus 1 is displayed as shown in FIG. 15 (M1). displays on the display 15 a coping method screen showing coping methods based on the inspection results.
  • the countermeasure screen for the case where the user 10's eye moisture level is low includes, as the information on the ophthalmological clinic, at least one of the following information: Contains any one.
  • the term "medical care” is used as a term including "diagnosis” and "treatment”. That is, the information about the ophthalmology clinic is at least one of information prompting medical care (diagnosis or treatment) by the ophthalmology clinic, information about medical care (diagnosis or treatment) at the ophthalmology clinic, and information about the recommended ophthalmology clinic. may contain
  • the coping method screen for the case where the user 10's eye moisture level is low is displayed by an ophthalmologist's clinic, such as "First, we recommend that you see an ophthalmologist.”
  • a message prompting the user 10 to undergo medical treatment and information on medical treatment at an ophthalmological clinic are provided to the user 10, such as "Dry eye will be diagnosed by examining the quality of tears while confirming symptoms through medical interviews.” message is displayed on the display 15.
  • the examination apparatus 1 displays an icon 159 on the display 15 for notifying the user 10 of the nearest ophthalmological clinic to the user 10 as information on the recommended ophthalmic clinic.
  • the examination apparatus 1 acquires information on the ophthalmic clinic closest to the user 10 from the server device 2 via the network 5 and displays the acquired information on the display 15 .
  • the examination apparatus 1 may search for an ophthalmological clinic closest to the user 10 by connecting to the Internet via the network 5 and display the search results on the display 15 .
  • the inspection device 1 may search for the nearest eye clinic to the user 10 based on the location information held by the inspection device 1 .
  • the inspection device 1 may search for the nearest ophthalmic clinic of the user 10 based on the information input by the user 10 (for example, the address of the user 10).
  • the inspection apparatus 1 provides the information regarding the ophthalmology clinic, information regarding the examination by the ophthalmology clinic, information regarding the examination at the ophthalmology clinic, and information regarding the recommended ophthalmology clinic to the user. 10. This prompts the user 10 to go to the ophthalmologist's office, and allows the user 10 to acquire information about the nearest ophthalmologist's office.
  • the inspection apparatus 1 displays all of the information on the ophthalmological clinic, information on prompting medical treatment by the ophthalmic clinic, information on medical treatment at the ophthalmic clinic, and information on the recommended ophthalmic clinic. 15, or at least one of the information regarding these eye clinics may be displayed on the display 15.
  • FIG. 15 (M1) the inspection apparatus 1 displays all of the information on the ophthalmological clinic, information on prompting medical treatment by the ophthalmic clinic, information on medical treatment at the ophthalmic clinic, and information on the recommended ophthalmic clinic. 15, or at least one of the information regarding these eye clinics may be displayed on the display 15.
  • FIG. 15 (M1) the inspection apparatus 1 displays all of the information on the ophthalmological clinic, information on prompting medical treatment by the ophthalmic clinic, information on medical treatment at the ophthalmic clinic, and information on the recommended ophthalmic clinic. 15, or at least one of the information regarding these eye clinics may be displayed on the display 15.
  • FIG. 15 (M1) the inspection apparatus 1 displays
  • the examination apparatus 1 displays, as information related to ophthalmology clinics, information prompting medical care by an ophthalmology clinic, information related to medical care at an ophthalmology clinic, and recommended at least any one of the information about the ophthalmological clinic may be displayed on the display 15 .
  • the examination apparatus 1 can prompt the user 10 to undergo medical treatment by an ophthalmologist just in case, even if the moisture level of the user's 10 eye is medium or high.
  • the inspection apparatus 1 displays on the display 15 a countermeasure screen indicating a countermeasure based on the inspection result.
  • the coping screen for the user 10 whose eyes are moderately moist includes information on recommended eye drops.
  • the coping method screen for the case where the eye moisture level of the user 10 is moderate includes recommended eye drops such as "over-the-counter drugs recommended for self-care.” to the user 10 and a message for introducing the function of the recommended eye drops to the user 10, such as ⁇ eye drops with a high water-retaining function for those who want to keep their eyes moist''.
  • recommended eye drops such as "over-the-counter drugs recommended for self-care.”
  • the inspection device 1 displays an icon 160 on the display 15 for informing the user 10 of detailed information on the recommended eye drops.
  • the examination device 1 acquires detailed information on recommended eye drops from the server device 2 via the network 5 and displays the acquired information on the display 15 .
  • the examination apparatus 1 may search for detailed information on recommended eye drops by connecting to the Internet via the network 5 and display the search results on the display 15 .
  • the eye drops recommended by the inspection device 1 may be eye drops or eye ointment.
  • the inspection device 1 provides the user 10 with information on recommended eye drops based on the inspection results of the self-check. This allows the user 10 to obtain information on the optimum eye drops for self-care of the eyes.
  • the examination apparatus 1 may display information on recommended eye drops on the display 15 on the countermeasure screen for when the user 10 has low eye moisture level. In this way, when the user 10's eyes have a low degree of moisture, the user 10 is urged to undergo medical treatment at an ophthalmologist's office, and the user 10 is provided with information on eye drops that are optimal for self-care of the eyes.
  • FIG. 16 is a flowchart relating to eye moisture degree inspection processing executed by the server device 2 .
  • the inspection process shown in FIG. 16 is performed by the processor 21 of the server device 2 executing the inspection program 231 .
  • the server device 2 executes the inspection process shown in FIG. 16 on condition that a predetermined start condition is satisfied.
  • a start condition as shown in FIG. 5B, the user 10 has operated an icon 151 for starting the self-check.
  • "S" is used as an abbreviation for "STEP".
  • the server device 2 acquires the risk check result (S1). Specifically, the server device 2 acquires the risk check result of the user 10 input from the inspection device 1 via the network 5 .
  • the server device 2 determines whether or not a captured moving image including a captured image of the eye of the user 10 obtained by the camera 16 of the inspection device 1 has been input (S2).
  • the shot video of the eye includes a still image of the eye immediately after blinking and a still image of the eye after a predetermined time (for example, 5 seconds) has passed since blinking.
  • the server apparatus 2 repeats the process of S2 when the captured moving image is not input (NO in S2).
  • the server device 2 selects from the captured moving image a still image of the eye immediately after blinking and a still image of the eye after a predetermined time (for example, 5 seconds) has elapsed since the blink. A still image is extracted (S3).
  • the server device 2 extracts the fluctuation degree of each of the two eye images by image recognition (S4).
  • the server device 2 examines the moisture level of the eye based on the time-series change in the degree of fluctuation in the two eye images (S5).
  • FIG. 17 is a diagram for explaining an eye moisture level test.
  • the inspection apparatus 1 uses the camera 16 to start photographing at timing t1 immediately after blinking, and then finishes photographing at timing t2 five seconds later.
  • the inspection device 1 transmits the captured video data to the server device 2 .
  • the server device 2 acquires a still image at timing t1 immediately after blinking (an example of a "first still image”) and a predetermined time after blinking.
  • a still image (an example of a "second still image”) at timing t2 after (5 seconds in the example of FIG. 17) has been extracted (processing corresponding to S3 in FIG. 16).
  • FIG. 8 (G2) each of these two still images includes an image of user 10's face.
  • the server device 2 extracts an eye image 301 from the still image at timing t1 and extracts an eye image 302 from the still image at timing t2 by image recognition.
  • the server device 2 extracts the degree of fluctuation of the eye image 301 at timing t1, and extracts the degree of fluctuation of the eye image 302 at timing t2 (process corresponding to S4 in FIG. 16).
  • the state of tears becomes unstable after a period of time without blinking. Therefore, in the case of dry eye, the image of the eye after a lapse of time without blinking has a greater degree of fluctuation than the image of the eye immediately after blinking. That is, the greater the degree of fluctuation of the eye image, the more unstable the tear state, and such an eye image indicates that the eye has a low moisturizing degree and/or suffers from dry eye. or that you may be suffering from dry eye.
  • the outside scenery (the background of the city in this example) projected on the surface of the eye (for example, the cornea) is generally clearly represented.
  • the outside scenery background of the city reflected on the surface of the eye (cornea) is represented in a blurred manner.
  • the “fluctuation degree of eye image” means the degree of blurring, blurring, or fluctuation of an object projected on the surface of the eye (for example, the cornea) shown in the image.
  • the server device 2 compares the eye image 301 at the timing t1 and the eye image 302 at the timing t2, and observes the change in the degree of fluctuation as described above.
  • the moisture level of the eye is inspected (process corresponding to S5 in FIG. 16).
  • timing t2 is not limited to the timing five seconds after blinking, and may be any timing as long as it is the timing at which the eye moisture degree can be tested based on the change in the degree of fluctuation of the eye image. good too.
  • the eye image 302 to be compared with the eye image 301 immediately after blinking is not limited to one, and may be multiple.
  • the server device 2 extracts the eye image 301 at timing t1 immediately after blinking, then extracts the eye image 302 at timing t2 after the first predetermined time (for example, 5 seconds) has elapsed, and further extracts the eye image 302. , Extracting eye images at timing t3 after a second predetermined time (for example, 7 seconds) has elapsed, and observing changes in the degree of fluctuation in these multiple eye images to inspect the moisture level of the eyes. You may In this way, the server device 2 can inspect the moisture level of the eye based on a plurality of eye images extracted at each of a plurality of timings that have elapsed immediately after blinking. can be inspected.
  • the inspection apparatus 1 is not limited to the process of extracting a plurality of eye images from a moving image of a face (eyes).
  • the inspection apparatus 1 acquires the first still image (photograph) by photographing the face of the user 10 at timing t1 immediately after blinking, and then at a timing after a predetermined time (for example, 5 seconds) has passed.
  • a second still image (picture) may be acquired by photographing the face of the user 10 at t2.
  • the server device 2 may extract an eye image from each of the plurality of still images acquired in this manner.
  • the server device 2 acquires the subjective symptom check result (S6). Specifically, the server device 2 acquires the subjective symptom check result of the user 10 input from the examination device 1 via the network 5 .
  • the server device 2 calculates the score used when determining the final self-check result (S7).
  • a predetermined score is assigned to the result of the eye moisture degree check using an image, and a predetermined score is assigned to each item of the subjective symptom check. Predetermined points are assigned to each risk check item.
  • the server device 2 refers to the calculation table, and calculates points in a point-adding system based on the results of the eye moisturizing degree check using images, the subjective symptom check results, and the risk check results. For example, when the user 10 checks the item "I feel dry eyes" in the subjective symptom check, the server device 2 adds a predetermined score, and in the risk check, "use of eye drops".
  • the server device 2 acquires the total score based on the results of the eye moistness level check using images, the results of the subjective symptom check, and the results of the risk check.
  • the server device 2 extracts a judgment message as a self-check result based on the score obtained by referring to the calculation table and a predetermined reference value.
  • the server device 2 displays the message "Your eye's moisture level is low” and the message “We recommend that you see an ophthalmologist as soon as possible,” as shown in FIG.
  • the “true” cause of the decrease in the moisture level of the pupil may be known.”, and the result is output to the inspection device 1.
  • the server device 2 generates a final result in consideration of the test result of the eye moisture degree using the image, the risk check result, and the subjective symptom check result.
  • the result of the self-check can be output with higher accuracy than generating the final result based only on the results of the inspection.
  • the server device 2 determines whether or not the score calculated in S7 is equal to or greater than the reference value (S8). If the score is equal to or higher than the reference value, that is, if the degree of moisture in the eye is low (YES in S8), the server device 2 acquires information about the ophthalmology clinic as shown in FIG. Include (S9).
  • the server device 2 determines whether the recommended eye drops shown in FIG. 15 (M2) Information is acquired and included in the inspection result (S10).
  • the server device 2 may acquire information on recommended eye drops as shown in FIG. 15 (M2) and include it in the test results even when the degree of moisture in the eyes is low.
  • the server device 2 may acquire information about the ophthalmological clinic as shown in FIG. 15 (M1) and include it in the examination results even if the moisture level of the eyes is medium or high.
  • the server device 2 is not limited to generating the final result based on the subjective symptom check result, the risk check result, and the test result of the moisture level of the eyes using the image.
  • the server device 2 may generate a final result based on at least one of the subjective symptom check result and the risk check result, and the test result of the eye moisture level using the image.
  • the server device 2 outputs the generated inspection result to the inspection device 1 (S11). As a result, inspection results as shown in FIGS. 13 to 15 are displayed on the display 15 of the inspection apparatus 1. FIG. After that, the server device 2 terminates this process.
  • the server device 2 executes the examination process according to the examination program 231, so that the user 10 can easily perform an eye self-check using the examination device 1.
  • the server apparatus 2 executes the inspection process to inspect the moisture level of the user's 10 eyes. You may inspect the moisture degree of.
  • FIG. 18 is a diagram showing the configuration of an inspection system 1000a according to another embodiment.
  • inspection apparatus 1a stores inspection program 231, estimation model 232, eye drop information 233, ophthalmology clinic information 234, and calculation table 237 included in server apparatus 2 shown in FIG. may be stored.
  • the processor 11 of the inspection device 1a inspects the moisture level of the eye based on the photographed image included in the photographed moving image obtained by photographing the eye with the camera 16 and the estimation model 232 including the neural network 2321.
  • the test results may be displayed on the display 15 as the final test results together with the eye drops information 233 or the eye clinic information 234 . That is, the inspection device 1a may execute the processing corresponding to the inspection processing of the server device 2 shown in FIG.
  • the inspection device 1 can inspect the moisture level of the eye based on the change in the degree of fluctuation of the image of the eye.
  • a large degree of fluctuation of the image of the eye means that the stability of the tear film is lowered (dry eye). Therefore, the inspection device 1 can also inspect the stability of the tear film (dry eye) based on the change in the degree of fluctuation of the image of the eye.
  • the stability of the tear film can also be measured by measuring the time from opening the eye until the tear layer on the surface of the eye breaks down (also called Break Up Time or BUT). evaluated.
  • the inspection device 1 can also measure BUT and evaluate the stability of the tear film based on changes in the degree of fluctuation of the image of the eye.
  • the test device 1 can also measure the non-invasive tear break-up time (NIBUT) to assess tear film stability.
  • NEBUT non-invasive tear break-up time
  • test system 1000 the test device 1, the test method, and the test program for testing the degree of moisture in the eye are described as the test system, the test device, the test method, and the test system for testing the stability of the tear film. It is applicable to each of the inspection programs.
  • descriptions of the inspection system 1000, the inspection apparatus 1, the inspection method, and the inspection program for inspecting the degree of moisture in the eye are the respective descriptions of the inspection system, the inspection apparatus, the inspection method, and the inspection program for inspecting the presence or absence of dry eye. applicable to
  • the present disclosure relates to a test system 1000 for testing eye moisture (tear film stability, presence or absence of dry eye).
  • the inspection system 1000 performs an eye examination based on the camera 16, the captured image obtained by the camera 16 capturing an image of the eye, and an estimation model 232 including a neural network 2321.
  • a processor 21 (examination unit) that examines the moisture level (stability of the tear film, presence or absence of dry eye), and a display 15 that displays the examination results by the processor 21 are provided.
  • the user 10 objectively inspects the moisture level of his or her eyes (stability of the tear film, presence or absence of dry eye) by photographing his/her own eyes using the camera 16 of the inspection device 1. be able to.
  • the user 10 can easily perform an eye self-check using the examination apparatus 1 .
  • the term “captured image” refers to either a “still image” (so-called photo) captured by camera shooting or a “still image” included in a “captured moving image” captured by camera shooting. good too.
  • the test unit is configured to test the degree of moisturization of the eye (stability of the tear film, presence or absence of dry eye) based on at least a "still image” (image contained in a photograph or video).
  • the estimation model 232 is based on the learning data 4 including the photographed images and test results of the degree of moisture in the eye (stability of the tear film, presence or absence of dry eye). It is trained to test the degree of moisture in the eye (tear film stability, presence or absence of dry eye) from images.
  • the inspection system 1000 can use the learned estimation model 232 to inspect the moisture level of the eye of the user 10 (stability of the tear film, presence or absence of dry eye) from the captured image.
  • the captured images are a first still image at timing t1 immediately after blinking, and a second still image at timing t2 after a predetermined time (for example, 5 seconds) has passed since blinking. and still images of
  • the inspection system 1000 compares the still image immediately after blinking with the still image after a predetermined time (for example, 5 seconds) has passed since blinking to determine the degree of moisture in the user's 10 eyes (tears). liquid layer stability, presence or absence of dry eye) can be tested.
  • a predetermined time for example, 5 seconds
  • each of the first still image and the second still image is extracted from a moving image obtained by camera 16 photographing the eye.
  • the user 10 can capture a moving image of his/her own eye using the camera 16, and the inspection system 1000 extracts two still images from the captured moving image and compares the two images.
  • the user's 10 eye moisture level can be tested. Therefore, the user 10 does not need to shoot a still image immediately after blinking and a still image after a predetermined time (for example, 5 seconds) has passed since blinking with the camera 16. (tear film stability, presence or absence of dry eye) can be tested.
  • each of the first still image and the second still image is an image of a face including at least eyes.
  • the eye image is extracted from the face image included in each of the first still image and the second still image.
  • the inspection system 1000 extracts an image of the eye portion from each of the two still images and compares the two to determine the degree of moisture in the eye of the user 10 (stability of the tear film, dry eye). presence or absence) can be inspected. Therefore, the user 10 does not need to photograph only the eye portion with the camera 16, and can inspect the moisture level of the eye (stability of the tear film, presence or absence of dry eye) as easily as possible.
  • the processor 21 calculates the degree of fluctuation of the eye image extracted from the first still image and the degree of fluctuation of the eye image extracted from the second still image. Based on the degree of fluctuation, the degree of moisture in the eye (stability of the tear film, presence or absence of dry eye) is examined.
  • the inspection system 1000 compares the degree of fluctuation of the eye image extracted from each of the two still images, thereby determining the moisture level of the eye of the user 10 (stability of the tear film, presence or absence of dry eye). ) can be inspected. Therefore, the inspection system 1000 can more accurately inspect the moisture level of the eye (stability of the tear film, presence or absence of dry eye).
  • the display 15 further displays an eye image included in the captured image.
  • the user 10 can confirm the image of his own eye used for the self-check on the display 15.
  • the eye image displayed on the display 15 may be the second still image at the timing t2 shown in FIG.
  • the display 15 further displays information on recommended eye drops, as shown in FIG. 15 (M2).
  • the user 10 can obtain information on the optimum eye drops for self-care of the eyes.
  • the display 15 further outputs information regarding ophthalmic clinics.
  • the user 10 can be prompted to go to the ophthalmologist's office and further obtain information about the ophthalmologist's office.
  • the information about the ophthalmic clinic includes at least one of information prompting medical treatment by the ophthalmic clinic, information about medical treatment at the ophthalmic clinic, and information about the recommended ophthalmic clinic. including one.
  • the user 10 is prompted to go to an ophthalmologist's office, and can obtain information on recommended ophthalmologist's offices.
  • the display 15 displays at least one check result of subjective eye symptoms and the possibility that the eye has an ophthalmologic disease, and the examination by the processor 11. Display test results based on
  • the user 10 can acquire the result of examining the moisture level of the eye (stability of the tear film, presence or absence of dry eye) in consideration of at least one of the subjective symptom check result and the risk check result. can do.
  • the inspection system 1000 further includes an inspection device 1 and a server device 2 capable of communicating with the inspection device 1, as shown in FIG.
  • Inspection device 1 includes camera 16 and display 15 .
  • the server device 2 includes a processor 21 (inspection unit).
  • the user 10 can use the inspection device 1 and the server device 2 included in the inspection system 1000 to easily perform an eye self-check.
  • the present disclosure relates to an inspection device 1a that inspects the degree of moisture in the eye (tear film stability, presence or absence of dry eye).
  • the inspection apparatus 1a uses the camera 16, the photographed image obtained by photographing the eye with the camera 16, and the estimation model 232 including the neural network 2321, based on the degree of moistness of the eye (
  • a processor 11 examination unit for examining the stability of the tear film and the presence or absence of dry eye) and a display 15 for displaying the examination results by the processor 11 are provided.
  • the user 10 objectively inspects the moisture level of his/her eyes (stability of the tear film, presence or absence of dry eye) by photographing his/her own eyes using the camera 16 of the inspection device 1a. be able to.
  • the user 10 can easily perform an eye self-check using the inspection device 1a.
  • the present disclosure relates to an inspection device 1 that inspects the degree of moisture in the eye (tear film stability, presence or absence of dry eye).
  • the inspection device 1 comprises a camera 16 , a communication device 12 for communicating with a server device 2 comprising an estimation model 232 including a neural network 2321 , and a display 15 .
  • the communication device 12 transmits to the server device 2 the captured moving image obtained by the camera 16 capturing an image of the eye.
  • the communication device 12 receives the test result of the moisture level of the eye (stability of the tear film, presence or absence of dry eye) obtained by the server device 2 based on the captured image of the eye extracted from the captured moving image and the estimation model 232. do.
  • the display 15 displays inspection results.
  • the user 10 objectively inspects the moisture level of his or her eyes (stability of the tear film, presence or absence of dry eye) by photographing his/her own eyes using the camera 16 of the inspection device 1. be able to.
  • the user 10 can easily perform an eye self-check using the examination apparatus 1 .
  • the present disclosure relates to an inspection method for inspecting the moisture level of the eye (tear film stability, presence or absence of dry eye) by the processor 21 (computer).
  • the inspection method includes a step of inputting a photographed image obtained by photographing the eye with the camera 16 (S2 in FIG. 16), and based on the photographed image and an estimation model 232 including a neural network 2321, the moisture content of the eye. 16), and a step of outputting the results of the examination (S11 in FIG. 16).
  • the user 10 objectively inspects the moisture level of his or her eyes (stability of the tear film, presence or absence of dry eye) by photographing his/her own eyes using the camera 16 of the inspection device 1. be able to.
  • the user 10 can easily perform an eye self-check using the examination apparatus 1 .
  • the present disclosure relates to an inspection program 231 that inspects the degree of moisture in the eye (tear film stability, presence or absence of dry eye).
  • the inspection program 231 includes a step (S2 in FIG. 16) of inputting the photographed image obtained by photographing the eye with the camera 16 to the processor 21 (computer), and an estimation model including the photographed image and the neural network 2321.
  • the user 10 objectively inspects the moisture level of his or her eyes (stability of the tear film, presence or absence of dry eye) by photographing his/her own eyes using the camera 16 of the inspection device 1. be able to.
  • the user 10 can easily perform an eye self-check using the examination apparatus 1 .

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