Program of determining notification destination, method of determining notification destination, and device of determining notification destination

Abstract

To determine an appropriate notification destination as a notification destination which is notified of information about a patient.SOLUTION: There is provided a program of determining a notification destination, the program causing a computer to execute a process comprising: processing of classifying at least one of a feature amount of expression and face color of a patient into one of a plurality of stages, based on an acquired face image by obtaining the face image of the patient; and processing of determining a notification destination of information ( FIG. 10) about the patient, based on a result of the foregoing classification.SELECTED DRAWING: Figure 10

Description

[Technical field]

[0001] The present invention relates to a notification destination determination program, a notification destination determination method, and a notification destination determination device. [Background technology]

[0002] Traditionally, caregivers engaged in home care would visit the patient's home to directly observe the patient and interview the patient to grasp the patient's condition, and record it in a daily report, etc. Recently, patient information has also been shared between people related to the patient (caregivers, medical professionals, etc.) using SNS (Social Networking Service), etc. In this case, caregivers can take notes on the patient's information on the SNS, and people related to the patient can check the contents of the notes (patient information). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2002-300316 A [Patent Document 2] JP 2012-155631 A Summary of the Invention [Problem to be solved by the invention]

[0004] Caregivers are busy because they are responsible for many patients. In addition, caregivers have less medical knowledge than medical professionals. For this reason, caregivers may miss small changes or signs in patients and may not be able to accurately grasp their patients' conditions.

[0005] Therefore, if it were possible to notify the appropriate parties when there is a change in a patient that the caregiver does not notice, it would be possible to respond to the patient more quickly and the burden on the caregiver would be reduced.

[0006] In one aspect, the present invention aims to provide a notification destination determination program, a notification destination determination method, and a notification destination determination device that are capable of determining an appropriate notification destination to notify of information about a patient. [Means for solving the problem]

[0007] In one aspect, the notification destination determination program is a program that causes a computer to execute a process of acquiring a facial image of a patient, classifying at least one of the patient's facial expression features and facial color into one of a plurality of stages based on the acquired facial image, and determining a notification destination of information about the patient based on the result of the classification. Effect of the Invention

[0008] It is possible to determine an appropriate notification destination for notifying information about a patient. [Brief description of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram illustrating an outline of a configuration of an information notification system according to an embodiment. [Diagram 2] FIG. 2(a) is a diagram showing an example of the hardware configuration of a server, and FIG. 2(b) is a diagram showing an example of the hardware configuration of a user terminal. [Diagram 3] FIG. 3 is a functional block diagram of the server. [Figure 4] FIG. 4 is a diagram showing an example of the information input screen. [Diagram 5] 5(a) and 5(b) are diagrams showing examples of input on the information input screen. [Figure 6] FIG. 6 is a diagram showing the data structure of the team information storage unit. [Figure 7] FIG. 7 is a flowchart showing an example of processing by the server. [Figure 8] FIG. 8 is a diagram showing a screen for photographing. [Figure 9]FIG. 9(a) is a diagram showing an example of a face illustration, and FIG. 9(b) is a diagram showing dimensions a, b, and c used in evaluating facial expressions. [Figure 10] FIG. 10 is a diagram showing an example of the notification screen. [Figure 11] FIG. 11 is a diagram showing an example of the message screen. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] An embodiment of the information notification system will be described in detail below with reference to Figs. 1 to 11. The information notification system 100 of this embodiment is a system for notifying an appropriate notification destination of information regarding a patient in a situation where a communication tool is used between various professions (medical workers, care workers, etc.) related to home medical care and home care. The communication tool is, for example, a social networking service (SNS). By using an SNS within a team made up of medical workers, care workers, etc., it is possible to share information (daily care reports, contact information, etc.) of patients under the team's care within the team, and to notify (mention) information to a specific person within the team.

[0011] The information notification system 100 has a system configuration as shown in Fig. 1. Specifically, the information notification system 100 includes a server 10 as a notification destination determination device, and a plurality of user terminals 70. The server 10 and the plurality of user terminals 70 are connected to a network 80 such as the Internet.

[0012] The server 10 is an information processing device that operates the SNS and executes a process of notifying an appropriate notification destination of information about a patient. FIG. 2(a) shows a hardware configuration of the server 10. As shown in FIG. 2(a), the server 10 includes a CPU (Central Processing Unit) 90, a ROM (Read Only Memory) 92, a RAM (Random Access Memory) 94, a storage (SSD (Solid State Drive) or HDD (Hard Disk Drive)) 96, a network interface 97, and a portable storage medium drive 99. These components of the server 10 are connected to a bus 98. In the server 10, the CPU 90 executes a program (including a notification destination determination program) stored in the ROM 92 or HDD 96, or a program read by the portable storage medium drive 99 from the portable storage medium 91, thereby realizing the functions of each unit shown in FIG. 3. The functions of each unit shown in FIG. 3 may be realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The individual components in FIG. 3 will be described in detail later.

[0013] The user terminal 70 is a terminal owned by each person belonging to the team, and is, for example, a PC (Personal Computer), a smartphone, a tablet terminal, etc. The user terminal 70 is capable of viewing and operating the screen of the SNS. In addition, the user terminal 70 is configured to display information notified from the server 10.

[0014] Fig. 2(b) shows the hardware configuration of the user terminal 70. As shown in Fig. 2(b), the user terminal 70 includes a CPU 190, a ROM 192, a RAM 194, a storage 196, a network interface 197, a display unit 193, an input unit 195, and a camera 189. These components of the user terminal 70 are connected to a bus 198. The display unit 193 includes a liquid crystal display or the like, and the input unit 195 includes a keyboard, a mouse, a touch panel, and the like.

[0015] (About Server 10 functions) FIG. 3 shows a functional block diagram of the server 10.

[0016] 3, in the server 10, the CPU 90 executes a program to function as an SNS processing unit 20, an image acquisition unit 30, an illustration generation unit 32, a facial expression evaluation unit 34, a facial color evaluation unit 36, a notification destination determination unit 38, a notification information collection unit 40, and a notification unit 42. Note that Fig. 3 also illustrates an SNS information storage unit 120, an illustration storage unit 130 (storage unit), and a team information storage unit 132 stored in a storage 196 or the like.

[0017] The SNS processing unit 20 executes processing related to the exchange of information within a team via SNS. For example, when visiting caregiver A wishes to share information about patient X within the team, the SNS processing unit 20 displays an information input screen as shown in Fig. 4 on the display unit 193 of the user terminal 70 in response to the operation of the user terminal 70 by visiting caregiver A. Note that the information input screen in Fig. 4 is provided with an input field 102 for inputting patient information, as well as a send button, a delete button, and the like.

[0018] When visiting caregiver A inputs information about patient X in the input field 102 of this information input screen as shown in FIG. 5(a) and presses the send button, the SNS processing unit 20 makes the input information viewable on the user terminal 70 of each person in the team. The SNS processing unit 20 also manages the input information in the SNS information storage unit 120.

[0019] Here, when visiting caregiver A enters information about patient X in the input field 102 as shown in FIG. 5(b), he / she may enter "@" at the beginning of the information followed by the name of a person in the team (for example, "@care manager E"). When "@care manager E" is entered in this way, it means that the entered information has been mentioned for care manager E. In other words, it means that the entered information is addressed to "care manager E." When information is mentioned, the SNS processing unit 20 also stores the mention information in the SNS information storage unit 120.

[0020] Returning to FIG. 3, the image acquisition unit 30 acquires a facial image (facial photograph) of the patient captured using the camera 189 of the user terminal 70. It is assumed that the visiting caregiver or the like captures a facial image of the patient using the user terminal 70 every time they visit the patient's home. The facial image is linked to various information such as the date and time of capture, the name and identification information of the patient being photographed, and the name and identification information of the photographer. The image acquisition unit 30 transmits the acquired facial image (and the information linked to the facial image) to the illustration generation unit 32.

[0021] The illustration generating unit 32 generates a facial illustration of the patient based on the facial image received from the image acquiring unit 30. The illustration generating unit 32 stores the facial illustration of the patient in the illustration storage unit 130 together with information linked to the facial image.

[0022] The facial expression evaluation unit 34 evaluates the facial expression of the patient based on the face illustration generated by the illustration generation unit 32 and stored in the illustration storage unit 130. The method of evaluating the facial expression of the patient will be described in detail later.

[0023] The complexion evaluation section 36 evaluates the complexion of the patient based on the face illustration generated by the illustration generation section 32 and stored in the illustration storage section 130. The method of evaluating the complexion of the patient will be described in detail later.

[0024] In this embodiment, the facial expression evaluation unit 34 and the complexion evaluation unit 36 ​​are included to realize a function as a classification unit that classifies at least one of the facial expression and complexion of the patient into one of a plurality of stages.

[0025] The notification destination determination unit 38 determines a notification destination to which the patient information is to be notified based on the evaluation results of the facial expression evaluation unit 34 and the complexion evaluation unit 36. When determining the notification destination, the notification destination determination unit 38 refers to the team information storage unit 132 and the SNS information storage unit 120. The team information storage unit 132 manages information on teams organized for each patient, that is, information on people (medical workers and care workers) related to each patient, and manages data such as that shown in FIG. 6. For example, the team information storage unit 132 stores information that the team of patient X includes medical workers (doctor B, nurse C, pharmacist D) and care workers (care manager E, visiting care workers A and F) as shown in FIG. 6.

[0026] Returning to FIG. 3, when it is necessary to notify a person in a team of patient information, the notification information collecting unit 40 collects the content to be notified from the SNS information storing unit 120 and the illustration storing unit 130.

[0027] The notification unit 42 notifies the information collected by the notification information collection unit 40 to the notification destination determined by the notification destination determination unit 38.

[0028] (For details on Server 10 processing) Next, the details of the processing of the server 10 will be described in detail with reference to the flowchart of Fig. 7 and other drawings as appropriate. Note that the SNS processing unit 20 of the server 10 is assumed to be executing processing related to the SNS in parallel with the processing of Fig. 7.

[0029] When the process of FIG. 7 is started, first, in step S10, the image acquisition unit 30 waits until a face image is captured by any of the user terminals 70. When each person (photographer) in the team captures a face image of the patient, the person displays a screen for capturing images as shown in FIG. 8 on the user terminal 70. Then, the photographer adjusts the capturing direction, the capturing magnification, the capturing distance, and the like so that the patient's face is generally positioned within the dashed ellipse on the screen, and then presses the capture button. This allows the patient's face image to be captured. When the face image is captured, the user terminal 70 transmits the captured face image to the server 10. When the user terminal 70 transmits the captured face image to the server 10, the determination in step S10 is affirmative, and the image acquisition unit 30 proceeds to step S12.

[0030] In step S12, the image acquisition unit 30 acquires the face image transmitted from the user terminal 70. The face image is assumed to be linked to the patient's name, information about the photographer, and information about the date and time of shooting. The image acquisition unit 30 transmits the acquired face image and the information linked to the face image to the illustration generation unit 32.

[0031] Next, in step S14, the illustration generating unit 32 generates a face illustration from the face image received from the image acquiring unit 30, and stores the face illustration in the illustration storage unit 130. Note that various known methods can be used as a method for generating a face illustration from a face image. The illustration generating unit 32 stores the generated face illustration and information linked to the face image in the illustration storage unit 130. In this case, the illustration storage unit 130 stores the face illustration instead of the face image, so that the patient's personal information can be protected. Note that the generation process of the face illustration may be performed by an external server. That is, the face image acquired by the image acquiring unit 30 may be transmitted to an external server, and the face illustration generated by the external server may be acquired by the server 10.

[0032] Next, in step S16, the facial expression evaluation unit 34 evaluates the facial expression of the patient based on the facial illustration stored in the illustration storage unit 130. For example, assume that the facial illustration stored in the illustration storage unit 130 is an illustration as shown in FIG. 9(a). In this case, the facial expression evaluation unit 34 uses machine learning or the like to identify dimensions a, b, and c as shown in FIG. 9(b). The dimension a is a dimension indicating the length of the face, and is the distance from the top of the forehead to the bottom of the chin. The dimension b is the distance from the bottom of the lower lip to the bottom of the chin. In addition, the dimension c is the distance from the corner of the mouth to the bottom of the chin. Note that the dimensions a, b, and c may be dimensions of parts different from the above. For example, the dimension a may be the distance from the top of the head to the bottom of the chin.

[0033] Using these dimensions a, b, and c, the facial expression evaluation unit 34 calculates an index P indicating the degree to which the corners of the mouth are turned up, as a feature amount of the facial expression, from the following equation (1). P = {(bc) / a} × 100(%) … (1)

[0034] For example, if the corners of the mouth are turned up, (bc) will be a negative value, and the more the corners of the mouth are turned up, the smaller the value. On the other hand, if the corners of the mouth are turned down, (bc) will be a positive value, and the more the corners of the mouth are turned down, the larger the value. In other words, the smaller the value of index P, the brighter the patient's facial expression (the patient is more energetic), and the larger the value of index P, the darker the patient's facial expression (the patient is less energetic).

[0035] Based on the index P, the facial expression evaluation unit 34 evaluates the facial expression of the patient as follows (classifies the facial expression into one of a plurality of evaluations). Rating 5: 3% or less index P Rating 4: 1%≦Index P<3% Evaluation 3: -1%≦Index P<1% Evaluation 2: -3%≦Index P<-1% Evaluation 1: Index P<-3%

[0036] The patient with the brightest facial expression is given an "Evaluation 1," and the patient with the darkest facial expression is given an "Evaluation 5."

[0037] For the evaluation criteria of the above evaluations 1 to 5, evaluation criteria prepared in advance are used for a predetermined period from the start of photographing the patient, and after the predetermined period has passed, the evaluation criteria may be adjusted using accumulated data of photographed face images and face illustrations of the patient. For example, the evaluation criteria may be determined by having members of a team evaluate each of the photographed face images and accumulated data of face illustrations, assigning correct answer data, and performing machine learning using the accumulated data and the correct answer data.

[0038] In this embodiment, the patient's facial expression is evaluated from a facial illustration generated from a facial image. However, because a facial illustration often emphasizes (deforms) characteristic parts of the facial image, the patient's facial expression can be evaluated more appropriately than when a facial image is used.

[0039] Next, in step S18, the complexion evaluation unit 36 ​​evaluates the complexion of the patient based on the facial illustration stored in the illustration storage unit 130. For example, the complexion evaluation unit 36 ​​evaluates the complexion based on the average brightness (value M) of pixels included in a part of the facial illustration (e.g., the cheek part). For example, the complexion evaluation unit 36 ​​pre-sets brightness ranges A to E in order from brightest to brightest, and rates the complexion as A (best complexion) when value M is included in range A. Also, when value M is included in range B to E, the complexion is rated as B to E (rating E is the worst complexion).

[0040] The evaluation criteria for the above evaluations A to E may be prepared in advance for a predetermined period of time after the patient's photographing starts, and after the predetermined period of time has passed, the evaluation criteria may be adjusted using accumulated data of the photographed face images and face illustrations of the patient. For example, the evaluation criteria may be determined by having a person in the team evaluate each of the photographed face images and accumulated data of face illustrations, assigning correct answer data, and performing machine learning using the accumulated data and the correct answer data.

[0041] The facial color evaluation unit 36 ​​may evaluate the facial color based on the saturation of pixels included in a part of the facial illustration. The facial color evaluation unit 36 ​​may also evaluate the facial color based on both lightness and saturation. In this case, the facial color can be evaluated based on, for example, the sum or product of the lightness scoring result and the saturation scoring result, or a value based on another formula.

[0042] In this embodiment, the patient's complexion is evaluated from a facial illustration generated from a facial image. However, because a facial illustration often emphasizes (deforms) characteristic parts of the facial image, the complexion can be evaluated more appropriately than when a facial image is used.

[0043] Next, in step S20, the notification destination determination unit 38 judges whether the facial expression is a predetermined evaluation. Here, as an example, the notification destination determination unit 38 judges whether the evaluation of the facial expression is evaluation 3 to 5 (gloomy expression). If the judgment in this step S20 is negative, that is, if the evaluation of the facial expression is evaluation 1 or 2 and there is no problem with the facial expression, there is no need to share the patient's information within the team (no need for care), and therefore all the processing in FIG. 7 is terminated.

[0044] On the other hand, if the determination in step S20 is positive, that is, if the facial expression is rated as 3 to 5 and the facial expression is gloomy, the process moves to step S22 since it is necessary to share information about the patient (care is necessary).

[0045] When the process proceeds to step S22, the notification destination determination unit 38 determines, as the notification destination, a person who satisfies the first condition (a mention destination in this embodiment). The notification destination determination unit 38 refers to the SNS information storage unit 120 and determines, as the notification destination, a person who has mentioned information about a patient (patient X) photographed by a photographer (visiting care worker A) who photographed an image during a predetermined period in the past. For example, as shown in FIG. 5(b), if visiting care worker A has mentioned care manager E, the notification destination determination unit 38 determines care manager E as the notification destination. Note that, when there are multiple mention destinations, the notification destination determination unit 38 may determine multiple people as the notification destinations.

[0046] Next, in step S24, the notification destination determination unit 38 judges whether the facial color is a predetermined evaluation. Here, as an example, the notification destination determination unit 38 judges whether the evaluation of the facial color is evaluation E (worst). If the judgment in this step S24 is negative, the notification destination is not added and the process proceeds to step S28.

[0047] On the other hand, if the determination in step S24 is positive, the process proceeds to step S26, where the notification destination determination unit 38 adds people who satisfy the second condition (in this embodiment, medical professionals in the team) to the notification destinations. In the example of Fig. 6, the notification destination determination unit 38 adds doctor B, nurse C, and pharmacist D, who are medical professionals, to the notification destinations.

[0048] Next, in step S28, the notification information collecting unit 40 collects notification information from the SNS information storage unit 120 and the illustration storage unit 130. In the present embodiment, as an example, the notification information collecting unit 40 collects information on care that is usually provided (provided at a predetermined frequency) by the photographer (visiting caregiver A) to the photographed patient (patient X). In addition, the notification information collecting unit 40 collects face illustrations of the photographed patient (patient X) for a predetermined period of time in the past (e.g., one week) from the illustration storage unit 130.

[0049] Next, in step S30, the notification unit 42 executes notification to the notification destination. For example, the notification unit 42 first transmits a notification screen as shown in FIG. 10 to the notification destination user terminal 70. The notification screen in FIG. 10 displays the patient's name, the date of photography, the evaluation result of the facial expression, the evaluation result of the complexion (physical condition), and past care contents (information on the care usually performed). Furthermore, the notification screen in FIG. 10 displays face illustrations from a predetermined period of the past (for example, one week) in chronological order. This allows the notification destination person to check information on patients who are estimated to have a bad expression or are in poor physical condition. In this case, the notification screen displays face illustrations instead of facial images, so that the patient's personal information can be protected.

[0050] When the notification destination user terminal 70 has logged out of the service provided by the server 10, the notification unit 42 may transmit a message screen as shown in FIG. 11 to another terminal (such as a smartphone) used by the notification destination. The message screen in FIG. 11 is a screen for informing the notification destination that there is a patient who needs care. The notification destination who has checked this message screen can check the notification screen in FIG. 10 by logging in to the service provided by the server 10 using the user terminal 70. In this way, the notification destination can check the information on the patient who has a bad expression or a pale complexion early on.

[0051] With the above, the entire process in FIG. 7 is completed.

[0052] As described above in detail, according to this embodiment, the image acquisition unit 30 acquires a facial image of the patient, and the illustration generation unit 32 generates a facial illustration from the facial image. Then, the facial expression evaluation unit 34 evaluates the facial expression of the patient based on the facial illustration, and the facial color evaluation unit 36 ​​evaluates the facial color of the patient based on the facial illustration. Then, the notification destination determination unit 38 determines the notification destination to which the patient's information is to be notified based on the evaluation results of the facial expression evaluation unit 34 and the facial color evaluation unit 36. As a result, in this embodiment, the notification destination to which the patient's information should be notified can be appropriately determined based on the patient's facial expression and facial color. In addition, by notifying the determined notification destination of the patient's information, the notification destination can be promptly notified of information about a patient with a bad facial expression or facial color. As a result, even if a visiting caregiver or the like misses a change in the patient, the change in the patient can be notified to an appropriate person in the team. In addition, since the occurrence of a change in the patient is automatically notified to an appropriate person in the team, the burden on the visiting caregiver or the like can be reduced.

[0053] Furthermore, in this embodiment, the facial expression evaluation unit 34 and the complexion evaluation unit 36 ​​deform the facial image and evaluate the facial expression and complexion based on a face illustration in which the facial features are emphasized, so that the facial expression and complexion can be appropriately evaluated.

[0054] In this embodiment, the illustration storage unit 130 stores a face illustration generated from a face image in the illustration storage unit 130, and the notification information collection unit 40 collects face illustrations of the patient over a predetermined period of time in the past as information to be notified to the notification destination. That is, in this embodiment, the face image is not stored in the illustration storage unit 130, and the face image is not notified to the notification destination, so that the patient's personal information can be protected.

[0055] In this embodiment, whether to include mention recipients (persons who satisfy a first condition) in the notification destinations is determined based on the evaluation result of the facial expression evaluation unit 34, and whether to include medical personnel (persons who satisfy a second condition) in the notification destinations is determined based on the evaluation result of the complexion evaluation unit 36. This makes it possible to notify appropriate people of patient information according to the patient's condition.

[0056] In the above embodiment, the notification destination determination unit 38 determines the mention destination as the notification destination when the facial expression evaluation unit 34 evaluates the facial expression as "dark" (evaluation 3 to 5), but this is not limiting. For example, the notification destination may be determined in advance for each evaluation stage of the facial expression evaluation unit 34. In addition, in the above embodiment, the notification destination determination unit 38 determines the medical personnel as the notification destination when the facial expression evaluation unit 36 ​​evaluates the facial expression as the worst (evaluation E), but this is not limiting. For example, the notification destination may be determined in advance for each evaluation stage of the facial expression evaluation unit 36.

[0057] In the above embodiment, the facial expression evaluation unit 34 and the facial color evaluation unit 36 ​​evaluate the facial expression and the facial color based on a facial illustration, but the present invention is not limited to this. The facial expression evaluation unit 34 and the facial color evaluation unit 36 ​​may evaluate the facial expression and the facial color based on a facial image. In this case, the illustration generation unit 32 may be omitted, a facial image storage unit may be provided instead of the illustration storage unit 130, and the notification information collection unit 40 may collect facial images for a predetermined period of time instead of facial illustrations for a predetermined period of time of the patient.

[0058] In the above embodiment, the server 10 includes the facial expression evaluation unit 34 and the complexion evaluation unit 36, but the present invention is not limited to this. That is, the server 10 may include only one of the facial expression evaluation unit 34 and the complexion evaluation unit 36. In this case, the notification destination determination unit 38 may determine the notification destination based on the evaluation result of either the facial expression evaluation unit 34 or the complexion evaluation unit 36.

[0059] In the above embodiment, the facial expression evaluation unit 34 evaluates the facial expression based on the degree to which the corners of the mouth are turned up, but the facial expression may be evaluated based on angle information of other facial features. For example, the angle of the corners of the eyes and the angle of the eyebrows may be used as the angle information of other facial features. Instead of the angle information of the facial features, other facial expression features (such as the degree to which the cheeks are turned up and the state of wrinkles between the eyebrows) may be used.

[0060] The above processing functions can be realized by a computer. In that case, a program is provided that describes the processing contents of the functions that the processing device should have. The above processing functions are realized on the computer by executing the program on the computer. The program that describes the processing contents can be recorded on a computer-readable recording medium (excluding carrier waves).

[0061] When a program is distributed, it is sold in the form of a portable recording medium on which the program is recorded, such as a DVD (Digital Versatile Disc), a CD-ROM (Compact Disc Read Only Memory), etc. The program can also be stored in a storage device of a server computer and transferred from the server computer to other computers via a network.

[0062] A computer that executes a program stores, for example, a program recorded on a portable recording medium or a program transferred from a server computer in its own storage device. The computer then reads the program from its own storage device and executes processing in accordance with the program. The computer can also read the program directly from a portable recording medium and execute processing in accordance with that program. The computer can also execute processing in accordance with the received program each time a program is transferred from the server computer.

[0063] The above-described embodiment is a preferred example of the present invention, but the present invention is not limited to this embodiment and can be modified in various ways without departing from the scope of the present invention.

[0064] In addition, the following supplementary notes are disclosed in relation to the above-described embodiment. (Appendix 1) Obtain a facial image of the patient, classifying at least one of a facial expression feature amount and a facial color of the patient into one of a plurality of stages based on the acquired facial image; determining a notification destination of the information regarding the patient based on the result of the classification; A notification destination determination program that causes a computer to execute a process. (Supplementary Note 2) The notification destination determination program according to Supplementary Note 1, wherein the facial expression feature amount includes angle information of predetermined facial features. (Supplementary Note 3) The notification destination determination program according to Supplementary Note 2, wherein the predetermined features are any one of a corner of a mouth, a corner of an eye, or an eyebrow. (Supplementary Note 4) The destination determination program according to any one of Supplementary Notes 1 to 3, wherein the complexion is at least one of skin brightness and skin saturation. (Appendix 5) A notification destination determination program described in any one of Appendices 1 to 4, characterized in that in the classification process, an illustration is generated from the facial image, and at least one of the patient's facial expression features and facial color is classified into one of a plurality of stages based on the generated illustration. (Appendix 6) An illustration generated from the face image is stored in a storage unit; notifying the notification destination determined in the process of determining the notification destination of information including the illustration of the patient; 6. The notification destination determination program according to claim 5, characterized in that the program causes the computer to execute a process. (Appendix 7) In the classification process, the facial expression features and facial color of the patient are classified into one of a plurality of stages; In the process of determining the notification destinations, it is determined whether the notification destinations include notification destinations that satisfy a first condition based on a classification result of one of the facial expression features and facial color of the patient, and it is determined whether the notification destinations include notification destinations that satisfy a second condition based on the classification result of the other of the facial expression features and facial color of the patient. 7. The notification destination determination program according to claim 1, (Appendix 8) The notification destination determination program according to any one of Appendices 1 to 7, characterized in that the reference value used in the classification process is determined based on at least one of facial expression features and facial color of the patient obtained in the past. (Appendix 9) Obtain a facial image of the patient, Based on the acquired face image, classifying at least one of the facial expression features and the facial color of the patient into one of a plurality of stages; determining a notification destination of the information regarding the patient based on the result of the classification; A notification destination determination method, the processing of which is executed by a computer. (Appendix 10) An image acquisition unit for acquiring a facial image of a patient; a classification unit that classifies at least one of a facial expression feature amount and a facial color of the patient into one of a plurality of stages based on the acquired facial image; and a notification destination determination unit that determines a notification destination of the information regarding the patient based on a result of the classification. [Explanation of symbols]

[0065] 10 Server (notification destination determination device) 30 Image acquisition unit 34 Facial Expression Evaluation Unit (Part of the Classification Unit) 36 Complexion evaluation unit (part of the classification unit) 38 Notification destination determination unit 130 Illustration storage section (storage section)

Claims

1. Acquire a facial image of the patient; classifying at least one of a facial expression feature amount and a facial color of the patient into one of a plurality of stages based on the acquired facial image; determining a notification destination of the information regarding the patient based on the result of the classification; A notification destination determination program that causes a computer to execute a process.

2. 2. The computer-readable medium according to claim 1, wherein the facial expression feature amount includes angle information of predetermined facial features.

3. 3. The notification destination determination program according to claim 2, wherein the predetermined features are any one of a corner of a mouth, a corner of an eye, and an eyebrow.

4. 2. The notification destination determination program according to claim 1, wherein the complexion is at least one of skin brightness and skin saturation.

5. The notification destination determination program according to claim 1, characterized in that, in the classification process, an illustration is generated from the facial image, and at least one of the patient's facial expression features and facial color is classified into one of a plurality of stages based on the generated illustration.

6. The illustration generated from the facial image is stored in a storage unit. notifying the notification destination determined in the process of determining the notification destination of information including the illustration of the patient; 6. The notification destination determination program according to claim 5, which causes the computer to execute a process.

7. In the classification process, the facial expression features and facial color of the patient are classified into one of a plurality of stages; In the process of determining the notification destinations, it is determined whether the notification destinations include notification destinations that satisfy a first condition based on a classification result of one of the facial expression features and facial color of the patient, and it is determined whether the notification destinations include notification destinations that satisfy a second condition based on the classification result of the other of the facial expression features and facial color of the patient.

2. The notification destination determination program according to claim 1,

8. 2. The notification destination determination program according to claim 1, wherein the reference value used in the classification process is determined based on at least one of facial expression features and facial color of the patient obtained in the past.

9. Acquire a facial image of the patient; classifying at least one of a facial expression feature amount and a facial color of the patient into one of a plurality of stages based on the acquired facial image; determining a notification destination of the information regarding the patient based on the result of the classification; A notification destination determination method, the processing of which is executed by a computer.

10. an image acquisition unit for acquiring a facial image of a patient; a classification unit that classifies at least one of a facial expression feature amount and a facial color of the patient into one of a plurality of stages based on the acquired facial image; and a notification destination determination unit that determines a notification destination of the information regarding the patient based on a result of the classification.

Images