Employment support device, employment support method, and program

Abstract

A work assisting device (100) comprises: an acquisition unit (102) that acquires biological information of a user and resume information of the user; a calculation unit (104) that uses the acquired biological information and resume information to calculate an evaluation value indicating a health risk for the user; and an identifying unit (106) that uses the evaluation value indicating the health risk to identify a candidate task to present to the user.

Description

[Technical Field]

[0001] The present invention relates to an employment support device, an employment support method, and a recording medium. [Background technology]

[0002] Patent Document 1 describes an example of a health management system with employment support that can meet the needs of users seeking employment support, such as elderly people. This system, in which a user terminal and a main server are connected via a network, includes a database for registering user information, a work ability score evaluation unit for evaluating each user's work ability score, a health status score evaluation unit for evaluating each user's health status score, a program provision unit for providing employment support programs and health improvement programs, an employment course certification unit for certifying each user's employment course, an employment certification information provision unit for providing the user's employment certification information to the employer, and a point redemption unit for redeeming employment points based on the user's employment performance. This configuration enables the system described in Patent Document 1 to link employment support for elderly people to educational support for children. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2019-175447 Summary of the Invention [Problem to be solved by the invention]

[0004] The system described in Patent Document 1 evaluates a user's condition using an employment ability score and a health status score. The employment ability score is generated by a system administrator inputting the user's evaluation of the evaluation items on an input screen of an employment support site, and the health status score is generated by the user inputting the medical interview evaluation and actual measurement results on an input screen of an online health interview support site. For this reason, the technology described in Patent Document 1 requires manual data input for the evaluation in advance, which is time-consuming and causes problems such as complicated system processing and a high load.

[0005] In view of the above-mentioned problems, one example of the object of the present invention is to provide an employment support device, an employment support method, and a recording medium that can support employment that is suited to one's health condition through a simple process. [Means for solving the problem]

[0006] According to one aspect of the present invention, An acquisition means for acquiring biometric information of a user and resume information of the user; a calculation means for calculating an evaluation value indicating a health risk of the user using the acquired biometric information and resume information; and a specifying means for specifying candidate tasks to be presented to the user using the assessment value indicating the health risk. Employment assistance devices are provided.

[0007] According to one aspect of the present invention, One or more computers Acquire the user's biometric information and the user's resume information; calculating an evaluation value indicating a health risk of the user using the acquired biometric information and resume information; There is provided an employment support method in which candidate tasks to be presented to the user are identified using the evaluation value indicating the health risk.

[0008] According to one aspect of the present invention, On the computer, A procedure for acquiring biometric information of a user and resume information of the user; a step of calculating an evaluation value indicating a health risk of the user using the acquired biometric information and resume information; A computer-readable recording medium is provided that stores a program for executing a procedure for identifying candidate tasks to be presented to the user using the assessment value indicating the health risk.

[0009] Another aspect of the present invention may be a program that causes at least one computer to execute the method of the above aspect, or a computer-readable recording medium on which such a program is recorded. This recording medium includes a non-transitory tangible medium. The computer program includes computer program code that, when executed by a computer, causes the computer to implement the employment support method on the employment support device.

[0010] Any combination of the above components, and any transformation of the present invention into a method, device, system, recording medium, computer program, etc., are also valid aspects of the present invention.

[0011] Furthermore, the various components of the present invention do not necessarily have to be independent entities, but may be formed as a single member by multiple components, one component may be formed from multiple components, one component may be part of another component, or part of one component may overlap with part of another component, etc.

[0012] Furthermore, although the method and computer program of the present invention describe a number of steps in a sequential order, the order in which the steps are described does not limit the order in which the steps are executed. Therefore, when implementing the method and computer program of the present invention, the order of the steps can be changed as long as it does not cause any problems in terms of the content.

[0013] Furthermore, the multiple steps of the method and computer program of the present invention are not limited to being executed at different times, and therefore, a step may occur while another step is being executed, or the execution timing of a step may partially or completely overlap with the execution timing of another step, etc. [Effects of the Invention]

[0014] According to one aspect of the present invention, it is possible to provide an employment support device, an employment support method, and a recording medium that support employment in accordance with one's health condition through a simple process. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a diagram showing an overview of an employment support device according to an embodiment; [Figure 2] 4 is a flowchart showing an example of the operation of the employment support device of the present embodiment. [Figure 3] 1 is a diagram conceptually illustrating a system configuration of an employment support system according to an embodiment. [Figure 4] FIG. 2 is a block diagram illustrating an example of the hardware configuration of a computer that realizes the employment support device of the embodiment. [Figure 5] FIG. 2 is a functional block diagram illustrating an example of a functional configuration of the employment support device according to the embodiment. [Figure 6] 10A and 10B are diagrams illustrating examples of data structures of biometric information and resume information of a user. [Figure 7] FIG. 2 is a diagram illustrating an example of a data structure of health risk information. [Figure 8] FIG. 10 illustrates an example data structure of a work item list. [Figure 9] 10 is a flowchart illustrating an example of the operation of the employment support device according to the embodiment. [Figure 10] FIG. 10 is a diagram illustrating an example of a task candidate screen. [Figure 11] FIG. 2 is a diagram illustrating an example of a data structure of health risk information. [Figure 12] FIG. 10 illustrates an example data structure of a work item list. [Figure 13]10 is a flowchart illustrating an example of the operation of the employment support device according to the embodiment. [Figure 14] FIG. 2 is a diagram illustrating an example of a data structure of health risk information according to the present embodiment. [Figure 15] 10 is a flowchart illustrating an example of the operation of the employment support device according to the embodiment. [Figure 16] FIG. 2 is a functional block diagram illustrating an example of a functional configuration of the employment support device according to the embodiment. [Figure 17] FIG. 10 is a diagram illustrating an example of the data structure of a reward item list. [Figure 18] 10 is a flowchart illustrating an example of the operation of the employment support device according to the embodiment. [Figure 19] 10 is a flowchart illustrating an example of the operation of the employment support device according to the embodiment. [Figure 20] FIG. 10 is a diagram illustrating an example of a data structure of help information. [Figure 21] FIG. 10 is a functional block diagram illustrating another example of the functional configuration of the employment support device according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0016] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In all drawings, similar components are designated by similar reference numerals, and their description will be omitted as appropriate. In addition, in the following drawings, configurations of parts that are not related to the essence of the present invention are omitted and are not shown.

[0017] In the embodiments, "acquisition" includes at least one of the following: a device going to retrieve data or information stored in another device or storage medium (active acquisition), and inputting data or information output from another device into the device (passive acquisition). Examples of active acquisition include making a request or inquiry to another device and receiving a reply, and accessing and reading information from another device or storage medium. An example of passive acquisition is receiving information that is distributed (or transmitted, pushed, etc.). Furthermore, "acquisition" may also mean selecting and acquiring data or information from received data or information, or selecting and receiving distributed data or information.

[0018] <Minimum configuration example> 1 is a diagram showing an overview of an employment support device 100 according to an embodiment. The employment support device 100 includes an acquisition unit 102, a calculation unit 104, and an identification unit 106. The acquisition unit 102 acquires biometric information of the user 20 and resume information of the user. The calculation unit 104 calculates an evaluation value indicating the health risk of the user using the acquired biometric information and resume information. The identifying unit 106 uses the evaluation value indicating the health risk to identify candidate tasks to be presented to the user.

[0019] <Example of operation> FIG. 2 is a flowchart showing an example of the operation of the employment support device 100 of this embodiment. First, the acquisition unit 102 acquires the biometric information of the user and the resume information of the user (step S101). Then, the calculation unit 104 calculates an evaluation value indicating the health risk of the user using the acquired biometric information and resume information (step S103). Then, the identifying unit 106 uses the evaluation value indicating the health risk to identify candidate tasks to be presented to the user (step S105).

[0020] According to this employment support device 100, the acquisition unit 102 acquires the user's biometric information and resume information, the calculation unit 104 calculates an assessment value indicating the user's health risk using the acquired biometric information and resume information, and the identification unit 106 uses the assessment value indicating the health risk to identify candidate tasks to present to the user. This allows the user to be assigned a job. Therefore, using the employment support device 100, it is possible to appropriately support employment that is suited to the user's health condition through a simple process.

[0021] A detailed example of the employment support device 100 will be described below.

[0022] (First embodiment) <System Overview> FIG. 3 is a diagram conceptually showing the system configuration of the employment support system 1 according to the embodiment. The employment support system 1 includes an employment support device 100. The employment support device 100 includes a storage device 120. The storage device 120 may be provided inside or outside the employment support device 100. In other words, the storage device 120 may be hardware that is integrated with the employment support device 100, or may be hardware that is separate from the employment support device 100.

[0023] The employment support device 100 is, for example, a server computer, and may further include a web server.

[0024] The employment support device 100 can include a user terminal 30 and a wearable terminal 32 connected via a communication network 3. Furthermore, the employment support device 100 may include a support recipient terminal 50 connected via the communication network 3. The user terminal 30 is a terminal operated by a user 20, and the support recipient terminal 50 is a terminal operated by a support recipient 40.

[0025] The wearable device 32 is worn by the user 20, acquires biometric information of the user 20, and transmits the acquired biometric information to the employment support device 100 via the user terminal 30 or directly. When the biometric information is transmitted via the user terminal 30, the wearable device 32 transmits the biometric information to the user terminal 30, for example, using near field communication (NFC). While the wearable device 32 is illustrated as a wristwatch, this is not a limitation. Alternatively, a user terminal 30 equipped with a camera, such as a smartphone of the user 20, may analyze images captured by the camera on the user terminal 30 through image processing using a predetermined application, and estimate biometric information that is then transmitted to the employment support device 100. Examples of biometric information estimated here include, but are not limited to, heart rate, body temperature, blood pressure, respiratory rate, and stress level.

[0026] The user 20 performs work to support the support recipient 40. The user 20 is a person who has experience in at least one of housework and childcare. The user 20 is a person who is not currently employed. The user 20 is, for example, 50 years old or older, and is preferably older than the age at which osteoporosis and dementia begin to appear (elderly). However, the age of the user 20 may also be younger than 50. The user 20 can also be considered an elderly person who has not yet developed an illness, but because of their advanced age, they can be considered to have potential health risks. Therefore, when supporting employment, it is preferable to assign tasks with a workload that is appropriate for the health risks.

[0027] Furthermore, users 20 are not limited to elderly women, and may include third party supporters (people dispatched from government, companies, organizations, etc.) who sympathize with or support such efforts.

[0028] Support recipient 40 is a person who wishes to receive support for raising a child. Support recipient 40 is, in particular, a parent who has at least one child 42. Furthermore, support recipient 40 is a parent in a single-parent household. Furthermore, support recipient 40 is a woman, and is the mother of a single-parent household, a so-called single mother. Support recipient 40 may also include parents in households where the couple is separated and the marriage has effectively broken down. Support recipient 40 is preferably a person whose income is lower than the average income of a child-rearing household (for example, below a certain percentage), who is the so-called working poor, or a person whose income is unstable (for example, whose monthly income difference is above a certain value).

[0029] It is preferable that the recipients of support 40 are people who are not eligible for childcare support (subsidies, etc.) from the government or who have difficulty raising the funds to use similar services provided by private companies.

[0030] Since the support recipient 40 is a woman, it is preferable that the user 20 supporting the support recipient 40 is a woman. Furthermore, since women are at higher risk of developing osteoporosis and dementia than men, it is also preferable to target a woman as the user 20 from the perspective of disease prevention. Therefore, hereinafter, the user will also be referred to as an "elderly woman."

[0031] In the figure, one user 20, one support recipient 40, and two children 42 of each support recipient 40 are shown. However, multiple users 20 and multiple support recipients 40 can use this employment support system 1. Furthermore, the number of children 42 of the support recipient 40 is not limited to two, but may be at least one, or two or more. The employment support system 1 matches multiple users 20 and multiple support recipients 40, and the user 20 supports the support recipient 40 who is raising children.

[0032] The user terminal 30 and the support recipient terminal 50 are computers such as smartphones, tablet terminals, and personal computers.

[0033] When using the employment support system 1, the user 20 and the support recipient terminal 50 register in advance. When registering, account information including, for example, an account name and password for login authentication is registered. Alternatively, the system may be linked to account information of an existing SNS (Social Networking Service).

[0034] Furthermore, identity verification may be performed at the time of use, and biometric authentication information for this purpose may be registered in advance and used to log in. The biometric authentication information may include at least one feature such as face, iris, vein, auricle, and fingerprint. Furthermore, the biometric authentication information may include biometric information for behavioral biometric authentication such as handwriting authentication, gait authentication, and keystroke authentication.

[0035] Possible methods for using the services of this employment support system 1 include installing and launching a specific application on each terminal, or accessing a specific website from each terminal using a browser, etc. By logging in to the employment support system 1 using pre-registered account information, users can use the services once authentication is successful.

[0036] <Hardware configuration example> Figure 4 is a block diagram illustrating the hardware configuration of a computer 1000 that realizes the employment support device 100 in Figure 1 and Figures 5, 16, and 21 described below. The user terminal 30, wearable terminal 32, and support recipient terminal 50 in Figure 3 are also realized by the computer 1000. In addition, the functions of the employment support device 100 may be realized by the user terminal 30 or the support recipient terminal 50 sharing some of the functions.

[0037] The computer 1000 includes a bus 1010 , a processor 1020 , a memory 1030 , a storage device 1040 , an input / output interface 1050 , and a network interface 1060 .

[0038] The bus 1010 is a data transmission path for transmitting and receiving data among the processor 1020, memory 1030, storage device 1040, input / output interface 1050, and network interface 1060. However, the method of connecting the processor 1020 and the like to each other is not limited to bus connection.

[0039] The processor 1020 is implemented by a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or the like.

[0040] The memory 1030 is a main storage device realized by a RAM (Random Access Memory) or the like.

[0041] The storage device 1040 is an auxiliary storage device realized by a hard disk drive (HDD), a solid state drive (SSD), a memory card, a read-only memory (ROM), or the like. The storage device 1040 stores program modules that realize each function of the employment support device 100 (for example, the acquisition unit 102, calculation unit 104, identification unit 106, output processing unit 108, and the generation unit 110 and matching unit 112, which will be described later). The processor 1020 loads each of these program modules into the memory 1030 and executes them, thereby realizing each function corresponding to the program module. The storage device 1040 may also store each data of the storage device 120 of the employment support device 100.

[0042] The program module may be recorded on a recording medium. The recording medium on which the program module is recorded may include a non-transitory, tangible medium usable by the computer 1000, and the program code readable by the computer 1000 (processor 1020) may be embedded in the medium.

[0043] The input / output interface 1050 is an interface for connecting the computer 1000 with various input / output devices. The input / output interface 1050 also functions as a communication interface for performing short-range wireless communication such as Bluetooth (registered trademark) and NFC (Near Field Communication).

[0044] The network interface 1060 is an interface for connecting the computer 1000 to a communication network. This communication network is, for example, a LAN (Local Area Network) or a WAN (Wide Area Network). The method for connecting the network interface 1060 to the communication network may be a wireless connection or a wired connection.

[0045] The computer 1000 then connects to necessary equipment (e.g., the display, operation keys, touch panel, camera, speaker, microphone of the user terminal 30 or the support recipient terminal 50, the display, keyboard, mouse, speaker, microphone, etc. of the employment support device 100) via the input / output interface 1050 or the network interface 1060.

[0046] Each component of the employment support device 100 in each embodiment shown in Figure 1 and in Figures 5, 16, and 21 described below is realized by any combination of hardware and software of the computer 1000 in Figure 4. Those skilled in the art will understand that there are many variations in the realization methods and devices. The functional block diagrams showing the employment support device 100 in each embodiment show logical functional blocks rather than a hardware-based configuration.

[0047] <Example of functional configuration> An example of the functional configuration of the employment support device 100 according to the embodiment will be described below. FIG. 5 is a functional block diagram illustrating an example of the functional configuration of the employment support device 100 according to the embodiment. The employment support device 100 further includes an output processing unit 108 in addition to the configuration of the employment support device 100 in Fig. 1. The output processing unit 108 outputs the work item candidates identified by the identification unit 106 to an output device (for example, a display of the user terminal 30).

[0048] Each component will be described in detail below. The acquisition unit 102 acquires biometric information of the user 20 and resume information used when the user 20 applies for a job. The information acquired by the acquisition unit 102 is stored in the storage device 120 in association with the user ID of the user 20.

[0049] The children 42 of the support recipients 40 preferably include preschool children. This is because school-age children receive more financial support from the government than preschool children, and because compulsory education means children can be left at school during the day, making it easier for the support recipients 40 to secure working hours. For this reason, the employment support system 1 targets mothers with preschool children aged 0 to 6, who are particularly difficult to reach with government support.

[0050] The work that the user 20 supports the support recipient 40 with is, for example, at least one of housework and childcare. For example, the work includes housework performed at the residence of the support recipient 40, such as doing laundry, hanging out laundry, taking in laundry, folding laundry, cleaning, tidying up, taking out the trash, washing dishes, and preparing meals, as well as childcare tasks (so-called childcare) such as taking care of the child 42, reading picture books to the child, playing pretend games or house cooking, playing hand games, singing songs (nursery songs, nursery rhymes, etc.), watching over the child while playing with blocks or building blocks, and helping with drawing and crafts.

[0051] The biological information acquired by the acquisition unit 102 includes health information indicating the health condition of the user 20. Furthermore, the biological information including the health information indicating the health condition includes information related to bone mass.

[0052] The acquisition unit 102 acquires health information indicating the health condition of the user 20, and the calculation unit 104 calculates an evaluation value indicating the health risk, so it becomes possible to evaluate the risk of developing dementia or osteoporosis before it becomes a disease, and to prevent the disease from occurring. In particular, by acquiring information on bone mass, it becomes more likely that the risk of developing osteoporosis, which is specific to elderly women, can be reduced before it occurs.

[0053] For example, by providing exercise support that selects support tasks for the support recipient 40 so that the user 20 receives a load that improves the amount of daily activity, it is possible to reduce the risk of the user 20 developing osteoporosis. Alternatively, as will be described in detail in an embodiment below, by providing two-way communication support through support tasks for the support recipient 40, in particular by selecting tasks that enable two-way communication, such as conversation with the child 42, it is possible to reduce the risk of the user 20 developing dementia.

[0054] FIG. 6 is a diagram showing an example of the data structure of the biometric information 200 and resume information 210 of the user 20. As shown in FIG. The biometric information 200 of the user 20 may include at least one of health information indicating the health condition of the user 20, such as the weight of the user 20 measured with a general body composition scale, muscle mass, body fat percentage, visceral fat level, subcutaneous fat percentage, basal metabolic rate, skeletal muscle percentage, BMI (Body Mass Index), body age, body water content, and estimated bone mass.

[0055] In the example of FIG. 6(a), the biometric information 200 is 、 It includes at least identification information (user ID) of user 20, acquisition date and time of the biometric information, and information on bone mass (e.g., estimated bone mass). The acquisition date and time is preferably the date and time when the biometric information was measured. Furthermore, when multiple types of biometric information are acquired, it is preferable to include the measurement date and time of each piece of biometric information.

[0056] In another example, the biological information 200 may include biological information acquired from the wearable device 32 worn by the user 20. For example, the biological information 200 may include at least one of heart rate, number of steps, calories burned, walking record, oxygen saturation, blood pressure, body temperature, and electrocardiogram information. In the example of FIG. 6(a), the acquisition date and time is preferably the date and time when the biological information is measured by the wearable device 32, but is not limited thereto, and may be, for example, the date and time when the user terminal 30 receives the biological information from the wearable device 32.

[0057] Furthermore, in another example, the user may use the user terminal 30 to input the measurement results of biological information from an input screen based on the test results at the time of medical examination or the results of a health check.

[0058] 6(b), the resume information 210 includes at least the identification information (user ID), name, and date of birth (or age) of the user 20. The resume information 210 may further include the date and time when the information was acquired or stored.

[0059] The resume information 210 of the user 20 is information on a resume that the user 20 uses when applying for a job supporting the support recipient 40. The resume information 210 may include general resume information, such as name, photo, date of birth, age, sex, family composition, address, work history, educational background, licenses, special skills, etc.

[0060] The resume information of the user 20 can be obtained, for example, by selecting a resume information input screen from a menu screen (not shown) that is displayed when the user logs in to the employment support system 1 using the user terminal 30, and accepting the information entered by the user 20 on the input screen. A facial photograph can be obtained by uploading image file data.

[0061] Furthermore, the resume information of user 20 may include information regarding the motivation of user 20. For example, information indicating the degree of interest in improving one's own health, the degree of interest in interacting with others, the degree of interest in contributing to society, etc. may be accepted by providing options in advance on the input screen, or by providing a free-form input field.

[0062] Based on this motivation, if the motivation is to improve health, the identification unit 106 can gradually change the work content presented to the user 20 as candidates to those that are more demanding, based on this information.

[0063] The timing at which the acquisition unit 102 acquires the biometric information 200 and the resume information 210 differs. The biometric information 200 is acquired before starting to use the services provided by the employment support system 1. Thereafter, the biometric information 200 may be acquired periodically, for example, daily, monthly, semi-annually, or annually, for each type of biometric information, for the purpose of monitoring the health status of the user 20. The resume information 210 is acquired when applying for a job provided by the employment support system 1. Furthermore, it is preferable that the resume information 210 be acquired when there is a change in the content of the resume.

[0064] The calculation unit 104 calculates an evaluation value indicating the health risk of the user 20 using the acquired biometric information 200 and resume information 210. The biometric information 200 includes information related to the bone mass of the user 20, and the evaluation value indicating the health risk may include an evaluation value indicating the risk of developing osteoporosis. The evaluation value may be, for example, a value indicating the presence or absence of a risk of developing osteoporosis (for example, 1 for "risk of developing" and 0 for "no risk of developing"), or a value indicating the probability of developing the disease.

[0065] In particular, it will be possible to evaluate the risk of developing osteoporosis, a problem particular to elderly women, thereby increasing the possibility of reducing the risk of developing osteoporosis before it actually occurs.

[0066] The calculation unit 104 calculates an evaluation value indicating the risk of developing osteoporosis using the estimated age of the user 20 estimated using the information on bone mass and the age information of the user 20 included in the resume information 210.

[0067] Specifically, the calculation unit 104 uses a table linking bone mass with age to acquire the age linked to the bone mass of the user 20 from the biometric information 200 acquired by the acquisition unit 102, and sets the acquired age as the estimated age. Then, the acquisition unit 102 acquires information related to the age of the user 20 (for example, date of birth or age) from the resume information 210, and the calculation unit 104 identifies the actual age of the user 20 from the acquired information related to the age of the user 20.

[0068] The calculation unit 104 compares the identified actual age with the estimated age, and if the estimated age is older than the actual age by a certain number of years or more (for example, 5 years older), the evaluation value indicating the health risk is set to a value indicating the risk of developing osteoporosis.

[0069] However, the age difference between the actual age and the estimated age may vary depending on the actual age. For example, the older the actual age, the smaller the age difference used as the standard for determining whether or not there is a risk of developing osteoporosis. This is because as the actual age increases, the rate of bone loss increases, and the age difference in the rate of bone loss becomes smaller.

[0070] As another example, when the bone mass of user 20 falls outside the range of the standard deviation α of the distribution of normal bone mass for each chronological age, calculation unit 104 may set the health risk evaluation value to a value indicating a risk of developing osteoporosis (for example, 1). However, when the bone mass is greater than the normal bone mass, calculation unit 104 sets the health risk evaluation value to a value indicating no risk of developing osteoporosis (for example, 0).

[0071] As yet another example, using a table in which information on average bone mass by age is registered, calculation unit 104 may compare the estimated bone mass of user 20 from the biometric information 200 acquired by acquisition unit 102 with the average bone mass of people of the same age as user 20, and if user 20's estimated bone mass is lower than the average by more than a predetermined value, the health risk assessment value may be a value indicating a risk of developing osteoporosis.

[0072] In addition, if the calculation unit 104 determines in the process of calculating the risk of developing osteoporosis that the estimated bone mass of the user 20 is within the range of "development" (indicates an abnormal value), it is preferable that the output processing unit 108 outputs notification information recommending that the user undergo a medical examination (detailed examination) at a hospital or the like before assigning work to the employment support system 1.

[0073] In this way, it is possible to evaluate the risk of developing osteoporosis, which is a problem particular to elderly women, and this increases the possibility of reducing the risk of developing osteoporosis before it actually occurs.

[0074] 7 is a diagram showing an example data structure of health risk information 220. Health risk information 220 includes an evaluation value indicating the risk of developing osteoporosis, which is calculated by calculation unit 104 and linked to a user ID. The evaluation value indicating the risk of developing osteoporosis is stored as health risk information 220 in storage device 120, linked to the user ID of user 20.

[0075] The identifying unit 106 identifies candidate tasks that the user 20 can take on from among the work using the evaluation value indicating the health risk.

[0076] 8 is a diagram showing an example data structure of task item list 230. Task item list 230 includes, for each task, a workload level, an estimated task time, and an average calorie expenditure value for performing that task for that task time. Task item list 230 is stored in storage device 120.

[0077] In this example, the workload levels are set in ascending order of calorie consumption, i.e., ascending order of workload, from 1 to 6. However, the workload levels are not limited to 6 levels and may be any number of levels.

[0078] The work item list 230 may also be generated for each support recipient. This is because the workload may differ even for the same work content depending on the situation of the support recipient 40. FIG. 21 is a functional block diagram showing another example of the functional configuration of the employment support device 100 according to the embodiment. The acquisition unit 102 acquires target person attribute information indicating the attributes of the support target 40 . The employment support device 100 may further include a generation unit 110 that generates the task item list 230 based on the subject attribute information. The identifying unit 106 identifies candidate tasks to be presented to the user 20 from among the tasks included in the task item list 230 generated by the generating unit 110 . The work item list 230 includes load information for each work item for each support recipient 40 .

[0079] The target person attribute information may further include attribute information of the children 42 of the support target 40, such as the number, gender, and age of the children 42. For example, the load information (for example, calories burned) in the task item list 230 may differ depending on the number, sex, age, etc. of the children 42 of the support recipient 40.

[0080] Because the work of the user 20 includes taking care of the children 42 of the support recipient 40, the workload may differ depending on the age, sex, and number of the children 42. Therefore, a work item list 230 in which the workload is set taking into consideration the attributes of the children 42, separate from the support recipient 40, can be used to identify candidate tasks by the identification unit 106. This makes it possible to accurately identify the workload of tasks to be presented to the user 20, and to present tasks with appropriate workloads to the user 20.

[0081] The identifying unit 106 identifies the tolerable load range of the user 20 based on the evaluation value indicating the health risk, and identifies candidate tasks to be presented to the user 20 based on the load information determined for each task.

[0082] For example, the identification unit 106 may use the measurement results of the activity meter of the user 20 to identify the track record of the exercise habit and identify the range of the tolerable load of the user 20.

[0083] The allowable load range may be a limit on the workload of each task, or may be a limit on the total workload when the user 20 selects multiple tasks. In the latter case, the output processing unit 108 may add up the workloads of the tasks selected by the user 20 on the task candidate screen 300 presented to the user 20, and if the total exceeds the allowable load range, a message notifying the user of this may be output, or tasks that exceed the allowable load range may not be selected. The output processing unit 108 may also suggest alternative tasks that satisfy the allowable load range.

[0084] The total workload of the above tasks may be the sum of the workload level values ​​described above, or may be the sum of the calories burned indicating the workload of each task. Furthermore, the workload may be set, for example, using the work environment conditions described below. For example, when performing tasks in a residence with stairs, the calories burned due to climbing up and down the stairs may be calculated by multiplying the total calories burned for tasks requiring climbing up and down the stairs or for all tasks by a predetermined coefficient (a value greater than 1), or the workload level may be increased by a predetermined level.

[0085] In this way, the range of allowable load can be set taking into consideration the exercise habits of the user 20, so that a user 20 who exercises regularly can select work that involves a higher load, and a user 20 who does not exercise regularly can avoid selecting work that involves too much load, thereby preventing accidents and injuries during work.

[0086] Specifically, the identification unit 106 acquires, for example, an assessment value of the health risk of the user 20 from the health risk information 220 in Fig. 7, and if the assessment value of the health risk satisfies a criterion, identifies a workload level within the range of the tolerable workload for the user 20 based on the assessment value of the health risk, extracts work items corresponding to the identified workload level from the work item list 230 in Fig. 8, and identifies them as candidates for work that the user 20 can undertake. Here, the criterion includes whether the assessment value of the health risk indicates that the workload needs to be reduced or increased.

[0087] If the health risk evaluation value does not meet the criteria, that is, if the evaluation value indicates that user 20 has no health risk and therefore there is no need to reduce or increase or decrease the workload, the identification unit 106 may not identify the workload level of user 20, and may instead consider all work items as candidates for work that user 20 can handle.

[0088] If the health risk assessment value meets the criteria, i.e., if the assessment value indicates that user 20 has a health risk and therefore a workload reduction or increase is necessary, the identification unit 106 sets a limit on the workload level set for each task, extracts task items that do not exceed the limit, and identifies them as candidate tasks for user 20. For example, if user 20's health risk assessment value indicates a risk of developing osteoporosis, the workload level limit is set to a first reference value (e.g., level 4 of a multi-level system), and tasks with workload levels equal to or less than the first reference value are extracted and identified as candidate tasks. Alternatively, for example, the identification unit 106 may extract tasks in the task item list 230 with workload levels equal to or greater than a second reference value (e.g., level 5 of a multi-level system) and identify them as candidate tasks. Furthermore, if the health risk indicates a risk of developing dementia, which will be described later, a different reference value may be used for identification.

[0089] In this way, even if the risk of developing osteoporosis is the same, the method of limiting the workload level may be different. For example, the method may be different depending on the user's 20 daily exercise habits, basic physical strength, and whether or not the user 20 is motivated to improve their health. In this way, the work can be selected according to the user's 20 workload tolerance. Note that whether or not the user 20 is motivated to improve their health can be determined by referring to information about the motivation for applying in the resume information described above.

[0090] Furthermore, if the user 20 does not have a daily exercise habit, it is preferable to initially set the workload level low. It is expected that low-load work will provide an opportunity to develop an exercise habit and promote the establishment of the habit. Thereafter, as the user 20 continues working and develops an exercise habit, their physical strength improves, and when the evaluation value indicates that their health risk has improved, the identification unit 106 may increase the workload level based on the evaluation value. In this way, it is expected that the establishment of an exercise habit, including for users 20 who do not have a daily exercise habit, will reduce the risk of developing osteoporosis and contribute to improving their healthy life expectancy.

[0091] <Example of operation> FIG. 9 is a flowchart showing an example of the operation of the employment support device 100 according to the embodiment. This flow is executed the first time the user 20 starts using the services of the employment support system 1.

[0092] 9 correspond to step S101 in Fig. 2, and steps S123 to S129 in Fig. 9 correspond to step S103 in Fig. 2. Steps S131 to S135 in Fig. 9 correspond to step S105 in Fig. 2.

[0093] First, the acquisition unit 102 acquires the actual age information of the user 20 from the resume information 210 (step S111). Then, the calculation unit 104 executes a processing routine (S120) for estimating the risk of developing osteoporosis. The osteoporosis development risk estimation processing routine S120 includes steps S121 to S129, which are surrounded by a dashed line in the figure.

[0094] In the osteoporosis onset risk estimation processing routine S120, the calculation unit 104 first acquires the biometric information 200 (step S121). Here, the bone mass of the user 20 is acquired as the biometric information 200. Then, the calculation unit 104 calculates the age estimated from the bone mass of the user 20, and sets the calculated age as the estimated age (step S123).

[0095] Then, calculation unit 104 compares the actual age acquired in step S121 with the estimated age estimated in step S123, and if the estimated age is older than the actual age by a certain number of years (YES in step S125), it sets the evaluation value of the risk of developing osteoporosis as a risk of onset (for example, 1) as the evaluation value of the health risk of user 20 (step S127). On the other hand, if the estimated age is not older than the actual age by a certain number of years (NO in step S125), calculation unit 104 sets the evaluation value of the risk of developing osteoporosis as a risk of no onset (for example, 0) as the evaluation value of the health risk of user 20 (step S129). The evaluation value of the risk of developing osteoporosis is stored in health risk information 220 (FIG. 7) as the evaluation value of the health risk, linked to the user ID of user 20.

[0096] The identification unit 106 then acquires the assessment value of the health risk of the user 20 from the health risk information 220 and identifies the workload level according to the assessment value of the health risk of the user 20 (step S131). For example, if there is a risk of developing osteoporosis, the identification unit 106 may identify the workload level in the task item list 230 as 4 or less according to the assessment value of the risk of developing osteoporosis. In this case, tasks in the task item list 230 with a workload level of 4 or less are extracted as candidates (step S133). Conversely, if there is a risk of developing osteoporosis, the identification unit 106 may identify the workload level in the task item list 230 as 3 or more according to the assessment value of the risk of developing osteoporosis. In this case, tasks in the task item list 230 with a workload level of 3 or more are extracted as candidates (step S133).

[0097] Here, when the evaluation value of the risk of developing osteoporosis indicates that the risk is higher than the standard, it is preferable to set the level low at the start of work with a high workload to avoid the possibility of risk of stress fractures, etc. Thereafter, when the evaluation value of the risk of developing osteoporosis falls below the standard, it is preferable to gradually set the workload level higher.

[0098] On the other hand, if the assessment value of the risk of developing osteoporosis indicates that there is a risk of developing the disease but is lower than the standard, the workload level may be set slightly higher, with the aim of improving health through work. In this case, too, it is preferable to set the level low when starting work, and then gradually increase the level if there are no problems after monitoring the assessment value of the health risk of user 20 for a predetermined period of time.

[0099] The output processing unit 108 presents the tasks extracted in step S133 to the user 20 as candidate tasks that the user 20 can handle (step S135). For example, the output processing unit 108 displays a task candidate screen 300 of FIG. 10 on the display of the user terminal 30.

[0100] 10 is a diagram showing an example of a task candidate screen 300. The task candidate screen 300 includes a list of task candidates that the user 20 can handle. The list on the task candidate screen 300 includes task items, estimated times required for the tasks, and check boxes 302 that allow the user 20 to select from the candidates the task that the user 20 wishes to handle.

[0101] On the task candidate screen 300 (FIG. 10), the user 20 can select a task item for which he or she wishes to be in charge from among the assigned tasks.

[0102] As described above, according to this embodiment, the employment support device 100 includes an acquisition unit 102, a calculation unit 104, an identification unit 106, and an output processing unit 108. The acquisition unit 102 acquires biometric information of the user 20 and resume information of the user 20. The calculation unit 104 calculates an evaluation value indicating a health risk of the user 20 using the acquired biometric information and resume information. The identification unit 106 uses the evaluation value indicating the health risk to identify candidate tasks to present to the user 20. The output processing unit 108 outputs the candidate tasks identified by the identification unit 106 to an output device (for example, a display of the user terminal 30).

[0103] This configuration allows for a simple process to appropriately support employment suited to one's health condition. In particular, from the perspective of preventing illness, it is possible to appropriately support employment for elderly people who are in a state of health that does not require diagnosis at a medical institution, particularly women who are at high risk of developing dementia and osteoporosis. This is expected to extend healthy life expectancy and help resolve social issues such as rising medical and nursing care costs.

[0104] Furthermore, while taking into consideration occupational safety, it will be possible to provide elderly people (especially elderly women) with opportunities to participate in society and establish contact points with society. Furthermore, it will be possible to utilize elderly human resources. For example, when utilizing elderly human resources, it is expected that highly specialized qualified individuals and individuals with long work histories will be utilized. Similarly, by focusing on the long history and high level of experience of elderly women as housewives, the Employment Support System 1 will make it possible to provide elderly human resources without work history with opportunities to participate in society.

[0105] Furthermore, since the support recipients 40 are single mothers with preschool children, it is possible to support single mothers with preschool children who are not elementary or junior high school children (requiring learning support) receiving school assistance. Since taking care of preschool children 42 is included in the work of the user 20, it also supports the stable continuation of employment for single mothers, making it possible to encourage their social participation and economic independence. Therefore, it may also be a clue to solving the issue of poverty among women.

[0106] Furthermore, because it is possible to limit the workload level and identify candidate tasks, it becomes possible to assign reasonable tasks that take into consideration the health of elderly women at work.In particular, by assessing the risk of developing osteoporosis, a problem specific to elderly women, and selecting candidate tasks based on the evaluation value, it is highly possible to reduce the risk of developing osteoporosis.

[0107] By performing the work, the user 20 can improve the level of daily activity and maintain or improve his / her health condition.

[0108] (Second embodiment) This embodiment is similar to the first embodiment, except that it has a configuration in which candidate tasks are identified using the risk of developing dementia as an assessment value of health risk. The employment support device 100 of this embodiment has the same configuration as the first embodiment, and will be described using Figure 5. The configuration of this embodiment may be combined with at least one of the configurations of the other embodiments to the extent that no contradiction occurs.

[0109] <Example of functional configuration> In this embodiment, the biometric information 200 acquired by the acquisition unit 102 includes a facial image of the user 20. The calculation unit 104 calculates an evaluation value indicating a health risk based on the age of the user 20 estimated from the face image and the age of the user 20 included in the resume information 210.

[0110] The health risk calculated from the face image may be, for example, the risk of developing dementia, the risk of developing arteriosclerosis, etc. The risk of developing arteriosclerosis will be described in another embodiment below. The risk of developing dementia is explained below.

[0111] Specifically, the acquisition unit 102 acquires, for example, a facial image of the user 20 included in the resume information 210 of the user 20. Alternatively, the acquisition unit 102 may acquire video captured during an online interview with the user 20. The calculation unit 104 causes an image processing device (not shown) to perform an age estimation process using the facial image of the user 20. The age estimation technology can be a general technology and is not particularly limited. Furthermore, the acquisition unit 102 acquires information related to the age of the user 20 (for example, date of birth or age) from the resume information 210. Then, the calculation unit 104 determines the actual age of the user 20 from the information related to the age of the user 20 acquired by the acquisition unit 102.

[0112] Then, the calculation unit 104 compares the identified actual age with the estimated age, and if the estimated age is older than the actual age by a certain number of years or more (for example, 5 years older), the evaluation value indicating the health risk is set to a value indicating the risk of developing dementia.

[0113] 11 is a diagram showing an example data structure of health risk information 220. Health risk information 220 includes an evaluation value indicating the risk of developing dementia, which is calculated by calculation unit 104 and linked to a user ID. The evaluation value indicating the risk of developing dementia is stored in storage device 120 as health risk information 220, linked to the user ID of user 20.

[0114] The identifying unit 106 identifies candidate tasks that the user 20 can take on from among the work using the evaluation value indicating the health risk.

[0115] FIG. 12 is a diagram showing an example of the data structure of the work item list 232. As shown in FIG. The task item list 230 in Fig. 8 is for when exercise support is required, and the task item list 232 in Fig. 12 is for when communication support is required. The task item list 232 is provided separately from the task item list 230 for when exercise support is required in Fig. 8, and is stored in the storage device 120.

[0116] The task list 232 stores, for each task, the average estimated task time, the calories burned per unit time when performing the task, the percentage of the amount of speech during the task relative to the estimated task time, and the level of interactivity of communication for the task, all of which are associated with each other. The percentage of speech is an index of the degree of continuity of the conversation (length of interaction).

[0117] In this example, the interactivity level of communication is set to the following three levels, but is not limited to these. Level 3 is where ongoing conversations are expected. Level 2 is a level where there is conversation, but it may end up being a one-off exchange. Level 1 is a level where one-sided conversation may occur, for example, where reading a picture book is possible.

[0118] The interactivity level of work communication is divided into three levels, from level 1 to 3. The interactivity of communication is a level that indicates the degree of conversational exchange, with levels 1 to 3 indicating a greater amount of conversation.

[0119] The identification unit 106, for example, obtains the health risk assessment value of the user 20 (in this embodiment, the assessment value of the risk of developing dementia) from the health risk information 220 in Figure 11, and if the health risk assessment value meets the criteria, in other words, if it indicates that there is a risk of developing dementia (requires communication support), it extracts work items with communication interactivity level 3 from the work item list 232 and identifies them as candidates for work that the user 20 can handle.

[0120] If the evaluation value of the health risk does not satisfy the criteria, that is, if the evaluation value indicates that the user 20 has no health risk and therefore communication support is unnecessary, the identification unit 106 may include all of the work items as candidates for work that the user 20 can undertake. However, it may also include some of the work items as candidates.

[0121] For example, if the health risk assessment value of user 20 indicates a risk of developing dementia, the identification unit 106 limits the level of interactivity of communication to level 3 and extracts only tasks at level 3. Alternatively, tasks may be extracted using the amount of speech in the task item list 232. For example, the identification unit 106 may extract tasks for which the amount of speech is equal to or greater than a predetermined value.

[0122] For example, the amount of speech may be measured by capturing an image of the user 20 actually performing an activity involving interaction with the child 42 of the support recipient 40 and analyzing the generated video data. The identification unit 106 may identify the activity using the amount of speech. Alternatively, an activity may be identified assuming a case in which the user 20 feels tired because the child 42 of the support recipient 40 is sociable and talks a lot, despite the user 20 having a low level of interactivity in communication. For example, when the user 20 has a low level of interactivity in communication, or when the child 42 of the support recipient 40 is sociable and talks a lot, the identification unit 106 may include, as candidates, activities with a low level of interactivity in communication.

[0123] <Example of operation> FIG. 13 is a flowchart showing an example of the operation of the employment support device 100 according to the embodiment. This flow is executed the first time that user 20 starts using the services of employment support system 1. The flow of Fig. 13 also includes step S111 and step S135, which are the same as the flow of Fig. 9. The flow of Fig. 13 is the same as the flow of Fig. 9 except that it has a processing routine (S200) for estimating the risk of developing dementia instead of the osteoporosis onset risk estimation processing routine S120 of Fig. 9, and has steps S141 to S145 instead of steps S131 to S133 of Fig. 9.

[0124] First, the acquisition unit 102 acquires the actual age information of the user 20 from the resume information 210 (step S111). Then, the calculation unit 104 executes a dementia onset risk estimation processing routine (S200). The dementia onset risk estimation processing routine S200 includes steps S201 to S209, which are surrounded by a dashed line in the figure.

[0125] In the dementia onset risk estimation processing routine S200, the calculation unit 104 first acquires biometric information 200 (step S201). Here, a facial image of the user 20 is acquired as the biometric information 200. The facial image of the user 20 is acquired, for example, from the facial image of the user 20 included in the resume information 210. Then, the calculation unit 104 causes an image processing device to perform age estimation processing using the facial image of the user 20, and acquires an estimated age (step S203).

[0126] Then, calculation unit 104 compares the actual age acquired in step S201 with the estimated age acquired in step S203, and if the estimated age is older than the actual age by a certain number of years (YES in step S205), it sets the evaluation value of the risk of developing dementia as a risk of onset (for example, 1) as the evaluation value of the health risk of user 20 (step S207). On the other hand, if the estimated age is not older than the actual age by a certain number of years (NO in step S205), calculation unit 104 sets the evaluation value of the risk of developing dementia as no risk of onset (for example, 0) as the evaluation value of the health risk of user 20 (step S209). The evaluation value of the health risk is stored in health risk information 220 (FIG. 11).

[0127] The identification unit 106 then refers to the health risk information 220 to determine whether or not there is a health risk for the user 20, and if there is a health risk (YES in step S141), identifies candidate tasks that the user 20 can undertake by limiting the candidate tasks to those corresponding to the assessment value of the health risk for the user 20 (step S143). For example, if there is a health risk (here, the risk of developing dementia), the identification unit 106 may limit the interactivity of communication in the task item list 230 to level 3. In this case, tasks with interactivity of work communication at level 3 are extracted from the task item list 230 as candidates.

[0128] If there is no health risk (NO in step S141), no restrictions are placed on the work items, and the identification unit 106 identifies all of the work items in the work item list 230 as candidate work that the user 20 can handle (step S145). Note that it is assumed that the work item list 230 includes work that is targeted at elderly women. In other words, taking into consideration the average physical strength of elderly women, the work item list 230 preferably includes work that is appropriate for the health condition of elderly women, and preferably does not include work that is excessively burdensome for elderly women.

[0129] The output processing unit 108 presents the tasks identified in step S143 or step S145 to the user 20 as candidate tasks that the user 20 can handle (step S135). For example, the output processing unit 108 displays a task candidate screen 300 of Fig. 10 on the display of the user terminal 30. On the task candidate screen 300, the user 20 can select a task item that the user 20 wishes to handle from the assigned tasks.

[0130] As described above, according to this embodiment, the biometric information 200 acquired by the acquisition unit 102 includes a facial image of the user 20. Then, the calculation unit 104 estimates the age of the user 20 from the facial image. The calculation unit 104 calculates an evaluation value indicating the risk of developing dementia as an evaluation value indicating a health risk, using the difference between the age obtained from the age estimation result and the actual age of the user 20 included in the resume information 210.

[0131] In this way, the employment support device 100 of this embodiment not only achieves the same effects as the above-described embodiment, but also evaluates the risk of developing dementia, which is a problem particularly specific to elderly women, and can select tasks based on the evaluation value, thereby increasing the possibility of reducing the risk of developing dementia while supporting elderly women in their employment.

[0132] (Third embodiment) In the first embodiment described above, the calculation unit 104 estimates the age of the user 20 using the bone mass of the user 20 as biometric information, and calculates the evaluation value of the risk of developing osteoporosis using the difference between the actual age and the estimated age. On the other hand, in the second embodiment, the calculation unit 104 estimates the age of the user 20 using a facial image of the user 20 as biometric information, and calculates the evaluation value of the risk of developing dementia using the difference between the actual age and the estimated age. In this embodiment, the calculation unit 104 estimates the age using both the bone mass and facial image of the user 20 as biometric information, and calculates both the evaluation value of the risk of developing osteoporosis and the evaluation value of the risk of developing dementia.

[0133] The employment support device 100 of this embodiment has the same configuration as the first and second embodiments, and will be described using Figure 5. However, the configuration of this embodiment may be combined with at least one of the configurations of the other embodiments to the extent that no contradiction occurs.

[0134] <Example of functional configuration> The biometric information 200 acquired by the acquisition unit 102 includes information about bone mass and a facial image of the user 20. The resume information 210 acquired by the acquisition unit 102 includes information about the age of the user 20 (for example, date of birth or age). The calculation unit 104 calculates an evaluation value indicating the health risk of the user 20 using the acquired biometric information 200 and resume information 210.

[0135] Specifically, the calculation unit 104 identifies the actual age of the user 20 from information relating to the age of the user 20 acquired by the acquisition unit 102. Using a table linking bone mass with age, the calculation unit 104 acquires the age corresponding to the estimated bone mass of the user 20 using a table of average bone mass by age based on the estimated bone mass of the user 20 from the biometric information 200 acquired by the acquisition unit 102, and sets this as the estimated age. Meanwhile, the calculation unit 104 causes the image processing device to perform age estimation processing using an image of the face of the user 20, and acquires the estimated age of the user 20.

[0136] Then, the calculation unit 104 compares the specified actual age with the estimated age based on bone mass, and if the estimated age is older than the actual age by a certain number of years (for example, five years older), the evaluation value indicating the health risk is set to a value indicating the risk of developing osteoporosis.Furthermore, the calculation unit 104 compares the specified actual age with the estimated age based on the facial image, and if the estimated age is older than the actual age by a certain number of years (for example, five years older), the evaluation value indicating the health risk is set to a value indicating the risk of developing dementia.

[0137] 14 is a diagram showing an example of the data structure of health risk information 220 according to this embodiment. Health risk information 220 includes an evaluation value indicating the risk of developing osteoporosis and an evaluation value indicating the risk of developing dementia, both calculated by calculation unit 104, linked to a user ID. The evaluation value indicating the risk of developing dementia for user 20 and the evaluation value indicating the risk of developing dementia for user 20 are linked to the user ID of user 20 and stored in storage device 120 as health risk information 220.

[0138] The identifying unit 106 identifies candidate tasks that the user 20 can take on from among the work using the evaluation value indicating the health risk. In the above embodiment, candidate tasks that user 20 can undertake are identified using an evaluation value of one type of health risk. In this embodiment, candidate tasks that user 20 can undertake are identified using evaluation values ​​that indicate two types of health risks. Examples of how to handle the evaluation values ​​that indicate these two types of health risks are shown below, but are not limited to these. (a1) The health risk assessment value is calculated by adding the assessment value of the risk of developing osteoporosis and the assessment value of the risk of developing dementia and dividing the result by 2. For example, in addition to simple addition, a method can be considered that focuses on the relationship between the risks of developing each disease and takes into account the correlation. When adding in (a2) and (a1), the evaluation value of each risk is multiplied by a coefficient to calculate the evaluation value of the health risk. The sum of the two coefficients is set to 1. Alternatively, for example, machine learning may be used to take into account the working environment conditions so that the evaluation value converges to 0 to 1. (a3) If either the evaluation value for the risk of developing osteoporosis or dementia indicates that there is a risk of developing the disease, that evaluation value is used. (a4) Identify the work load levels that can be determined using the assessed risk values ​​for osteoporosis and dementia.

[0139] The identification unit 106 then acquires the health risk assessment value of the identified user 20, and if the health risk assessment value meets the criteria, identifies the workload level that the user 20 can handle based on the health risk assessment value, extracts task items corresponding to the identified workload level from the task item list 230 of FIG. 8, and identifies them as candidate tasks that the user 20 can handle. Here, the criteria include the health risk assessment value indicating that a reduction in workload is necessary. The restriction of the workload level based on the health risk is the same as in the first embodiment, and therefore will not be described here.

[0140] However, in the case of (a4) above, there are two evaluation values ​​indicating health risks. Therefore, in the case of (a4), two types of task item lists 230 may be prepared: one for osteoporosis and one for dementia. The identification unit 106 may extract task items corresponding to the respective load levels corresponding to the two types of evaluation values ​​identified in (a4) from the corresponding task item lists 230.

[0141] <Example of operation> FIG. 15 is a flowchart showing an example of the operation of the employment support device 100 according to the embodiment. This flow is executed the first time that user 20 starts using the services of employment support system 1. The flow of Fig. 15 includes step S111, an osteoporosis onset risk estimation processing routine S120, and steps S131 to S135, which are the same as the flow of Fig. 9, and further includes dementia onset risk estimation processing routine S200 and step S145 of Fig. 13.

[0142] First, the acquisition unit 102 acquires the actual age information of the user 20 from the resume information 210 (step S111). Then, the calculation unit 104 executes a processing routine (S120) for estimating the risk of developing osteoporosis. This processing routine is the same as the processing described in the first embodiment. By this processing routine S120, the calculation unit 104 calculates an evaluation value of the risk of developing osteoporosis for the user 20. The calculated evaluation value of the risk of developing osteoporosis is stored in the storage device 120 as health risk information 220 (FIG. 14) in association with the user ID of the user 20.

[0143] Furthermore, in parallel with this processing routine S120, the calculation unit 104 executes a dementia onset risk estimation processing routine (S200). By this processing routine S200, the calculation unit 104 calculates an evaluation value of the dementia onset risk of the user 20. However, the processing routine S120 and the processing routine S200 do not have to be processed in parallel, and may be processed sequentially. The calculated evaluation value of the dementia onset risk is further linked to the user ID of the user 20 and stored in the storage device 120 as health risk information 220 (FIG. 14).

[0144] The identification unit 106 then refers to the health risk information 220 (FIG. 14) to determine whether or not there is a health risk for the user 20, and if there is a health risk (YES in step S131), identifies candidate tasks that the user 20 can undertake by limiting the candidate tasks to those corresponding to the assessment value of the health risk for the user 20 (step S133). For example, if the assessment value of at least one of the risk of developing osteoporosis and the risk of developing dementia indicates that there is a risk of developing the disease, the identification unit 106 may limit the workload level in the task item list 230 to 4 or less. In this case, tasks with a workload level of 4 or less are extracted from the task item list 230 as candidates.

[0145] If the evaluation values ​​for both the risk of developing osteoporosis and the risk of developing dementia indicate that there is no risk of developing the disease (NO in step S131), no restrictions are placed on the work items, and the identification unit 106 identifies all work items in the work item list 230 as candidates for work that the user 20 can handle (step S145).

[0146] The output processing unit 108 presents the tasks identified in step S133 or step S145 to the user 20 as candidate tasks that the user 20 can handle (step S135). For example, the output processing unit 108 displays a task candidate screen 300 of Fig. 10 on the display of the user terminal 30. On the task candidate screen 300 (Fig. 10), the user 20 can select a task item that the user 20 wishes to handle from among the assigned tasks.

[0147] As described above, according to this embodiment, the calculation unit 104 calculates an evaluation value indicating the risk of developing osteoporosis and an evaluation value indicating the risk of developing dementia, and the identification unit 106 uses these evaluation values ​​to identify candidate tasks that the user 20 can handle.

[0148] In this way, the employment support device 100 of this embodiment achieves the same effects as the above-mentioned embodiments, and in particular, can evaluate both the risk of developing osteoporosis and the risk of developing dementia, which are problems specific to elderly women, and can select tasks based on both evaluation values, thereby increasing the possibility of reducing the risk of developing both osteoporosis and dementia while supporting elderly women in their employment.

[0149] Furthermore, if we can reduce the risk of developing osteoporosis and dementia, it is expected that this will help solve problems such as the 2025 problem, which is the rising cost of medical care and nursing care due to an aging society.

[0150] (Fourth embodiment) FIG. 16 is a functional block diagram illustrating an example of the functional configuration of the employment support device 100 according to the embodiment. The employment support device 100 of this embodiment is similar to the first to third embodiments, except that it has a configuration for matching a user 20 with a support recipient 40. The employment support device 100 of this embodiment further has a matching unit 112 in addition to the configuration of the employment support device 100 in Fig. 5. However, the configuration of this embodiment may be combined with at least one of the configurations of the other embodiments to the extent that no contradiction occurs.

[0151] <Example of functional configuration> The work includes work related to the children 42 of the support recipients 40. Resume information 210 includes information regarding user's 20 parenting experience. The acquisition unit 102 acquires support recipient attribute information including attributes of the child 42 of the support recipient 40. The matching unit 112 generates combinations of users 20, support recipients 40, and children 42 using the resume information 210 and support recipient attribute information.

[0152] The resume information 210 includes whether the user 20 has experience raising children and the gender of the children. In addition, the resume information 210 may also include the family structure of the user 20 (amount of daily conversation).

[0153] Furthermore, the resume information 210 may include information about the "personality" of the child 42 of the user 20 as attribute information of the child 42. The personality of the child 42 may include sociability, introversion, picky eating, getting bored easily, etc. Specifically, the input screen for the resume information 210 may allow the support recipient 40 to selectively input a subjective evaluation of the child 42.

[0154] For example, the matching unit 112 pairs a user 20 who has experience raising a boy with a support recipient 40 who has a boy. The matching unit 112 pairs a user 20 who has a lot of daily conversation with a support recipient 40 who has a sociable child.

[0155] Since the support of the user 20 includes taking care of the child 42 of the support recipient 40, matching the attributes of the child 42 with the attributes of the user 20 increases the possibility of finding a good match between the child 42 and the user 20. If the combination is a good match, it becomes possible to continue the support.

[0156] The acquisition unit 102 further acquires environmental information relating to the environment in which the work is performed. The matching unit 112 generates a combination of the user 20 and the support recipient 40 by further using the environmental information and the evaluation value of the health risk of the user 20 .

[0157] The environmental information includes, for example, information indicating the load condition within the support activity area, including the travel section to the home of the support recipient 40 (for example, whether there are steps, whether there are slopes, whether there are elevators or escalators, etc.). Furthermore, the environmental information includes information indicating the barrier-free status of the home of the support recipient 40 (whether there are steps, whether there are stairs, whether there are handrails, etc.).

[0158] For example, the matching unit 112 may identify the travel route using the address listed in the resume information 210 of the user 20 and the address of the support recipient 40, and perform the matching process using the results of determining whether the user 20 is able to commute to the home of the support recipient 40.

[0159] For example, if the user 20 is at risk of developing osteoporosis (requires exercise support), the support recipient 40 who has a low burden indicated by the environmental information is paired with the user 20. For example, the matching unit 112 pairs the support recipient 40 whose travel route has no steps or slopes, has elevators or escalators, and whose home is barrier-free, with the user 20 who is at risk of developing osteoporosis (requires exercise support).

[0160] In this way, by taking the work environment into consideration, the user 20 can work safely, and the occurrence of accidents and injuries while the user 20 is working can also be reduced.

[0161] The acquisition unit 102 acquires a reward item list 250 that determines rewards for the work of the user 20. The matching unit 112 further uses the reward to generate a pair of the user 20 and the support recipient 40.

[0162] The work of user 20 includes mutual aid activities. The support recipient 40 can reduce or offset the compensation to user 20 by adopting a system that provides non-monetary compensation to user 20. As described above, the support recipient 40 is often a single mother or the like who is struggling financially, so it is preferable that the compensation to user 20 does not involve the exchange of money.

[0163] 17 is a diagram showing an example of the data structure of the reward item list 250. As shown in the reward item list 250, the support recipient 40 provides the user 20 with anything that helps the user 20, makes the user 20 happy, or is beneficial to the user 20 as a reward.

[0164] The reward item list 250 may be, for example, proposed by the user 20 to the support recipient 40 and selected by the support recipient 40, or proposed by the support recipient 40 to the user 20 and selected by the user 20, or both. The reward item list 250 may be selected from predetermined items, or may be freely proposed by the user 20 or the support recipient 40, or may be a combination of both.

[0165] Furthermore, the resume information 210 of the user 20 may include consideration items such as medical history and hospital visit status. Matching may be performed based on whether the reward item list 250 includes a reward corresponding to the consideration item. For example, a reward such as accompanying a user 20 to a hospital visit may be matched to a user 20 who needs to visit a hospital.

[0166] The reward item list 250 may also be exchanged when the user 20 and the support recipient 40 reach an agreement on whether or not to receive support. In other words, the reward item list 250 may be presented to the user 20 and the support recipient 40 matched by the matching unit 112, and the reward may be decided and an agreement may be reached.

[0167] In this way, by providing compensation other than money, even single mothers in financially difficult situations can continue to receive support. In other words, it is possible to encourage continued use by support recipients40.

[0168] The matching unit 112 may also detect the amount of conversation and identify compatibility by performing audio processing on a video of the user 20 and the child 42 when they are together. The matching unit 112 may also perform image processing on a video of the user 20 and the child 42 when they are together, performing facial expression analysis and behavior analysis, and identifying compatibility.

[0169] For example, the matching unit 112 may acquire the proportion of time spent with a blank expression or silence, the frequency and degree of smiling, the presence and frequency of actions such as nodding and the like, the speed of conversation, and the amount of change in intonation to determine compatibility. Alternatively, the matching unit 112 may determine compatibility by determining whether the conversation of the user 20 is easy for the child 42 to understand, whether the child 42 speaks slowly and clearly, and whether easy-to-understand words are used.

[0170] The matching unit 112 pairs the user 20 and the child 42 (support recipient 40) who are determined to be compatible. By matching them together, there is a high possibility that continued use can be promoted.

[0171] <Example of operation> FIG. 18 is a flowchart showing an example of the operation of the employment support device 100 according to the embodiment. First, the acquisition unit 102 acquires the resume information 210 including information about the child-rearing experience of the user 20 (step S401). Furthermore, the acquisition unit 102 acquires support recipient attribute information indicating the attributes of the child 42 (step S403).

[0172] The matching unit 112 uses the resume information 210 and the support recipient attribute information to generate combinations of the user 20, the support recipient 40, and the child 42 (step S405). For example, a user 20 who has experience raising a boy is paired with a support recipient 40 who has a boy.

[0173] As described above, according to this embodiment, the employment support device 100 has a matching unit 112. The acquisition unit 102 acquires support recipient attribute information indicating the attributes of the child 42. The matching unit 112 uses the resume information 210 and the support recipient attribute information to generate combinations of the user 20, the support recipient 40, and the child 42.

[0174] In this way, the employment support device 100 of this embodiment not only achieves the same effects as the above-described embodiment, but also increases the possibility of finding a compatible pairing between the child 42 and the user 20, and if the pairing is compatible, it becomes possible to continue providing support. By promoting the continued use of support, it becomes possible to increase the possibility of the support recipient 40 switching from non-regular employment such as part-time to full-time employment, and to encourage the support recipient 40 to become economically independent.

[0175] (Fifth embodiment) This embodiment is similar to any of the above embodiments, except that it has a configuration in which the health risk of the user 20 is periodically monitored and, if any changes are detected, the support work is reviewed. The employment support device 100 of this embodiment has the same configuration as the employment support device 100 of FIG. 5, and will be described using FIG. 5. Note that the configuration of this embodiment may be combined with at least one of the configurations of the other embodiments to the extent that no contradiction occurs.

[0176] <Example of functional configuration> The acquisition unit 102 periodically acquires biometric information 200 and resume information 210. When the acquisition unit 102 acquires the information, the calculation unit 104 calculates the health risk of the user 20 . When a change in the health risk is detected, the identifying unit 106 updates the candidates for the work that the user 20 can take on.

[0177] <Example of operation> FIG. 19 is a flowchart showing an example of the operation of the employment support device 100 according to the embodiment. First, health risk monitoring is performed periodically (step S501). Specifically, the acquisition unit 102 periodically acquires the biometric information 200 and resume information 210 of the user 20, and the calculation unit 104 calculates the health risk of the user 20 when the acquisition unit 102 acquires the information.

[0178] The identification unit 106 then determines whether there is a change between the calculated health risk and the past health risk of the user 20 (step S503). If there is a change (YES in step S503), the identification unit 106 updates candidates for tasks that the user 20 can handle (step S505). Specifically, the identification unit 106 executes the process of at least one of the flowcharts in Figures 9, 13, and 15 of the above embodiment. If there is no change in the health risk (NO in step S503), step S505 is bypassed and the process ends.

[0179] In the process of determining a change in health risk in step S503, when determining whether a sudden change has occurred, it is determined whether the amount of change calculated by comparing only the previous health risk exceeds a certain value. On the other hand, when determining whether a gradual change has occurred, it may be determined whether the changes in multiple amounts of health risk over a certain period of time are on a decreasing or increasing trend.

[0180] Furthermore, since the amount of exercise may decrease with age, a learning engine may be generated to simulate changes in health risks with the age of the user 20 and used in the above determination. This may enable a determination in advance that the probability that the user 20 will be unable to provide sufficient support to the support recipient 40 increases as the user 20 ages, thereby reducing the lead time for finding a replacement supporter for the user 20. Meanwhile, taking into account the health condition of the user 20, which changes with age, it may be possible to match the user 20 with another support recipient 40 with a lighter workload (for example, fewer children 42, older, or female) and assign the work to that support recipient 40 based on the determination result.

[0181] Furthermore, when it is determined in step S503 that there is a change in health risk (YES in step S503), the identification unit 106 may use the task item list 230, including the help information 260, to identify candidate tasks that the user 20 can handle, and the output processing unit 108 may display the candidate tasks including the help information 260 on the display of the user terminal 30 of the user 20.

[0182] FIG. 20 is a diagram showing an example of the data structure of the help information 260. The help information 260 further associates each task in the task item list 230 of FIG. 8 with a child's help and the amount of reduction in workload level due to that help.

[0183] The help information 260 allows the support recipient 40 to specify in advance which help they can provide using the support recipient terminal 50. Then, the user 20 can select a task after checking the help actions from the candidate tasks.

[0184] As described above, according to this embodiment, the health risk of the user 20 is monitored periodically, and if there is a change, the assistance work is reviewed. In this way, the employment support device 100 of this embodiment not only achieves the same effects as the above-described embodiment, but also makes it possible to provide work with an appropriate load that matches changes in the health risks of the user 20 due to aging.

[0185] Furthermore, having the child 42 help with the work can reduce the workload of the user 20. For the child 42, helping out can be a form of discipline, and for the user 20, it has the advantage of helping them cope with the decline in physical strength that comes with aging, and mutual assistance activities between the supporter and the supported can be smoothly realized.

[0186] Although the embodiments of the present invention have been described above with reference to the drawings, these are merely examples of the present invention, and various other configurations can also be adopted. <Calculating the risk of developing dementia> For example, in the above embodiment, the risk of developing dementia is calculated based on the discrepancy between the estimated age of appearance using a facial image of the user 20 and the actual age of the user 20. In other embodiments, information indicating the frequency of communication in the user 20's daily life, the number of people with whom they communicate, and the relationships between the people with whom they communicate (for example, whether they are relatives or other people, and the size of their personal network) can be acquired, and the risk of developing dementia can be calculated by machine learning or deep learning.

[0187] <Facial expression analysis and behavior analysis> The biometric information 200 includes a facial image of the user 20 . The acquisition unit 102 acquires a video captured during an online interview with the user 20. The calculation unit 104 performs at least one of facial expression analysis and behavior analysis of the user 20 using the video, and calculates an evaluation value indicating the health risk of the user 20.

[0188] For example, facial expression analysis Yu The richness of the facial expressions of user 20 (such as the number of times the user smiles) may be acquired, and an evaluation value of the risk of dementia onset of user 20 may be calculated.

[0189] According to this configuration, the accuracy of the evaluation value of the risk of developing dementia of user 20 can be further improved.

[0190] <Risk of developing arteriosclerosis> In the above embodiment, a configuration for calculating the risk of developing dementia from a face image has been described in detail. In other embodiments, a configuration for calculating the risk of developing arteriosclerosis from a face image may also be considered. For example, the calculation unit 104 estimates the vascular age by performing image processing on the face image. The calculation unit 104 then calculates an evaluation value indicating a health risk based on the actual age and the estimated vascular age obtained from the resume information 210. More specifically, the specified actual age is compared with the estimated age, and if the actual age exceeds the estimated age, the evaluation value indicating the health risk is set to a value indicating a risk of developing arteriosclerosis. Note that if the actual age exceeds the estimated age by a certain number of years or more, the evaluation value indicating the health risk may also be set to a value indicating a risk of developing arteriosclerosis. In this way, the calculation unit 104 can estimate health risks such as arteriosclerosis that may occur due to vascular aging based on the face image and the resume information 210.

[0191] The workload levels set in the task item list 230 may be set based on METs (Metabolic equivalents), which indicate exercise intensity. Multiple workload levels may be set for a single task. For example, a workload level set based on calories burned and a workload level set based on exercise intensity may be linked to a specific task and managed.

[0192] The identification unit 106 may change the workload level to be referenced depending on the assessment value indicating the health risk when identifying candidate tasks that the user 20 can undertake from among the task items in the task item list 230. For example, if the assessment value indicating the health risk is a value indicating the risk of developing arteriosclerosis, the identification unit 106 may identify candidate tasks that the user can undertake based on a workload level set based on METs, which indicate exercise intensity.

[0193] When changing the workload level to be referenced according to the assessment value indicating the health risk, the number of workload levels to be referenced may be increased or decreased. Furthermore, the reference may be limited to only specific items. In this way, the identifying unit 106 can identify task items that are suitable for the assessment value of the health risk of user 20 as candidate tasks to be presented to the user.

[0194] In addition, although the flowcharts used in the above description describe multiple steps (processes) in a sequential order, the execution order of the steps in each embodiment is not limited to the order described. In each embodiment, the order of the steps shown in the drawings can be changed to the extent that the content is not affected. Furthermore, at least one step may be performed by another operating entity, such as another device or person. Furthermore, the above-described embodiments can be combined to the extent that the content is not contradictory.

[0195] Although the present invention has been described above with reference to the embodiments, the present invention is not limited to the above embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention. In the present invention, when information about users (users 20, support recipients 40, and children 42) is acquired and used, it is assumed that this is done lawfully.

[0196] Some or all of the above-described embodiments can be described as, but are not limited to, the following supplementary notes. 1. An acquisition means for acquiring biometric information of a user and resume information of the user; a calculation means for calculating an evaluation value indicating a health risk of the user using the acquired biometric information and resume information; and a specifying means for specifying candidate tasks to be presented to the user using the evaluation value indicating the health risk. 2. In the employment support device described in 1., The biometric information includes health information indicating the health condition of the user. 3. In the employment support device described in 2., The health information includes information on bone mass. 4. In the employment support device described in 3., The employment support device, wherein the evaluation value indicating the health risk includes an evaluation value indicating the risk of developing osteoporosis. 5. In the employment support device described in 4., The calculation means is an employment support device that calculates an evaluation value indicating the risk of developing osteoporosis using the user's age estimated using the information on bone mass and the user's age included in the resume information. 6. In the employment support device according to any one of 1. to 5., the biometric information includes a facial image of the user; The calculation means calculates an evaluation value indicating the health risk based on the age estimated from the facial image and the age of the user included in the resume information. 7. In the employment support device according to any one of 1. to 6., The identification means identifies the user's tolerable load range based on the evaluation value indicating the health risk, and identifies candidate tasks to be presented to the user based on load information defined for each task. 8. In the employment support device according to any one of 1. to 7., The work includes supporting the support recipient and mutual aid activities. 9. In the employment support device described in 8., the acquisition means acquires target person attribute information indicating attributes of the support target person, further comprising a generating means for generating a task item list based on the target person attribute information; The identification means identifies candidate tasks to be presented to the user from among the tasks included in the task item list. 10. In the employment support device according to 8. or 9., The work includes work related to the child of the support recipient, the resume information includes information regarding the user's parenting experience; the acquisition means acquires support recipient attribute information including attributes of the child of the support recipient; The employment support device further comprises a matching means for generating a combination of the user and the support recipient using the resume information and the support recipient attribute information. 11. In the employment support device described in 10., the acquisition means acquires the reward selected by the user from a reward item list that defines rewards for the user's work; The matching means further uses the selected reward to generate a combination of the user and the support recipient. 12. The employment support device according to 10. or 11. The acquisition means further acquires environmental information relating to an environment in which the work is performed, The matching means generates a pair of the user and the support recipient by further using the environmental information and the evaluation value of the health risk of the user. 13. In the employment support device according to any one of 1. to 12., the biometric information includes a facial image of the user; The acquisition means acquires a video captured during an online interview with the user, The calculation means uses the video to perform at least one of facial expression analysis and behavior analysis of the user, and calculates an evaluation value indicating the health risk of the user.

[0197] 14. One or more computers Acquire the user's biometric information and the user's resume information; calculating an evaluation value indicating a health risk of the user using the acquired biometric information and resume information; An employment support method that uses the evaluation value indicating the health risk to identify candidate tasks to be presented to the user. 15. In the employment support method described in 14., The employment support method, wherein the biometric information includes health information indicating the health condition of the user. 16. In the employment support method described in 15., The employment support method, wherein the health information includes information on bone mass. 17. In the employment support method described in 16., An employment support method, wherein the evaluation value indicating the health risk includes an evaluation value indicating the risk of developing osteoporosis. 18. In the employment support method described in 17., One or more computers An employment support method that calculates an evaluation value indicating the risk of developing osteoporosis using the user's age estimated using the information on bone mass and the user's age included in the resume information. 19. In the employment support method described in any one of 14. to 18., the biometric information includes a facial image of the user; One or more computers An employment support method that calculates an evaluation value indicating the health risk based on the age estimated from the facial image and the age of the user included in the resume information. 20. In the employment support method described in any one of 14. to 19., One or more computers An employment support method that identifies the user's tolerable load range based on an evaluation value indicating the health risk, and identifies candidate tasks to be presented to the user based on load information defined for each task. 21. In the employment support method described in any one of 14. to 20., The employment support method includes supporting the support recipient and mutual aid activities. 22. In the employment support method described in 21., One or more computers Acquire target person attribute information indicating the attributes of the support target person; generating a work item list based on the target person attribute information; A work support method for identifying candidate tasks to be presented to the user from among the tasks included in the task item list. 23. In the employment support method described in 21. or 22., The work includes work related to the child of the support recipient, the resume information includes information regarding the user's parenting experience; One or more computers Acquire support recipient attribute information including attributes of the child of the support recipient; A method for employment support, which generates a combination of the user and the support recipient using the resume information and the support recipient attribute information. 24. In the employment support method described in 23., One or more computers obtain the reward selected by the user from a reward item list that defines rewards for the user's work; The employment support method further uses the selected reward to generate a combination of the user and the support recipient. 25. In the employment support method described in 23. or 24., One or more computers Furthermore, environmental information regarding the environment in which the work is performed is acquired; The employment support method further uses the environmental information and the evaluation value of the health risk of the user to generate a combination of the user and the support recipient. 26. In the employment support method described in any one of 14. to 25., the biometric information includes a facial image of the user; One or more computers Acquire a video taken during an online interview with the user; An employment support method that uses the video to perform at least one of facial expression analysis and behavior analysis of the user and calculates an evaluation value indicating the health risk of the user.

[0198] 27. To the computer, A procedure for acquiring biometric information of a user and resume information of the user; a step of calculating an evaluation value indicating a health risk of the user using the acquired biometric information and resume information; A program for executing a procedure for identifying candidate tasks to be presented to the user using the evaluation value indicating the health risk. 28. In the program described in 27., The biometric information includes health information indicating the health condition of the user. 29. In the program described in 28., The health information includes information about bone mass. 30. In the program described in 29., The evaluation value indicating the health risk includes an evaluation value indicating the risk of developing osteoporosis. 31. In the program described in 30., In the calculation step, the program calculates an evaluation value indicating the risk of developing osteoporosis using the user's age estimated using the information on bone mass and the user's age included in the resume information. 32. In the program according to any one of 27. to 31., the biometric information includes a facial image of the user; In the calculating step, the program calculates an evaluation value indicating the health risk based on the age estimated from the face image and the age of the user included in the resume information. 33. In the program according to any one of 27. to 32., In the identification procedure, the program identifies the user's tolerable load range based on the evaluation value indicating the health risk, and identifies candidate tasks to be presented to the user based on load information defined for each task. 34. In the program according to any one of 27. to 33., The program, wherein the work includes providing support to recipients and mutual aid activities. 35. In the program described in 34., In the step of acquiring, target person attribute information indicating attributes of the support target is acquired; causing a computer to execute a procedure for generating a task item list based on the target person attribute information; In the step of specifying, a program specifies candidate tasks to be presented to the user from among the tasks included in the task item list. 36. In the program described in 34. or 35., The work includes work related to the child of the support recipient, the resume information includes information regarding the user's parenting experience; In the step of acquiring, support recipient attribute information including attributes of the child of the support recipient is acquired; A program for causing a computer to execute a procedure for generating a combination of the user and the support recipient using the resume information and the support recipient attribute information. 37. In the program described in 36., In the step of acquiring, the reward selected by the user is acquired from a reward item list that defines rewards for the work of the user; The program further uses the selected reward in the step of generating the combination to generate a combination of the user and the support recipient. 38. In the program described in 36. or 37., In the step of acquiring, environmental information relating to an environment in which the work is performed is further acquired; The program further uses the environmental information and the evaluation value of the health risk of the user to generate a combination of the user and the support recipient in the step of generating the combination. 39. In the program according to any one of 27. to 38., the biometric information includes a facial image of the user; In the step of acquiring, a video captured during an online interview with the user is acquired; In the calculation step, the program performs at least one of facial expression analysis and behavior analysis of the user using the video, and calculates an evaluation value indicating the health risk of the user.

[0199] 40. To the computer, A procedure for acquiring biometric information of a user and resume information of the user; a step of calculating an evaluation value indicating a health risk of the user using the acquired biometric information and resume information; A computer-readable recording medium storing a program for executing a procedure for identifying candidate tasks to be presented to the user using the evaluation value indicating the health risk. 41. The recording medium according to 40., A computer-readable recording medium storing a program, wherein the biometric information includes health information indicating the health condition of the user. 42. The recording medium according to 41, A computer-readable recording medium storing a program, wherein the health information includes information about bone mass. 43. The recording medium according to 42., A computer-readable recording medium storing a program, wherein the evaluation value indicating the health risk includes an evaluation value indicating the risk of developing osteoporosis. 44. The recording medium according to 43., A computer-readable recording medium storing a program that, in the calculation procedure, calculates an evaluation value indicating the risk of developing osteoporosis using the user's age estimated using information regarding the bone mass and the user's age included in the resume information. 45. The recording medium according to any one of items 40 to 44, the biometric information includes a facial image of the user; A computer-readable recording medium storing a program that, in the calculation procedure, calculates an evaluation value indicating the health risk based on the age estimated from the facial image and the age of the user included in the resume information. 46. ​​The recording medium according to any one of items 40 to 45, A computer-readable recording medium storing a program that, in the identification procedure, identifies the user's tolerable load range based on the evaluation value indicating the health risk, and identifies candidate tasks to be presented to the user based on load information defined for each task. 47. From 40. 4 6. The recording medium according to any one of claims 1 to 5, The work includes supporting support recipients and mutual aid activities. A computer-readable recording medium storing a program. 48. In the recording medium according to 47, In the step of acquiring, target person attribute information indicating attributes of the support target is acquired; causing a computer to execute a procedure for generating a task item list based on the target person attribute information; a computer-readable recording medium storing a program for identifying candidate tasks to be presented to the user from among tasks included in the task item list in the identifying procedure; 49. In the recording medium according to 47. or 48., The work includes work related to the child of the support recipient, the resume information includes information regarding the user's parenting experience; In the step of acquiring, support recipient attribute information including attributes of the child of the support recipient is acquired; A computer-readable recording medium storing a program for causing a computer to execute a procedure for generating a combination of the user and the support recipient using the resume information and the support recipient attribute information. 50. In the recording medium described in 49., In the step of acquiring, the reward selected by the user is acquired from a reward item list that defines rewards for the work of the user; A computer-readable recording medium storing a program for generating a combination of the user and the support recipient by further using the selected reward in the step of generating the combination. 51. In the recording medium according to 49. or 50., In the step of acquiring, environmental information relating to an environment in which the work is performed is further acquired; A computer-readable recording medium storing a program, in which, in the step of generating the combination, a combination of the user and the support recipient is generated by further using the environmental information and the evaluation value of the health risk of the user. 52. The recording medium according to any one of items 40 to 51, the biometric information includes a facial image of the user; In the step of acquiring, a video captured during an online interview with the user is acquired; A computer-readable recording medium storing a program in which, in the calculation procedure, the video is used to perform at least one of facial expression analysis and behavior analysis of the user, and an evaluation value indicating the health risk of the user is calculated. [Explanation of symbols]

[0200] 1. Employment support system 3. Communication Network 20 users 30 User terminals 32 Wearable devices 40 Support recipients 50 Support recipient terminals 100 Employment support device 102 Acquisition Department 104 Calculation Unit 106 Specific section 108 Output Processing Unit 112 Matching Section 120 Storage device 200 Biometric Information 210 Resume Information 220 Health Risk Information 230 Work Item List 232 Work Item List 250 Reward Item List 260 Help Information 300 Work candidate screen 302 Checkbox 1000 computers 1010 Bus 1020 processor 1030 memory 1040 Storage Device 1050 Input / Output Interface 1060 Network Interface

Claims

1. An acquisition means for acquiring biometric information of a user and resume information including the age of the user; a calculation means for calculating an evaluation value indicating a health risk of the user based on a difference between an age estimated from the acquired biometric information and an age identified from the resume information; and a specifying means for specifying candidate tasks to be presented to the user using the evaluation value indicating the health risk.

2. The employment support device according to claim 1, the acquiring means acquires the biometric information including a facial image of the user; The calculation means is an employment support device that calculates an evaluation value indicating the user's health risk, which indicates that there is a risk of developing dementia, based on the difference between the age estimated from the acquired facial image and the user's age included in the resume information.

3. In the employment support device according to claim 1 or 2, the acquiring means acquires the biometric information including a facial image of the user; The calculation means is an employment support device that calculates an evaluation value indicating the user's health risk, which indicates that the user is at risk of developing arteriosclerosis, based on the difference between the vascular age estimated from the acquired facial image and the user's age included in the resume information.

4. In the employment support device according to any one of claims 1 to 3, the acquiring means acquires the biometric information including information about the user's bone mass; The calculation means calculates an evaluation value indicating the user's health risk, which indicates that the user is at risk of developing osteoporosis, based on the difference between the age estimated from the acquired bone mass and the user's age included in the resume information.

5. The employment support device according to any one of claims 1 to 4, The identification means identifies the user's tolerable load range based on the evaluation value indicating the health risk, and identifies candidate tasks to be presented to the user based on load information defined for each task.

6. The employment support device according to any one of claims 1 to 5, The work includes supporting the support recipient and mutual aid activities.

7. 7. The employment support device according to claim 6, the acquisition means acquires target person attribute information indicating attributes of the support target person, further comprising a generating means for generating a task item list based on the target person attribute information; The identification means identifies candidate tasks to be presented to the user from among the tasks included in the task item list.

8. 8. The employment support device according to claim 6 or 7, The work includes work related to the child of the support recipient, the resume information includes information regarding the user's parenting experience; the acquisition means acquires support recipient attribute information including attributes of the child of the support recipient; The employment support device further comprises a matching means for generating a combination of the user and the support recipient using the resume information and the support recipient attribute information.

9. One or more computers Acquire biometric information of a user and resume information including the user's age; calculating an evaluation value indicating a health risk of the user based on a difference between an age estimated from the acquired biometric information and an age identified from the resume information; An employment support method that uses the evaluation value indicating the health risk to identify candidate tasks to be presented to the user.

10. On the computer, A procedure for acquiring biometric information of a user and resume information including the user's age; calculating an evaluation value indicating a health risk of the user based on a difference between an age estimated from the acquired biometric information and an age identified from the resume information; A program for executing a procedure for identifying candidate tasks to be presented to the user using the evaluation value indicating the health risk.

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