Non-face-to-face training management system, control method therefor, and program

Abstract

A non-face-to-face training management system that is communicatively connected to an instructor terminal and a trainee terminal via a network comprises: an instruction reception unit that receives, via the instructor terminal, an instruction for training to be performed by the user of the trainee terminal; a provision unit that provides one or more training contents to the trainee terminal on the basis of the instruction; a collection unit that collects, via the trainee terminal, training result data indicating a training operation of the user of the trainee terminal during a period in which the one or more training contents are being provided; and a storage unit that records the training result data in association with the configuration of the one or more training contents.

Description

Non-face-to-face training management system, its control method, and program

[0001] The present invention relates to a non-face-to-face training management system, a control method thereof, and a program.

[0002] Traditionally, for the purposes of medical care, health maintenance, skill acquisition, etc., training and support such as prescribed exercises, rehabilitation, and skill acquisition have been provided to trainers (hereinafter referred to as "trainers") under the direction of medical professionals or supervisors (hereinafter collectively referred to as "instructors"). With the recent development of communication and mobile technologies, there has been an increase in services that can provide such support remotely or without face-to-face contact.

[0003] By providing non-face-to-face training support, it is now possible to reduce the travel burden on instructors and trainers and to conserve resources required for support. For example, inpatient rehabilitation tends to be expensive, but enabling non-face-to-face rehabilitation can reduce the costs associated with hospitalization (such as securing space and traveling for trainers). Furthermore, home-visit rehabilitation tends to limit the opportunities and frequency of support due to the instructor's limited resources. However, enabling non-face-to-face rehabilitation can alleviate the limitations on the opportunities and frequency of support. Home-visit and inpatient rehabilitation also tend to impose a high financial burden on trainers, but enabling non-face-to-face rehabilitation can reduce the financial burden and further enable continuous rehabilitation.

[0004] From the above perspectives, there is a desire to further improve the convenience of non-face-to-face training support. For example, in training support, it is important to properly manage the evaluation of training, whether it was implemented, and the implementation records from the perspective of the trainee's medical care and health maintenance. In addition, training implementation records can serve as the basis for calculating medical expenses and nursing care costs for medical professionals, so they must be properly recorded and managed.

[0005] For example, Patent Document 1 describes a support system for performing remote cardiac rehabilitation, which controls the load on a load device operated by the rehabilitation practitioner while collecting and managing the practitioner's status information during operation.

[0006] Japanese Patent Application Laid-Open No. 2023-095536

[0007] There is a demand for further improvements in the convenience of non-face-to-face training support services, including support performance management, performance evaluation, appropriate support provision, and reduction of the support work burden in the non-face-to-face training support described above.

[0008] In view of the above problems, the present invention aims to improve the convenience of conducting non-face-to-face training.

[0009] In order to solve the above problems, one aspect of the present invention has the following configuration: A non-face-to-face training management system communicatively connected to an instructor terminal and a trainee terminal via a network, comprising: an instruction receiving unit that receives, via the instructor terminal, instructions for training to be performed by a user of the trainee terminal; a providing unit that provides one or more training contents to the trainee terminal based on the instructions; a collecting unit that collects training performance data that indicates training actions of the user of the trainee terminal when the one or more training contents are being provided via the trainer terminal; and a storage unit that records the training performance data in association with the configuration of the one or more training contents.

[0010] Another aspect of the present invention has the following configuration: A control method for a non-face-to-face training management system communicatively connected to an instructor terminal and a trainee terminal via a network, comprising: an instruction receiving step of receiving, via the instructor terminal, instructions for training to be performed by a user of the trainee terminal; a providing step of providing, based on the instructions, one or more training contents to the trainee terminal; a collecting step of collecting, via the trainer terminal, training performance data indicating training actions of the user of the trainee terminal when the one or more training contents are being provided; and a storing step of recording the training performance data in a storage unit in association with the configuration of the one or more training contents.

[0011] Another aspect of the present invention has the following configuration: That is, a program causing a computer communicatively connected to an instructor terminal and a trainee terminal via a network to execute the following steps: an instruction receiving step of receiving, via the instructor terminal, instructions for training to be performed by a user of the trainee terminal; a providing step of providing, based on the instructions, one or more training contents to the trainee terminal; a collecting step of collecting, via the trainer terminal, training performance data indicating training actions of the user of the trainee terminal when the one or more training contents are being provided; and a storing step of recording the training performance data in a storage unit in association with the configuration of the one or more training contents.

[0012] According to the present invention, it is possible to improve the convenience of conducting non-face-to-face training.

[0013] FIG. 1 is a block diagram showing an example of the configuration of a non-face-to-face training management system according to a first embodiment of the present invention; FIG. 2 is a functional block diagram showing a non-face-to-face training management server according to a first embodiment of the present invention; FIG. 3 is a functional block diagram showing an instructor terminal according to a first embodiment of the present invention; FIG. 4 is a functional block diagram showing a trainer terminal according to a first embodiment of the present invention; FIG. 5 is a processing sequence of the entire system according to a first embodiment of the present invention; FIG. 6 is a table diagram showing an example of the database configuration of training events according to a first embodiment of the present invention; FIG. 7 is a table diagram showing an example of the database configuration of training results according to a first embodiment of the present invention; FIG. 8 is a table diagram showing an example of the database configuration of training results according to a first embodiment of the present invention;

[0014] Hereinafter, embodiments of the present invention will be described with reference to the drawings. Note that the embodiment described below is one embodiment for explaining the present invention and is not intended to be interpreted as limiting the present invention. Furthermore, not all configurations described in each embodiment are necessarily essential configurations for solving the problems of the present invention. Furthermore, in each drawing, the same components are assigned the same reference numerals to indicate their correspondence. Note that to avoid unnecessary redundancy and to facilitate understanding by those skilled in the art, some of the description may be omitted or simplified. For example, detailed descriptions of already well-known matters or redundant descriptions of substantially identical configurations may be omitted.

[0015] In the following description, one embodiment of the present invention will be described assuming a situation in which a trainee performs rehabilitation or other training remotely under the direction of a doctor or other instructor. Note that some or all of the functions and components of the embodiments described below are not limited to application to remote medical training, but may be applied to various fields and services. Furthermore, the present invention may be modified, adjusted, expanded, or the like as appropriate depending on the field or service to which it is applied.

[0016] In the following description, "non-face-to-face training" generally includes training conducted when the instructor and trainer are located in different locations, either spatially or temporally. In other words, non-face-to-face training can be conducted when the instructor and trainer do not meet face-to-face or asynchronously. Furthermore, "training" may include medical training and non-medical training. Medical training refers to training whose purpose is medical. Medical training may include, for example, treatment, rehabilitation, and other health-related procedures. Examples of medical training include physical therapy training, occupational therapy training, and speech-language-hearing training. Non-medical training refers to training whose purpose is non-medical (e.g., beauty, language learning, sports, playing a musical instrument, operating equipment, or acquiring other skills).

[0017] An "instructor" refers to a person whose role is to instruct training. Examples of instructors include medical professionals, practitioners (therapists, estheticians, etc.), and lecturers (trainers, instructors, etc.). Medical professionals include physical therapists, occupational therapists, speech-language-hearing therapists, chiropractors, doctors, and nurses. A "trainer" refers to a person who performs training in accordance with the instructed training content. Examples of trainers include patients, recipients of treatment, and students. Note that the subjects included in the above terms are not limited to the above and may be adjusted appropriately depending on the content of the training.

[0018] <First embodiment> [System configuration] Fig. 1 is a schematic diagram showing an example of the configuration of a non-face-to-face training management system (information processing system) according to a first embodiment of the present invention. The non-face-to-face training management system 1 is a system whose main function is to support non-face-to-face training by a trainee under the instructions of, for example, an instructor. The non-face-to-face training management system 1 enables the provision, recording, management, and sharing of data indicating the content of the training to be performed by the trainee (hereinafter also referred to as "training data") and data serving as evidence (facts) of the training that has been performed (hereinafter also referred to as "training performance data").

[0019] Here, the following description will be given taking as examples of institutions that use this system a medical institution (such as a hospital) where an instructor doctor works and a home where a trainer user trains. However, the present invention is not limited to this, and can be applied to any environment where non-face-to-face training, which will be described later, is carried out. The non-face-to-face training management system 1 is configured to include a non-face-to-face training management server 100, an instructor terminal 200, and a trainee terminal 300. The devices that make up the non-face-to-face training management system 1 are configured to be able to communicate via a network NW.

[0020] The non-face-to-face training management server 100 is a device for providing various functions provided by the non-face-to-face training management system 1 to the instructor terminal 200 and the trainee terminal 300. The non-face-to-face training management server 100 provides applications for non-face-to-face training support to the instructor terminal 200 and the trainee terminal 300, and also collects and manages various information via each terminal. Note that some or all of the functions described below may be provided by the instructor terminal 200 or the trainee terminal 300. The non-face-to-face training management server 100 may be configured on-premise using a general-purpose computer such as a workstation or personal computer, or may be logically implemented by cloud computing. In this embodiment, for convenience of explanation, one non-face-to-face training management server 100 is illustrated as an example, but the present invention is not limited to this. Multiple non-face-to-face training management servers 100 may be used, and servers with different roles, such as an authentication server and a database server, may also be included.

[0021] The instructor terminal 200 is an operation terminal used by an instructor, such as a doctor, to instruct the content of non-face-to-face training. The instructor terminal 200 may be configured, for example, as an information processing device such as a personal computer, tablet terminal, smartphone, or POS terminal. The instructor terminal 200 provides users with web services provided by the non-face-to-face training management server 100 and the functions of applications installed and running on the instructor terminal 200. While the example of FIG. 1 shows one instructor terminal 200, more instructor terminals 200 may be used. The configurations of the multiple instructor terminals 200 may be different or the same. Furthermore, the available functions may differ depending on the role and authority of the instructor using the instructor terminal 200. The instructor terminal 200 may be installed, for example, in a medical institution (such as a hospital) where the instructor doctor works.

[0022] The trainer terminal 300 is an operation terminal used by a trainee who conducts non-face-to-face training. The trainer terminal 300 may be configured, for example, as an information processing device such as a personal computer, tablet terminal, smartphone, POS terminal, or dedicated terminal. The trainer terminal 300 provides the user with web services provided by the non-face-to-face training management server 100 and the functions of applications installed and running on the trainer terminal 300. While the example of FIG. 1 shows one trainer terminal 300, more trainer terminals 300 may be used. The configurations of the multiple trainer terminals 300 may be different or the same depending on the content of the non-face-to-face training to be conducted. The instructor terminal 200 may be installed, for example, in the trainee's home, which serves as the training location.

[0023] Although not shown in Figure 1, more devices may be communicatively connected via the network NW. For example, the non-face-to-face training management server 100 may cooperate with an external system (not shown) to collect and register video data and audio data created as training content, which will be described later.

[0024] The network NW is configured by the Internet, an intranet, a wireless LAN (Local Area Network), a WAN (Wide Area Network), etc. Note that the communication standards and wired / wireless communication standards related to the network NW are not particularly limited, and the network NW may be configured by combining multiple communication standards.

[0025] 2 is a block diagram showing an example of the functional configuration of the non-face-to-face training management server 100 according to this embodiment. The non-face-to-face training management server 100 includes a control unit 110, a storage unit 130, and a communication unit 140. Each unit is configured to be able to communicate with each other via an internal bus or the like.

[0026] The control unit 110 controls the operation of the non-face-to-face training management server 100. The control unit 110 is composed of, for example, a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), an NPU (Neural Network Processing Unit), etc., and provides various functions by reading and executing various programs and data stored in the memory unit 130. The control unit 110 functions as, for example, a data management unit 111, a data collection unit 112, a display control unit 113, a training data setting unit 114, a performance data extraction unit 115, a training performance evaluation unit 116, a data analysis unit 117, a feedback generation unit 118, a training menu determination unit 119, a training menu adjustment unit 120, an auxiliary device control unit 121, a learning processing unit 122, and a communication control unit 123.

[0027] The data management unit 111 manages the recording, referencing, updating, etc. of data in various databases (hereinafter referred to as "DBs") configured in the storage unit 130. Examples of data managed in each DB will be described later.

[0028] The data collection unit 112 collects data from various DBs configured in the storage unit 130 based on user instructions, etc. The data collected by the data collection unit 112 is not limited to data stored in the storage unit 130, but may also be collected by inquiring externally (for example, the instructor terminal 200 or the trainee terminal 300).

[0029] The display control unit 113 generates and controls the display of various UI (User Interface) screens to be displayed on the instructor terminal 200 and the trainee terminal 300. The display control unit 113 also controls the display of UI screens for receiving various instructions from the instructor terminal 200 and the trainee terminal 300. For example, the display control unit 113 may provide the instructor terminal 200 with data to be displayed on the UI screen.

[0030] The training data setting unit 114 sets training data to be performed by the target trainee based on instructions from the instructor received via the instructor terminal 200. The training data consists of one or more training events to be performed by the trainee. The training events are associated with content (hereinafter referred to as "training content") to be referenced when the trainee performs training. The training content is composed of formats such as moving images, still images, audio, and text, and is prepared so that it can be played back on the trainer terminal 300. In other words, the training content can be used as a model for the trainee when training.

[0031] The performance data extracting unit 115 extracts data corresponding to the training events that constitute the training data from the training performance data that was performed based on the training data. An example of the extraction will be described later.

[0032] The training performance evaluation unit 116 evaluates the training performance data based on the instructor's input and associates the performance with the evaluation data. The training performance evaluation may be performed for the entire training performance data corresponding to one training, or for each of multiple training events included in one training.

[0033] The data analysis unit 117 analyzes the non-face-to-face training of the trainee based on the training data, training performance data, evaluation data, etc. The data analysis unit 117 may evaluate the training performance based on various data. The data analysis unit 117 may also statistically analyze and evaluate the results of multiple non-face-to-face training sessions by a certain trainee. Based on the analysis results, the data analysis unit 117 generates learning data for an AI (Artificial Intelligence) model (described later).

[0034] The feedback generation unit 118 provides feedback regarding the training content to the instructor or trainee based on the processing results of the training performance evaluation unit 116 and the data analysis unit 117.

[0035] The training menu determination unit 119 determines and proposes a training menu based on instructions from an instructor, training results from a trainee, etc. Here, the "training menu" refers to a combination of one or more training events that make up the training data.

[0036] The training menu adjustment unit 120 adjusts the training menu based on instructions from the instructor, the training performance of the trainee, etc. The method of proposing a training menu by the training menu determination unit 119 and adjusting the training menu by the training menu adjustment unit 120 will be described later in a modified example using an AI model as an example.

[0037] The assist device control unit 121 controls an assist device 400 for assisting non-face-to-face training. The assist device 400 may be, for example, a robot for assisting passive exercise in rehabilitation. Alternatively, the assist device 400 may be an input / output device such as a display or a microphone used by an assistant (for example, a family member or other supporter) who supports the passive exercise of the trainee.

[0038] The learning processing unit 122 performs a learning process for the AI ​​model, which will be described later. For example, the learning process may use learning data obtained by the data analysis unit 117, or may use learning data set manually. Details of the AI ​​model will be described later. Multiple AI models may be provided, and different models may be used depending on the content to be output. Furthermore, multiple versions of the AI ​​model may be managed depending on the level of learning. Furthermore, when multiple AI models are combined to perform higher-level inference, the combination patterns and processing orders of these AI models may also be managed together.

[0039] The communication control unit 123 controls communication with external devices (for example, the instructor terminal 200 and the trainee terminal 300) and transmits and receives data.

[0040] The storage unit 130 is a storage device for storing programs, data, etc. for executing various control processes and functions within the control unit 110. The storage unit 130 is composed of volatile / non-volatile storage devices such as RAM (Random Access Memory), ROM (Read Only Memory), HDD (Hard Disk Drive), and flash memory. The storage unit 130 includes a DB for managing data corresponding to the functions described below.

[0041] The program 131 is a program for providing the non-face-to-face training management service according to this embodiment. The program 131 may include setting parameters for providing the non-face-to-face training management service, format information related to the screen configuration, and the like.

[0042] The trainee DB 132 manages information about trainees who perform training (hereinafter also referred to as "trainee information"). The trainee information may include, for example, items such as identification information for uniquely identifying the trainee, symptoms, training status, training history, and instructor in charge.

[0043] The instructor DB 133 manages information about instructors who give instructions on training (hereinafter also referred to as "instructor information"). The instructor information may include, for example, items such as identification information for uniquely identifying the instructor, the trainer in charge, field of expertise, instruction history, etc.

[0044] The training event DB 134 manages information on the type of training performed by the trainee (hereinafter also referred to as "training type information"). Various training contents are prepared for the training event depending on the content of the training. For example, in the case of physical therapy training, training events include bending and stretching, standing on one leg, and bending forward. In the case of occupational therapy training, training events include holding chopsticks and changing clothes. In the case of speech-language hearing training, training events include vocalization and reading aloud. In addition, the number of sets for the training event, the number of repetitions per set (also called "number of reps"), and repetition time may also be specified. Specific examples of training events will be described later.

[0045] The training data DB 135 manages the training data that is set for each trainee and that the trainee is to perform. The training data is set for each trainee and is composed of a combination of one or more training events (hereinafter also referred to as a "training menu"). Details of the training data will be described later.

[0046] The training performance DB 136 manages training performance data of training conducted by the trainee. In addition to the training performance data collected from the trainee terminal 300, the training performance DB 136 also manages unit performance data corresponding to one or more training events that make up the training performance data. The unit performance data is extracted from the training performance data by the performance data extraction unit 115. Examples of unit performance data will be described later. The training performance DB 136 also manages evaluation data for the training performance data. The evaluation data may include, in addition to evaluations by the instructor, evaluations by the data analysis unit 117, for example.

[0047] The assist device DB 137 manages information about the assist devices 400 that assist the trainee in training (hereinafter also referred to as "assist device information"). The assist device information may include items such as identification information for uniquely identifying the assist device, specifications, functions, and the content of the training that the assist device can provide.

[0048] The AI ​​model DB 138 manages AI models for determining, evaluating, adjusting, and the like, training menus. The AI ​​model DB 138 manages multiple AI models according to input / output and purpose. Examples of AI models will be described later. Note that the learning process generally involves a high processing load. Therefore, from the perspective of load distribution, the learning process may be performed on a device (not shown) other than the non-face-to-face training management server 100, and an AI model that has progressed to a certain degree of learning may be acquired by the non-face-to-face training management server 100 and stored in the AI ​​model DB 138. The configuration and learning algorithm of the AI ​​model are not particularly limited, and known methods may be used, but they are configured to enable input / output as described below.

[0049] The communication unit 140 is a communication interface for communicating with external devices via the network NW. The communication unit 140 may be configured to be compatible with a plurality of communication standards depending on the configuration of the network NW.

[0050] 3A is a block diagram showing an example of the functional configuration of the instructor terminal 200 used by an instructor who instructs non-face-to-face training according to this embodiment. The instructor terminal 200 includes a control unit 210, a storage unit 220, an operation unit 230, a display unit 240, a communication unit 250, and an external IF (Interface) 260.

[0051] The control unit 210 controls the operation of the instructor terminal 200. The control unit 210 is composed of, for example, a CPU (Central Processing Unit) and a GPU (Graphics Processing Unit), and provides various functions by reading and executing various programs and data stored in the storage unit 220.

[0052] The storage unit 220 is a storage device for storing programs, data, etc. for executing various control processes and functions of the control unit 210. The storage unit 220 is configured from volatile / non-volatile storage devices such as RAM (Random Access Memory), ROM (Read Only Memory), HDD (Hard Disk Drive), and flash memory.

[0053] The operation unit 230 is an interface for receiving operations from the user of the instructor terminal 200. The operation unit 230 may be configured with a mouse, a keyboard, etc. The display unit 240 is an interface for displaying various screens and is configured with a display, etc. A touch panel display in which the operation unit 230 and the display unit 240 are integrated may be used.

[0054] The communication unit 250 is a communication interface for communicating with external devices via the network NW. The communication unit 250 may be configured to support multiple communication standards depending on the configuration of the network NW. The external IF 260 is an interface for connecting with various devices, and may be, for example, a connection interface with an imaging unit (not shown) for capturing images or sensors for acquiring predetermined information.

[0055] 3B is a block diagram showing an example of the functional configuration of a trainee terminal 300 used by a trainee who performs non-face-to-face training according to this embodiment. The trainee terminal 300 includes a control unit 310, a storage unit 320, an operation unit 330, a display unit 340, a communication unit 350, a camera 360, a sensor 370, and an external IF (Interface) 380.

[0056] The control unit 310 is responsible for controlling the operation of the trainee terminal 300. The control unit 310 is composed of, for example, a CPU (Central Processing Unit) and a GPU (Graphics Processing Unit), and provides various functions by reading and executing various programs and data stored in the storage unit 320.

[0057] The storage unit 320 is a storage device for storing programs, data, etc. for executing various control processes and functions of the control unit 310. The storage unit 320 is configured from volatile / non-volatile storage devices such as a RAM (Random Access Memory), a ROM (Read Only Memory), an HDD (Hard Disk Drive), and a flash memory.

[0058] The operation unit 330 is an interface for receiving operations from the user of the trainee terminal 300. The operation unit 330 may be composed of a mouse, a keyboard, etc. The display unit 340 is an interface for displaying various screens and is composed of a display, etc. A touch panel display in which the operation unit 330 and the display unit 340 are integrated may be used.

[0059] The communication unit 350 is a communication interface for communicating with external devices via the network NW. The communication unit 350 may be configured to be compatible with a plurality of communication standards depending on the configuration of the network NW.

[0060] The camera 360 is an imaging device for capturing images of the area around the trainee terminal 300. The sensor 370 is a detection device for acquiring biometric data of the user of the trainee terminal 300 and information about the surrounding environment. The sensor 370 may be composed of various sensors, such as a microphone, a distance sensor, a temperature sensor, a vibration sensor, a heart rate monitor, and a blood pressure monitor. The biometric data may include, for example, electromyography, electroencephalography, electrocardiography, body temperature, blood pressure, and viewpoint. In this embodiment, the camera 360 and the sensor 370 are used to acquire information when the trainee is conducting non-face-to-face training. In other words, the camera 360 and the sensor 370 may be used to record, record, and measure video data, still image data, audio data, operation data, and biometric data during non-face-to-face training.

[0061] The external IF 380 is an interface for connecting to various devices. The external IF 380 is connected to, for example, an assisting device 400 for assisting passive exercise in non-face-to-face training. The assisting device 400 is a device for assisting in non-face-to-face training. The configuration of the assisting device 400 may be selected depending on the type of training in non-face-to-face training and is not particularly limited. For example, the assisting device 400 may be a display on which an assistant assisting the trainee in performing passive exercise can view a video of the passive exercise. Alternatively, the assisting device 400 may be a robot that assists the trainee in performing passive exercise. Alternatively, the assisting device 400 may be a measuring device for measuring predetermined information of the trainee during non-face-to-face training. The assisting device 400 may be connected and activated by the trainee or an instructor depending on the content of the non-face-to-face training. Furthermore, the operation of the assisting device 400 during non-face-to-face training may be controlled based on instructions from the non-face-to-face training management server 100.

[0062] [Processing Sequence] Figure 4 is a sequence diagram showing the overall processing flow of the non-face-to-face training management service according to this embodiment. This processing sequence is realized by cooperation between the non-face-to-face training management server 100, the instructor terminal 200, and the trainee terminal 300. Note that the processing of each device is realized, for example, by the control unit of each device reading and executing the programs and data stored in the memory unit.

[0063] In step S401, the instructor terminal 200 requests information about the trainee who is the target of the non-face-to-face training based on an instruction from the instructor. The trainee information may be registered in advance in the non-face-to-face training management server 100 by operation of the instructor or trainee. The request here may include identification information for uniquely identifying the instructor or trainee. The instructor terminal 200 may display a UI screen (not shown) for receiving instructions from the instructor and search for the trainee who is the target of training via the UI screen.

[0064] In step S402, the non-face-to-face training management server 100 identifies a trainee to be trained based on a request from the instructor terminal 200. The information identified here may include medical condition, past training history, evaluation of training performance, etc. Furthermore, the non-face-to-face training management server 100 may identify information on training events that can be set for the trainee based on the trainee's past training history, attributes, etc.

[0065] In step S403, the non-face-to-face training management server 100 provides the instructor terminal 200 with information about the trainee identified in step S402.

[0066] In step S404, the instructor terminal 200 displays the trainee information provided by the non-face-to-face training management server 100 in step S403. Furthermore, the instructor terminal 200 accepts non-face-to-face training settings for the trainee based on the various information indicated in the trainee information. The non-face-to-face training settings here include training data consisting of one or more training events to be performed by the target trainee. The non-face-to-face training settings may also include the time, period, frequency, and information about the assistive device 400 to be performed.

[0067] In step S405, the non-face-to-face training management server 100 records the setting information for the target trainee based on the setting received from the instructor terminal 200 in step S404.

[0068] In step S406, the non-face-to-face training management server 100 notifies the trainee terminal 300 used by the target trainee of information related to the non-face-to-face training. This notification may be made via the application of the non-face-to-face training management service according to this embodiment, or via other communication tools.

[0069] In step S407, the trainee terminal 300 displays the information notified in step S406 from the non-face-to-face training management server 100. For example, the trainee terminal 300 may display details of the non-face-to-face training content, the start time, information about the equipment (such as the auxiliary device 400) required for the non-face-to-face training, and the like.

[0070] In step S408, the trainee terminal 300, based on instructions from the trainee, requests the non-face-to-face training management server 100 to start training. For example, the trainee terminal 300 may display a UI screen (not shown) for receiving instructions from the trainee, and present the trainee with training options that can be performed via the UI screen so that the trainee can select one.

[0071] In step S409, the non-face-to-face training management server 100 identifies training content for the training type of the non-face-to-face training to be performed by the trainee, based on the request received in step S408 from the trainee terminal 300. If multiple training types are specified, training content corresponding to each of the multiple training types is identified.

[0072] In step S410, the non-face-to-face training management server 100 provides training data including the training content identified in step S409 to the trainee terminal 300. The training data here may include information about the assisting device 400 and a control signal for the assisting device 400 depending on the training content. In addition, the training data may include information for an assistant in non-face-to-face training.

[0073] In step S411, the trainee terminal 300 presents the training data provided in step S410. In addition, the trainee terminal 300 activates the auxiliary device 400, the camera 360 for collecting training performance data, and the sensor 370 based on the training data. The training content included in the training data may be provided in the form of moving images, audio, or the like.

[0074] In step S412, the trainee terminal 300 collects information about the trainee during the non-face-to-face training as training performance data in conjunction with the presentation and playback of training content related to the non-face-to-face training. The training performance data collected here may vary depending on the type of training content. Multiple types of data may be collected as training performance data. Furthermore, the collected data itself may be treated as training performance data, or the collected raw data may be processed by applying a predetermined process on the trainee terminal 300 side and treated as training performance data. After the non-face-to-face training is completed, the trainee terminal 300 transmits the collected training performance data to the non-face-to-face training management server 100. This transmission may be performed in real time, or may be performed after compiling all data from the start to the end of the non-face-to-face training.

[0075] In step S413, the non-face-to-face training management server 100 records the training performance data transmitted from the trainee terminal 300 in step S412 in association with the information of the trainee who performed the training.

[0076] In step S414, the non-face-to-face training management server 100 extracts the training performance data recorded in step S413 as unit performance data based on the configuration of one or more training contents in the corresponding training data. An example of this extraction will be described later. The non-face-to-face training management server 100 then records the extracted unit performance data in association with the trainee's information.

[0077] In step S415, the non-face-to-face training management server 100 notifies the instructor terminal 200 used by the instructor that the non-face-to-face training has been carried out.

[0078] In step S416, the instructor terminal 200 displays the training performance data of the trainee. Display examples will be described later. At this time, the instructor terminal 200 may display the training performance data in association with the training data. At this time, the instructor terminal 200 may display evaluation information on the training performance data that was automatically performed by the non-face-to-face training management server 100.

[0079] In step S417, the instructor terminal 200 accepts an evaluation of the training performance data displayed in step S416. Examples of the evaluation will be described later. The instructor terminal 200 may also accept, from the instructor, a determination as to whether the evaluation of the training performance data, which was automatically performed by the non-face-to-face training management server 100, is appropriate or not, as evaluation information. Thereafter, the instructor terminal 200 transmits the accepted evaluation information to the non-face-to-face training management server 100.

[0080] In step S418, the non-face-to-face training management server 100 records the evaluation information received from the instructor terminal 200 in association with the training performance data.

[0081] In step S419, the non-face-to-face training management server 100 notifies the trainee terminal 300 of the evaluation result. The notification here may be the evaluation result for one non-face-to-face training session, or may be a statistical evaluation result for multiple non-face-to-face training sessions.

[0082] In step S420, the trainee terminal 300 displays the evaluation result of the non-face-to-face training notified in step S419, and then ends this processing flow.

[0083] [Database Configuration Example] Figures 5, 6A, and 6B show examples of database configurations according to this embodiment. Figure 5 is a table diagram showing an example of the configuration of training event information 500 for training events of non-face-to-face training according to this embodiment. The training event information 500 is managed in the training event DB 134 of the non-face-to-face training management server 100 shown in Figure 2.

[0084] The training event information 500 includes an event ID 501, an event name 502, an objective 503, a body part 504, a required time 505, and a load level 506. The event ID 501 is identification information for uniquely identifying a training event. The event name 502 is the name of the training event. The objective 503 indicates the objective of the training, and may indicate, for example, symptoms that are effective. The body part 504 may indicate an effective body part or a body part to be moved in the training. The required time 505 indicates the time for performing the training event. The load level 506 indicates the level of load in the training. Multiple levels of load may be set in advance, and classification may be based on these.

[0085] FIG. 6A is a table diagram showing an example of the configuration of training data 600 according to this embodiment. The training data 600 is managed in the training data DB 135 shown in FIG. 2. The training data 600 includes a training ID 601, a training instructor 602, a trainee 603, a planned training date 604, a training implementation date 605, a training evaluation date 606, a training evaluator 607, a training event 608, and an overall evaluation 609. The training ID 601 is identification information for uniquely identifying the training data. The training instructor 602 indicates the instructor who instructed the training. The trainee 603 indicates the trainee who is to implement the training. The planned training implementation date 604 indicates information about the date and time when the training will be implemented. The planned training implementation date 604 may be specified as a period. The training implementation date 605 indicates the date and time when the trainee implemented the training. The training evaluator 607 indicates the evaluator who evaluates the implemented training. The evaluator and the instructor may be the same or different. One or more training items to be performed as training are specified in the training item 608. The overall evaluation 609 indicates an overall evaluation of the results of the training.

[0086] FIG. 6B is a table diagram showing an example of the configuration of training performance data 610 according to this embodiment. As shown in the training event 608 of the training data 600, one piece of training data includes one or more training events. In this embodiment, performance data is stored as evidence (facts) of training implementation for each of the one or more training events, and an evaluation for each is configurable. The training performance data 610 includes a training ID 611, a training order 612, a training item 613, training performance 614, and a training evaluation 615. The training ID 611 corresponds to the training ID 601 in FIG. 6A. The training order 612 and the training item 613 correspond to the order and items specified in the training event 608 in FIG. 6A. The training performance 614 indicates unit performance data performed corresponding to each training event. The concept of unit performance data will be described later. The training evaluation 615 indicates the results of evaluation based on each unit performance data.

[0087] The configurations of the information shown in Figures 5, 6A, and 6B are merely examples and are not limiting. Each piece of information may include more items. Furthermore, the information items may be changed or the associated information items may be changed depending on the configuration of each DB shown in Figure 2.

[0088] [Training performance data] Figures 7 and 8 are conceptual diagrams showing an example of the configuration of training performance data in the non-face-to-face training management service according to this embodiment. For example, as shown in Figure 7, one training data set is set up as a sequence of multiple training events, namely "Training event A," "Training event A," "Training event A," "Rest," "Training event B," "Training event B," and "Training event B." Here, rest will be described as a single event. Furthermore, since a required time is set for each training event, the total required time required to complete a series of training events is the total required time.

[0089] The trainee performs training in accordance with training content such as video and audio specified in the training data. At that time, training performance data is collected via the trainee terminal 300. The training performance data includes performance data corresponding to each training event (hereinafter referred to as "unit performance data"). In this embodiment, unit performance data corresponding to each training event is extracted based on the playback timing of the training content for each training event and the collection timing of the training performance data. Then, this unit performance data is managed in association with the training data and the training performance data.

[0090] Furthermore, in this embodiment, the training performance data as a whole can be evaluated, and each unit performance data can be evaluated. Therefore, evaluation data for each unit performance data is recorded in association with each other.

[0091] FIG. 8 shows an example of training performance data acquired while a trainee is training according to training data. Here, an example of video is shown as the training performance data. As shown in FIG. 7 , an example is shown in which training data is composed of multiple training events, rest periods, and multiple training events. Here, one-legged standing is performed as the training event. As described above, the required time is specified for the training content of one training event. Therefore, by associating the playback timing of the training content with the collection timing of the training performance data, the range of each unit of performance data can be identified.

[0092] For example, if it can be determined that the timing (t=0 s) when playback of multiple training contents constituting the training data starts and the timing when collection of training performance data starts coincide, the time required for each training content can be extracted as unit performance data. Alternatively, playback of multiple training contents constituting the training data can be started, and the timing when the trainee recognizes the training content and starts moving can be used as the timing to start extracting unit performance data. The example of Figure 7 shows a case where the required time for the training event "standing on one leg" is 20 seconds, and the period from Ts=400 to Ts=420 of the training performance data is extracted as one unit performance data.

[0093] More specifically, if the training event "standing on one leg" is performed with 10 repetitions per set and two sets, and the evaluation point is the fifth repetition of the second set, the start time Ts of the unit performance data is 400 s (= 20 x 10 x (2-1) + 20 x (5-1) + 120 x (2-1)). Also, the end time Te of the unit performance data is 420 s (= 20 x 10 x (2-1) + 20 x 5 + 120 x (2-1)).

[0094] 9A, 9B, and 10 are diagrams showing configuration examples of UI screens for checking and evaluating training performance data according to this embodiment. The UI screens shown in Fig. 9A, 9B, and 10 are displayed, for example, in step S416 or step S417 in Fig. 4.

[0095] The UI screen 900 is a UI screen for specifying desired training performance data. By specifying the instructor, trainer, and training implementation date, the evaluator can confirm the content of the training performance data that matches the conditions. In this example, it is assumed that "AAAA" is specified as the instructor of the non-face-to-face training, "BBBB" as the implementer of the non-face-to-face training, and "YY / MM / DD" as the implementation date of the non-face-to-face training. In this case, training performance data that matches the conditions is identified, and the content of the training performance data is displayed so that it can be confirmed via the UI screen 900. Note that other information may be used as search conditions when confirming the training performance data.

[0096] Item 901 displays information about the instructor, trainee, and training implementation date in the training performance data. The displayed information is not limited to this and may include other items. Setting item 902 accepts specification of the portion of the training performance data that the user wishes to confirm. In this embodiment, the screen is configured to allow the user to specify unit performance data corresponding to a desired training event from among multiple training events that constitute the training performance data. In the example of FIG. 9A , one or more training events that constitute the training data can be selected in list format (e.g., "standing on one leg"). Furthermore, if the user wishes to confirm the entire training performance data, the user can specify the desired item in the setting item 902. After specifying the setting item 902, pressing the execute button 903 transitions to a UI screen 910 shown in FIG. 9B .

[0097] The UI screen 910 shown in FIG. 9B is a UI screen for checking training performance data. In the UI screen 910, items 911 display various information set in the setting items 902 of the UI screen 900. The display area 912 is an area for displaying a video of the specified training performance data. When a play button 915 is pressed, the video of the specified training performance data can be played and checked. Acquired audio and the like may be output along with the playback of the video. Furthermore, information acquired by a sensor or the like, elapsed time, and the like may be presented in the information item 913. When a back button 914 is pressed, the screen returns to the UI screen 900 of FIG. 9A. When an evaluation button 916 is pressed, the screen transitions to a UI screen 1000 shown in FIG. 10.

[0098] The UI screen 1000 shown in FIG. 10 is a UI screen for inputting an evaluation of the training performance data confirmed on the UI screen 910 of FIG. 9B. Item 1001 displays information about the confirmed training performance data. The evaluation input area 1002 is used to input an evaluation of the training performance data confirmed on the UI screen 910 of FIG. 9B (e.g., findings on medical procedures, future improvements, progress, etc.). In this example, the evaluation is input in a free-form format, but this is not limited to this. Multiple levels of evaluation may be selectable in a list format. Alternatively, as described above, the non-face-to-face training management server 1000 may automatically perform the evaluation and present the results, and the evaluator may determine whether the evaluation is acceptable and specify the results. When the decision button 1003 is pressed, the information entered in the evaluation input area 1002 is registered as the evaluation result. When the cancel button 1004 is pressed, the evaluation is interrupted and the screen transitions to another screen, such as the UI screen 900.

[0099] Although not shown in Figures 9A, 9B, 10, etc., information regarding whether or not the training performance data and the unit performance data have been evaluated, and information regarding data that has not been evaluated may be clearly displayed. This may allow management to prevent the instructor from missing any evaluations. Furthermore, the results of evaluation and analysis on the system side may be displayed on the UI screens shown in Figures 9B, 10, etc.

[0100] [Processing Flow] (Data Extraction Process) Figure 11 is a flowchart showing the flow of the process for extracting unit performance data from training performance data according to this embodiment. This process flow is executed as part of the process of step S414 in Figure 4. This process flow is realized, for example, by the control unit 110 of the non-face-to-face training management server 100 reading and executing programs and various data stored in the memory unit 130. Here, for ease of explanation, the processing entity will be described as the non-face-to-face training management server 100.

[0101] Before this processing flow is started, it is assumed that training performance data of non-face-to-face training conducted by a trainee in accordance with training data has been collected.

[0102] In step S1101, the non-face-to-face training management server 100 acquires the collected training performance data.

[0103] In step S1102, the non-face-to-face training management server 100 acquires training data corresponding to the training performance data acquired in step S1101.

[0104] In step S1103, the non-face-to-face training management server 100 identifies the sequence and unit time of one or more training events that make up the training data based on the configuration of the training data acquired in step S1102.

[0105] In step S1104, the non-face-to-face training management server 100 matches the configuration identified in step S1103 with the training performance data acquired in step 1101. That is, the non-face-to-face training management server 100 identifies the position (time) corresponding to each training event in the training performance data as described with reference to FIG.

[0106] In step S1105, the non-face-to-face training management server 100 extracts unit performance data corresponding to each training event from the training performance data based on the matching result in step S1104.

[0107] In step S1106, the non-face-to-face training management server 100 records the unit performance data extracted in step S1105.

[0108] In step S1107, the non-face-to-face training management server 100 determines whether the training performance data is to be analyzed. The analysis target may be set in advance corresponding to the training type, or may be set according to the trainee. Alternatively, the instructor may set the analysis target individually. If the training performance data is to be analyzed (step S1107: YES), the processing of the non-face-to-face training management server 100 proceeds to step S1108. On the other hand, if the training performance data is not to be analyzed (step S1107: NO), this processing flow ends.

[0109] In step S1108, the non-face-to-face training management server 100 analyzes the training performance data. The analysis method is not particularly limited, and known methods may be used. For example, the analysis method may involve estimating the skeletal structure of the trainee appearing in the video, or computing characteristic features of the audio data (e.g., accent, pitch, etc.). The analysis method to be applied may be set according to the training event. For example, known methods such as those disclosed in Japanese Patent Nos. 5820366, 6675462, and 7209333 may be used for the skeletal structure estimation process. Furthermore, for example, known methods such as those disclosed in Japanese Patent Nos. 7005567, 6774551, 6585154, and 5120826 may be used for computing characteristic features of the audio data. Using these methods not only allows for data analysis, but also allows for data volume reduction.

[0110] In step S1109, the non-face-to-face training management server 100 records the analysis results from step S1108 in association with the training performance data, and then ends this processing flow.

[0111] (Training performance data collection process) FIG. 12 is a flowchart showing the flow of the training performance data collection process according to this embodiment. This process flow is a process for collecting training performance data while monitoring the implementation of non-face-to-face training in real time. This process flow is executed as part of the process of step S413 in FIG. 4. This process flow is realized, for example, by the control unit 110 of the non-face-to-face training management server 100 reading and executing programs and various data stored in the memory unit 130. Here, for ease of explanation, the processing entity will be described as the non-face-to-face training management server 100.

[0112] This processing flow is a process performed when the non-face-to-face training management server 100 collects training performance data in real time while non-face-to-face training is being conducted. Therefore, when the trainee terminal 300 transmits training performance data from the start to the end of non-face-to-face training collectively to the non-face-to-face training management server 100, a different processing flow from this processing flow is performed. Furthermore, when this processing flow is executed, processing equivalent to the matching shown in part of Figure 11 (equivalent to the processing in step S1104) is performed in addition to the collection of training performance data, so part of the processing shown in Figure 11 may be omitted.

[0113] In step S1201, the non-face-to-face training management server 100 receives a training request from the trainee terminal 300. The training request here may include information about the trainee and information about the requested non-face-to-face training.

[0114] In step S1202, the non-face-to-face training management server 100 acquires the corresponding training data based on the request received in step S1201.

[0115] In step S1203, the non-face-to-face training management server 100 identifies training content corresponding to one or more training events specified in the training data acquired in step S1202.

[0116] In step S1204, the non-face-to-face training management server 100 determines whether or not a training start instruction has been received from the trainee terminal 300. The training start instruction here may include information regarding the preparation state of various equipment necessary for non-face-to-face training. If a training start instruction has been received (step S1204: YES), the processing of the non-face-to-face training management server 100 proceeds to step S1205. On the other hand, if a training start instruction has not been received (step S1204: NO), the non-face-to-face training management server 100 waits until a training start instruction is received.

[0117] In step S1205, the non-face-to-face training management server 100 determines whether or not it is ready to acquire training performance data associated with the implementation of non-face-to-face training. For example, the non-face-to-face training management server 100 may make this determination based on the activation status of the camera 360 and the sensor 370 on the trainee terminal 300. If it is ready to acquire training performance data (step S1205: YES), the processing of the non-face-to-face training management server 100 proceeds to step S1207. On the other hand, if it is not ready to acquire training performance data (step S1205: NO), the processing of the non-face-to-face training management server 100 proceeds to step S1206.

[0118] In step S1206, the non-face-to-face training management server 100 sends an error notification to the trainee terminal 300 to prompt the trainee terminal 300 to prepare for non-face-to-face training. The error notification here may include notifications prompting the trainee to start up and set up various devices, prepare, etc. Thereafter, the processing of the non-face-to-face training management server 100 returns to step S1204 and repeats the processing.

[0119] In step S1207, the non-face-to-face training management server 100 starts acquiring training performance data via the trainee terminal 300. The training performance data collected here may be the data itself acquired by the camera 360 or sensor 370 of the trainee terminal 300, or may be data to which processing such as compression has been applied. Alternatively, the trainee terminal 300 may be controlled to perform the skeletal structure estimation processing and the calculation processing of the characteristic parts of the voice data as described above, and then transmit the processing results to the non-face-to-face training management server 100.

[0120] In step S1208, the non-face-to-face training management server 100 starts monitoring the training performance data that is continuously acquired while the non-face-to-face training is being carried out.

[0121] In step S1209, the non-face-to-face training management server 100 starts playing the training content in the training data via the trainee terminal 300.

[0122] In step S1210, the non-face-to-face training management server 100 determines whether an abnormal value has been detected based on the monitored training performance data and predetermined conditions. For example, this determination may be made when the trainee cannot be identified in the video image or when an abnormal value exceeding a predetermined threshold has been detected in the biometric data. If an abnormal value has been detected (step S1210: YES), the non-face-to-face training management server 100 proceeds to step S1211. On the other hand, if an abnormal value has not been detected (step S1210: NO), the non-face-to-face training management server 100 proceeds to step S1214.

[0123] In step S1211, the non-face-to-face training management server 100 determines whether or not the non-face-to-face training needs to be interrupted based on the abnormal value detected in step S1210. For example, the non-face-to-face training management server 100 may determine to interrupt the training if an abnormal value that may affect the trainee's body is detected or if it is not possible to determine that the trainee has been training for a certain period of time. More specifically, this may be the case when a predetermined change in the trainee's physical condition occurs, such as when the trainee's heart rate or body temperature exceeds a predetermined value. If it is determined that the non-face-to-face training needs to be interrupted (step S1211: YES), the non-face-to-face training management server 100 proceeds to step S1213. On the other hand, if it is determined that the non-face-to-face training does not need to be interrupted (step S1211: NO), the non-face-to-face training management server 100 proceeds to step S1212.

[0124] In step S1212, the non-face-to-face training management server 100 notifies the trainee terminal 300 of an error associated with the detection of the abnormal value in step S1210. This error notification may include information on the determined abnormal value and a notification to check the status of the non-face-to-face training. Thereafter, the processing of the non-face-to-face training management server 100 returns to step S1210, and the non-face-to-face training continues.

[0125] In step S1213, the non-face-to-face training management server 100 notifies the trainee terminal 300 that the non-face-to-face training will be suspended. This suspension notification may include information on the basis of which the non-face-to-face training has been determined to be suspended. Thereafter, the processing of the non-face-to-face training management server 100 proceeds to step S1218.

[0126] In step S1214, the non-face-to-face training management server 100 determines whether the training content being played has ended. If the training content being played has ended (step S1214: YES), the processing of the non-face-to-face training management server 100 proceeds to step S1215. On the other hand, if the training content being played has not ended (step S1214: NO), the processing of the non-face-to-face training management server 100 returns to step S1210 and repeats the processing.

[0127] In step S1215, the non-face-to-face training management server 100 sets a tag for extracting unit performance data in the training performance data. That is, the non-face-to-face training management server 100 sets a dividing position in the training performance data.

[0128] In step S1216, the non-face-to-face training management server 100 determines whether there are any subsequent training events in the specified training data. If there are any subsequent training events (step S1216: YES), the processing of the non-face-to-face training management server 100 proceeds to step S1217. On the other hand, if there are no subsequent training events, that is, if all training events have been completed (step S1216: NO), the processing of the non-face-to-face training management server 100 proceeds to step S1218.

[0129] In step S1217, the non-face-to-face training management server 100 instructs the trainee terminal 300 to play back the training content corresponding to the next training event. Thereafter, the processing of the non-face-to-face training management server 100 returns to step S1210 and the processing is repeated.

[0130] In step S1218, the non-face-to-face training management server 100 ends the processing of playing the training content, monitoring the data, and acquiring the data.

[0131] In step S1219, the non-face-to-face training management server 100 records the acquired training performance data in association with the training data, and then ends this processing flow.

[0132] (Passive Exercise Assistance Processing) FIG. 13 is a flowchart showing the flow of control processing in a training event that assumes passive exercise in non-face-to-face training according to this embodiment. Passive exercise in this embodiment will be described using examples of a training event that assumes assistance by an assist device 400 such as a robot, and a training event that assumes manual assistance. This processing flow is executed as part of step S410 and step S411 in FIG. 4. This processing flow is realized, for example, by the control unit 110 of the non-face-to-face training management server 100 reading and executing programs and various data stored in the memory unit 130. For ease of explanation, the processing entity will be described as the non-face-to-face training management server 100.

[0133] In step S1301, the non-face-to-face training management server 100 acquires training data related to non-face-to-face training.

[0134] In step S1302, the non-face-to-face training management server 100 determines whether the training data acquired in step S1301 includes a training event corresponding to passive exercise. Information regarding whether or not the training event corresponds to passive exercise may be specified, for example, in the training event information. If a training event corresponding to passive exercise is included (step S1302: YES), the processing of the non-face-to-face training management server 100 proceeds to step S1303. On the other hand, if a training event corresponding to passive exercise is not included (step S1302: NO), this processing flow ends. In this case, non-face-to-face training other than passive exercise may be performed.

[0135] In step S1303, the non-face-to-face training management server 100 determines whether or not cooperation with the assist device 400 is required for passive exercise. Cooperation here refers to the case where an assist device 400, such as a robot, that supports passive exercise is controlled. If cooperation with the assist device 400 is required (step S1303: YES), the processing of the non-face-to-face training management server 100 proceeds to step S1304. On the other hand, if cooperation with the assist device 400 is not required (step S1303: NO), the processing of the non-face-to-face training management server 100 proceeds to step S1311.

[0136] In step S1304, the non-face-to-face training management server 100 acquires information about the assist device 400 that will be linked in the training event corresponding to the passive exercise. Here, the non-face-to-face training management server 100 acquires information about the assist device 400 that should be prepared on the trainee terminal 300 side and information related to its control from the assist device DB 137.

[0137] In step S1305, the non-face-to-face training management server 100 instructs the trainee terminal 300 to prompt the trainee terminal 300 to prepare the auxiliary device 400 acquired in step S1304. This instruction may include information regarding the activation, attachment, and settings of the auxiliary device 400.

[0138] In step S1306, the non-face-to-face training management server 100 communicates with the trainee terminal 300 and the like to determine whether or not preparation of the auxiliary device 400 is complete. If preparation of the auxiliary device 400 is complete (step S1306: YES), the processing of the non-face-to-face training management server 100 proceeds to step S1307. If preparation of the auxiliary device 400 is not complete (step S1306: NO), the processing of the non-face-to-face training management server 100 returns to step S1305 and waits until preparation is complete.

[0139] In step S1307, the non-face-to-face training management server 100 starts acquiring training performance data.

[0140] In step S1308, the non-face-to-face training management server 100 causes the trainee terminal 300 to start playing the training content.

[0141] In step S1309, the non-face-to-face training management server 100 starts controlling the assist device 400 for passive exercise.

[0142] In step S1310, the non-face-to-face training management server 100 determines whether the non-face-to-face training has been completed. If the non-face-to-face training has been completed (step S1310: YES), the processing of the non-face-to-face training management server 100 proceeds to step S1316. On the other hand, if the non-face-to-face training has not been completed (step S1311: NO), the non-face-to-face training management server 100 continues processing until the non-face-to-face training has been completed.

[0143] In step S1311, the non-face-to-face training management server 100 instructs the trainee terminal 300 to prompt the assistant to prepare for passive exercise. Separate instructions may be given to the trainee and the assistant.

[0144] In step S1312, the non-face-to-face training management server 100 communicates with the trainee terminal 300 and the like to determine whether the trainee and assistant are ready. If the preparation is complete (step S1312: YES), the processing of the non-face-to-face training management server 100 proceeds to step S1313. If the preparation is not complete (step S1312: NO), the processing of the non-face-to-face training management server 100 returns to step S1311 and waits until the preparation is complete.

[0145] In step S1313, the non-face-to-face training management server 100 starts acquiring training performance data.

[0146] In step S1314, the non-face-to-face training management server 100 causes the trainee terminal 300 to start playing the training content. The training content to be played here may be training content for the trainee and training content for the assistant played separately. In this case, the training content for the assistant may be provided using a separately provided display, speaker, or the like as the auxiliary device 400.

[0147] In step S1315, the non-face-to-face training management server 100 determines whether the non-face-to-face training has been completed. If the non-face-to-face training has been completed (step S1315: YES), the processing of the non-face-to-face training management server 100 proceeds to step S1316. On the other hand, if the non-face-to-face training has not been completed (step S1315: NO), the non-face-to-face training management server 100 continues processing until the non-face-to-face training is completed.

[0148] In step S1316, the non-face-to-face training management server 100 causes the trainee terminal 300 to stop playing the training content.

[0149] In step S1317, the non-face-to-face training management server 100 records the training performance data acquired during the non-face-to-face training in association with the training data, and then ends this processing flow.

[0150] Although not shown in Fig. 13, abnormal values ​​may be detected and errors may be notified during non-face-to-face training, similar to the processing in Fig. 12. In such cases, control may be performed to stop the operation of the robot, which is the assist device 400, or to change the method of assistance provided by the assistant.

[0151] 13 has been described as processing by the non-face-to-face training management server 100, a configuration may also be adopted in which some of the processing is performed by the trainee terminal 300. For example, the control of the auxiliary device 400 may be synchronized with the playback of training content, and the trainee terminal 300 may control the auxiliary device 400 based on a control signal associated with the training content.

[0152] As described above, this embodiment makes it possible to improve the convenience of implementing non-face-to-face training, for example, the convenience of managing support results for non-face-to-face training, evaluating results, providing appropriate support, reducing the workload of support work, and the like.

[0153] [Variations] It is expected that each training item used in non-face-to-face training will be adjusted according to the trainee. For example, the following forms can be mentioned. - If a certain training menu is highly rated, the load of the training items included in the training menu is increased. - If some of the training items among multiple training items included in a certain training menu are poorly rated, that training item is changed to another training item. - In training related to speech, the training content (speech content) is adjusted to suit the trainee's condition in order to produce the intended speech (speech that is easy for a third party to hear).

[0154] It is also envisioned that the unit performance data included in the training performance data is automatically evaluated and the evaluation results are presented to the instructor. An AI model based on machine learning technology can be utilized to adjust such training menus and evaluate the training performance data. For example, a learning process based on deep learning or the like can be performed to construct an AI model (trained model) that outputs desired output data for input data. Since there are various learning algorithms, learning methods, and learning data for generating an AI model, they are not limited to those described below and may be adjusted as appropriate.

[0155] In this modification, among the above-mentioned use cases of the AI ​​model, training related to speech will be described as an example. When other use cases are assumed, learning methods and learning data according to input and output are used.

[0156] An AI model performs inference processing based on input data and outputs the desired output data. AI models are trained to produce more appropriate output using machine learning, deep learning, Bayesian modeling optimization, etc. This phase is divided into a "learning phase" for building an AI model and an "inference phase" for using the built AI model.

[0157] FIG. 14A is a conceptual diagram illustrating the learning phase for constructing an AI model according to this embodiment. A pair of training performance data 1401 and training content 1402 corresponding to a training event is used as learning data 1400 for the learning process. The training content 1402 is defined according to the content of the training event, such as video data, audio data, or text data. The learning data 1400 may be prepared manually or may be automatically generated during the processing sequence shown in FIG. 4. Because the learning process generally involves a high processing load, it is desirable to perform the learning process at a timing separate from the processing sequence shown in FIG. 4 .

[0158] For convenience, an AI model in the middle of the learning process will be referred to as a "learning model," and an AI model whose learning process has progressed to a certain extent will be referred to as a "trained model." The degree of learning is not particularly limited and may be arbitrary. Furthermore, depending on the degree of learning, different output data may be obtained from the AI ​​model even with the same input data. In this example, the input to the learning model 1403 is training content 1402 corresponding to the training event. Furthermore, the output from the learning model 1403 is modified training content (hereinafter referred to as "modified content").

[0159] As described above, in this example, training related to speech is assumed, and therefore the training content 1402 is assumed to be voice data. Note that the data is not limited to voice data, and may be, for example, text data indicating the content of the speech. Furthermore, the training performance data 1401 paired with the training content 1402 is voice data resulting from speech made by a trainee with reference to the training content 1402.

[0160] When training performance data 1401 and training content 1402 are input to a learning model 1403, modified content 1404 is output. A difference determination process 1405 is performed between this modified content 1404 and the learning data 1400, and a parameter adjustment process 1406 of the learning model 1403 is repeated depending on the result, thereby progressing the learning process.

[0161] In difference determination processing 1405, the difference between the training performance data 1401 and the training content 1402 (for convenience, referred to as "difference A") and the difference between the training content 1402 and the modified content 1404 (for convenience, referred to as "difference B") are determined. Then, in parameter adjustment processing 1406, the parameters of the learning model 1403 are adjusted so that difference A and difference B determined in difference determination processing 1405 approach each other.

[0162] In this example, difference A is the difference between the training content and the result of speech produced by a trainee with reference to the training content. Difference B is the difference between the training content and the corrected content corrected by the learning model 1403. Based on these differences, the speech content shown in the training content tailored to the speaker is adjusted. In other words, the sounds shown in the training content (i.e., the sounds that the speaker is expected to utter) are adjusted so that the sounds uttered by the speaker (trainee) approach the target sounds (i.e., sounds that a third party listening to the speaker can easily recognize as having a predetermined meaning).

[0163] For example, suppose that trainee A refers to "arigatou (thank you)" shown in the training content and speaks, resulting in "aiatou (love you)." In response to this, the training content is adjusted so that trainee A's speech results in "arigatou (thank you)." For example, taking into account the characteristics of trainee A's speech, the adjusted training content may be adjusted to "atigotou (atigotou)." The learning process is carried out assuming such an output.

[0164] 14B is a conceptual diagram illustrating the inference phase that uses an AI model according to this embodiment. A trained model 1413 constructed in the learning phase shown in FIG. 14A is used. Note that the degree of learning is not particularly limited, and a trained model 1413 that has undergone a certain level of learning processing may be used.

[0165] Collected data 1410 is obtained by pairing training performance data 1411 of a certain trainee with training content 1412 when the training performance data 1411 was collected. The collected data 1410 can be obtained, for example, in step S413 of Fig. 4. By inputting this collected data 1410 into a trained model 1413, it is possible to generate training content 1414 adjusted to suit the target trainee.

[0166] (Training Data Adjustment Process) FIG. 15 is a flowchart showing the process flow for adjusting training content based on the trainee's training performance data in non-face-to-face training according to this embodiment. Here, as described with reference to FIGS. 14A and 14B, the training content is adjusted using an AI model obtained through the learning process. This process flow may be executed under the instruction of an instructor as part of step S404 in FIG. 4. This process flow is realized, for example, by the control unit 110 of the non-face-to-face training management server 100 reading and executing programs and various data stored in the memory unit 130. For ease of explanation, the non-face-to-face training management server 100 will be described as the processing entity.

[0167] In step S1501, the non-face-to-face training management server 100 acquires training performance data of the target trainee. The trainee here may be designated by the instructor, or all trainees may be included.

[0168] In step S1502, the non-face-to-face training management server 100 acquires an evaluation of the training performance data acquired in step S1501. The evaluation here may be an evaluation value obtained by an instructor, or may be performed using the AI ​​model for evaluation as described above. Furthermore, the evaluation here may be an evaluation of the entire training performance data, or an evaluation of each unit performance data included in the training performance data.

[0169] In step S1503, the non-face-to-face training management server 100 determines whether the evaluation obtained in step S1502 is below a predetermined threshold. The threshold here is assumed to be predefined and stored. The evaluation of the entire training performance data may be compared with the threshold, or individual unit performance data may be compared with the threshold. If the evaluation is below the threshold (step S1503: YES), the non-face-to-face training management server 100 proceeds to step S1504. On the other hand, if the evaluation is not below the threshold (step S1503: NO), this processing flow ends.

[0170] In step S1504, the non-face-to-face training management server 100 determines whether the training data corresponding to the training performance data can be adjusted using an AI model. For example, the non-face-to-face training management server 100 may determine whether the content of the training content corresponding to a training event, the combination of training events, or the load level of a training event can be adjusted. Information regarding whether adjustment is possible may be set for each training event. If one training performance data includes multiple unit performance data, this determination may be made for each training event corresponding to each of the multiple unit performance data. If adjustment using an AI model is possible (step S1504: YES), the non-face-to-face training management server 100 proceeds to step S1505. On the other hand, if adjustment using an AI model is not possible (step S1504: NO), this processing flow ends.

[0171] In step S1505, the non-face-to-face training management server 100 uses an AI model to adjust the training events that make up the training data corresponding to the training performance data. The adjustment may be a change in the combination of training items, an adjustment in the load level, or a change in the content of the training content as described above.

[0172] In step S1506, the non-face-to-face training management server 100 presents the training data adjusted in step S1505 to the instructor. The presentation method here is not particularly limited, but for example, the instructor terminal 200 may display a UI screen (not shown) so that the difference between the data before and after the change can be seen.

[0173] In step S1507, the non-face-to-face training management server 100 determines whether updating of training data is permitted based on an instruction from the instructor via the instructor terminal 200. If updating is permitted (step S1507: YES), the processing of the non-face-to-face training management server 100 proceeds to step S1508. On the other hand, if updating is not permitted (step S1507: NO), this processing flow ends.

[0174] In step S1508, the non-face-to-face training management server 100 updates the training data for the target trainee with the adjusted training data, and then ends this processing flow.

[0175] As described above, this modification makes it possible to adjust the training menu and training content according to the training performance of the trainee, thereby enabling more efficient non-face-to-face training.

[0176] Other Embodiments In the above embodiment, a configuration example was shown in which the instructor terminal 200 and the trainee terminal 300 send and receive data via the non-face-to-face training management server 100. However, the present invention is not limited to this, and a configuration in which some processing is directly exchanged between the instructor terminal 200 and the trainee terminal 300 may also be used. In this case, for example, it is possible to reduce the processing load on the non-face-to-face training management server 100 and suppress the amount of data communication via the non-face-to-face training management server 100.

[0177] Furthermore, the various data (training performance data, etc.) stored in the above-described embodiment are expected to be used in various ways related to non-face-to-face training. For example, if the non-face-to-face training is related to medical care, the data may be used as the basis for claiming medical expenses. Furthermore, if the non-face-to-face training is related to learning, the data may be used as the basis for calculating learning time. The use of the data collected in this way is not particularly limited, and the data may be used differently depending on the type and content of the non-face-to-face training.

[0178] Furthermore, in the present invention, a program or application for realizing the functions of one or more of the above-described embodiments can be supplied to a system or device using a network or a storage medium, etc., and one or more processors in the computer of the system or device can read and execute the program.

[0179] Alternatively, the functions may be realized by a circuit that realizes one or more functions (for example, an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array)).

[0180] Although various embodiments have been described above with reference to the drawings, it goes without saying that the present disclosure is not limited to these examples. It is clear to those skilled in the art that various modifications, alterations, substitutions, additions, deletions, and equivalents may be made within the scope of the claims, and it is understood that these also fall within the technical scope of the present disclosure. Furthermore, the components of the various embodiments described above may be combined in any manner without departing from the spirit of the invention.

[0181] As such, the present invention is not limited to the above-described embodiments, and the present invention also contemplates the mutual combination of the various components of the embodiments, as well as modifications and applications by those skilled in the art based on the description in the specification and well-known techniques, and these modifications and applications are included in the scope of protection sought.

[0182] This application is based on a Japanese patent application (Patent Application No. 2024-042490) filed on March 18, 2024, the contents of which are incorporated herein by reference.

[0183] As described above, the present specification discloses the following:

[0184] (Technology 1) A non-face-to-face training management system (e.g., 1, 100) communicatively connected to an instructor terminal (e.g., 200) and a trainer terminal (e.g., 300) via a network (e.g., NW), the non-face-to-face training management system having: an instruction receiving unit (e.g., 110, 113, 114, 123) that receives instructions for training to be performed by a user of the trainer terminal via the instructor terminal; a providing unit (e.g., 110, 113, 123) that provides one or more training contents to the trainer terminal based on the instructions; a collecting unit (e.g., 110, 112, 123) that collects training performance data indicating training actions of the user of the trainer terminal when the one or more training contents are provided via the trainer terminal; and a memory unit (e.g., 110, 111, 115) that records the training performance data in association with the configuration of the one or more training contents. This configuration makes it possible, for example, to improve convenience in implementing non-face-to-face training. Specifically, it will be possible to improve convenience in terms of non-face-to-face training support performance management, performance evaluation, appropriate support provision, and reduction of support work load.

[0185] (Technology 2) The non-face-to-face training management system according to Technology 1 further includes a selection receiving unit (e.g., 110, 111, 113, 123) that selectably presents at least a portion of the training performance data corresponding to the configuration of the one or more training contents via the instructor terminal, and a performance display unit (e.g., 110, 111, 113, 118, 123) that displays at least a portion of the training performance data selected by the selection receiving unit on the instructor terminal. This configuration allows, for example, a non-face-to-face training instructor to easily check performance data for the non-face-to-face training.

[0186] (Technology 3) The non-face-to-face training management system according to Technology 2, wherein the performance display unit displays an evaluation of at least a portion of the training performance data via the instructor terminal in a manner that allows the evaluation to be accepted, and the storage unit stores the evaluation of at least a portion of the training performance data in association with the training performance data. With this configuration, it becomes possible to accept and manage evaluations made for some or all of the instructed non-face-to-face training, for example.

[0187] (Technology 4) The non-face-to-face training management system according to Technology 3 further includes an adjustment unit (e.g., 110, 117, 119, 120) that adjusts at least a portion of the training content corresponding to the training performance data based on an evaluation of at least a portion of the training performance data. With this configuration, for example, it becomes possible to adjust the training content of the training events that make up the non-face-to-face training according to the evaluation results of the non-face-to-face training. Therefore, it becomes possible to present candidates for training content that are appropriate for the trainee.

[0188] (Technology 5) The non-face-to-face training management system according to any one of Technology 1 to Technology 4, further comprising: an evaluation unit (e.g., 110, 116) that evaluates the training performance data; and an evaluation presentation unit (e.g., 110, 118) that presents the evaluation results by the evaluation unit to at least one of the instructor terminal and the trainee terminal. With this configuration, for example, it becomes possible to automatically evaluate non-face-to-face training and present the evaluation results to the instructor of the non-face-to-face training. Therefore, it becomes possible to support the instructor's evaluation work of non-face-to-face training and reduce the evaluation burden.

[0189] (Technology 6) The non-face-to-face training management system according to any one of Technologies 1 to 5, further comprising a device control unit (e.g., 110, 121, 123) that is communicatively connected to an assisting device (e.g., 400) that assists the training of a user using the trainee terminal, and that controls the operation of the assisting device so as to assist the training movements of the user using the trainee terminal in accordance with the content of the training content when the training content is being provided. This configuration enables control that assumes passive exercise as non-face-to-face training, for example. Furthermore, it becomes possible to control the assisting device when performing passive exercise in synchronization with the training content.

[0190] (Technology 7) The non-face-to-face training management system according to any one of Technology 1 to Technology 6, wherein the providing unit provides the trainee terminal with training content for both the user who performs training based on the instructions and an assistant who assists the user in his / her training movements. With this configuration, for example, it becomes possible to present separate training content related to non-face-to-face training to not only the trainee who performs passive exercise, but also the assistant who performs the passive exercise. This makes it possible to provide non-face-to-face training with a wider range of applications.

[0191] (Technology 8) The non-face-to-face training management system according to any one of Technology 1 to Technology 7, further comprising a content adjustment unit (e.g., 110, 122) that adjusts the content of the predetermined training content based on predetermined training content and training performance data obtained from training actions performed by the user in accordance with the predetermined training content so that the results of the training actions by the user are closer to the content of the predetermined training content. With this configuration, it is possible to adjust the content of the training content in non-face-to-face training, for example, in accordance with the training performance of the trainee.

[0192] (Technology 9) The non-face-to-face training management system according to Technology 8, wherein the predetermined training content is training content related to pronunciation, and the content adjustment unit adjusts the first training content to a second training content based on training performance data of the user's pronunciation in accordance with the first training content related to pronunciation so that the user's pronunciation approaches the pronunciation of the first training content. This configuration makes it possible to adjust the content of the training content according to the trainee's characteristics, for example, in non-face-to-face training related to speech. It also makes it possible to adjust the training content so that the trainee's output is the intended output.

[0193] (Technology 10) The non-face-to-face training management system according to Technology 8 or Technology 9, wherein the content adjustment unit adjusts the training content to suit the user using an AI (Artificial Intelligence) model that receives as input the predetermined training content and training performance data obtained from training actions performed by the user in accordance with the predetermined training content and outputs the adjusted training content. With this configuration, it is possible to adjust the training content to suit the trainee, for example, by using an AI model based on learning data configured from pairs of training data and training performance data.

[0194] (Technology 11) The non-face-to-face training management system according to any one of Technology 1 to Technology 10, wherein the training content is composed of one or more sets of one or more training events. With this configuration, it is possible to implement non-face-to-face training that assumes a training menu composed of various training events, for example.

[0195] (Technology 12) The non-face-to-face training management system according to any one of Technology 1 to Technology 11, wherein the training performance data includes at least one of moving image data, still image data, audio data, operation data, biometric data, and processed data obtained by processing raw data detected by a sensor. With this configuration, for example, it becomes possible to collect various types of data as evidence of the performance of non-face-to-face training.

[0196] (Technology 13) The non-face-to-face training management system according to any one of Technology 1 to Technology 12, wherein the training content is composed of at least one of moving image data, still image data, audio data, and character data. With this configuration, it is possible to provide various types of data as training content for training events that constitute non-face-to-face training, for example.

[0197] (Technology 14) A control method for a non-face-to-face training management system (e.g., S1, 100) communicatively connected to an instructor terminal (e.g., 200) and a trainer terminal (e.g., 300) via a network (e.g., NW), the control method comprising: an instruction receiving step (e.g., S404) of receiving, via the instructor terminal, instructions for training to be performed by a user of the trainer terminal; a providing step (e.g., S410) of providing one or more training contents to the trainer terminal based on the instructions; a collecting step (e.g., S413) of collecting, via the trainer terminal, training performance data indicating training actions of the user of the trainer terminal when the one or more training contents are being provided; and a storing step (e.g., S413, S414) of recording the training performance data in a storage unit (e.g., 130) in association with the configuration of the one or more training contents. This configuration makes it possible, for example, to improve convenience in conducting non-face-to-face training. Specifically, it will be possible to improve convenience in terms of non-face-to-face training support performance management, performance evaluation, appropriate support provision, and reduction of support work load.

[0198] (Technology 15) A program for causing a computer (e.g., 100) communicatively connected to an instructor terminal (e.g., 200) and a trainer terminal (e.g., 300) via a network (e.g., NW) to execute the following: an instruction receiving step (e.g., S404) of receiving, via the instructor terminal, instructions for training to be performed by a user of the trainer terminal; a providing step (e.g., S410) of providing one or more training contents to the trainer terminal based on the instructions; a collecting step (e.g., S413) of collecting training performance data indicating training actions of the user of the trainer terminal when the one or more training contents are being provided via the trainer terminal; and a storing step (e.g., S413, S414) of recording the training performance data in a storage unit (e.g., 130) in association with the configuration of the one or more training contents. This configuration, for example, can improve convenience in conducting non-face-to-face training. Specifically, it can improve convenience in non-face-to-face training support performance management, performance evaluation, appropriate support provision, and support work load reduction.

[0199] The present invention is useful, for example, as an apparatus, system, and method for improving the convenience of conducting non-face-to-face training.

[0200] 1...Non-face-to-face training management system 100...Non-face-to-face training management server 110...Control unit 111...Data management unit 112...Data collection unit 113...Display control unit 114...Training data setting unit 115...Actual data extraction unit 116...Training performance evaluation unit 117...Data analysis unit 118...Feedback generation unit 119...Training menu determination unit 120...Training menu adjustment unit 121...Assist device control unit 122...Learning processing unit 123...Communication control unit 130...Memory unit 131...Program 132...Trainer DB 133...Instructor DB 134...Training event DB 135...Training data DB 136...Training performance DB 137...Assist device DB 138...AI model DB 140...Communication unit 200...Instructor terminal 210...Control unit 220...Memory unit 230...Operation unit 240 display unit 250 communication unit 260 external IF 300 trainee terminal 310 control unit 320 storage unit 330 operation unit 340 display unit 350 communication unit 360 camera 370 sensor 380 external IF 400 auxiliary device

Claims

1. A non-face-to-face training management system that is communicatively connected to an instructor terminal and a trainer terminal via a network, comprising: an instruction receiving unit that receives, via the instructor terminal, instructions for training to be conducted by a user of the trainer terminal; a providing unit that provides one or more training contents to the trainer terminal based on the instructions; a collecting unit that collects training performance data that indicates the training actions of the user of the trainer terminal when the one or more training contents are being provided via the trainer terminal; and a memory unit that records the training performance data in association with the configuration of the one or more training contents.

2. A non-face-to-face training management system as described in claim 1, further comprising: a selection receiving unit that selectably presents at least a portion of the training performance data corresponding to the configuration of the one or more training contents via the instructor terminal; and a performance display unit that displays at least a portion of the training performance data selected by the selection receiving unit on the instructor terminal.

3. The non-face-to-face training management system described in claim 2, wherein the performance display unit displays an evaluation of at least a portion of the training performance data via the instructor terminal in a manner that allows the evaluation to be accepted, and the memory unit stores the evaluation of at least a portion of the training performance data in association with the training performance data.

4. The non-face-to-face training management system according to claim 3, further comprising an adjustment unit that adjusts at least a portion of the training content corresponding to the training performance data based on an evaluation of at least a portion of the training performance data.

5. The non-face-to-face training management system according to claim 1, further comprising: an evaluation unit that evaluates the training performance data; and an evaluation presentation unit that presents the evaluation results by the evaluation unit to at least one of the instructor terminal and the trainee terminal.

6. The non-face-to-face training management system according to claim 1, further comprising a device control unit that is communicatively connected to an auxiliary device that assists the training of the user using the trainer terminal, and that controls the operation of the auxiliary device so as to assist the training actions of the user using the trainer terminal in accordance with the content of the training content when the training content is being provided.

7. A non-face-to-face training management system as described in claim 1, wherein the providing unit provides the trainee terminal with training content for the user who performs training based on the instructions and for an assistant who assists the user's training movements.

8. A non-face-to-face training management system as described in claim 1, further comprising a content adjustment unit that adjusts the content of the specified training content based on specified training content and training performance data obtained from training actions performed by the user in accordance with the specified training content so that the results of the training actions performed by the user are closer to the content of the specified training content.

9. The non-face-to-face training management system described in claim 8, wherein the specified training content is training content related to pronunciation, and the content adjustment unit adjusts the first training content to second training content based on training performance data of the user's pronunciation in accordance with first training content related to pronunciation so that the user's pronunciation approaches pronunciation equivalent to that of the first training content.

10. The non-face-to-face training management system described in claim 8, wherein the content adjustment unit adjusts the content of the training content to suit the user using an AI (Artificial Intelligence) model that receives as input the specified training content and training performance data obtained from training actions performed by the user in accordance with the specified training content and outputs the adjusted training content.

11. The non-face-to-face training management system according to claim 1, wherein the training content is configured as one or more sets of one or more training events.

12. The non-face-to-face training management system of claim 1, wherein the training performance data includes at least one of video data, still image data, audio data, operation data, biometric data, and processed data processed from raw data detected by a sensor.

13. The non-face-to-face training management system according to claim 1, wherein the training content is composed of at least one of moving image data, still image data, audio data, and text data.

14. A control method for a non-face-to-face training management system that is communicatively connected to an instructor terminal and a trainer terminal via a network, comprising: an instruction receiving step of receiving, via the instructor terminal, instructions for training to be carried out by a user of the trainer terminal; a providing step of providing, based on the instructions, one or more training contents to the trainer terminal; a collecting step of collecting, via the trainer terminal, training performance data that indicates the training actions of the user of the trainer terminal when the one or more training contents are being provided; and a storage step of recording the training performance data in a storage unit in association with the configuration of the one or more training contents.

15. A program for causing a computer communicatively connected to an instructor terminal and a trainer terminal via a network to execute the following steps: an instruction receiving step for receiving, via the instructor terminal, instructions for training to be performed by the user of the trainer terminal; a provision step for providing, based on the instructions, one or more training contents to the trainer terminal; a collection step for collecting, via the trainer terminal, training performance data indicating the training actions of the user of the trainer terminal when the one or more training contents are being provided; and a storage step for recording the training performance data in a storage unit in association with the configuration of the one or more training contents.

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