Information processing device, information processing method, program, and information processing system

Abstract

To provide an information processing device, an information processing method, a program, and an information processing system capable of presenting preventive action proposals before the body condition of a user worsens, and keeping the body condition of the user in a good health.SOLUTION: An information processing device includes a body condition information acquisition part that acquires body condition information of a user, a body condition information prediction part that predicts occurrence of a body condition disorder on the basis of the body condition information, and an action proposal information generation part that generates, for each user, action proposal information for enabling the user to avoid the body condition disorder on the basis of user information when occurrence of a body condition disorder is predicted.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an information processing device, an information processing method, a program, and an information processing system. [Background technology]

[0002] In recent years, the decline in the labor force due to the declining birthrate has become a serious social issue, leading to an increasing demand for technology that enables efficient working methods. In addition, attention is being paid to increasing self-efficacy and job satisfaction by supporting the creation of an environment where workers can continuously demonstrate their abilities. Therefore, technology is being considered that suggests actions to be taken to improve the situation based on the worker's physical condition and level of fatigue.

[0003] Patent Document 1 discloses a mood change support device that presents to a user tasks that are likely to provide a mood change for the user with the aim of improving productivity. This mood change support device determines whether a mood change is necessary based on the user's state, and if it determines that a mood change is necessary, presents to the user tasks that will directly contribute to productivity and are likely to provide a mood change for the user.

[0004] Patent document 2 discloses a fatigue recovery support device that estimates the contribution of at least one of sleep and behavior to fatigue recovery for the purpose of recovering from fatigue, and presents to the user at least one of sleep conditions and behavior suitable for fatigue recovery based on the estimation results.

[0005] Patent document 3 describes an information processing device that includes a biometric information fluctuation prediction unit that predicts fluctuations in biometric information from sensor information according to a framework based on knowledge about the user's poor health and predicts the occurrence of poor health based on the fluctuations in the biometric information, and an action support information generation unit that generates action support information for the user to avoid the occurrence of poor health when the occurrence of poor health is predicted. Summary of the Invention [Problem to be solved by the invention]

[0006] However, the above-mentioned technology does not take into account the user's future physical condition when creating action suggestions and when determining the timing of making action suggestions.As a result, it is not possible to provide sufficient preventive action suggestions before the user's physical condition deteriorates, making it difficult to maintain the user's condition in good condition.

[0007] The present invention has been made in consideration of the above, and aims to provide an information processing device, an information processing method, a program, and an information processing system that can present preventive action suggestions before a user's health condition deteriorates, thereby maintaining the user's health condition. [Means for solving the problem]

[0008] In order to solve the above-mentioned problems and achieve the objectives, the present invention comprises a health information acquisition unit that acquires health information of a user, a health information prediction unit that predicts the occurrence of poor health based on the health information, and an action suggestion information generation unit that generates action suggestion information for each user based on the user information when the occurrence of poor health is predicted, to help the user avoid the poor health. [Effects of the Invention]

[0009] According to the present invention, it is possible to provide a preventive action suggestion before the user's physical condition deteriorates, thereby enabling the user to maintain good physical condition. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram illustrating a configuration of an action suggestion system according to the first embodiment. [Figure 2] FIG. 2 is a diagram illustrating an example of a hardware configuration of the action suggestion device according to the first embodiment. [Figure 3] FIG. 3 is a diagram illustrating an example of a hardware configuration of the user terminal according to the first embodiment. [Figure 4]FIG. 4 is a diagram illustrating an example of a functional configuration of the action suggestion system according to the first embodiment. [Figure 5] FIG. 5 shows an example of various processes performed by the action suggestion system according to the first embodiment and events that trigger the various processes. [Figure 6] FIG. 6 is a diagram for explaining details of the process of registering basic user information of a new user and performing login authentication in the action suggestion system according to the first embodiment. [Figure 7] FIG. 7 is a diagram for explaining details of the process of performing login authentication in the action suggestion system according to the first embodiment. [Figure 8] FIG. 8 is a diagram illustrating an example of details of the process of acquiring physical condition information and executing action suggestions in the action suggestion system according to the first embodiment. [Figure 9] FIG. 9 is a diagram illustrating an example of details of a process for creating an action proposal schedule based on physical condition prediction in the action proposal system according to the first embodiment. [Figure 10] FIG. 10 is a diagram illustrating an example of details of a process for executing an action proposal according to an action proposal schedule in the action proposal system according to the first embodiment. [Figure 11] Figure 11 is a diagram showing an example of a screen displayed to a user by a display control unit when a user terminal acquires health information and supplementary information through user input during the process of acquiring health information and executing action suggestions in the action suggestion system according to the first embodiment. [Figure 12] Figure 12 is a diagram showing an example of a screen displayed to a user by a display control unit on a user terminal to present action suggestion information to the user during the process of acquiring physical condition information and executing action suggestions in the action suggestion system according to the first embodiment. [Figure 13] Figure 13 is a diagram showing an example of a screen displayed to a user by a display control unit in a user terminal to present action suggestion information to the user during the process of executing an action suggestion in accordance with an action suggestion schedule in the action suggestion system according to the first embodiment. [Figure 14] Figure 14 is a diagram showing an example of a screen that a user terminal presents to a user in order to obtain behavioral feedback information through user input in the process of obtaining physical condition information and executing behavioral suggestions in the behavior suggestion system according to the first embodiment, and in the process of executing behavioral suggestions according to a behavioral suggestion schedule. [Figure 15] FIG. 15 is a diagram illustrating an example of a configuration of an action suggestion system according to the second embodiment. [Figure 16] FIG. 16 is a diagram illustrating a configuration of an action suggestion system according to the third embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of an information processing device, an information processing method, a program, and an information processing system will be described in detail with reference to the accompanying drawings.

[0012] (First embodiment) FIG. 1 is a diagram illustrating a configuration of an action suggestion system according to a first embodiment. The action suggestion system is an example of an information processing system that makes suggestions corresponding to user actions. In this embodiment, the action suggestion system includes an action suggestion device 1 (an example of an information processing device) and a user terminal 2 (an example of a terminal device), which are interconnected via a network. The network is a network through which an unspecified number of people communicate, and is constructed using the Internet, a LAN (Local Area Network), or the like. The user terminal 2 and the action suggestion device 1 can access the Internet via the network and can obtain information published on the Internet. In this embodiment, the action suggestion device 1 and the user terminal 2 function as examples of information processing devices, but this is not limiting; either the action suggestion device 1 or the user terminal 2 may function as an example of an information processing device.

[0013] The action suggestion device 1 is a device that makes suggestions for user actions, and is, for example, a server. The action suggestion device 1 includes a CPU (Central Processing Unit), a main memory device, an auxiliary memory device, a network I / F, etc. The action suggestion device 1 may be realized by one or more information processing devices equipped with a general server OS (Operating System), etc., or may be realized as a virtual server on one or more information processing devices using hardware virtualization technology, or may be realized as a server built on IaaS or PaaS provided by a cloud vendor.

[0014] The action suggestion device 1 can send and receive data to and from the user terminal 2 via a network. The action suggestion device 1 can communicate by receiving a request from the user terminal 2 and returning a result. In addition, the action suggestion device 1 can unilaterally send data to the user terminal 2. This can be done, for example, by sending data via email or by push notification.

[0015] The user terminal 2 is a terminal used by a user, such as a PC or a smartphone. The user terminal 2 includes a CPU, a main memory device, an auxiliary memory device, a network I / F, an input device, a video output device, an audio output device, etc. Note that multiple users may use the same user terminal 2 if the user terminal 2 has a function to individually identify multiple users. On the other hand, the user terminal 2 may be configured such that one user terminal 2 is assigned to each user.

[0016] Fig. 2 is a diagram illustrating an example of the hardware configuration of the action suggestion device 1 according to the first embodiment. As illustrated in Fig. 2, the action suggestion device 1 is constructed, for example, by a computer and includes a CPU 201, a ROM 202, a RAM 203, an EEPROM 204, a hard disk (HD) 205, a hard disk drive (HDD) controller 206, a display 207, a short-range communication I / F 208, a CMOS sensor 209, and an image sensor I / F 210. The action suggestion device 1 further includes a network I / F 211, a keyboard 212, a pointing device 213, a media I / F 215, an external device connection I / F 216, an audio input / output I / F 217, a microphone 218, a speaker 219, and a bus line 220.

[0017] Of these, the CPU 201 controls the overall operation of the action suggestion device 1. The ROM 202 stores programs and the like used to drive the CPU 201. The RAM 203 is used as a work area for the CPU 201. The EEPROM 204 reads or writes various data such as applications under the control of the CPU 201. The HD 205 stores various data such as programs. The HDD controller 206 controls the reading or writing of various data from or to the HD 205 under the control of the CPU 201. Here, the action suggestion device 1 may have a hardware configuration in which an SSD (Solid State Drive) is installed instead of the HD 205 and the HDD controller 206. The display 207 displays various information such as a cursor, menus, windows, characters, or images. In this embodiment, the display 207 functions as an example of display means. The short-range communication I / F 208 is a communication circuit for performing data communication with a communication device or communication terminal equipped with a wireless communication interface such as NFC (Near Field Communication), Bluetooth (registered trademark, omitted hereinafter), or Wi-Fi (registered trademark, omitted hereinafter). The CMOS sensor 209 is a type of built-in imaging means that captures an image of a subject under the control of the CPU 201 to obtain image data or video data. Note that the imaging means may be an imaging means configured as a CCD (Charge Coupled Device) sensor or the like, rather than a CMOS sensor. The imaging element I / F 210 is a circuit that controls the driving of the CMOS sensor 209.

[0018] The network I / F 211 is an interface for data communication using the communication network 100. The keyboard 212 is a type of input means having multiple keys for inputting characters, numbers, various instructions, etc. Note that, instead of or in addition to the keyboard 212, an input means such as a touch panel for operating predetermined buttons, icons, etc. may be used. The pointing device 213 is a type of input means for selecting and executing various instructions, selecting a processing target, moving a cursor, etc. The media I / F 215 controls reading and writing (storing) data from and to a recording medium 214 such as a flash memory. The external device connection I / F 216 is an interface for connecting various external devices and is connected to the user terminal 2 using a dedicated wired cable. Note that the external device may be a USB (Universal Serial Bus) memory, etc. The audio input / output I / F 217 is a circuit for processing input and output of audio signals between a microphone 218 and a speaker 219 under the control of the CPU 201. The microphone 218 is a built-in circuit that converts sound into an electrical signal and acquires information using the electrical signal by capturing voice or sound waves emitted from an external speaker or the like. The speaker 219 is a built-in circuit that converts the electrical signal into physical vibrations to produce sounds such as music or voice. The bus line 220 is an address bus, data bus, or the like that electrically connects the components such as the CPU 201.

[0019] Fig. 3 is a diagram illustrating an example of the hardware configuration of a user terminal according to the first embodiment. As illustrated in Fig. 3, the user terminal 2 is constructed, for example, by a computer, and includes a CPU 301, a ROM 302, a RAM 303, an EEPROM 304, a display 307, a near-field communication I / F 308, a CMOS sensor 309, and an image sensor I / F 310. The user terminal 2 further includes a network I / F 311, a touch panel 312, a pointing device 313, a media I / F 315, an external device connection I / F 316, an audio input / output I / F 317, a microphone 318, a speaker 319, and a bus line 320.

[0020] Of these, the CPU 301 controls the overall operation of the user terminal 2. The ROM 302 stores programs and the like used to drive the CPU 301. The RAM 303 is used as a work area for the CPU 301. The EEPROM 304 reads and writes various data such as applications under the control of the CPU 301. The EEPROM 304 stores various setting data (information) and the like. Here, the user terminal 2 may have a hardware configuration equipped with an SSD (Solid State Drive) instead of the EEPROM 304. The display 307 displays various information such as a cursor, menus, windows, characters, or images. In this embodiment, the display 307 functions as an example of a display unit. The short-range communication I / F 308 is a communication circuit for performing data communication with a communication device or communication terminal equipped with a wireless communication interface such as NFC (Near Field Communication), Bluetooth (registered trademark, omitted below), or Wi-Fi (registered trademark, omitted below). The CMOS sensor 309 is a type of built-in imaging means that captures an image of a subject and obtains image data or video data under the control of the CPU 301. The imaging means may be an imaging means configured with a CCD (Charge Coupled Device) sensor or the like instead of a CMOS sensor. The imaging element I / F 310 is a circuit that controls the driving of the CMOS sensor 309.

[0021] The network I / F 311 is an interface for data communication using the communication network 100. The touch panel 312 is a type of input device equipped with multiple keys for inputting characters, numbers, various instructions, etc. Note that, instead of or in addition to the touch panel 312, an input device such as a keyboard for operating predetermined buttons, icons, etc. may be used. The pointing device 313 is a type of input device for selecting and executing various instructions, selecting a processing target, moving a cursor, etc. The media I / F 315 controls the reading and writing (storage) of data from and to a recording medium 314 such as a flash memory. The external device connection I / F 316 is an interface for connecting various external devices and is connected to other devices or communication terminals using a dedicated wired cable. Note that the external device may be a USB (Universal Serial Bus) memory, etc. The audio input / output I / F 317 is a circuit that processes the input and output of audio signals between a microphone 318 and a speaker 319 under the control of the CPU 301. The microphone 318 is a built-in circuit that converts sound into an electrical signal and acquires information using the electrical signal by capturing voice or sound waves emitted from an external speaker or the like. The speaker 319 is a built-in circuit that converts the electrical signal into physical vibrations to produce sounds such as music or voice. The bus line 320 is an address bus, data bus, or the like that electrically connects the components such as the CPU 301.

[0022] The program may be recorded on a computer-readable recording medium as an installable or executable file, or may be distributed by downloading it over a network. Examples of recording media include CD-Rs (Compact Disc Recordables), DVDs (Digital Versatile Disks), Blu-ray Discs (Blu-ray is a registered trademark; omitted below), SD cards, and USB memory sticks. The recording media may be provided domestically or internationally as a program product.

[0023] 4 is a diagram showing an example of the functional configuration of the action suggestion system according to the first embodiment. In this embodiment, the action suggestion device 1 includes a transmitting / receiving unit 101, an acquiring unit 102, a calculation processing unit 103, a predicting unit 104, a determining unit 105, a suggestion generating unit 106, a memory reading unit 107, and a memory unit 108. These are functions or means realized by cooperative operation of devices constituting the hardware in response to instructions from a CPU 201 that operates according to a program.

[0024] The transmitting / receiving unit 101 is realized by the processing of the CPU 201 on the network I / F 211, and transmits and receives various data to and from the user terminal 2 and the Internet via the network.

[0025] The acquisition unit 102 is mainly realized by the processing of the CPU 201, and acquires various data as needed using the memory / readout unit 107 and the transmission / reception unit 101. Specifically, the acquisition unit 102 functions as an example of a physical condition information acquisition unit that acquires physical condition information indicating the physical condition of the user. Here, the physical condition information acquisition unit may acquire physical condition information accepted by an input acceptance means, or may acquire physical condition information from sensor information including the user's biological information. The acquisition unit 102 also functions as an example of an environment acquisition unit that acquires environmental information indicating the state of the environment (e.g., the environment around the user). The acquisition unit 102 also functions as an example of a feedback acquisition unit that acquires feedback information (action feedback information) in response to action suggestion information. Here, the action suggestion information is information regarding an action suggested to the user. Furthermore, the acquisition unit 102 also functions as an example of a supplemental information acquisition unit that acquires supplemental information, which is information that may affect the relationship between the physical condition information and the environmental information.

[0026] The calculation processing unit 103 is mainly realized by the processing of the CPU 201, and generates a health condition estimation model based on the health condition information stored in the health condition history DB and the environmental information stored in the environmental history DB. That is, the calculation processing unit 103 functions as an example of a relationship calculation unit that calculates a health condition estimation model (an example of a relationship) between health condition information and environmental information based on at least one piece of health condition information and at least one piece of environmental information stored in a storage unit such as the health condition history DB and the environmental history DB. Specifically, the calculation processing unit 103 may calculate a health condition estimation model between the health condition information and environmental information specific to a user based on the health condition information and environmental information, some or all of which are associated with the user.

[0027] The prediction unit 104 is mainly realized by the processing of the CPU 201 and predicts health information at a certain time in the future based on a health information estimation model and environmental information acquired by the acquisition unit 102. This allows for more accurate prediction of health information by predicting health information based on accumulated information. For example, the prediction unit 104 may predict health information at a certain time in the future based on a health information estimation model, which is an example of the relationship between user-specific health information and environmental information, and the environmental information acquired by the acquisition unit 102. This allows for more accurate prediction of health information by taking into account the user's individual tendencies. Furthermore, the prediction unit 104 may predict health information at a certain time in the future based on supplementary information acquired by the acquisition unit 102. This allows for more accurate prediction of health information by taking into account third information that affects the relationship between health information and environmental information. That is, the prediction unit 104 functions as an example of a health information prediction unit that predicts fluctuations in health information from health information acquired by the acquisition unit 102 and predicts the occurrence of a user's illness (poor health) based on the fluctuations in health information.

[0028] The determination unit 105 is realized mainly by the processing of the CPU 201, and determines whether the acquired physical condition information and the predicted physical condition information indicate poor health. Here, the physical condition information indicating poor health means that the user's physical condition indicated by the physical condition information can be said to be in an undesirable state.

[0029] The proposal generator 106 is mainly realized by the processing of the CPU 201, and determines the time to execute a proposed action and the content of the proposed action mainly based on the physical condition information, and outputs the result as action proposal information. That is, the proposal generator 106 functions as an example of an action proposal information generator that, when a user's illness is predicted, generates, for each user, action proposal information for the user to avoid illness based on user information for user authentication received by the user terminal 2 or the like (an example of an input receiving means). Here, the user information is information for identifying the user, and in this embodiment, includes a user ID. Specifically, if it is determined that action proposal information should be generated based on the user ID, the proposal generator 106 generates the action proposal information, and if it is determined that action proposal information should not be generated based on the user ID, the proposal generator 106 does not generate the action proposal information.

[0030] Furthermore, when the physical condition information acquired by the acquisition unit 102 indicates that the user is in poor health, the suggestion generation unit 106 generates action suggestion information that suggests to the user that the user should take an action aimed at improving the poor health. Furthermore, when the physical condition information predicted by the prediction unit 104 indicates that the user is in poor health, the suggestion generation unit 106 generates action suggestion information that suggests to the user that the user should take an action aimed at preventing the poor health. Furthermore, the suggestion generation unit 106 may generate one piece of action suggestion information from among multiple candidates for action suggestion information based on the user ID. In this case, the suggestion generation unit 106 selects the action suggestion information to be generated based on the suitability of the candidate for action suggestion information for the user, which is calculated in advance. That is, the suggestion generation unit 106 may generate action suggestion information based on the suitability for each user, which is stored in the storage unit 108 (behavior suitability DB described later) in association with the user ID, an action ID (an ID identifying a candidate for action suggestion information), and an expected effect.

[0031] Furthermore, the calculation processing unit 103 adjusts the suitability of the action suggestion information for the user based on the action feedback information acquired by the acquisition unit 102. That is, the calculation processing unit 103 functions as an example of an update unit that updates the suitability of the action suggestion information for each user. As a result, by continuing to use the action suggestion system, the suitability can be brought closer to a correct value.

[0032] Furthermore, when the health information predicted by the prediction unit 104 indicates that the user is unwell, the proposal generation unit 106 specifies the proposed execution time (proposed action execution time) as a time that is earlier than the time predicted to occur when the unwell condition is subtracted from the time when the unwell condition is predicted to occur by at least one of the time required to perform the action included in the action proposal information and the time from the completion of the action until the effect of the action is produced.

[0033] The storage / reading unit 107 is realized by the processing of the CPU 201 on at least one storage unit 108 of the main storage device and the auxiliary storage device, and stores various data in the storage unit 108 and reads various data from the storage unit 108.

[0034] The storage unit 108 is an example of a storage unit that stores various types of information such as a user basic information DB, a physical condition history DB, an environmental history DB, a supplementary information history DB, an action DB, an action proposal schedule DB, and an action compatibility DB.

[0035] The user basic information DB stores and manages various information about users (user basic information), including the user's name, date of birth, occupation, age, gender, location, etc., in association with a user ID uniquely assigned to each user. The user ID may be anything that can uniquely identify each user, and may be a character string such as "U0101" or "U0102," or an email address, etc. The information stored and managed in the user basic information DB may include an identification code for identifying the user terminal 2 used by the user, so that data can be sent unilaterally from the action suggestion device 1 to the user terminal 2.

[0036] The health history DB stores and manages the health information acquired by the acquisition unit 102 up to now, along with the user ID and the time of acquisition.

[0037] The environment history DB stores and manages the environment information acquired by the acquisition unit 102 along with the acquisition time. If the environment information is related to a specific user, the environment history DB also stores and manages the user ID of the user.

[0038] The supplemental information history DB stores and manages the supplemental information acquired by the acquisition unit 102 up to now, along with the user ID and the acquisition time.

[0039] The action DB stores and manages candidate action suggestion information to be proposed to the user. As shown in Table 1 below, the action DB stores and manages action suggestion information including action content and the effects of the action, in association with an action ID uniquely assigned to each action. The action content may be a character string representing the action that the user should perform, or may be an image, video, audio, or a combination of these.

[0040] In this embodiment, the term "behavior" refers to anything in general, including how the user uses their time and their state of mind, and refers to something that the user performs to obtain some effect. It should be noted that actions that do not involve active movement, such as "daydreaming without doing anything" or "paying attention to one's breathing," are also referred to as "behavior." Examples of behavior include "warming the back of the ears with a hot towel" to prevent or alleviate a headache, and "doing 20 squats" to wake up from drowsiness and restore concentration.

[0041] The action proposal schedule DB stores and manages action proposal schedules to be performed for users. The action proposal schedule DB stores and manages information, including the user ID of the user to whom the action proposal is to be performed, the action ID of the action proposal information to be proposed, the time when the action proposal is to be performed, the time when the user's illness is predicted to occur, remarks, and whether the proposal has already been implemented, in association with an action proposal schedule ID uniquely assigned to each action proposal schedule. Here, the remarks are information presented to the user together with the proposed action content to provide additional information to the user when an action is proposed. An example of this is a character string indicating the reason why the action proposal device 1 decided to make an action proposal, such as "There is a high possibility that a 'headache' will occur from now on."

[0042] The behavioral compatibility DB stores and manages the compatibility of each candidate action suggestion information for each user. As shown in Table 2 below, the behavioral compatibility DB stores and manages information indicating the user ID, action ID, effect of the action, and the compatibility of the candidate action suggestion information having the action ID for the user having the user ID. Here, the compatibility of the candidate action suggestion information for the user represents the degree of expected effect that will occur when the user performs the action indicated by the action suggestion information. The effect of the action is also included in the information stored and managed in the behavioral compatibility DB along with the action ID in order to deal with cases where an action has multiple effects. A compatibility is assigned to each effect. [Table 1] [Table 2]

[0043] As the initial state of the degree of suitability, some default value (for example, "1") may be set, or the average value of a set of similar users may be set based on basic user information acquired in advance.

[0044] The advantages of varying the fitness for each user from the initial state are as follows: If a fixed default value is set, the user will not be able to enjoy the benefits of personal optimization at all soon after starting to use the system (the so-called cold start problem), but if the average value for a set of similar users is set as the initial state, it is possible to expect the system to operate with a certain degree of personal optimization from the beginning of its use.

[0045] In this embodiment, the user terminal 2 includes a transmission / reception unit 111, an operation reception unit 112, an acquisition unit 113, a display control unit 114, a storage / readout unit 115, and a storage unit 116. These are functions or means realized by the cooperative operation of devices constituting the hardware in accordance with instructions from a CPU 301 that operates according to a program.

[0046] The transmitting / receiving unit 111 is realized by the processing of the CPU 301 on the network I / F 311, and transmits and receives various data to and from the user terminal 2 and the Internet via the network.

[0047] The operation receiving unit 112 is realized by an input device, and receives input from the user.

[0048] The acquisition unit 113 is realized mainly by the processing of the CPU 301, and acquires various data as required using the storage / read unit 115 and the transmission / reception unit 111.

[0049] The display control unit 114 is mainly realized by the processing of the CPU 301 on at least one of the video output device and the audio output device, and controls the presentation of various screens and information to the user. Specifically, the display control unit 114 functions as an example of a display control unit that displays action suggestion information generated for the user on a display unit such as the display 307. As a result, if the user's physical condition is predicted to deteriorate, action suggestion information for preventing the deterioration of the user's physical condition can be presented to the user before the deterioration progresses. As a result, preventative action suggestion information can be presented to the user before the user's physical condition deteriorates, allowing the user's physical condition to be maintained in good condition. Furthermore, the display control unit 114 displays the action suggestion information generated for the user at the action suggestion execution time specified by the suggestion generation unit 106. This more reliably prevents illness.

[0050] The storage / reading unit 115 is realized by the processing of the CPU 301 on at least one of the main storage device and the auxiliary storage device, and stores various data in the storage unit 116 and reads various data from the storage unit 116 .

[0051] In the above, the functions of the action suggestion device 1 may be integrated into the user terminal 2, and the user terminal 2 may execute the processing of the action suggestion device 1 described below, or the user terminal 2 may have some of the functions of the action suggestion device 1, and the user terminal 2 may execute the processing of those some of the functions.

[0052] 5 shows an example of various processes performed by the action suggestion system according to the first embodiment and events that trigger these processes. First, an example of the processes performed when a user starts using the system will be described. When a new user whose basic user information has not yet been registered in the user basic information DB starts using the system, the action suggestion device 1 registers the new user's basic user information and performs login authentication (step S1). On the other hand, when a user whose basic user information has already been registered in the user basic information DB starts using the system, the action suggestion device 1 performs login authentication and identifies the user who has started using the system (step S2).

[0053] When either the new user registration process (step S1) or the login authentication process (step S2) is completed, the action suggestion device 1 can uniquely identify the user who is using the action suggestion device 1 via the user terminal 2 using the login information shared between the action suggestion device 1 and the user terminal 2.

[0054] Next, an example of acquiring physical condition information and executing action suggestions will be described. In order for the action suggestion device 1 (prediction unit 104) to accurately predict the user's future physical condition information, it is necessary to derive the relationship between environmental information and physical condition information by accumulating these. To this end, the action suggestion device 1 (acquisition unit 102) acquires physical condition information using a physical condition information acquisition start event as a trigger (step S3). The acquisition of environmental information is performed in the process described below (step S4).

[0055] Furthermore, if the acquired physical condition information indicates that the user is unwell, the user terminal 2 (display control unit 114) presents the user with action suggestion information for improving the condition. Examples of events that trigger the acquisition of physical condition information include "a time designated in advance by the user or developer has arrived," "a certain amount of time has passed since the last execution," and "there has been a significant change in environmental information." This process may also be triggered by a user request. In this way, if the user senses that they are unwell, they can request an action suggestion system to suggest an action.

[0056] The acquired physical condition information is a collection of all of the candidate conditions that correspond to the user's physical condition among at least one type of candidate condition. For example, if the candidate conditions are "headache," "sleepy," "feeling tired," "eye strain," "lower back pain," and "feeling dazed," and the user's physical condition corresponds to either "headache" or "sleepy" and nothing else, the physical condition information can be expressed as "(headache, sleepy)." On the other hand, if the user's physical condition does not correspond to any of the candidate conditions, it can be expressed as "()." The physical condition information may also include a numerical value representing the intensity of the corresponding condition. In this case, the physical condition information would look like "headache: 0.9, sleepy: 0.2."

[0057] Furthermore, in the process shown in step S3, supplementary information for predicting physical condition is also acquired. The supplementary information for predicting physical condition is supplementary information that is added to explanatory variables to enable more accurate estimation of physical condition information, such as "whether or not the user slept well last night" or "whether or not the user ate breakfast." Note that the acquisition of supplementary information is not performed every time the process shown in step S3 is performed, but is performed as needed. For example, one example of supplementary information, "whether or not the user slept well last night," only needs to be acquired once at the beginning of each day.

[0058] Next, an example of creating an action proposal schedule based on physical condition prediction will be described. The action proposal device 1 (acquisition unit 102) acquires environmental information in response to an environmental information acquisition start event (step S4). After acquiring the environmental information, the action proposal device 1 (prediction unit 104) predicts the user's future physical condition information based on the acquired environmental information, the supplementary information acquired in the process shown in step S3, and a physical condition estimation model. Furthermore, if the predicted future physical condition information thereafter indicates poor health, the action proposal device 1 (proposal generation unit 106) generates action proposal information to prevent the poor health, determines the action proposal execution time for presenting the action proposal information, generates an action proposal schedule based on these, and registers it in the action proposal schedule DB.

[0059] Examples of environmental information acquisition start events include "a time designated in advance by the user or developer has arrived" or "a certain amount of time has passed since the last execution time." This process may also be triggered by a user request. When generating a health condition estimation model, if a pair of health condition information and environmental information acquired at approximately the same time is required, it is desirable to execute a process to acquire health condition information (step S4) immediately before or after executing this process.

[0060] The environmental information acquired here is information about the environment and situation surrounding the user, such as the temperature, humidity, air pressure, weather, CO2 concentration, etc., at the user's location. In addition, by performing arithmetic processing on the information on the left, the amount of fluctuation per unit time, etc., may be calculated and included in the environmental information.

[0061] The environmental information may also include the user's working environment and working conditions, such as the time elapsed since the start of work, the duration of PC operation, and the time spent seated. Furthermore, the environmental information may also include predicted values ​​of environmental information at a certain point in the future, such as a weather forecast. This may enable more accurate health predictions.

[0062] Next, an example of the execution of an action proposal according to the action proposal schedule will be described. The user terminal 2 (display control unit 114) presents the action proposal information to the target user according to the action proposal schedule registered in the action proposal schedule DB (step S5). This process is preferably executed constantly as a resident task.

[0063] Next, an example of generating a physical condition estimation model will be described. The action suggestion device 1 (calculation processing unit 103) generates a physical condition estimation model using physical condition information and environmental information accumulated by acquiring physical condition information (step S3) and environmental information (step S4). Here, the physical condition estimation model takes time t and explanatory variables as input and outputs estimated information on the user's physical condition time t from the present.

[0064] The time t that can be input to the physical condition estimation model may be variable or may be fixed, for example, 30 minutes. Furthermore, by generating multiple physical condition estimation models with fixed time t for different fixed values, it is possible to obtain estimated information on the user's physical condition after two or more times t, and this may be referred to as a physical condition estimation model.

[0065] An example of the format of estimated information on physical condition output by the physical condition estimation model is one that indicates the probability that each candidate condition will be present after time t. Specific examples in this case are headache: 0.2, sleepiness: 0.1, fatigue: 0.7, tired eyes: 0.4, and drowsy: 0.4.

[0066] Furthermore, if the physical condition information acquired by the process shown in step S3 is a numerical representation of the intensity of the corresponding ailment, such as "headache: 0.9, sleepiness: 0.2," the estimated physical condition information may be an estimated value of the intensity of each ailment after time t expressed in a similar format. The explanatory variables are primarily environmental information. The explanatory variables may be a single piece of environmental information or multiple pieces of environmental information arranged in a time series. The explanatory variables may also include values ​​generated by performing arithmetic processing on the environmental information or the time series of environmental information.

[0067] Furthermore, the explanatory variables may include supplemental information that is effective for the environmental information. Supplemental information that is effective for the environmental information is supplemental information that can be most reasonably used together with the environmental information to predict physical condition. For example, it is reasonable to use the supplemental information "I slept well the night of February 1st" together with the environmental information for the following day, February 2nd. However, if there is further supplemental information "I slept well the night of February 2nd," it is not reasonable to use the supplemental information "I slept well the night of February 1st" together with the environmental information for February 3rd and thereafter.

[0068] An example of a method for generating a physical condition estimation model will be described below. Here, we will take the example of generating a physical condition estimation model with t fixed. First, the calculation processing unit 103 generates a time series of explanatory variables using a time series of environmental information that can be acquired from the environmental history DB and supplemental information valid for each environmental information. The explanatory variables that make up the time series of explanatory variables are associated with the acquisition time of the most recent environmental information acquired among the environmental information used to generate the explanatory variables, and this will be simply referred to as the time of the explanatory variables.

[0069] The calculation processing unit 103 generates training data consisting of pairs of explanatory variables and physical condition information by performing the following operations on each explanatory variable that makes up the time series of explanatory variables. First, the calculation processing unit 103 finds the time when a fixed value of t is added to the time of the explanatory variable. Next, the calculation processing unit 103 selects from the time series of physical condition information the physical condition information that was acquired at the time closest to the found time. Finally, the calculation processing unit 103 associates the selected physical condition information with the explanatory variable to form a pair. Note that if the time when a fixed value of t is added to the time of the explanatory variable is separated by a certain amount from the time when the physical condition information paired with that explanatory variable was acquired, the calculation processing unit 103 may not include it in the training data.

[0070] Using the training data created by the above method, a known machine learning model (e.g., logistic regression, linear regression, SVM, decision tree, random forest, neural network) is trained. The trained machine learning model becomes a health condition estimation model.

[0071] When sufficient training data for a user has not been accumulated, such as in the early stages of use, the estimation accuracy of the physical condition estimation model may be insufficient (commonly referred to as the cold start problem). To address this issue, the calculation processing unit 103 may use an auxiliary model generated by averaging physical condition estimation models for users with similar attributes (e.g., age, gender, occupation) to correct the output of the physical condition estimation model when the amount of training data is small. Note that the auxiliary model may be one generated in advance during the development stage.

[0072] As an example, the output of the physical condition estimation model is corrected using an auxiliary model as shown in the following equation (1).

number

number

[0073] 6 is a diagram for explaining details of the process of registering basic user information of a new user and performing login authentication in the action suggestion system according to the first embodiment. The process shown in FIG. 6 is a detailed example of the process shown in step S1 in FIG. 5. First, the user transmits a new user registration request to the action suggestion device 1 through the user terminal 2 (step S601). Next, upon receiving the new user registration request, the action suggestion device 1 requests the user terminal 2 to send the basic user information of the new user via the transmitter / receiver 101 (steps S602 and S603).

[0074] Next, when the user terminal 2 receives the request for user basic information via the transmitting / receiving unit 111 (step S604), it prompts the user to input the user basic information, and acquires the user basic information via the acquiring unit 113 through the user's input operation (step S605). Next, the user terminal 2 transmits the acquired user basic information to the action suggestion device 1 via the transmitting / receiving unit 111 (step S606). Next, when the action suggestion device 1 receives the user basic information via the transmitting / receiving unit 101 (step S607), it stores it in the user basic information DB.

[0075] Next, the action suggestion device 1 generates login information for the user and transmits the generated login information to the user terminal 2 via the transmitting / receiving unit 101 (steps S608 and S609). Next, the user terminal 2 receives the login information via the transmitting / receiving unit 111 (step S610) and stores it in the storage unit 116. In subsequent communications with the action suggestion device 1, the user terminal 2 adds the login information to the information to be transmitted. This allows the action suggestion device 1 to uniquely identify the user who is using the action suggestion device 1 via the user terminal 2.

[0076] Fig. 7 is a diagram for explaining details of the login authentication process in the action suggestion system according to the first embodiment. The process shown in Fig. 7 is details of the process shown in step S2 in Fig. 5. First, the user terminal 2 prompts the user to input a user ID and password, and acquires the user ID and password from the user's input (step S701). Then, the user terminal 2 transmits the acquired user ID and password to the action suggestion device 1 via the transmitter / receiver 111 (step S702).

[0077] Next, when the action suggestion device 1 receives the user ID and password from the user terminal 2 via the transmitting / receiving unit 101 (step S703), it refers to the user basic information DB and checks whether there is user basic information including the same user ID and password as the received user ID and password, and if such user basic information exists, it determines that authentication is successful (step S704: Yes), and authenticates the user using the action suggestion device 1 through the user terminal 2 as the user corresponding to that user basic information. On the other hand, if there is no user basic information including the same user ID and password as the received user ID and password (step S704: No), the action suggestion device 1 notifies the user terminal 2 via the transmitting / receiving unit 101 that authentication has failed.

[0078] If the user authentication is successful, the action suggestion device 1 generates login information for the user and transmits it to the user terminal 2 via the transmitter / receiver 101 (steps S705 and S706). Next, the user terminal 2 receives the login information via the transmitter / receiver 111 and stores it in the storage unit 116 (step S707). In subsequent communications with the action suggestion device 1, the user terminal 2 adds the login information to the information it transmits. This allows the action suggestion device 1 to uniquely identify the user who is using the action suggestion device 1 via the user terminal 2.

[0079] FIG. 8 is a diagram illustrating an example of details of the process of acquiring physical condition information and executing action suggestions in the action suggestion system according to the first embodiment. The process illustrated in FIG. 8 is a detailed example of the process illustrated in step S3 in FIG. 5. First, the action suggestion device 1 transmits a request for physical condition information and supplemental information to the user terminal 2 via the transmitting / receiving unit 101 (step S801). If the process illustrated in step S3 in FIG. 3 is initiated by a user request, this request is a process of transmitting an input form for physical condition information and supplemental information to the user terminal 2 as a response to the user request. On the other hand, if the process illustrated in step S3 in FIG. 5 is initiated by a physical condition information acquisition start event, the action suggestion device 1 unilaterally transmits a request for physical condition information and supplemental information to the user terminal 2 (for example, by a push notification). Note that a request for supplemental information is made as needed. For example, it is sufficient to request supplemental information indicating "whether you slept well last night" at the beginning of the day. If a request for supplemental information is not required, only physical condition information is requested.

[0080] Next, when the user terminal 2 receives a request to input physical condition information and supplemental information (or only physical condition information) via the transmitting / receiving unit 111 (step S802), the display control unit 114 prompts the user to input information, and the acquisition unit 113 acquires the physical condition information (and supplemental information) through the user's input via the operation acceptance unit 112 (step S803). Then, the user terminal 2 transmits the acquired physical condition information to the action suggestion device 1 via the transmitting / receiving unit 111 (step S804).

[0081] Next, when the action suggestion device 1 receives the physical condition information and supplemental information via the transmitting / receiving unit 101 (step S805), it stores the physical condition information in the physical condition history DB and the supplemental information in the supplemental information history DB together with the time of acquisition. Next, the determination unit 105 of the action suggestion device 1 determines whether the acquired physical condition information indicates the user's illness (step S806). For example, if the physical condition information is a set of at least one or more candidate illness conditions that correspond to the user's physical condition (e.g., "headache, sleepy"), the determination unit 105 determines that the set does not indicate illness if it is an empty set, and otherwise determines that the user is sick. Also, if the physical condition information includes the intensity of each candidate illness condition, such as "headache: 0.9, sleepy: 0.3," the determination unit 105 determines whether there is an illness condition whose intensity exceeds a threshold. This threshold may be common to all candidate illness conditions, or may be set individually for each candidate illness condition.

[0082] If it is determined in step S806 that the acquired physical condition information indicates that the user is unwell (step S806: Yes), the proposal generator 106 of the action proposal device 1 generates action proposal information by the following process and transmits it to the user terminal 2 via the transmitter / receiver 101 (steps S807 and S808). The proposal generator 106 first acquires, from the action DB, action proposal information that is effective for improving the condition indicated by the physical condition information. Whether it is effective or not is determined by referring to the effects of the action stored in association with the action proposal information. For example, if the physical condition information indicates an unwell condition such as "headache," the proposal generator 1 acquires action proposal information in which the effect of the action includes "effective in improving headaches."

[0083] Furthermore, if the suitability managed in the behavioral suitability DB is less than a predetermined threshold (e.g., 1), the suggestion generation unit 106 determines that performing the behavior will be ineffective and does not suggest the behavior. If the behavior DB contains two or more behaviors that are effective in improving the condition indicated by the physical condition information, the suggestion generation unit 106 selects the behavioral suggestion information to be proposed using the suitability managed in the behavioral suitability DB. If the suitability is expressed as a numerical value, the suggestion generation unit 106 may determine the selection probability of each behavioral suggestion information to be proportional to its suitability, and select the behavioral suggestion information according to the determined selection probability. Note that for behavioral suggestion information with two or more effects, the suitability corresponding to the effect that is effective in resolving the user's condition indicated by the physical condition information is used. The number of behavioral suggestion information selected here may be one, two, or more.

[0084] Next, the action suggestion device 1 transmits the action suggestion information selected by the above method to the user terminal 2. The action suggestion information may also include information indicating what kind of poor health condition the action content included in the action suggestion information aims to improve.

[0085] When the action suggestion device 1 completes transmission of the action suggestion information, the calculation processing unit 103 of the action suggestion device 1 generates a physical condition estimation model using the above-described method based on the information stored in the physical condition history DB, the environmental history DB, and the supplementary information history DB, and stores the model in the storage unit 108 (step S809). When the user terminal 2 receives the action suggestion information from the action suggestion device 1 via the transmission / reception unit 111, the user terminal 2 presents the action suggestion information to the user via the display control unit 114 (steps S810 and S811).

[0086] Thereafter, the user terminal 2 waits at least until the user completes the action, and then prompts the user to input action feedback information for the action. In this feedback, the user mainly evaluates whether the action was effective or not, and inputs the result into the user terminal 2. The user terminal 2 transmits the feedback result input by the user to the action suggestion device 1 as action feedback information via the transmitter / receiver 111 (steps S812 and S813).

[0087] When the action suggestion device 1 receives action feedback information from the user terminal 2 via the transmitter / receiver 101 (step S814), it updates the suitability (step S815). This update is performed so that the suitability becomes larger if the action is effective, and conversely, so that the suitability becomes smaller if the action is ineffective. For example, if the suitability is expressed numerically and the action feedback information evaluates the effectiveness of the action on a five-point scale (e.g., 1: ineffective, 5: effective), the suitability is updated as follows: If the evaluation is 1, the new fitness is calculated by multiplying the fitness by 0.8. If the evaluation is 2, the new fitness is calculated by multiplying the fitness by 0.9. If the evaluation is 3, the new fitness is calculated by multiplying the fitness by 1.0. If the evaluation is 4, the fitness is multiplied by 1.1 to become the new fitness. If the rating is 5, the new fitness is calculated by multiplying the fitness by 1.2. The method shown here is just an example and is not limited to this.

[0088] FIG. 9 is a diagram illustrating an example of details of the process of creating an action suggestion schedule based on physical condition prediction in the action suggestion system according to the first embodiment. The process illustrated in FIG. 9 is a detailed example of the process illustrated in step S4 of FIG. 5. First, the action suggestion device 1 acquires environmental information using the acquisition unit 102 (step S901). The acquisition unit 102 then stores the acquired environmental information in the environmental history DB together with the acquisition time. If the environmental information relates to weather such as temperature, humidity, and atmospheric pressure, the information may be acquired from the Internet via a network connected to the transmission / reception unit 101, with reference to the user's location included in the user's basic information. If the environmental information includes information related to the user's work environment or work situation, and the terminal used by the user for work matches the user terminal 2, and information related to the work environment or work situation can be acquired from the user, the information related to the work environment and work situation may be acquired from the user terminal 2.

[0089] Next, the action suggestion device 1 acquires supplementary information valid for the environmental information from the supplementary information history DB using the acquisition unit 102 (step S902). Next, the prediction unit 104 of the action suggestion device 1 generates explanatory variables based on the acquired environmental information and supplementary information, and generates future physical condition information of the user time t from the current time by inputting the generated explanatory variables and time t into the physical condition estimation model (step S903). Note that if the physical condition estimation model can only accept a fixed time t, that value is input. On the other hand, if two or more types of time t can be accepted, physical condition information for time t may be generated for some or all of them to form a time series of physical condition information.

[0090] Next, the determination unit 105 of the action suggestion device determines whether the future physical condition information generated by the prediction unit 104 indicates that the user is unwell (step S904). For example, if the physical condition information indicates the probability that each of the candidate physical conditions will correspond to that condition after time t, such as "headache: 0.2, sleepiness: 0.1, fatigue: 0.7, tired eyes: 0.4, spaced out: 0.4," the determination unit 105 lists the physical conditions whose probability exceeds a predetermined threshold, and if there is one or more such physical conditions, determines that the physical condition information indicates that the user is unwell. This threshold may be common to all the candidate physical conditions, or may be set individually for each.

[0091] If it is determined in step S904 that the future physical condition information generated by the prediction unit 104 indicates that the user is feeling unwell (step S904: Yes), the proposal generation unit 106 generates action proposal information and action proposal execution times by the following process, generates action proposal schedule information based on them, and stores it in the action proposal schedule DB (steps S905 to S907). First, the proposal generation unit 106 acquires from the action DB an action that is effective in preventing the unwell indicated by the physical condition information. Whether or not it is effective is determined by referring to the effect of the action that is stored in association with the action. For example, if the physical condition information indicates an unwell state of "headache," the proposal generation unit 106 acquires an action whose effect is "effective in preventing headaches."

[0092] If the behavior DB contains two or more behaviors that are effective in preventing the illness indicated by the physical condition information, the suggestion generator 106 selects an action to suggest using the suitability managed in the behavior suitability DB. The selection method here is the same as the process shown in step S3 of Figure 5 above.

[0093] Next, the proposal generation unit 106 generates action proposal information including the action content of the action acquired by the above-mentioned method. The proposal generation unit 106 may also include, in the action proposal information, information indicating the type of improvement in the condition that the action content included in the action proposal information is intended to achieve. Next, the proposal generation unit 106 generates an action proposal execution time. To prevent the condition from developing, the action proposal execution time is specified so that the time at which the effect of the action will be achieved is earlier than the time at which the condition indicated by the estimated physical condition information will occur. One example of a method for specifying the action proposal execution time is to specify a time that is a predetermined, sufficiently long time in the past than the time at which the condition is predicted to occur. Furthermore, if the effect of the action stored in association with the action includes information regarding the time until the effect of the action is achieved, the action proposal execution time may be specified taking this information into consideration.

[0094] Next, the proposal generation unit 106 generates action proposal schedule information by summarizing the action proposal information generated by the above-mentioned method, the action proposal execution time, and the time when the illness is predicted to occur. The action proposal schedule information may further include remark information. The remark information is information that is presented to the user along with the proposed action content to provide the user with additional information when suggesting an action. An example of remark information is a string of characters that indicates the reason why the action suggestion device 1 decided to suggest an action, such as "There is a high possibility that 'headache' will occur from now on."

[0095] Next, the proposal generation unit 106 stores the generated action proposal schedule information in the action proposal schedule DB. Note that if similar action proposal schedule information is already stored in the action proposal schedule DB, it may not be stored. For example, if two pieces of action proposal schedule information are action proposals for preventing similar illnesses and the action proposal execution times are close to each other, they can be said to be similar.

[0096] Finally, the calculation processing unit 103 of the action suggestion device 1 generates a physical condition estimation model using the above-mentioned method based on the information stored in the physical condition history DB, the environmental history DB, and the supplementary information history DB, and stores it in the memory unit 108 (step S908).

[0097] 10 is a diagram illustrating an example of details of the process of executing an action proposal according to an action proposal schedule in the action proposal system according to the first embodiment. The process illustrated in FIG. 10 is a detailed process of the process illustrated in step S5 of FIG. 5. First, the acquisition unit 102 of the action proposal device 1 acquires, from the action proposal schedule DB, an action proposal schedule that has the earliest action proposal execution time specified among the action proposal schedules that have not yet been executed (step S1001). Next, the action proposal device 1 waits until the action proposal execution time of the acquired action proposal schedule arrives (step S1002).

[0098] Next, the action suggestion device 1 transmits the action suggestion information included in the acquired action suggestion schedule to the user terminal 2 via the transmitter / receiver 101 (step S1003). After transmitting the action suggestion information, the action suggestion device 1 stores in the action suggestion schedule DB that the action suggestion schedule has been executed (step S1004).

[0099] When the user terminal 2 receives the action suggestion information from the action suggestion device 1 via the transmitter / receiver 111 (step S1005), it presents the action suggestion information to the user via the display control unit 114 (step S1006). Thereafter, the user terminal 2 waits at least until the time when the user is predicted to become unwell, and then prompts the user to input action feedback information for the action. In this feedback, the user mainly evaluates whether the action was effective and inputs the result into the user terminal 2. The user terminal 2 transmits the feedback result input by the user to the action suggestion device 1 as action feedback information (steps S1007 and S1008).

[0100] When the action suggestion device 1 receives action feedback information from the user terminal 2 via the transmitter / receiver 101 (step S1009), it updates the compatibility (step S1010). The update method here is the same as the process shown in step S3 of FIG. 5 above.

[0101] 11 is a diagram showing an example of a screen displayed to a user by a display control unit when a user terminal acquires physical condition information and supplemental information through user input in the process of acquiring physical condition information and executing action suggestions in the action suggestion system according to the first embodiment. The question items "Did you sleep well last night?" and "Did you have breakfast?" on the screen shown in FIG. 11 correspond to the supplemental information. Also, the question item "Please select all that apply" on the screen shown in FIG. 11 corresponds to physical condition information.

[0102] Fig. 12 is a diagram showing an example of a screen displayed to a user by a display control unit on a user terminal to present action suggestion information to the user in the process of acquiring physical condition information and executing action suggestions in the action suggestion system according to the first embodiment. In the screen shown in Fig. 12, the physical condition information acquired in the process shown in step S3 of Fig. 5 indicates the poor health conditions of "headache" and "sleepy," and a suggested action for "headache" is "warm behind your ears with a hot towel or the like," and a suggested action for "sleepy" is "do 20 squats."

[0103] 13 is a diagram showing an example of a screen displayed to a user by a display control unit of a user terminal to present action suggestion information to the user in the process of executing an action suggestion according to an action suggestion schedule in the action suggestion system according to the first embodiment. On the screen shown in Fig. 13, the action suggestion device 1 predicts that the user's future physical condition is highly likely to become unwell, such as "headache," and suggests an action to "warm behind your ears with a hot towel or the like" as a preventative measure.

[0104] 14 is a diagram showing an example of a screen that a user terminal presents to a user in order to acquire action feedback information through user input in the process of acquiring physical condition information and executing action suggestions, or in the process of executing action suggestions according to an action suggestion schedule, in the action suggestion system according to the first embodiment. The screen shown in FIG. 14 presents the action content to be fed back and the expected effect of the action, and allows the user to evaluate whether the expected effect actually occurred on a five-point scale. The screen shown in FIG. 14 also displays an option that allows the user to select "not performed" in case the user did not perform the suggested action.

[0105] In this way, according to the action suggestion system of the first embodiment, when it is predicted that the user's physical condition will deteriorate, it is possible to present the user with action suggestion information for preventing the deterioration of the user's physical condition before the deterioration progresses. As a result, it is possible to present the user with preventative action suggestion information before the user's physical condition deteriorates, thereby maintaining the user's physical condition in good condition.

[0106] (Second embodiment) In this embodiment, an action suggestion system includes a sensing device that acquires environmental information and physical condition information. In the following description, a description of the same configuration as in the first embodiment will be omitted.

[0107] 15 is a diagram showing an example of the configuration of an action suggestion system according to the second embodiment. In addition to the configuration of the action suggestion system according to the first embodiment, the action suggestion system according to this embodiment further includes a sensing device 1500 connected to a network. In this configuration, the action suggestion device 1 can also use information obtainable from the sensing device 1500 to generate environmental information or user physical condition information.

[0108] The sensing device 1500 is, for example, a thermometer, a hygrometer, and a barometer installed in the workplace where the user works. In this case, the acquisition unit 102 of the action suggestion device 1 can acquire the temperature, humidity, and barometric pressure as environmental information from the sensing device 1500.

[0109] Furthermore, if the sensing device 1500 is a camera (for example, a surveillance camera installed in the workplace) or a microphone that can capture images of the user while they are working, by analyzing the images and sounds obtained from these, it is possible to obtain environmental information related to the user's working environment and working conditions, such as the duration of the user's PC operation, the amount of time the user is seated, and the level of noise.

[0110] This allows for more accurate environmental information to be acquired compared to acquiring environmental information from the Internet as in the first embodiment, potentially improving the accuracy of physical condition prediction. Furthermore, with this configuration, the process of creating an action proposal schedule based on physical condition prediction (the process shown in step S4 in FIG. 5) can be executed as frequently as "every 10 seconds." This makes it possible to more reliably predict the user's illness and prevent its occurrence. Furthermore, it allows for the accumulation of more environmental information, potentially improving the accuracy of physical condition prediction.

[0111] Furthermore, if the system is configured to acquire information from video footage of the user at work that can be used to infer the user's physical condition, such as whether or not the user makes gestures that suggest a headache (for example, holding their head), the degree to which their eyelids are open, and their complexion, physical condition information can be generated based on this information. In this case, some or all of the user's input can be omitted in the process of acquiring physical condition information and executing action suggestions (the process shown in step S3 of FIG. 5).

[0112] In this way, the action suggestion system according to the second embodiment can acquire physical condition information and execute suggested actions (the process shown in step S3 of FIG. 5) more frequently without increasing the burden on the user, and can detect the user's condition earlier and suggest actions. In addition, it can accumulate more physical condition information, which may improve the accuracy of physical condition prediction.

[0113] (Third embodiment) In this embodiment, a sensing device is connected to a user terminal of an action suggestion system. In the following description, a description of the same configuration as in the second embodiment will be omitted.

[0114] 16 is a diagram showing the configuration of an action suggestion system according to a third embodiment. In addition to the configuration of the first embodiment, the action suggestion system according to this embodiment has a sensing device 1500 connected to a user terminal 2. Examples and advantages of this configuration are similar to those of the action suggestion system according to the second embodiment.

[0115] The programs executed by the action suggestion device 1 and the user terminal 2 of this embodiment are provided in advance in the ROM 202, 302, etc. The programs executed by the action suggestion device 1 and the user terminal 2 of this embodiment may be provided by being recorded in an installable or executable file format on a computer-readable recording medium such as a CD-ROM, a flexible disk (FD), a CD-R, or a digital versatile disk (DVD).

[0116] Furthermore, the programs executed by the action suggestion device 1 and the user terminal 2 of this embodiment may be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network. Also, the programs executed by the action suggestion device 1 and the user terminal 2 of this embodiment may be provided or distributed via a network such as the Internet.

[0117] The program executed by the action suggestion device 1 and the user terminal 2 in this embodiment has a modular configuration including the above-mentioned units (transmission / reception unit 101, acquisition unit 102, calculation processing unit 103, prediction unit 104, judgment unit 105, proposal generation unit 106, memory reading unit 107, transmission / reception unit 111, operation reception unit 112, acquisition unit 113, display control unit 114, and memory reading unit 115), and in actual hardware, a processor such as CPU 201, 301 reads and executes the program from the above-mentioned ROM 202, 302, loading the above-mentioned units onto the main memory, and the transmission / reception unit 101, acquisition unit 102, calculation processing unit 103, prediction unit 104, judgment unit 105, proposal generation unit 106, memory reading unit 107, transmission / reception unit 111, operation reception unit 112, acquisition unit 113, display control unit 114, and memory reading unit 115 are generated on the main memory.

[0118] For example, aspects of the present invention are as follows. <1> a physical condition information acquisition unit that acquires physical condition information of a user; a physical condition information prediction unit that predicts occurrence of poor physical condition based on the physical condition information; an action suggestion information generation unit that generates, for each user, action suggestion information for the user to avoid the poor health condition based on user information when the occurrence of the poor health condition is predicted; An information processing device comprising: The physical condition information acquisition unit may acquire physical condition information accepted by the input acceptance means, or may acquire physical condition information from sensor information including biometric information of the user. The physical condition information prediction unit predicts fluctuations in the physical condition information from the physical condition information and can predict poor physical condition based on the fluctuations in the physical condition information. The user information may be accepted by the input acceptance means. <2> the action suggestion information generation unit generates the action suggestion information when it is determined that the action suggestion information should be generated based on the user information, and does not generate the action suggestion information when it is determined that the action suggestion information should not be generated based on the user information; <1> The information processing device described in <3> the action suggestion information generation unit generates one of the plurality of action suggestion information candidates based on the user information; <1> or <2> The information processing device described in <4> the action suggestion information generation unit generates the action suggestion information based on the user and a degree of suitability for each user stored in a storage means in association with the candidate of the action suggestion information; <3> The information processing device described in <5> an update unit that updates the suitability for each user; <4> The information processing device described in <6> a feedback acquisition unit that acquires feedback information on the action suggestion information, the action suggestion information generation unit adjusts the suitability of the action suggestion information for the user based on the feedback information acquired by the feedback acquisition unit. <5> The information processing device described in <7> a display control unit that displays the action suggestion information on a display unit; <1> from <6> 10. The information processing device according to claim 9, wherein <8> an environment acquisition unit that acquires environment information indicating the state of the environment; a health condition prediction unit that predicts the health condition information at a certain point in the future based on the environmental information acquired by the environment acquisition unit, when the physical condition information predicted by the physical condition prediction unit indicates poor physical condition of the user, the action suggestion information generation unit specifies a suggested execution time that is earlier than a time that is obtained by subtracting from the predicted time when the poor physical condition will occur at least one of a time required to perform the action included in the action suggestion information and a time from the completion of the action until an effect of the action is produced, the display control unit displays the generated action suggestion information for the user at the suggestion execution time. <7> The information processing device described in <9> a storage unit that stores the physical condition information acquired by the physical condition information acquisition unit and the environmental information acquired by the environmental acquisition unit; a relationship calculation unit that calculates a relationship between the physical condition information and the environmental information based on at least one piece of physical condition information and at least one piece of environmental information stored in the storage unit, the physical condition information prediction unit predicts the physical condition information at a certain point in time in the future based on the relationship between the physical condition information and the environmental information calculated by the relationship calculation unit and the environmental information acquired by the environment acquisition unit. <8> The information processing device described in <10> the relationship calculation unit calculates a relationship between the physical condition information specific to the user and the environmental information based on the physical condition information and the environmental information, some or all of which are associated with the user; the physical condition information prediction unit predicts the physical condition information at a certain point in the future based on a relationship between the physical condition information specific to the user and the environmental information and the environmental information acquired by the environment acquisition unit; <9> The information processing device described in <11> a supplemental information acquisition unit that acquires information that may affect the relationship between the physical condition information and the environmental information as supplemental information; the physical condition information prediction unit predicts the physical condition information at a certain point in the future based on the supplemental information; <9> or <10> The information processing device described in <12> An information processing method executed by an information processing device, a health information acquisition step of acquiring health information of a user; a physical condition information prediction step of predicting occurrence of poor physical condition based on the physical condition information; an action suggestion information generating step of generating, for each user, action suggestion information for the user to avoid the poor health condition based on user information when the occurrence of the poor health condition is predicted; An information processing method that performs the above. <13> a health information acquisition step of acquiring health information of a user; a physical condition information prediction step of predicting occurrence of poor physical condition based on the physical condition information; an action suggestion information generating step of generating, for each user, action suggestion information for the user to avoid the poor health condition based on user information when the occurrence of the poor health condition is predicted; A program that causes a computer to execute the following. <14> An information processing system including an information processing device and a terminal device capable of communicating with the information processing device, a physical condition information acquisition unit that acquires physical condition information of a user; a physical condition information prediction unit that predicts occurrence of poor physical condition based on the physical condition information; an action suggestion information generation unit that generates, for each user, action suggestion information for the user to avoid the poor health condition based on user information when the occurrence of the poor health condition is predicted; a display control unit that displays the action suggestion information on a display unit of the terminal device; An information processing system comprising: [Explanation of symbols]

[0119] 1 Action suggestion device 2. User terminal 101,111 Transmitter / Receiver 102,113 Acquisition Department 103 Calculation processing unit 104 Prediction Department 105 Judgment Department 106 Proposal generation section 107,115 Memory reading section 108,116 storage section 112 Operation reception section 114 Display control unit [Prior art documents] [Patent documents]

[0120] [Patent Document 1] Patent No. 5493785 [Patent Document 2] Patent No. 6920434 [Patent Document 3] Japanese Patent Application Laid-Open No. 2016-110317

Claims

1. a physical condition information acquisition unit that acquires physical condition information of a user; a physical condition information prediction unit that predicts occurrence of poor physical condition based on the physical condition information; an action suggestion information generation unit that generates, for each user, action suggestion information for the user to avoid the poor health condition based on user information when the occurrence of the poor health condition is predicted; An information processing device comprising:

2. 2. The information processing device of claim 1, wherein the action suggestion information generation unit generates the action suggestion information when it is determined that the action suggestion information should be generated based on the user information, and does not generate the action suggestion information when it is determined that the action suggestion information should not be generated based on the user information.

3. The information processing device according to claim 1 , wherein the action suggestion information generating unit generates one of a plurality of candidates for the action suggestion information based on the user information.

4. The information processing device according to claim 3 , wherein the action suggestion information generating unit generates the action suggestion information based on the user and a degree of suitability for each user stored in a storage means in association with the candidate action suggestion information.

5. The information processing apparatus according to claim 4 , further comprising an update unit that updates the suitability for each user.

6. a feedback acquisition unit that acquires feedback information on the action suggestion information, The information processing device according to claim 5 , wherein the action suggestion information generation unit adjusts the suitability of the action suggestion information for the user based on the feedback information acquired by the feedback acquisition unit.

7. The information processing device according to claim 1 , further comprising a display control unit that displays the action suggestion information on a display unit.

8. an environment acquisition unit that acquires environment information indicating the state of the environment; a health condition prediction unit that predicts the health condition information at a certain point in the future based on the environmental information acquired by the environment acquisition unit, when the physical condition information predicted by the physical condition prediction unit indicates poor physical condition of the user, the action suggestion information generation unit specifies a suggested execution time that is earlier than a time that is obtained by subtracting from the predicted time when the poor physical condition will occur at least one of a time required to perform the action included in the action suggestion information and a time from the completion of the action until an effect of the action is produced, The information processing device according to claim 7 , wherein the display control unit displays the generated action suggestion information for the user at the suggestion execution time.

9. a storage unit that stores the physical condition information acquired by the physical condition information acquisition unit and the environmental information acquired by the environmental acquisition unit; a relationship calculation unit that calculates a relationship between the physical condition information and the environmental information based on at least one piece of physical condition information and at least one piece of environmental information stored in the storage unit, 9. The information processing device according to claim 8, wherein the health information prediction unit predicts the health information at a certain point in the future based on the relationship between the health information and the environmental information calculated by the relationship calculation unit and the environmental information acquired by the environment acquisition unit.

10. the relationship calculation unit calculates a relationship between the physical condition information specific to the user and the environmental information based on the physical condition information and the environmental information, some or all of which are associated with the user; 10. The information processing device according to claim 9, wherein the physical condition information prediction unit predicts the physical condition information at a certain point in the future based on the relationship between the physical condition information specific to the user and the environmental information and the environmental information acquired by the environment acquisition unit.

11. a supplemental information acquisition unit that acquires information that may affect the relationship between the physical condition information and the environmental information as supplemental information; The information processing device according to claim 9 , wherein the physical condition information prediction unit predicts the physical condition information at a certain point in the future based on the supplemental information.

12. An information processing method executed by an information processing device, a health information acquisition step of acquiring health information of a user; a physical condition information prediction step of predicting occurrence of poor physical condition based on the physical condition information; an action suggestion information generating step of generating, for each user, action suggestion information for the user to avoid the poor health condition based on user information when the occurrence of the poor health condition is predicted; An information processing method that performs the above.

13. a health information acquisition step of acquiring health information of a user; a physical condition information prediction step of predicting occurrence of poor physical condition based on the physical condition information; an action suggestion information generating step of generating, for each user, action suggestion information for the user to avoid the poor health condition based on user information when the occurrence of the poor health condition is predicted; A program that causes a computer to execute the following.

14. An information processing system including an information processing device and a terminal device capable of communicating with the information processing device, a physical condition information acquisition unit that acquires physical condition information of a user; a physical condition information prediction unit that predicts occurrence of poor physical condition based on the physical condition information; an action suggestion information generation unit that generates, for each user, action suggestion information for the user to avoid the poor health condition based on user information when the occurrence of the poor health condition is predicted; a display control unit that displays the action suggestion information on a display unit of the terminal device; An information processing system comprising:

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