Information processing device, information processing method, and program

Abstract

This information processing system comprises a determination unit, a decision unit, and an output unit. The determination unit determines the state of a user who uses image content. The decision unit decides, on the basis of the state of the user, the detail of the image content for prompting the user to perform an action related to mindfulness. The output unit outputs the decided detail of the image content.

Description

Information processing device, information processing method, and recording medium

[0001] The present disclosure relates to an information processing device and the like.

[0002] Mindfulness is practiced to maintain a good mental and physical state through meditation or exercise. Mindfulness is, for example, an activity to improve one's mental and physical state through meditation or exercise. For example, a person who practices meditation as a form of mindfulness improves their internal state to one that is suitable for life or work through meditation. Mindfulness-related activities may also be supported by information processing devices. For example, an application program running on the information processing device may present the content and schedule of mindfulness-related activities.

[0003] The mood change support device of Patent Document 1 outputs an image showing the content of mindfulness during a worker's mood change period. With the mood change support device of Patent Document 1, the worker refers to the image and performs an action related to mindfulness.

[0004] Japanese Patent Application Laid-Open No. 2018-159979

[0005] In the mood change support device of Patent Document 1, it may be difficult to encourage the user to actually perform the action shown in the image.

[0006] In order to solve the above-mentioned problems, the present disclosure aims to provide an information processing system and the like that can make it easier for a user to take actions to improve their condition.

[0007] In order to solve the above problems, the information processing device of the present disclosure includes a determination means for determining the state of a user using image content, a determination means for determining the content of the image content that encourages the user to engage in mindfulness-related behavior based on the user's state, and an output means for outputting the content of the determined image content.

[0008] The information processing method disclosed herein determines the state of a user using image content, determines the content of the image content that will encourage the user to engage in mindfulness-related behavior based on the user's state, and outputs the content of the determined image content.

[0009] The recording medium of the present disclosure is a recording medium that non-temporarily records a program that causes a computer to execute the following processes: determining the state of a user who uses image content; determining the content of the image content that encourages the user to engage in mindfulness-related behavior based on the user's state; and outputting the content of the determined image content.

[0010] According to the present disclosure, actions to improve the user's condition are more likely to be taken.

[0011] FIG. 1 is a diagram illustrating an example of a configuration of an information processing system according to the present disclosure. FIG. 2 is a diagram schematically illustrating an example of a data flow according to the present disclosure. FIG. 3 is a diagram illustrating an example of a configuration of an information processing device according to the present disclosure. FIG. 4 is a diagram illustrating an example of a display screen according to the present disclosure. FIG. 5 is a diagram illustrating an example of a display screen according to the present disclosure. FIG. 6 is a diagram illustrating an example of an operation flow of an information processing device according to the present disclosure. FIG. 7 is a diagram illustrating an example of a hardware configuration according to the present disclosure.

[0012] An embodiment of the present disclosure will be described in detail with reference to the drawings. FIG. 1 is a diagram illustrating an example of the configuration of an information processing system. The action support system includes, for example, an information processing device 10, a terminal device 20, a sensor 30, and a management device 40. The information processing device 10 is connected to the management device 40, for example, via a network. The information processing device 10 is connected to the sensor 30, for example, via a network. The terminal device 20 is connected to the management device 40, for example, via a network. The information processing device 10 may also be connected to the terminal device 20 via a network. There may be multiple terminal devices 20, multiple sensors 30, and multiple management devices 40. The number of terminal devices 20 and sensors 30 may be set as appropriate. The terminal device 20 and the sensor 30 may also be an integrated system.

[0013] The information processing system is, for example, a system in which a user uses image content. The user is, for example, a person who uses image content by operating the terminal device 20. The image content is, for example, an entertaining image. The image may include a moving image, i.e., a video. The image content is used to provide entertainment to the user, for example, by using an image of a character. The image content is, for example, a game. If the image content is a game, the user is, for example, a person playing the game. In other words, if the image content is a game, the user is a player of the game. The image content may be an image displayed outside of when the game is being played. The game may be a game played using equipment installed in an amusement facility. The image content may also be an image displayed on a standby screen or standby screen of the terminal device 20. The image displayed on the standby screen or standby screen is, for example, an image displayed when the user is not operating the terminal device 20. The image content may also be displayed on the display screen when a condition for displaying the image content is met. The image content may also be an image that is constantly displayed in a part of the display screen or in the background. The image content is not limited to the above.

[0014] The information processing system is a system that supports a user's mindfulness-related behavior using, for example, image content. Mindfulness, for example, means maintaining a good mental and physical state. That is, mindfulness-related behavior is, for example, behavior that a user performs to maintain a good mental and physical state. The mental and physical state is, for example, an inner state or a physical state. When the mental and physical state is an inner state, maintaining a good inner state means, for example, clearing distracting thoughts. Maintaining a good inner state means, for example, reducing stress. Furthermore, maintaining a good inner state means, for example, maintaining a calm mood. For example, when a user is feeling depressed, the user performs mindfulness-related behavior to restore their emotions to a normal state. Furthermore, mindfulness-related behavior may calm the user's emotions when they are heightened. Furthermore, the physical state is, for example, a physical state that can affect the inner state. For example, when a user is tired, they are more likely to feel depressed. In this case, the user's fatigue is a physical state that can affect the inner state.

[0015] Examples of behaviors related to mindfulness by a user include behaviors that themselves lead to mindfulness and behaviors that serve as preparations for mindfulness. Examples of behaviors that themselves lead to mindfulness include at least one of meditation, walking, exercise, yoga, and eating. Meditation includes, for example, controlling breathing. Examples of behaviors that themselves lead to mindfulness may include sleeping. Furthermore, behaviors that themselves lead to mindfulness are not limited to the above. Furthermore, examples of behaviors that serve as preparations for mindfulness include, for example, acquiring items to be used in mindfulness. Examples of behaviors that acquire items to be used in mindfulness include purchasing items to be used in mindfulness. Examples of behaviors that serve as preparations for mindfulness may include researching items to purchase. Furthermore, examples of behaviors that serve as preparations for mindfulness include, for example, signing up for a mindfulness-related service. Examples of behaviors that serve as preparations for mindfulness may include researching the service to sign up for. Furthermore, examples of behaviors that serve as preparations for mindfulness are not limited to the above.

[0016] Supporting mindfulness-related behavior means, for example, encouraging a user to engage in mindfulness-related behavior. Supporting mindfulness-related behavior using image content means, for example, presenting a user with an image that motivates the user to engage in mindfulness-related behavior. Supporting mindfulness-related behavior means, for example, presenting an image that encourages a user to engage in mindfulness-related behavior. An image that encourages mindfulness-related behavior is, for example, an image of a game character that changes in response to the user's mindfulness-related behavior. Supporting mindfulness-related behavior may also mean causing an event to appear within the game that encourages the user to engage in mindfulness-related behavior. If the image that encourages mindfulness-related behavior is not a game character, for example, an image that the user likes may be used as the image that encourages mindfulness-related behavior. For example, the image that encourages mindfulness-related behavior may be a character from an animation work that the user likes. The image that encourages mindfulness-related behavior may be a character depicting an animal that the user likes. Images that encourage mindfulness-related behavior are not limited to the above.

[0017] FIG. 2 is a diagram schematically illustrating an example of data flow in an information processing system. The example in FIG. 2 is a diagram schematically illustrating a state in which a user is playing a game by operating a terminal device 20 and accessing a management device 40. In the example in FIG. 2, a camera captures an image of a user who is a game player. The camera is an example of a sensor 30. For example, the camera outputs captured image data to the information processing device 10. The information processing device 10 determines the user's state based on the acquired image data. The information processing device 10 then determines the state of a character in the game based on the user's state. The state of the character in the game changes depending on the user's state, for example. The information processing device 10 then outputs information indicating the determined state of the character to the management device 40, for example. That is, the information processing device 10 outputs information indicating the state of the character that changes depending on the user's state to the management device 40. The management device 40 outputs, for example, an image generated based on the state of the character acquired from the information processing device 10 to the terminal device 20 as an image of the game character. That is, the management device 40 displays an image of the character that changes depending on the user's state during the game. A user playing a game, for example, looks at an image of a character displayed as a game character on a display device (not shown) of the terminal device 20 and performs mindfulness-related behavior.

[0018] For example, if a user is a game player, when the user's fatigue is determined, the user's fatigue is reflected in the state of the character in the game. For example, an image of the character in a tired state is displayed on the game screen. For example, by seeing the image of the character in a tired state, the user recognizes that it is a good time to take a mindfulness-related action. Then, when the user takes a mindfulness-related action, the character's state returns to normal. In this way, reflecting the user's state and mindfulness-related actions in the game character can motivate the user to take a mindfulness-related action.

[0019] Here, a specific example of the configuration of the information processing device 10 will be described. Fig. 3 is a diagram showing an example of the configuration of the information processing device 10. The information processing device 10 basically includes a determination unit 12, a decision unit 14, and an output unit 16. The information processing device 10 also includes, for example, an acquisition unit 11, an estimation unit 13, a generation unit 15, and a storage unit 17.

[0020] The acquisition unit 11 acquires, for example, data regarding the user's state. The acquisition unit 11 acquires, for example, data regarding the user's state from the sensor 30. The acquisition unit 11 may acquire the data regarding the user's state from the sensor 30 via the terminal device 20. Furthermore, the acquisition unit 11 may acquire the data regarding the user's state from the sensor 30 via the management device 40. The data regarding the user's state is, for example, data used to determine the user's state. The user's state is, for example, the user's physical and mental state. For example, the data regarding the user's state is data regarding at least one of the user's internal state and physical state. In other words, the data regarding the user's state is, for example, data used to determine at least one of the user's internal state and physical state. Furthermore, the acquisition unit 11 acquires, for example, the user's state when the user is performing a mindfulness-related behavior. Furthermore, the acquisition unit 11 may acquire the user's state when the user has completed the mindfulness-related behavior.

[0021] The acquisition unit 11 may acquire the user's status at at least one of the timings of startup and termination of operation of the terminal device 20. The acquisition unit 11 may also acquire the user's status at at least one of the timings of start and termination of use of the terminal device 20. The timing of acquiring the user's status is not limited to the above.

[0022] The data regarding the user's condition is, for example, image data of the user. When the data regarding the user's condition is image data of the user, the sensor 30 is, for example, a camera that captures at least one of the user's facial expressions and body movements. For example, when the image content is a game, the data regarding the user's condition is, for example, image data of the user playing the game.

[0023] The data relating to the user's condition may be, for example, the user's biometric data. The user's biometric data is, for example, measurement data that may be affected by the user's internal and physical conditions. The biometric data is, for example, measurement data of at least one of body temperature, pulse rate, heart rate, blood pressure, and sweat rate. The biometric data is not limited to the above. The user's biometric data is, for example, measured by a sensor 30 worn by the user. Alternatively, a smartwatch worn by the user may be equipped with the sensor 30 that measures the biometric data.

[0024] The data relating to the user's state may be data on the user's speech and behavior. The data on the user's speech and behavior is, for example, data that reflects the user's internal state. The data on the user's speech and behavior is, for example, at least one of the following data: the voice of a conversation the user is having with another person, the voice input to a voice recognition device, and the voice that the user is making to provide commentary. The data on the user's speech and behavior is not limited to the above. In this case, the sensor 30 is a microphone that collects the user's voice.

[0025] The data relating to the user's state is data relating to the operation status of the device by the user. The data relating to the operation status of the device by the user is, for example, a log of the device operation by the user. The log of the device operation by the user is, for example, a log of operations in which the operation method may change depending on the user's internal state. The log of the device operation by the user may be a log of at least one of the following items: operation interval, operation speed, operation strength, operation error, and retry of operation. The operation strength is, for example, the strength of the force applied by the user to the device for operation. The log of the device operation by the user is not limited to the above. The data relating to the operation status of the device by the user is collected, for example, by the terminal device 20. The acquisition unit 11 then acquires the data relating to the operation status of the device by the user from the terminal device 20.

[0026] The determination unit 12 determines the state of a user using image content. Determining the user's state, for example, involves determining the degree of the state that may affect the user's daily life or work. For example, if the user's level of fatigue is high, the user may feel depressed and experience difficulties in daily life. In this case, the determination unit 12 determines the user's level of fatigue, for example, based on image data of the user. The determination unit 12 determines, for example, at least one of the user's physical state and internal state. The user's physical state is at least one of posture, fatigue level, load, movement of each body part, speed of movement, accuracy of movement, and rhythm of movement. The user's physical state is not limited to the above. The user's internal state is at least one of mental state, emotion, concentration, mood, motivation, relief, tension, fear, liking, and interest. The user's internal state is also not limited to the above.

[0027] The determination unit 12 determines the user's condition based on, for example, at least one of the user's image data, biometric data, audio data, and operation log. The determination unit 12 may also determine the user's condition based on a purchase history. Alternatively, the determination unit 12 may determine the user's condition based only on the purchase history. The data used by the determination unit 12 to determine the user's condition is not limited to the above. Alternatively, the determination unit 12 may determine the user's condition based on a timeline of the user's mindfulness-related behavior. By determining the user's condition based on a timeline of the user's mindfulness-related behavior, it is possible to determine, for example, the effect of the user's mindfulness-related behavior on improving the user's condition.

[0028] When the data regarding the user's condition is image data, the determination unit 12 determines at least one of the user's physical condition and internal state using, for example, an image recognition model. The image recognition model is, for example, a machine learning model that estimates the user's condition from image data. The image recognition model is, for example, a machine learning model that can recognize the emotions and fatigue level of a person whose face appears in an image included in a video based on, for example, a video of a person. The image recognition model recognizes the emotions and fatigue level of a person appearing in an image based on, for example, changes in feature points set on the person's face. The image recognition model may also recognize the emotions and fatigue level of a person appearing in an image based on, for example, changes in feature points set on the person's body parts. The image recognition model is generated, for example, by learning the relationship between an image showing at least one of the user's face and the user's body and the user's condition in the image.

[0029] When the data relating to the user's condition is voice data of the user's words and actions, the determination unit 12 determines at least one of the user's physical condition and internal state, for example, using a voice recognition model. The voice recognition model is a machine learning model that estimates the user's condition from the voice data of the user's words and actions. The voice recognition model estimates the user's condition based on, for example, changes in voice speed, pitch, and volume contained in the voice data. The voice recognition model is generated, for example, by learning the relationship between the voice data of the user's words and actions and the user's condition.

[0030] When the data relating to the user's condition is biometric data, the determination unit 12 determines at least one of the user's physical condition and internal state using a state estimation model. The state estimation model is a learning model that estimates the user's condition from the user's biometric data. The state estimation model is generated, for example, by learning the relationship between the user's biometric data and the user's condition.

[0031] When the data regarding the user's state is an operation log, the determination unit 12 determines at least one of the user's physical state and internal state using an operation state estimation model. The operation state estimation model is a learning model that estimates the user's state from the user's operation log. The state estimation model is generated, for example, by learning the relationship between the user's operation log and the user's state. The image recognition model, voice recognition model, state estimation model, and operation state estimation model are each generated, for example, by deep learning using a neural network. The learning algorithms that generate the image recognition model, voice recognition model, state estimation model, and operation state estimation model are not limited to those described above. Furthermore, the image recognition model, voice recognition model, state estimation model, and operation state estimation model are each generated, for example, in a system external to the information processing device 10.

[0032] The determination unit 12 determines the mindfulness-related behavior performed by the user based on, for example, the content of the output image content. The determination unit 12 determines whether the user is performing a mindfulness-related behavior based on, for example, image data of the user. The determination unit 12 may determine what kind of mindfulness-related behavior the user is performing based on image data of the user. That is, the determination unit 12 may determine the type of mindfulness-related behavior the user is performing based on, for example, image data of the user. Determining the type of mindfulness-related behavior means determining which behavior the user is performing, for example, meditation, exercise, yoga, eating, reading aloud, speaking, singing, or talking.

[0033] The determination unit 12 determines the user's mindfulness-related behavior using a determination model based on, for example, image data of the user captured by the acquisition unit 11. The determination model is a learning model that estimates the user's mindfulness-related behavior based on image data of the user. The determination model is generated, for example, by learning the relationship between the image data of the user captured and types of mindfulness-related behavior.

[0034] The determination unit 12 may determine whether the user is engaging in mindfulness-related behavior based on at least one of the user's biometric data and audio data of the user's words and actions. For example, when determining mindfulness-related behavior based on biometric data, the determination model is generated by learning the relationship between the biometric data when the user is engaging in mindfulness-related behavior and the type of mindfulness-related behavior. Furthermore, when determining mindfulness-related behavior based on audio data of words and actions, the determination model is generated by learning the relationship between the audio data when the user is engaging in mindfulness-related behavior and the type of mindfulness-related behavior. The determination model is generated, for example, by deep learning using a neural network. The learning algorithm for generating the determination model is not limited to the above. Furthermore, the determination model may be generated, for example, in a system external to the information processing device 10.

[0035] When the mindfulness-related behavior is meditation, the determination unit 12 determines whether the user is meditating, for example, based on image data of the user using a determination model. The determination unit 12 may determine the length of time the user has been meditating, for example, based on image data of the user using a determination model. The determination unit 12 may further determine at least one of the user's facial expression and body movement while the user is meditating, for example, based on image data of the user using a determination model. The determination unit 12 may estimate the user's level of concentration on meditation, for example, based on image data of the user using a determination model. The determination unit 12 may estimate the user's level of concentration on meditation, for example, based on body movement while the user is meditating. The determination unit 12 may estimate the user's level of calmness while the user is meditating, for example, based on image data of the user. The determination unit 12 estimates the user's level of calmness, for example, based on the user's facial expression while the user is meditating.

[0036] The determination unit 12 may determine the state of the user at at least one of the timings of starting up and ending operation of the terminal device 20. The determination unit 12 may also determine the state of the user at at least one of the timings of starting use and ending use of the terminal device 20. The timing of determining the state of the user is not limited to the above.

[0037] The estimation unit 13 estimates a mindfulness behavior method suitable for the user based on, for example, the state of the user. The mindfulness behavior method suitable for the user is, for example, at least one of the timing when the user needs to perform mindfulness behavior and a form of mindfulness behavior suitable for the user. If the timing for outputting image content that encourages the user to perform mindfulness behavior and the form of mindfulness behavior are determined, the estimation unit 13 does not need to estimate a mindfulness behavior method suitable for the user. The estimation unit 13 estimates a suitable timing for the user to perform mindfulness behavior based on, for example, the state of the user. The estimation unit 13 estimates a suitable timing for the user to perform mindfulness behavior based on, for example, at least one of the user's internal state and physical state. For example, when the user's fatigue level exceeds a standard for recommending mindfulness behavior, the estimation unit 13 estimates that it is recommended that the user immediately perform mindfulness behavior. Furthermore, when the user's fatigue level is increasing, the estimation unit 13 estimates, for example, the user's fatigue level from the present time onward, and estimates the timing when the user will need to take a mindfulness-related action.

[0038] The estimation unit 13 estimates, for example, mindfulness-related behaviors that are suitable for the user. The estimation unit 13 estimates the type of mindfulness behavior that is suitable for the user, for example, based on the state of the user. Here, estimating the type of mindfulness behavior that is suitable for the user means estimating which of meditation, exercise, yoga, eating, reading aloud, speaking, singing, and conversation is suitable for the user, for example. The estimation unit 13 may further estimate at least one of the number of times, duration, repetition frequency, intensity of load, and intake amount of the mindfulness-related behavior that is suitable for the user.

[0039] The relationship between the state of the user and the type of mindfulness behavior suitable for the user is set using, for example, a table. The estimation unit 13, for example, refers to the table and estimates a form of mindfulness behavior suitable for the user based on the state of the user. The estimation unit 13 may also estimate a form of mindfulness behavior suitable for the user using an estimation model based on the state of the user. The estimation model is, for example, a learning model that estimates a form of mindfulness behavior suitable for the user using the state of the user as input data. The estimation model is generated, for example, by learning the relationship between the state of the user and the form of mindfulness behavior suitable for the user. The estimation model is generated, for example, by deep learning using a neural network. The learning model used to generate the estimation model is not limited to the above. The estimation model may also be generated, for example, in a system external to the information processing device 10.

[0040] For example, when the determination unit 12 determines that the user is emotionally restless, the estimation unit 13 estimates that meditating to calm the user is a mindfulness-related behavior suitable for the user. Also, when the determination unit 12 determines that the user has a tendency to have high blood pressure, the estimation unit 13 estimates that consuming foods that lower blood pressure is a mindfulness-related behavior suitable for the user.

[0041] The estimation unit 13 estimates a form of mindfulness-related behavior suitable for the user, for example, further based on the user's purchase history. The estimation unit 13 may estimate a form of mindfulness-related behavior suitable for the user, for example, based only on the user's purchase history. For example, if the user purchases a supplement and the supplement is suitable for mindfulness, the estimation unit 13 may estimate that taking the supplement is suitable as a mindfulness-related behavior. Furthermore, the estimation unit 13 may estimate a form of mindfulness-related behavior suitable for the user from among behaviors the user can perform, based on the user's purchase history.

[0042] The estimation unit 13 may estimate a form of mindfulness-related behavior suitable for the user from among events that are actually taking place. The estimation unit 13 estimates a form of mindfulness-related behavior suitable for the user based on, for example, the user's state and a schedule of events taking place in the user's area of ​​residence. For example, when the user's emotions are unstable and a zazen event is being held at a temple, the estimation unit 13 estimates that going to the temple to practice zazen is a form of mindfulness-related behavior suitable for the user. Furthermore, for example, when the user has been inactive for a long time and a lecture on radio calisthenics is being held in the user's area of ​​residence, the determination unit 14 estimates that participating in radio calisthenics is a form of mindfulness-related behavior suitable for the user.

[0043] The estimation unit 13 may estimate a form of mindfulness-related behavior suitable for the user from among affiliated events or products. Products may include services. Affiliated events or products are, for example, events or products provided to users by an affiliate of a business providing image content. For example, in a case where the business is affiliated with a business selling supplements, the estimation unit 13 associates taking supplements provided by the affiliated business as a form of mindfulness-related behavior suitable for the user. Furthermore, in a case where the business is affiliated with a business operating a gym, the estimation unit 13 associates going to a gym operated by the affiliated business as a form of mindfulness-related behavior suitable for the user. Furthermore, in a case where the business is affiliated with a business operating an event, the estimation unit 13 estimates attending an event held by the affiliated business as a form of mindfulness-related behavior suitable for the user. Furthermore, in a case where the business is affiliated with a business operating a restaurant, the estimation unit 13 estimates going to eat a healthy menu provided by the affiliated restaurant as a form of mindfulness-related behavior suitable for the user. Furthermore, for example, in the case where the user is affiliated with a travel planning business, the estimation unit 13 estimates that participation in a trekking event held by the affiliated business is a form of mindfulness-related behavior suitable for the user. Events that are to be estimated as forms of mindfulness-related behavior are not limited to those mentioned above.

[0044] The estimation unit 13 may estimate a type of mindfulness-related behavior suitable for the user based on the state of the user at at least one of the timings when the terminal device 20 is started and when the operation is ended. Furthermore, the estimation unit 13 may estimate a type of mindfulness-related behavior suitable for the user based on the state of the user at at least one of the timings when the use of the terminal device 20 is started and when the use is ended.

[0045] For example, if the terminal device 20 is a terminal device for gaming, the estimation unit 13 may estimate a form of mindfulness-related behavior suitable for the user based on the state of the user at at least one of the timings of starting and ending the game. Furthermore, for example, if the terminal device 20 is a terminal device used for work, the estimation unit 13 estimates a form of mindfulness-related behavior that can improve work efficiency based on the state of the user when the terminal device 20 is started. Furthermore, for example, if the terminal device 20 is a terminal device used for work, the estimation unit 13 estimates a form of mindfulness-related behavior that can reduce the user's fatigue based on the state of the user when the terminal device 20 ends its operation. Furthermore, the estimation unit 13 may estimate whether or not mindfulness-related behavior is necessary based on the state of the user at at least one of the timings of starting up the terminal device 20 and ending the operation. When estimating whether or not mindfulness-related behavior is necessary, the estimation unit 13 may estimate a form of mindfulness-related behavior suitable for the user, for example, when it estimates that mindfulness-related behavior is necessary.

[0046] The determination unit 14 determines the content of image content that encourages the user to behave in a mindfulness-related manner based on the user's state. The determination unit 14, for example, determines at least one of the state of a character appearing in the image content and an event within the image content as the content of image content that encourages the user to behave in a mindfulness-related manner. Image content that encourages the user to behave in a mindfulness-related manner is, for example, image content that encourages behavior that improves the user's state. Improving the user's state refers to, for example, improving at least one of the user's internal state and physical state. Furthermore, improving the user's state may include maintaining at least one of the user's internal state and physical state in a good state. The determination unit 14, for example, determines at least one of the character's state and an event to be displayed as image content that encourages behavior that improves the user's internal state and physical state based on at least one of the user's internal state and physical state. The determination unit 14, for example, determines at least one of the character's state and an event that encourages the user to behave in a mindfulness-related manner based on the user's state. The determination unit 14 determines at least one of a character state and an event that encourages the user to behave in a mindfulness-related manner, for example, based on at least one of the user's internal state and physical state.

[0047] The internal state of the user is, for example, at least one of the following: mental fatigue level, emotion, emotional stability, and concentration level. The internal state of the user is not limited to the above. The physical state of the user is, for example, at least one of the user's posture, body temperature, pulse rate, heart rate, blood pressure, and sweat rate. The determination unit 14 may also determine at least one of a character state and an event that reflects the type of mindfulness-related behavior estimated by the estimation unit 13.

[0048] The relationship between the user's state and the character state and event displayed in the image content is set, for example, as table data. The determination unit 14 determines the content of the image content that encourages the user to engage in mindfulness-related behavior, for example, based on table data associating the user's internal or physical state with the character state. The determination unit 14 determines the character state, for example, based on table data associating the user's internal or physical state with the character state. The character state refers to, for example, how the character appears in the image of the image content and the characteristics of the character in the image content. The determination unit 14 also determines an event, for example, based on table data associating the user's internal or physical state with an event. An event refers, for example, to image content with content that is different from usual. The determination unit 14 uses, for example, a determination model to determine at least one of the character state and the event to be displayed as image content that encourages behavior that improves the user's state. The determination model is, for example, a learning model that determines the character state and event to be output in the image content based on the user's state. The decision model is generated, for example, by learning the relationship between the user's state and the character's state and events. The decision model is generated, for example, by deep learning using a neural network. The decision model is generated, for example, in a system external to the information processing device 10.

[0049] When the image content is a game, the determination unit 14 determines the state of a character operated by a user based on, for example, the state of the user. The determination unit 14 determines the state of a character operated by a user so that the state of the character operated by the user changes depending on the state of the user. For example, when the user is tired, the determination unit 14 determines the state of the character so that the character operated by the user is in a tired state. Furthermore, when the user is not performing a mindfulness-related behavior, the determination unit 14 may determine the state of the character so that the character operated by the user is in a tired state. Furthermore, for example, when the user is emotionally calm, the determination unit 14 determines the state of the character so that the character operated by the user is emotionally calm.

[0050] If the image content is a game, the determination unit 14 may determine at least one of the character's level, stage(s) that can be entered, scenario, usable weapons, usable items, usable spells, usable vehicles, and interlocutors based on the state of the user who is a game player. For example, the determination unit 14 may determine weapons to be used by the character so that the character can use better weapons as the user's internal state level increases through mindfulness-related behavior. Furthermore, for example, the determination unit 14 may determine a range of characters with which the character operated by the user can converse so that the user can talk to more characters as the user's emotional calmness increases through mindfulness-related behavior. The presence or absence of emotional calmness is determined, for example, based on the range of fluctuation in biometric data. Furthermore, for example, the determination unit 14 may determine an event in which the character will act in a special stage when the user's emotional calmness increases through mindfulness-related behavior.

[0051] The determination unit 14 may determine the content of the image content based on the quality of the mindfulness-related behavior performed by the user in accordance with the content of the output image content. For example, the determination unit 14 determines at least one of a character state and an event based on the result of an improvement in the user's internal state or physical state as a result of the user's mindfulness-related behavior. The determination unit 14 may determine at least one of a character state and an event based on, for example, the degree of improvement in the internal state or physical state as a result of the user's mindfulness-related behavior. The degree of improvement in the internal state or physical state may be set in multiple stages. The determination unit 14 may determine at least one of a character state and an event based on, for example, the stage of the degree of improvement in the internal state or physical state. When the degree of improvement in the internal state or physical state is greater than a standard, at least one of a special character state and a special event may be determined. The standard for determining the special character state and the special event is set, for example, to motivate the user to practice mindfulness.

[0052] The generation unit 15 generates, for example, an image of a character or instructions related to an image of a character. The character is, for example, a character in a game played by the user. When generating an image of a character in the information processing device 10, the generation unit 15 generates the image of the character based on, for example, the state of the character determined by the determination unit 14. The generation unit 15 generates the image of the character by, for example, reflecting the state of the character determined by the determination unit 14 in the image of the character. For example, when the character is tired, the generation unit 15 generates an image of the character in a tired state.

[0053] The generation unit 15 selects image parts according to the type and appearance of the character from an image database that stores the parts that make up the character, and then generates an image of the character by combining the selected images.

[0054] The generation unit 15 may output an image of a character that reflects the state of the user before the mindfulness-related behavior. Furthermore, the output unit 16 may generate an animated image of a character that reflects a change in the state of the user due to the mindfulness-related behavior.

[0055] The generation unit 15 may generate a character image using an image generation model. The image generation model is a learning model that uses, for example, the character type and the character state as input data and outputs a character image. The image generation model is generated using, for example, GAN (Generative Adversarial Networks). The learning algorithm for generating the image generation model is not limited to the above. Furthermore, the image generation model may be generated, for example, in a system external to the information processing device 10.

[0056] When a character image is generated in the terminal device 20 or the management device 40, the generation unit 15 generates instructions regarding the character image, for example, based on the state of the character determined by the determination unit 14. The instructions regarding the character image are, for example, information indicating criteria for image generation. The instructions regarding the character image include, for example, information regarding one or more items of the selection criteria for the character image, the adjustment value of the indicator indicating the state of the character, and the amount of change in the character's movement. The instructions regarding the character image are not limited to the above.

[0057] If the image content is a game, the adjustment value of the indicator indicating the character's status may be, for example, the recovery value of the character's stamina as a result of performing an action related to mindfulness. The adjustment value of the indicator indicating the character's status may also be a recovery value other than stamina. For example, the adjustment value of the indicator indicating the character's status may indicate a change in the character's level in the game. Furthermore, the adjustment value of the indicator indicating the character's status may indicate an item that has become available in the game as a result of performing an action related to mindfulness. The adjustment value of the indicator indicating the character's status is not limited to the above. Furthermore, the amount of change in the character's movement may be, for example, information regarding the amount of change in one or more of the character's posture, stride length, movement speed, and jump height as a result of performing an action related to mindfulness. The amount of change in the character's movement is not limited to the above.

[0058] The generation unit 15 may generate an event screen or a generation criterion for the event screen within the image content. When generating an event image in the information processing device 10, the generation unit 15 generates the event screen, for example, based on the event determined by the determination unit 14. The generation unit 15 selects image parts to be used in the event from an image database that stores each part that constitutes the event screen, for example, based on the content of the event. Then, the generation unit 15 generates the event screen by combining the selected images.

[0059] The generation unit 15 may generate an event screen using a screen generation model. The screen generation model may be generated using, for example, a GAN. The learning algorithm for generating the screen generation model is not limited to the above. Furthermore, the screen generation model may be generated in, for example, a system external to the information processing device 10.

[0060] When a character image is generated in the terminal device 20 or the management device 40, the generation unit 15 generates design standards for the event screen and rules for the event, for example, based on the event determined by the determination unit 14. For example, when the image content is a game, the generation unit 15 generates standards for items to be placed on the event screen and for characters that appear. The generation unit 15 also sets rules, such as conditions for achieving the event and incentives to be given to users upon achieving the event. The relationship between the event, the design standards for the event screen, and the rules for the event is set, for example, in a table. The generation unit 15 may also generate information that identifies the event, for example, based on the event determined by the determination unit 14. When generating information that identifies the event, the relationship between the content of the event and the information that identifies the event is shared between the information processing device 10 and the terminal device 20 or the management device 40.

[0061] The output unit 16 outputs the details of the image content determined by the determination unit 14. For example, if the image content is a game, the output unit 16 outputs the details of the image content determined by the determination unit 14 so that the details of the image content determined by the determination unit 14 are displayed on the game screen. The output unit 16 outputs, for example, the details of the image content determined by the determination unit 14. The output unit 16 outputs at least one of the character state and the event determined by the determination unit 14 as the details of the image content. The output unit 16 outputs the details of the image content determined by the determination unit 14 to, for example, the terminal device 20. The output unit 16 may output the details of the image content determined by the determination unit 14 to the management device 40. Furthermore, the output unit 16 may output the details of the image content determined by the determination unit 14 based on the timing appropriate for the mindfulness-related behavior estimated by the estimation unit 13.

[0062] Furthermore, the output unit 16 may output instructions regarding the image of the character generated by the generation unit 15 or generation criteria for the event screen as the content of the image content. The output unit 16 outputs instructions regarding the image of the character generated by the generation unit 15 or generation criteria for the event screen as the content of the image content, for example, to the terminal device 20 or the management device 40. The output unit 16 may also output the image of the character generated by the generation unit 15 or the event screen as the content of the image content. The output unit 16 outputs the image of the character generated by the generation unit 15 or the event screen as the content of the image content, for example, to the terminal device 20 or the management device 40.

[0063] The output unit 16 may further output a character that gives instructions for mindfulness-related behavior. The output unit 16 may output an animated image of a character that reflects the movements of the user in the mindfulness-related behavior that the user is performing in accordance with the content of the output image content.

[0064] The output unit 16 may further output time-series data of the user's state determined by the determination unit 12. The output unit 16 may output a history of mindfulness-related actions taken by the user according to the content of the output image content. The output unit 16 may also output an improvement effect of the user's state along with the history of mindfulness-related actions taken by the user. The output unit 16 may also output the improvement effect of the user's state using a character image. For example, the output unit 16 outputs a character image that reflects the user's state before and after a mindfulness-related action. The output unit 16 may also output an animated character image that reflects a change in the user's state due to a mindfulness-related action.

[0065] Fig. 4 is a diagram showing an example of a display screen when the user is a game player. The example of the display screen in Fig. 4 is a display screen of a game in which an animal character controlled by the player goes on an adventure. The example of the display screen in Fig. 4 shows a state in which the character's stamina is reduced by being caught in the rain. In this case, it is set so that when the player performs an action related to mindfulness, the character's stamina is restored by taking a rest.

[0066] The determination unit 12 determines the state of the user, who is a game player, based on, for example, an image of the user. For example, if it is determined that the user is fatigued, the determination unit 14 determines that the state of the character is one in which the character's physical strength will not recover unless the character rests and meditates. The output unit 16 then outputs the determined state of the character. A screen such as the example of the display screen in FIG. 4 is displayed on the display screen of the terminal device 20.

[0067] When a screen like the example display screen of Figure 4 is displayed, the determination unit 12 determines whether the user, who is a game player, has meditated, for example. If it is determined that the user has meditated, the generation unit 15 reflects the user's meditation in the character's state. Then, the output unit 16 outputs the character's state that reflects the user's meditation.

[0068] Fig. 5 is an example of a display screen in which the state of a character reflects the user's meditation in the state shown in the example of the display screen in Fig. 4. In the example of the display screen in Fig. 5, the user, who is a game player, meditated, causing the character to rest under a hole and recover its stamina. With the character's stamina restored, the user can, for example, progress through the game.

[0069] The example of the display screen in Fig. 6 is an example of a display screen of a game in which an animal character controlled by a player goes on an adventure, and which shows a different scene from the display screen shown in Fig. 4. The example of the display screen in Fig. 6 is a screen in which the character is standing on the bank of a river. The example of the display screen in Fig. 6 shows a state in which the character is unable to proceed due to the presence of a river. The example of the display screen in Fig. 6 shows a state in which the character is perplexed and sweating because he is unable to proceed.

[0070] Figure 7 is an example of a display screen in which, when the example display screen of Figure 6 is displayed, a boat appears as an item for moving on water when the user performs a mindfulness-related action. In the example display screen of Figure 7, an item that can be obtained by performing a mindfulness-related action is set, such as when a character meditates or rests at night, causing a boat to appear. In the example display screen of Figure 6, the character was unable to proceed beyond the riverbank, whereas in the example display screen of Figure 7, the character is moving on the water in a boat. In this way, when an item is needed to progress in the game, the user can progress in the game by performing a mindfulness-related action.

[0071] The storage unit 17 stores, for example, data for determining the user's state. The data used to determine the user's state includes, for example, image data of the user and biometric data of the user. The storage unit 17 stores, for example, estimation criteria for a form of mindfulness-related behavior suitable for the user. The storage unit 17 stores, for example, criteria for determining mindfulness-related behavior. The storage unit 17 stores, for example, image data of a character. The storage unit 17 also stores, for example, setting data and image data of in-game events. The storage unit 17 also stores an image recognition model, a voice recognition model, a state estimation model, an operation state estimation model, a judgment model, an estimation model, a decision model, an image generation model, and a screen generation model. Each of the learning models may be stored in a storage means external to the information processing device 10.

[0072] The terminal device 20 is, for example, a terminal device used by a user to view image content. The terminal device 20 acquires, for example, a character image from the output unit 16 of the information processing device 10. The terminal device 20 then outputs the character image to a display device (not shown). The terminal device 20 also acquires, for example, an event screen from the output unit 16 of the information processing device 10. The terminal device 20 then outputs the event screen to a display device (not shown).

[0073] The terminal device 20 may be, for example, a portable game console, a stationary game console, a smartphone, a mobile phone, a smartwatch, a tablet computer, or a personal computer. The terminal device 20 may also be a game console. The terminal device 20 may also be combined with AR (Augmented Reality) glasses or VR (Virtual Reality) glasses. The terminal device 20 may also be a part of a game machine. The terminal device 20 may also be a gaming machine installed in an amusement facility or a part of the gaming machine.

[0074] The sensor 30 measures the user's condition, for example. The sensor 30 is at least one of a camera, a vital sign sensor, and a microphone. The sensor 30 may be a combination of multiple types of sensors. The sensor 30 outputs acquired data to the acquisition unit 11 of the information processing device 10, for example. The sensor 30 may output acquired data to the acquisition unit 11 of the information processing device 10 via the terminal device 20, for example. The terminal device 20 and the sensor 30 may be integrated into one device. For example, the sensor 30 may be provided in a smartphone or a smartwatch. The sensor 30 may be provided in AR glasses or VR glasses.

[0075] The management device 40 outputs image content to, for example, the terminal device 20. For example, the management device 40 acquires, from the output unit 16 of the information processing device 10, an image of a character encouraging mindfulness-related behavior as the content of the image content. Then, the management device 40 outputs, for example, to the terminal device 20, image content including, on the display screen, an image of a character encouraging mindfulness-related behavior. The management device 40 also acquires, from the output unit 16 of the information processing device 10, an image of a character reflecting a mindfulness-related behavior performed by the user as the content of the image content. Then, the management device 40 outputs, for example, to the terminal device 20, image content including, on the display screen, an image of a character reflecting a mindfulness-related behavior performed by the user.

[0076] The management device 40 may also have a function to generate images to be used in image content. If the management device 40 has the function to generate images to be used in image content, the management device 40 acquires, for example, instructions regarding a character image or generation criteria for an event screen from the output unit 16 of the information processing device 10. Upon acquiring the instructions regarding a character image, the management device 40 generates an image of the character, for example, based on the instructions regarding the character image. The management device 40 then outputs, for example, to the terminal device 20, image content including the generated character image on the display screen. Upon acquiring generation criteria for an event screen, the management device 40 generates an image of the event, for example, based on the generation criteria for the event screen. The management device 40 then outputs, for example, to the terminal device 20, image content including the image of the event on the display screen.

[0077] If the image content is a game, the management device 40 stores, for example, data related to the game. The management device 40 also outputs, for example, the data related to the game to the terminal device 20. For example, the management device 40 outputs the data related to the game so that an image of a character or an event that encourages mindfulness-related behavior is displayed on the game screen. The management device 40 also outputs the data related to the game so that an image of a character or an event that reflects a mindfulness-related behavior performed by the user is displayed on the game screen. The terminal device 20 and the management device 40 may also be integrated into one device.

[0078] The following describes a process in which the information processing device 10 determines a character or event to be displayed to encourage a user to take mindfulness-related actions. Fig. 8 shows an example of an operational flow in the process in which the information processing device 10 determines a character to be displayed to encourage a user to take mindfulness-related actions. The following description will be given taking as an example a case in which the state of a user is determined based on an image of the user.

[0079] The acquisition unit 11 acquires, for example, an image of the user from the sensor 30 (step S11).

[0080] When the image of the user is acquired, the determination unit 12 determines the state of the user based on the image of the user (step S12). The determination unit 12 determines, for example, whether the user is in a state requiring mindfulness.

[0081] If the user is in a state requiring mindfulness (Yes in step S13), the output unit 16 outputs an image to encourage the user to take action related to mindfulness to the terminal device 20 via the management device 40 (step S14). For example, when it is determined that the user is fatigued and the output unit 16 encourages the user to take action related to mindfulness, the output unit 16 outputs an image of a character in a tired state to the terminal device 20 via the management device 40. The user's state is not limited to fatigue.

[0082] When the image for encouraging the user to take mindfulness-related actions is output, the determination unit 12 acquires an image of the user (step S15).

[0083] When the image of the user is acquired, the determination unit 12 determines the state of the user based on the image of the user (step S16).

[0084] If the user is performing a mindfulness-related behavior (Yes in step S17), the output unit 16 outputs an image of the character in an improved state to the terminal device 20, for example, via the management device 40 (step S18).

[0085] In step S13, if the state does not require mindfulness (No in step S13), the process returns to step S11, and acquisition of an image of the user and determination of the user's state continue.

[0086] In step S17, if the user is not engaging in mindfulness-related behavior (No in step S17), the output unit 16 continues to output, for example, an image of a character whose condition worsens. If the user is not engaging in mindfulness-related behavior, the output unit 16 outputs, for example, an image of a character whose condition worsens (step S19). After outputting the image of a character whose condition worsens, the process returns to step S14, and the output unit 16 outputs, for example, an image to encourage the user to engage in mindfulness-related behavior to the terminal device 20 via the management device 40.

[0087] The information processing device 10 of the present disclosure can also be applied to healthcare. Specifically, the information processing device 10 acquires, for example, vital data of a user. Then, the information processing device 10 determines the user's health condition using a determination model generated by machine learning. Instead of making the mindfulness-related determination (steps S13 and S17) in FIG. 9 , the information processing device 10 outputs an image that supports decision-making regarding actions related to improving the health condition (step S14). Note that, in addition to using the machine learning model generated by machine learning, the determination of the user's condition and the selection of images suitable for the user may also incorporate advice from medical professionals such as doctors.

[0088] The information processing device 10 determines the state of a user who uses image content. Based on the user's state, the information processing device 10 determines the content of the image content that encourages the user to take mindfulness-related actions. The information processing device 10 then outputs the determined content of the image content. In this way, by outputting the content of the image content that encourages the user to take mindfulness-related actions based on the determination result of the user's state who uses the image content, it is possible to make it easier for the user to take actions to improve their state.

[0089] When estimating the timing when a user needs to perform mindfulness-related behavior, the information processing device 10 outputs, for example, an image to encourage the user to perform the mindfulness-related behavior based on the estimated timing. Therefore, the user can perform the mindfulness-related behavior in accordance with the timing when the user needs to perform the mindfulness-related behavior. Therefore, by using the information processing device 10, the user can maintain a good mental and physical state. Furthermore, when estimating the form of mindfulness-related behavior that is suitable for the user, the information processing device 10 outputs, for example, an image to encourage the user to perform the mindfulness-related behavior based on the estimated form. Therefore, the user can perform the mindfulness-related behavior that is suitable for the user. Therefore, by using the information processing device 10, the effectiveness of performing the mindfulness-related behavior can be improved.

[0090] When the image content is a game, the information processing device 10, for example, determines the fatigue of a player playing the game using the terminal device 20. Then, based on the fatigue determination result, the information processing device 10 displays, within the image content of the game, an image of a character that encourages the player to engage in mindfulness-related behavior. For example, the information processing device 10 displays an image of a character with a fatigued expression. Seeing the image of the character with a fatigued expression makes the player feel the need to engage in mindfulness. By making the player feel the need to engage in mindfulness, the player will continue to engage in mindfulness-related behavior. Furthermore, for example, the information processing device 10 performs processing under a setting where, unless the player engages in mindfulness-related behavior, the character's fatigue will not recover and the game scenario will not progress. By performing such processing, the game player will engage in mindfulness-related behavior in order to progress in the game. Therefore, the game player will continue to engage in mindfulness-related behavior. In this way, by using the information processing device 10, the user can, for example, continue to engage in mindfulness-related behavior. In other words, by using the information processing device 10, it becomes easier for the user to engage in behavior that improves their condition.

[0091] Each process in the information processing device 10 may be distributed and executed among multiple information processing devices connected via a network. For example, the processes in the acquisition unit 11 and the determination unit 12 and the processes in the estimation unit 13, the decision unit 14, and the generation unit 15 may be executed in different information processing devices. It may be set as appropriate which of the multiple information processing devices executes each process in the information processing device 10. Furthermore, some or all of the processes in the information processing device 10 may be executed in the terminal device 20 or the management device 40.

[0092] Each process in the information processing device 10 can be realized by executing a computer program on the computer. Fig. 9 shows an example of the configuration of a computer 100 that executes a computer program that performs each process in the information processing device 10. The computer 100 includes a CPU (Central Processing Unit) 101, a memory 102, a storage device 103, an input / output I / F (Interface) 104, and a communication I / F 105.

[0093] The CPU 101 reads and executes computer programs for performing each process from the storage device 103. The CPU 101 may be configured with a combination of multiple CPUs. The CPU 101 may also be configured with a combination of a CPU and another type of processor. For example, the CPU 101 may be configured with a combination of a CPU and a graphics processing unit (GPU). The memory 102 is configured with a dynamic random access memory (DRAM) or the like, and temporarily stores computer programs executed by the CPU 101 and data being processed. The storage device 103 stores computer programs executed by the CPU 101. The storage device 103 is configured with, for example, a non-volatile semiconductor storage device. Other storage devices such as a hard disk drive may also be used for the storage device 103. The input / output I / F 104 is an interface that receives input from an operator and outputs display data, etc. The communication I / F 105 is an interface that transmits and receives data between the terminal device 20, the management device 40, and other information processing devices. The terminal device 20 may also have a similar configuration.

[0094] The computer program used to execute each process can also be stored and distributed on a computer-readable recording medium that non-temporarily stores data. Examples of recording media that can be used include magnetic tapes for recording data and magnetic disks such as hard disks. Optical disks such as CD-ROMs (Compact Disc Read Only Memory) can also be used as recording media. Non-volatile semiconductor storage devices can also be used as recording media.

[0095] A part or all of the above-described embodiments can be described as, but not limited to, the following supplementary notes.

[0096] [Supplementary Note 1] An information processing device comprising: a determination means for determining the state of a user who uses image content; a determination means for determining, based on the state of the user, the content of the image content that encourages the user to take mindfulness-related actions; and an output means for outputting the determined content of the image content.

[0097] [Supplementary Note 2] The information processing device according to Supplementary Note 1, wherein the determining means determines at least one of a state of a character appearing in the image content and an event within the image content as the content of the image content that encourages the user to engage in mindfulness-related behavior.

[0098] [Supplementary Note 3] The information processing device according to Supplementary Note 1 or 2, wherein the determining means determines an inner state of the user, and the determining means determines details of the image content that reflect the inner state of the user.

[0099] [Supplementary Note 4] The information processing device according to Supplementary Note 1 or 2, wherein when the determining means determines that the user has performed a mindfulness-related behavior in accordance with the content of the output image content, the determining means determines the content of the image content that reflects the mindfulness-related behavior performed by the user.

[0100] [Supplementary Note 5] The information processing device according to any one of Supplementary Notes 1 to 4, further comprising an estimation means for estimating a mindfulness behavior method suited to the user based on a state of the user.

[0101] [Supplementary Note 6] The information processing device according to Supplementary Note 5, wherein the estimation means estimates a timing when the user needs to perform a mindfulness-related behavior as a mindfulness behavior method suitable for the user, and the output means outputs the determined content of the image content based on the estimated timing.

[0102] [Supplementary Note 7] The information processing device according to Supplementary Note 5 or 6, wherein the estimation means estimates a form of mindfulness behavior suitable for the user as a mindfulness behavior method suitable for the user, and the determination means determines the content of the image content based on the estimated form of mindfulness behavior.

[0103] [Supplementary Note 8] The information processing device described in any one of Supplementary Notes 1 to 7, wherein the judgment means judges the quality of the mindfulness-related behavior performed by the user according to the content of the output image content, and the decision means decides the content of the image content based on the quality of the mindfulness-related behavior performed by the user judged by the judgment means.

[0104] [Supplementary Note 9] The information processing device described in any one of Supplementary Notes 1 to 8, wherein the determination means determines the state of the user based on at least one of image data of the user, biometric data of the user, audio data of the user's words and actions, and a log of operations by the user.

[0105] [Supplementary Note 10] The information processing device according to any one of Supplementary Notes 1 to 8, wherein the determination means determines the effect of the mindfulness based on at least one of image data of the user, biometric data of the user, audio data of the user's words and actions, and a log of operations by the user.

[0106] [Supplementary Note 11] The information processing device according to any one of Supplementary Notes 4 to 7, wherein the output means outputs an image of a character giving instructions on mindfulness-related behavior based on the form of mindfulness-related behavior suitable for the user estimated by the estimation means.

[0107] [Supplementary Note 12] The information processing device according to any one of Supplementary Notes 1 to 11, wherein the output means outputs an animated image of a character that reflects the movement of the user as the image to be displayed in the image content.

[0108] [Supplementary Note 13] The information processing device according to any one of Supplementary Notes 1 to 12, wherein the user is a game player, and the content of the image content is at least one of a state of a character appearing in the image content and an event within the image content.

[0109] [Supplementary Note 14] An information processing device comprising: a determination means for determining the state of a user who uses image content using a determination model generated by machine learning; a determination means for determining the content of image content that supports the user in making decisions about health care-related actions based on the state of the user; and an output means for outputting the determined content of the image content.

[0110] [Supplementary Note 15] An information processing method comprising: determining a state of a user who uses image content; determining, based on the state of the user, content of the image content that encourages the user to engage in mindfulness-related behavior; and outputting the determined content of the image content.

[0111] [Supplementary Note 16] The information processing method according to Supplementary Note 15, wherein at least one of a state of a character appearing in the image content and an event within the image content is determined as the content of the image content that encourages the user to engage in mindfulness-related behavior.

[0112] [Supplementary Note 17] The information processing method according to Supplementary Note 15 or 16, further comprising: determining an inner state of the user; and determining details of the image content that reflect the inner state of the user.

[0113] [Supplementary Note 18] The information processing method described in Supplementary Note 15 or 16, wherein when a mindfulness-related behavior performed by the user is determined based on the content of the output image content, the content of the image content is determined to reflect the determination result of the mindfulness-related behavior performed by the user.

[0114] [Supplementary Note 19] The information processing method according to any one of Supplementary Notes 15 to 18, further comprising estimating a mindfulness behavior method suited to the user based on the state of the user.

[0115] [Supplementary Note 20] The information processing method according to Supplementary Note 19, further comprising: estimating a timing when the user needs to perform a mindfulness-related behavior as a mindfulness behavior method suited to the user; and outputting the determined content of the image content based on the estimated timing.

[0116] [Supplementary Note 21] The information processing method according to Supplementary Note 19 or 20, further comprising: estimating a form of mindfulness behavior suitable for the user as a mindfulness behavior method suitable for the user; and determining the content of the image content based on the estimated form of mindfulness behavior.

[0117] [Supplementary Note 22] An information processing method described in any one of Supplementary Notes 15 to 21, comprising: determining the quality of the mindfulness-related behavior performed by the user based on the content of the previously output image content; and determining the content of the image content based on the determined quality of the mindfulness-related behavior performed by the user.

[0118] [Supplementary Note 23] The information processing method according to any one of Supplementary Notes 15 to 22, wherein the state of the user is determined based on at least one of image data of the user, biometric data of the user, audio data of the user's words and actions, and a log of operations by the user.

[0119] [Supplementary Note 24] The information processing method according to any one of Supplementary Notes 15 to 22, wherein the effect of the mindfulness is determined based on at least one of image data of the user, biometric data of the user, audio data of the user's words and actions, and a log of operations by the user.

[0120] [Supplementary Note 25] The information processing method according to any one of Supplementary Notes 19 to 21, further comprising outputting an image of a character that provides instructions for mindfulness-related behavior based on the estimated form of mindfulness-related behavior suitable for the user.

[0121] [Supplementary Note 26] The information processing method according to any one of Supplementary Notes 15 to 25, wherein an animated image of a character reflecting the movement of the user is output as the image displayed in the image content.

[0122] [Supplementary Note 27] The information processing method according to any one of Supplementary Notes 15 to 26, wherein the user is a game player, and the content of the image content is at least one of the state of a character appearing in the image content and an event within the image content.

[0123] [Supplementary Note 28] A recording medium that non-temporarily records a program that causes a computer to execute the following processes: a process of determining the state of a user who uses image content; a process of predetermining the content of image content that encourages the user to take mindfulness-related actions based on the state of the user; and a process of outputting the predetermining content of the image content.

[0124] [Supplementary Note 29] The recording medium according to Supplementary Note 28, which non-temporarily records a program that causes a computer to execute a process of determining at least one of the state of a character appearing in the image content and an event within the image content as content of the image content that encourages the user to engage in mindfulness-related behavior.

[0125] [Supplementary Note 30] The recording medium according to Supplementary Note 28 or 29, which non-temporarily records a program to be executed by a computer to determine the inner state of the user, and to determine the content of the image content that reflects the inner state of the user.

[0126] [Supplementary Note 31] A recording medium according to Supplementary Note 28 or 29, which non-temporarily records a program that causes a computer to execute a process of determining the content of the image content that reflects the judgment result of the mindfulness-related behavior performed by the user when the mindfulness-related behavior performed by the user is judged based on the content of the output image content.

[0127] [Supplementary Note 32] The recording medium according to any one of Supplementary Notes 28 to 31, which non-temporarily records a program that causes a computer to execute a process of estimating a mindfulness behavior method suitable for the user based on the state of the user.

[0128] [Supplementary Note 33] The recording medium of Supplementary Note 32 non-temporarily records a program that causes a computer to execute a process of estimating a timing when the user needs to take a mindfulness-related action as a mindfulness behavior method suited to the user, and outputting the determined details of the image content based on the estimated timing.

[0129] [Supplementary Note 34] A recording medium according to Supplementary Note 32 or 33, which non-temporarily records a program that causes a computer to execute a process of estimating a form of mindfulness behavior suitable for the user as a mindfulness behavior method suitable for the user, and determining the content of the image content based on the estimated form of mindfulness behavior.

[0130] [Supplementary Note 35] A recording medium according to any one of Supplementary Notes 29 to 34, which non-temporarily records a program that causes a computer to execute the following processes: a process of determining the quality of the mindfulness-related behavior performed by the user according to the content of the previously output image content; and a process of determining the content of the image content based on the determined quality of the mindfulness-related behavior performed by the user.

[0131] [Supplementary Note 36] A recording medium according to any one of Supplementary Notes 29 to 35, which non-temporarily records a program that causes a computer to execute a process of determining the state of the user based on at least one of image data of the user, biometric data of the user, audio data of the user's words and actions, and a log of operations by the user.

[0132] [Supplementary Note 37] A recording medium according to any one of Supplementary Notes 29 to 35, which non-temporarily records a program that causes a computer to execute a process of determining the effect of mindfulness based on at least one of image data of the user, biometric data of the user, audio data of the user's words and actions, and a log of operations by the user.

[0133] [Supplementary Note 38] A recording medium according to any one of Supplementary Notes 32 to 34, which non-temporarily records a program that causes a computer to execute a process of outputting an image of a character that gives instructions for mindfulness-related behavior based on the estimated form of mindfulness-related behavior suitable for the user.

[0134] [Supplementary Note 39] A recording medium according to any one of Supplementary Notes 29 to 38, which non-temporarily records a program that causes a computer to execute a process of outputting an animated image of a character that reflects the user's movements as an image to be displayed in the image content.

[0135] [Supplementary Note 40] The recording medium described in any one of Supplementary Notes 29 to 39, wherein the user is a game player, and the content of the image content is at least one of the state of a character appearing in the image content and an event within the image content.

[0136] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0137] REFERENCE SIGNS LIST 10 Information processing device 11 Acquisition unit 12 Determination unit 13 Estimation unit 14 Determination unit 15 Generation unit 16 Output unit 17 Storage unit 20 Terminal device 30 Sensor 40 Management device 100 Computer 101 CPU 102 Memory 103 Storage device 104 Input / output I / F 105 Communication I / F

Claims

1. A determination means for determining the state of a user using image content, A determination means for determining the content of image content that encourages the user to engage in mindfulness-related behaviors, based on the user's state. Output means for outputting the content of the determined image content and An information processing device equipped with the following features.

2. The determination means determines, as content of image content that encourages the user to engage in mindfulness-related behavior, the state of a character appearing in the image content and at least one of an event within the image content. The information processing apparatus according to claim 1.

3. The determination means determines the user's internal state, and the decision means determines the content of the image content that reflects the user's internal state. The information processing apparatus according to claim 1 or 2.

4. When the determination means determines that the user has performed a mindfulness-related action based on the content of the outputted image content, the decision means determines the content of the image content that reflects the mindfulness-related action performed by the user. The information processing apparatus according to claim 1 or 2.

5. The system further includes estimation means for estimating a mindfulness behavior method suitable for the user based on the user's condition. The information processing apparatus according to claim 1 or 2.

6. The estimation means estimates the timing at which the user needs to perform a mindfulness action, as a mindfulness action suitable for the user. The output means outputs the content of the image content determined based on the estimated timing. The information processing apparatus according to claim 5.

7. The estimation means estimates a form of mindfulness behavior suitable for the user as a method of mindfulness behavior suitable for the user, The determination means determines the content of the image content based on the estimated form of mindfulness behavior. The information processing apparatus according to claim 5.

8. The determination means determines the quality of the mindfulness behavior performed by the user according to the content of the outputted image content. The determination means determines the content of the image content based on the quality of the mindfulness behavior performed by the user as determined by the determination means. The information processing apparatus according to claim 1 or 2.

9. Determine the status of the user accessing the image content. Based on the user's state, the content of the image content is determined to encourage the user to engage in mindfulness-related behaviors. Output the content of the image content that has been determined. Information processing methods.

10. A process to determine the state of the user using the image content, Based on the user's state, a process is performed to predetermine the content of image content that encourages the user to engage in mindfulness-related behaviors. A process to output the content of the determined image content. A program that causes a computer to execute something.