Information processing device and information processing method

Abstract

An information processing device 1 comprises: a target data acquisition unit 134 that acquires target brainwave data indicating the state of brainwaves targeted by a user undergoing training related to brainwaves; a training-time data acquisition unit 131 that acquires training-time brainwave data indicating a training-time brainwave state, which is the state of the user's brainwaves obtained when the user underwent the training; and an output unit 135 that calculates the distance between brainwaves corresponding to the target brainwave data and brainwaves corresponding to the training-time brainwave data on the basis of the difference between the voltage of the brainwaves at each time indicated by the target brainwave data and the voltage of the brainwaves at each time indicated by the training-time brainwave data, and outputs the calculated distance.

Description

Information processing device and information processing method

[0001] The present invention relates to an information processing device and an information processing method.

[0002] Neurofeedback is known to enhance brain function by making a subject whose brain waves are being measured aware of the state of the measurement of the brain waves and training the subject to adjust the brain waves as the subject intends. For example, Patent Literature 1 discloses a device that performs neurofeedback, which is training for the subject to modify their own brain activity so that brain waves when the subject is relaxed are detected.

[0003] Special Publication No. 2020-501625

[0004] In conventional training, the subject's baseline brain waves are determined based on the results of measuring the subject's brain waves while the subject is in a resting state, and the effectiveness of the training is evaluated based on the amount of change from the determined baseline brain waves.This has led to the problem that it is not possible to grasp whether there is a difference between the brain wave state during training and other brain wave states, such as the subject's ideal brain wave state.

[0005] The present invention has been made in consideration of these points, and aims to enable a user to understand the difference between the state of brain waves during training and the state of brain waves at other times.

[0006] An information processing device according to a first aspect of the present invention comprises a target data acquisition unit that acquires target electroencephalogram data indicating a target electroencephalogram state for a user performing electroencephalogram training; a training data acquisition unit that acquires training electroencephalogram data indicating a training electroencephalogram state, which is the electroencephalogram state of the user when the user performs the training; and an output unit that calculates the distance between the electroencephalogram corresponding to the target electroencephalogram data and the electroencephalogram corresponding to the training electroencephalogram data based on the difference between the electroencephalogram voltage for each time indicated by the target electroencephalogram data and the electroencephalogram voltage for each time indicated by the training electroencephalogram data, and outputs the calculated distance.

[0007] The information processing device has a score identification unit that acquires identification information for identifying a state score, which is a score of one or more psychological states held by the user after the user has performed the training, and identifies the state score based on the acquired identification information, and a memory control unit that associates the state score for each of the user's multiple trainings with the training-time EEG data and stores them in a memory unit, and the target data acquisition unit estimates the user's brain wave state when a predetermined state score of the user, which is improved by the training, becomes a target score based on the relationship between the state score corresponding to each of the user's multiple trainings stored in association with the memory unit and the brain wave state at the time of training indicated by the training-time EEG data, and acquires EEG data indicating the estimated brain wave state as the target EEG data.

[0008] The score identification unit may acquire identification information for identifying the state score before the user performs the training and identify the state score before the user performs the training based on the acquired identification information; the training data acquisition unit acquires pre-training EEG data indicating the state of the user's brain waves before the user performs the training; the memory control unit associates the state score before the user performs each of the multiple trainings with the pre-training EEG data and stores them in the memory unit; the target data acquisition unit may estimate the state of the user's brain waves when a predetermined emotional score increased by the training reaches a target score, based on a relationship between the state score after the user has performed each of the multiple trainings and the EEG state at the time of training indicated by the training EEG data, and a relationship between the state score before the user performs each of the multiple trainings and the EEG state before training indicated by the pre-training EEG data, and acquire EEG data indicating the estimated EEG state as the target EEG data.

[0009] The score specification unit may acquire, as the specification information, information on the user's response to a questionnaire regarding the psychological state presented to the user, and specify the state score based on the acquired response information. The target data acquisition unit may accept, from the user, a selection of a psychological state that the user aims to achieve, and specify the target score corresponding to the accepted psychological state.

[0010] The training data acquisition unit may acquire a plurality of pieces of training EEG data corresponding to each of a plurality of trainings when the user performs the training a plurality of times, and the output unit may calculate a distance between the EEG corresponding to the target EEG data and the EEG corresponding to each of the plurality of training EEG data, and output information indicating the calculated distances.

[0011] The training data acquisition unit may acquire a plurality of pieces of training EEG data corresponding to each of a plurality of trainings when the user performs the training a plurality of times, and the output unit may calculate a distance between the EEG corresponding to the target EEG data and the EEG corresponding to each of the plurality of training EEG data, and based on the calculated distances, determine a speed at which the user's EEG state approaches the target EEG state, and output information indicating the determined speed.

[0012] The information processing device may have a memory unit that stores target electroencephalogram data of the user corresponding to each of a plurality of activity states, and the target data acquisition unit may accept a selection of one of the plurality of activity states from the user and acquire the target electroencephalogram data stored in the memory unit in association with the accepted activity state.

[0013] The information processing device may have a memory unit that stores electroencephalogram data of one or more target users, which indicates the electroencephalogram state of the target users when they are in a predetermined psychological state that is enhanced by the training, and the target data acquisition unit may accept a selection of one of the one or more target users from the user and acquire the electroencephalogram data of the selected target users stored in the memory unit as the target electroencephalogram data.

[0014] An information processing method according to a second aspect of the present invention includes the steps of: acquiring target electroencephalogram data indicating a target electroencephalogram state for a user performing electroencephalogram training; acquiring training electroencephalogram data indicating a training electroencephalogram state, which is the electroencephalogram state of the user when the user performs the training; and calculating the distance between the electroencephalogram corresponding to the target electroencephalogram data and the electroencephalogram corresponding to the training electroencephalogram data based on the difference between the electroencephalogram voltage for each time indicated by the target electroencephalogram data and the electroencephalogram voltage for each time indicated by the training electroencephalogram data, and outputting the calculated distance.

[0015] According to the present invention, it is possible to provide an effect that the user can grasp the difference between the electroencephalogram state during training and the electroencephalogram state at other times.

[0016] It is a diagram showing an overview of an information processing system. It is a diagram showing a configuration of an information processing device. It is a diagram showing an example of measurement history information. It is a diagram showing an example of a reception screen. It is a diagram showing an example of a comparison result screen.

[0017] [Outline of Information Processing System S] Fig. 1 is a diagram showing an outline of the information processing system S. The information processing system S is a system for implementing training to enhance the brain function of a user. As shown in Fig. 1, the information processing system S includes an information processing device 1, a terminal 2, and an electroencephalogram (EEG) measuring device 3. The information processing device 1 is a computer that is communicably connected to the terminal 2 via a communication network such as the Internet or a mobile phone network, and notifies the terminal 2 of an evaluation result of an electroencephalogram based on the electroencephalogram state of a user whose electroencephalogram is to be detected.

[0018] The terminal 2 is, for example, a tablet, a personal computer, a smartphone, etc. The terminal 2 is communicatively connected to an EEG measuring device 3 that measures the EEG of the target user via short-range wireless communication such as Bluetooth (registered trademark), wireless communication such as wireless LAN, or wired communication such as USB (registered trademark). Note that the EEG measuring device 3 may be communicatively connected to the information processing device 1 via a communication network such as the Internet line or a mobile phone network.

[0019] In this embodiment, the information processing device 1 acquires target electroencephalogram data indicating a target electroencephalogram state for a user undergoing electroencephalogram training ((1) in FIG. 1). The target electroencephalogram state for the user is, for example, an ideal electroencephalogram state for the user. The process of acquiring the target electroencephalogram data will be described later.

[0020] The information processing device 1 performs training related to electroencephalograms, for example, by displaying a training-related screen on the terminal 2 ((2) in FIG. 1). The information processing device 1 acquires training electroencephalogram data indicating the user's training electroencephalogram state, which is the state of the user's electroencephalogram measured by the electroencephalogram measuring device 3 when the training is performed ((3) in FIG. 1).

[0021] The information processing device 1 calculates the distance between the electroencephalogram (EEG) corresponding to the target EEG data and the electroencephalogram (EEG) corresponding to the training EEG data based on the difference between the EEG voltages at each time indicated by the target EEG data and the EEG voltages at each time indicated by the training EEG data ((4) in FIG. 1). This distance is calculated, for example, based on statistics of differences in the voltages of multiple EEGs at multiple points in time within a predetermined period indicated by each of the two EEG data. The larger this distance, the greater the difference in the shapes of the two EEGs. The information processing device 1 then outputs distance information indicating the calculated distance to the terminal 2 ((5) in FIG. 1). In this way, the information processing device 1 allows the user to understand the difference between the EEG state during training and the target EEG state as another EEG state.

[0022] [Configuration of information processing device 1] Next, a description will be given of the configuration of the information processing device 1. Fig. 2 is a diagram showing the configuration of the information processing device 1. As shown in Fig. 2, the information processing device 1 includes a communication unit 11, a storage unit 12, and a control unit 13. The communication unit 11 is an interface for connecting to a communication network such as the Internet line or a mobile phone network.

[0023] The storage unit 12 is a storage medium including a ROM (Read Only Memory), a RAM (Random Access Memory), etc. The storage unit 12 stores a program executed by the control unit 13. For example, the storage unit 12 stores a program that causes the control unit 13 to function as a training data acquisition unit 131, a score determination unit 132, a storage control unit 133, a target data acquisition unit 134, and an output unit 135.

[0024] The control unit 13 is, for example, a CPU (Central Processing Unit). The control unit 13 executes the programs stored in the storage unit 12, thereby functioning as a training data acquisition unit 131, a score determination unit 132, a storage control unit 133, a target data acquisition unit 134, and an output unit 135.

[0025] [Storage of Brain Wave Data] The information processing device 1 conducts brain wave training for the user multiple times so that the user can acquire target brain wave data indicating a target brain wave state. The information processing device 1 associates the brain wave data indicating the user's brain wave state acquired in each of the multiple training sessions with a state score, which is a score of the user's psychological state corresponding to the brain wave state, and stores the associated data in the storage unit 12. First, an example will be described in which the information processing device 1 stores the brain wave data indicating the user's brain wave state and the state score corresponding to the brain wave state in the storage unit 12.

[0026] The training data acquisition unit 131 acquires pre-training EEG data indicating a pre-training EEG state and training EEG data indicating a training EEG state. Here, the pre-training EEG state is the user's EEG state before the user performs EEG training. The training EEG state is the user's EEG state when the user performs the training. The EEG data is time-series data indicating the voltage of EEGs at each time.

[0027] For example, first, the training data acquisition unit 131 acquires the user ID by displaying a reception screen for accepting a user ID for identifying the user on the terminal 2. After acquiring the user ID, the training data acquisition unit 131 determines whether the number of pieces of electroencephalogram data associated with the user ID stored in the storage unit 12 is equal to or greater than a predetermined number.

[0028] When the number of electroencephalogram data associated with the user ID is less than a predetermined number, the training data acquisition unit 131 operates in a data accumulation mode and displays a reception screen for accepting selection of one of multiple psychological states. The psychological states are, for example, the user's mental states including a state of concentration and a state of relaxation, and states that indicate the user's emotions including a state of feeling joy and a state of feeling happiness. The training data acquisition unit 131 acquires the user ID of the user and accepts the selection of the psychological state from the user via the reception screen.

[0029] When the training data acquisition unit 131 receives a selection of the psychological state from the user, it causes the terminal 2 to display a message such as "The state of brain waves before starting training will be measured" for a predetermined period of time. Then, the training data acquisition unit 131 acquires, via the terminal 2, pre-training electroencephalogram data that indicates the state of brain waves of the user for a predetermined period of time before training, measured by the electroencephalogram measuring device 3.

[0030] Thereafter, the training data acquisition unit 131 carries out training related to electroencephalograms. Then, the training data acquisition unit 131 acquires, via the terminal 2, training electroencephalogram data indicating the training electroencephalogram state, which is the state of the user's electroencephalograms at the time of training, measured by the electroencephalogram measurement device 3. For example, if the selected psychological state is a "concentration state," the training data acquisition unit 131 displays a message such as "Training is about to begin. Please concentrate" on the terminal 2 for a predetermined period, and acquires training electroencephalogram data for the predetermined period.

[0031] The training data acquisition unit 131 may output, during training, stimulation information that provides the user with a stimulation corresponding to the selected psychological state. For example, the memory unit 12 stores psychological states and at least one of audio information indicating sounds and video information indicating videos as stimulation information that is believed to be effective for the psychological states. The training data acquisition unit 131 outputs at least one of audio and video to the terminal 2 based on the audio information and video information as stimulation information associated with the selected psychological state, thereby performing training related to electroencephalograms.

[0032] The score specifying unit 132 specifies a state score, which is a score of one or more psychological states held by the user. For example, the score specifying unit 132 acquires specifying information for specifying a state score of one or more psychological states held by the user before the user performs training, and specifies the state score based on the acquired specifying information. The specifying information is, for example, information on the user's responses to a questionnaire presented to the user.

[0033] For example, before the user performs training, the score identification unit 132 presents a questionnaire regarding the psychological state to the user by displaying the questionnaire on the terminal 2. The score identification unit 132 acquires, as pre-training identification information, information on the user's responses to the questionnaire regarding the psychological state presented to the user before training from the terminal 2. The score identification unit 132 identifies the state score before performing training based on the acquired pre-training identification information.

[0034] The score determination unit 132, for example, determines a state score using two parameters representing the emotions felt by the user based on questionnaire response information. The score determination unit 132 also determines a state score using one parameter for each of a plurality of mental states, such as concentration and relaxation, based on the questionnaire response information. For example, the storage unit 12 stores scoring information that associates each answer to a plurality of questionnaire items with the degree to which each parameter is to be added or subtracted. The score determination unit 132 refers to the scoring information and calculates the values ​​of each of the plurality of parameters based on the user's answers to each of the plurality of questionnaire items. The score determination unit 132 then determines the state score to be the values ​​of the two parameters corresponding to the emotions and the values ​​of the parameters for each of the plurality of mental states.

[0035] Similarly, after the user has performed training, the score identification unit 132 presents a questionnaire regarding the user's psychological state to the user via the terminal 2. Then, the score identification unit 132 acquires the user's response information to the questionnaire as identification information for identifying state scores of one or more psychological states that the user has after performing the training. The score identification unit 132 identifies the state score after performing the training based on the acquired post-training identification information.

[0036] The memory control unit 133 associates the state score before the user performs training, identified by the score identification unit 132, with the pre-training EEG data acquired by the training data acquisition unit 131, and stores them in the memory unit 12. For example, the memory control unit 133 associates the user ID of the user, the training content, the date and time of EEG measurement, the measurement conditions, the state score, and the EEG data acquired by the training data acquisition unit 131 on the reception screen, and stores them as measurement history information in the memory unit 12. The measurement conditions are information indicating whether the EEG measurement was performed before or during training. FIG. 3 is a diagram showing an example of measurement history information. As shown in FIG. 3, it can be seen that the user ID, the training content, the date and time of EEG measurement, the measurement conditions, the state score, and the EEG data are associated with each other.

[0037] Similarly, the memory control unit 133 associates the status score corresponding to the user after the training, identified by the score identification unit 132, with the training EEG data acquired by the training data acquisition unit 131 and stores them in the memory unit 12.

[0038] When the user performs multiple trainings, the memory control unit 133 associates the state score before the user performs the training with the pre-training EEG data corresponding to each of the multiple trainings and stores them in the memory unit 12, as in the measurement history information shown in Fig. 3, and also associates the state score after the user performs the training with the training EEG data and stores them in the memory unit 12. In this way, multiple pieces of EEG data corresponding to various psychological states of the user are accumulated in the memory unit 12.

[0039] [Output of Distance Between Target EEG State and EEG State During Training] Next, an example will be described in which the information processing device 1 outputs the distance between the target EEG state and the EEG state during training. For example, the training data acquisition unit 131 first causes the terminal 2 to display a reception screen for accepting a user ID for identifying the user, and acquires the user ID. After acquiring the user ID, the training data acquisition unit 131 determines whether the number of EEG data items associated with the user ID stored in the storage unit 12 is equal to or greater than a predetermined number.

[0040] When the number of pieces of electroencephalogram data associated with the user ID is less than a predetermined number, the training data acquisition unit 131 operates in a distance calculation mode and causes the target data acquisition unit 134 to acquire target electroencephalogram data.

[0041] The target data acquisition unit 134 acquires target electroencephalogram data indicating a target electroencephalogram state of a user undergoing electroencephalogram-related training. Specifically, the target data acquisition unit 134 first identifies a target score, which is a score that the user aims to achieve with respect to a predetermined state score that is to be improved by training. For example, the target data acquisition unit 134 causes the terminal 2 to display a reception screen that accepts the selection of a target psychological state of the user, and accepts the selection of the target psychological state of the user from the user.

[0042] FIG. 4 is a diagram showing an example of a reception screen. For example, the target data acquisition unit 134 displays the emotion circle diagram shown in FIG. 4( a) or the selection diagram shown in FIG. 4( b) on the reception screen. The emotion circle diagram is used by the target data acquisition unit 134 to select two parameters corresponding to the user's emotions. The selection diagram is used to select a parameter corresponding to one of the user's multiple mental states. The target data acquisition unit 134 accepts the selection of a psychological state from the user via the circle diagram or selection diagram. Note that the screen shown in FIG. 4( a) and the screen shown in FIG. 4( b) can be switched. The target data acquisition unit 134 identifies the state score corresponding to the psychological state accepted on the reception screen as the target score.

[0043] For example, suppose that the target data acquiring unit 134 has received a psychological state corresponding to plot P on the screen shown in Fig. 4(a). In this case, the target data acquiring unit 134 identifies two parameters of the emotion corresponding to plot P, namely, the value of a parameter on the horizontal axis and the value of a parameter on the vertical axis. Furthermore, because the target data acquiring unit 134 has not received a psychological state on the screen shown in Fig. 4(b), it identifies the parameter values ​​of the psychological states selectable on Fig. 4(b) as predetermined reference values. The target data acquiring unit 134 identifies a combination of the values ​​of the identified multiple parameters as the target score.

[0044] Next, the target data acquisition unit 134 estimates the user's brain wave state when the user's predetermined state score, which is increased by training, becomes the target score, based on the relationship between the state score after the user performs each of the multiple training exercises and the brain wave state during training indicated by the training brain wave data, and the relationship between the state score before the user performs each of the multiple training exercises, which is stored in association with the memory unit 12, and the pre-training brain wave state indicated by the pre-training brain wave data.

[0045] For example, an EEG estimation model, which is a program that estimates EEG data based on a state score, is stored in the memory unit 12. The EEG estimation model is a program that, in response to an input state score, outputs EEG data corresponding to the state score. The EEG estimation model has learned the user's state score stored in the memory unit 12 and the EEG state indicated by the EEG data corresponding to the state score based on training data. An EEG estimation model is provided individually for each of multiple users. The target data acquisition unit 134 inputs a target score corresponding to the user into the EEG estimation model generated for the user, and acquires the EEG data output from the EEG estimation model as target EEG data.

[0046] Although the target data acquiring unit 134 receives the user's selection of a target psychological state and acquires target electroencephalogram data corresponding to the selected psychological state, this is not limiting. For example, the target data acquiring unit 134 may receive the user's selection of one of a plurality of activity states and acquire target electroencephalogram data corresponding to the selected activity state.

[0047] In this case, the storage unit 12 stores target electroencephalogram data of the user corresponding to each of a plurality of activity states. For example, a state score appropriate for each of a plurality of activity states, such as studying, playing sports, or sleeping, is associated in advance. The storage control unit 133 then associates target electroencephalogram data obtained by inputting the state score associated with each of the plurality of activity states into the electroencephalogram estimation model with the target electroencephalogram data, and stores the associated data in the storage unit 12.

[0048] The target data acquisition unit 134 receives a selection of one of a plurality of activity states from the user, and acquires the target electroencephalogram data associated with the received activity state and stored in the storage unit 12. In this way, the user can perform training to bring the user closer to an electroencephalogram state suitable for the selected activity state.

[0049] The target data acquisition unit 134 may also acquire target electroencephalogram data of a target user, who is an ideal person for the user. In this case, one or more target users are made to wear the EEG measurement device 3, and electroencephalogram data of the target users is acquired, showing the electroencephalogram state of the target users when they reach a predetermined psychological state that is enhanced by training. The predetermined psychological state is, for example, a state of concentration or a state of relaxation. The storage unit 12 then stores the electroencephalogram data of the target users corresponding to each of the one or more target users, in association with the predetermined psychological state.

[0050] The target data acquisition unit 134 accepts a selection from one or more target users from the user. For example, the target data acquisition unit 134 displays on the terminal 2 a reception screen that accepts the selection of electroencephalogram data that the user wants to approximate from the electroencephalogram data of one or more target users. For example, the reception screen displays selectable electroencephalogram states when the target user is in a predetermined psychological state, such as "the electroencephalogram state of baseball player A when concentrating" or "the electroencephalogram state of shogi player B when concentrating." The target data acquisition unit 134 acquires the electroencephalogram data of the target user selected on the reception screen, which is stored in the storage unit 12, as target electroencephalogram data. In this way, the user can train to bring their own electroencephalogram state closer to the electroencephalogram state of the target user they are paying attention to.

[0051] The training data acquisition unit 131 acquires training electroencephalogram data indicating the user's training electroencephalogram state, which is the state of the user's brain waves when the user performs training. For example, the training data acquisition unit 131 displays a message that evokes the user's selected psychological state for a predetermined period of time, and acquires training electroencephalogram data indicating the user's brain wave state for the predetermined period of time.

[0052] Note that even when outputting the electroencephalogram distance, the information processing device 1 accumulates the electroencephalogram data in the storage unit 12. For example, the training data acquisition unit 131 acquires pre-training electroencephalogram data in the same way as when accumulating electroencephalogram data. The score determination unit 132 determines a state score based on the acquired electroencephalogram data, and the storage control unit 133 associates the acquired electroencephalogram data with the state score determined for the electroencephalogram data and stores them in the storage unit 12.

[0053] The output unit 135 calculates the distance between the electroencephalogram corresponding to the target electroencephalogram data and the electroencephalogram corresponding to the training electroencephalogram data based on the difference between the electroencephalogram voltage at each time indicated by the target electroencephalogram data and the electroencephalogram voltage at each time indicated by the training electroencephalogram data, and outputs the calculated distance.

[0054] For example, the output unit 135 calculates the distance between the electroencephalogram corresponding to the target electroencephalogram data and the electroencephalogram corresponding to the training electroencephalogram data using DTW (Dynamic Time Warping). DTW is a method of calculating, as the distance between two pieces of time series data, the distance corresponding to the matching when the distance, which is the sum of the differences between the values ​​corresponding to the times included in the first time series data and the values ​​corresponding to the times included in the second time series data, is minimized while changing the times included in the second time series data that are matched with the times included in the first time series data.

[0055] Although the output unit 135 calculates the distance between the electroencephalogram corresponding to the target electroencephalogram data and the electroencephalogram corresponding to the training electroencephalogram data using the DTW, the present invention is not limited to this. The output unit 135 may calculate the distance between the electroencephalogram corresponding to the target electroencephalogram data and the electroencephalogram corresponding to the training electroencephalogram data using another method, such as Euclidean distance, which calculates the root mean square of the values ​​of two time-series data at the same time, in order from the start times of the two time-series data.

[0056] Then, the output unit 135 outputs information indicating the calculated distance to the terminal 2. Note that the output unit 135 may associate the distance with a scale, such as whether the distance is short or long, and output information indicating the scale of the calculated distance to the terminal 2. In this way, the information processing device 1 can make it easier for the user to grasp the distance between the electroencephalogram corresponding to the target electroencephalogram data and the electroencephalogram corresponding to the training electroencephalogram data.

[0057] Furthermore, when training is performed multiple times to approach the same target electroencephalogram data, the output unit 135 may calculate the distance between the electroencephalogram corresponding to the target electroencephalogram data and the electroencephalogram corresponding to each of the multiple pieces of training electroencephalogram data. In this case, the memory control unit 133 stores the training electroencephalogram data and the target electroencephalogram data in association with each other in the measurement history information stored in the memory unit 12.

[0058] The output unit 135 then refers to the measurement history information and identifies a plurality of post-training EEG data corresponding to each of the plurality of trainings the user most recently performed for the same target EEG data. The output unit 135 calculates the distance between the EEG corresponding to the target EEG data and the EEG corresponding to each of the plurality of training EEG data, and identifies the speed at which the user's EEG state approaches the target EEG state based on the calculated distances.

[0059] For example, the output unit 135 calculates the distance by which the user's electroencephalogram state approaches the target electroencephalogram state per training session as the speed at which the user's electroencephalogram state approaches the target electroencephalogram state, and calculates the number of training sessions until the distance between the user's electroencephalogram state and the target electroencephalogram state becomes within a predetermined distance.The output unit 135 then outputs to the terminal 2 a comparison result screen showing the calculated distance for each of the multiple pieces of post-training electroencephalogram data, information indicating the speed at which the user's electroencephalogram state approaches the target electroencephalogram state, and information indicating the calculated number of training sessions.

[0060] 5 is a diagram showing an example of a comparison result screen. The screen shown in FIG. 5 displays a graph showing the distance calculated for each of the multiple sets of post-training EEG data, a message showing the speed at which the user's EEG state approaches the target EEG state, and a message showing the calculated number of training sessions. For example, by doing so, the user can understand how much training is required to approach the target EEG state.

[0061] In the above-described embodiment, pre-training EEG data is acquired before the user performs training, and the EEG data is associated with the condition score and stored in the storage unit 12. However, this is not limiting. For example, it is also possible not to acquire EEG data before training.

[0062] [Effects of the Present Embodiment] As described above, the information processing device 1 according to the present embodiment acquires target electroencephalogram data indicating a target electroencephalogram state for a user performing electroencephalogram training, and acquires training electroencephalogram data indicating the user's training electroencephalogram state, which is the user's electroencephalogram state when the user performs the training. The information processing device 1 then calculates the distance between the electroencephalograms corresponding to the target electroencephalogram data and the electroencephalograms corresponding to the training electroencephalogram data based on the difference between the electroencephalogram voltages for each time indicated by the target electroencephalogram data and the electroencephalogram voltages for each time indicated by the training electroencephalogram data, and outputs the calculated distance. In this way, the information processing device 1 allows the user to understand the difference between the electroencephalogram state during training and other electroencephalogram states.

[0063] The present invention has been described above using embodiments, but the technical scope of the present invention is not limited to the scope described in the above embodiments, and various modifications and changes are possible within the scope of the gist of the present invention. For example, all or part of the device can be configured by functionally or physically distributing or integrating in any unit. Furthermore, new embodiments resulting from any combination of multiple embodiments are also included in the embodiments of the present invention. The effects of the new embodiments resulting from the combination also have the effects of the original embodiments.

[0064] REFERENCE SIGNS LIST 1 Information processing device 2 Terminal 3 Electroencephalogram measuring device 11 Communication unit 12 Memory unit 13 Control unit 131 Training data acquisition unit 132 Score determination unit 133 Memory control unit 134 Target data acquisition unit 135 Output unit S Information processing system

Claims

1. An information processing device having: a target data acquisition unit that acquires target EEG data indicating a target EEG state for a user performing EEG training; a training data acquisition unit that acquires training EEG data indicating a training EEG state, which is the EEG state of the user when the user performs the training; and an output unit that calculates a distance between the EEG corresponding to the target EEG data and the EEG corresponding to the training EEG data based on the difference between the EEG voltage for each time indicated by the target EEG data and the EEG voltage for each time indicated by the training EEG data, and outputs the calculated distance.

2. An information processing device as described in claim 1, comprising: a score identification unit that acquires identification information for identifying a state score which is a score for one or more psychological states held by the user after the user has performed the training, and identifies the state score based on the acquired identification information; and a memory control unit that associates the state score for each of the user's multiple trainings with the training-time EEG data and stores them in a memory unit, wherein the target data acquisition unit estimates the user's brain wave state when a predetermined state score of the user, which is improved by the training, becomes a target score based on the relationship between the state score corresponding to each of the user's multiple trainings stored in association with the memory unit and the brain wave state at the time of training indicated by the training-time EEG data, and acquires brain wave data indicating the estimated brain wave state as the target EEG data.

3. The information processing device of claim 2, wherein the score identification unit acquires identification information for identifying the state score before the user performs the training, and identifies the state score before the user performs the training based on the acquired identification information; the training data acquisition unit acquires pre-training EEG data indicating the user's brain wave state before the user performs the training; the memory control unit associates the state score before the user performs each of the multiple trainings with the pre-training EEG data and stores them in the memory unit; and the target data acquisition unit estimates the user's brain wave state when a predetermined emotion score increased by the training becomes a target score based on a relationship between the state score after the user performs each of the multiple trainings and the brain wave state at the time of training indicated by the training EEG data, and a relationship between the state score before the user performs each of the multiple trainings and the brain wave state before training indicated by the pre-training EEG data, and acquires EEG data indicating the estimated brain wave state as the target EEG data.

4. An information processing device as described in claim 2 or 3, wherein the score determination unit acquires, as the identification information, response information of the user to a questionnaire regarding a psychological state presented to the user, and determines the state score based on the acquired response information.

5. The information processing device according to claim 2 or 3, wherein the target data acquisition unit receives from the user a selection of a psychological state that the user aims to achieve, and identifies the target score corresponding to the received psychological state.

6. The information processing device of claim 1, wherein the training data acquisition unit acquires a plurality of pieces of training EEG data corresponding to each of a plurality of trainings when the user performs the training a plurality of times, and the output unit calculates a distance between the EEG corresponding to the target EEG data and the EEG corresponding to each of the plurality of training EEG data, and outputs information indicating the calculated distances.

7. The information processing device of claim 1, wherein the training data acquisition unit acquires a plurality of training EEG data corresponding to each of a plurality of trainings when the user performs the training a plurality of times, and the output unit calculates a distance between the EEG corresponding to the target EEG data and the EEG corresponding to each of the plurality of training EEG data, determines a speed at which the user's EEG state approaches the target EEG state based on the calculated distances, and outputs information indicating the determined speed.

8. An information processing device as described in claim 1, further comprising a memory unit for storing target brain wave data of the user corresponding to each of a plurality of activity states, wherein the target data acquisition unit accepts a selection of one of the plurality of activity states from the user, and acquires the target brain wave data stored in the memory unit in association with the accepted activity state.

9. An information processing device as described in claim 1, further comprising a memory unit that stores electroencephalogram data of one or more target users, the electroencephalogram data indicating the electroencephalogram state of the one or more target users when the target users are in a specified psychological state that is enhanced by the training, and the target data acquisition unit accepts a selection of one of the one or more target users from the user, and acquires the electroencephalogram data of the selected target user stored in the memory unit as the target electroencephalogram data.

10. An information processing method executed by a computer, comprising the steps of: acquiring target EEG data indicating a target EEG state for a user performing EEG training; acquiring training EEG data indicating a training EEG state, which is the EEG state of the user when the user performs the training; and calculating a distance between the EEG corresponding to the target EEG data and the EEG corresponding to the training EEG data based on the difference between the EEG voltage for each time indicated by the target EEG data and the EEG voltage for each time indicated by the training EEG data, and outputting the calculated distance.

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