Information processor, information processing method, and program

Abstract

To provide an information processor, an information processing method, and a program capable of recognizing and improving its own state.SOLUTION: The information processor includes: a first brain wave acquisition unit that acquires first brain wave information of a user before reframing with respect to a stack point; a second brain wave acquisition unit that acquires second brain wave information of the user after the reframing; a model creation unit that creates a model for predicting whether brain wave information of the user is in a negative state or a positive state on the basis of the first brain wave information and the second brain wave information; and a neurofeedback unit that uses the model to perform neurofeedback for causing the second brain wave information.SELECTED DRAWING: Figure 1

Description

[Technical field]

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

[0002] An international comparative survey conducted in 2017 by Gallup, a major US polling company, reported that only 6% of employees in Japan were "enthusiastic," while 71% were "unenthusiastic," and 23% were "completely unenthusiastic," indicating that Japanese employees have the lowest level of work motivation in the world (the number of respondents was approximately 460,000).

[0003] "Work is hard work" is a notion that seems to be deeply rooted in the Japanese. It is not that "if it's not fun, it's not work," but rather that "if it's not fun, it's not work." I believe that this mentality is deeply rooted in the Japanese. International surveys have revealed the reality of "Japanese workers being the most anxious, dissatisfied, and unhappy in the world." For example, according to an international survey on work-life balance and other issues conducted by Randstad in December 2019, Japanese people have the lowest "job satisfaction" in the world. The "Edenred Ipsos Barometer," an international survey on employee wellbeing released in 2016, also highlights the "unhappiness" of Japanese company employees. The "unhappiness" of Japanese company employees is 44%, far below the 63% of Italy, which ranked 14th, and secures the lowest ranking. Despite this, it has been pointed out that they also have little motivation to make their work more enjoyable. Furthermore, Japan's per capita labor productivity has been roughly second lowest among the seven major OECD developed countries since 2008, and has been last since 2017. Labor productivity is caused by a combination of factors and is not necessarily due to low motivation to work alone, but it can at least be considered one of the factors. In Japan, which has become a society with a declining population, it is important to change the way people perceive their work and increase their motivation to work in order to continue to achieve sustainable economic growth and maintain a vibrant society, and to ensure that each employee can live a social life in which they feel a sense of purpose.

[0004] In the world of management science, the skill of changing the way you perceive your work or rediscovering it as enjoyable is called job crafting, and I would like to develop this job crafting, or in other words, the skill of "transforming your own work into something enjoyable."

[0005] Patent document 1 discloses that, for the purpose of creating and configuring at least one of a motivational campaign and a gamified task list on behalf of an administrator, a computer obtains inputs related to historical information, deadlines, and user-related information, or inputs related to information related to past tasks, current tasks, and user metadata, performs calculations on the inputs to generate outputs, and generates campaign timing and team composition, or task lists and point values ​​based on the outputs. Summary of the Invention [Problem to be solved by the invention]

[0006] However, although the technology described in Patent Document 1 is considered to be effective as a mechanism for concentrating on productive goals, the motivation campaign is ultimately extrinsic, and the effect is not very sustainable. In addition, the technology described in Patent Document 1 creates a sense of compulsion to work rather than voluntariness, and is therefore considered to be less effective in addressing the issues listed in the Background section.

[0007] The present invention has been made in view of the above, and has an object to provide an information processing device, an information processing method, and a program that are capable of recognizing and improving one's own condition. [Means for solving the problem]

[0008] In order to solve the above-mentioned problems and achieve the object, the present invention comprises a first electroencephalogram acquisition unit that acquires first electroencephalogram information of a user before reframing to a stack point, a second electroencephalogram acquisition unit that acquires second electroencephalogram information of the user after the reframing, a model creation unit that creates a model that predicts whether the user's electroencephalogram information is in a negative state or a positive state based on the first electroencephalogram information and the second electroencephalogram information, and a neurofeedback unit that uses the model to perform neurofeedback to generate the second electroencephalogram information. Effect of the Invention

[0009] According to the present invention, an effect is achieved in that a person can recognize his / her own condition and improve it. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram showing an example of a configuration of an information processing system according to the present embodiment. [Diagram 2] FIG. 2 is a diagram for explaining an example of a schematic configuration of an earphone set according to the present embodiment. [Diagram 3] FIG. 3 is a diagram illustrating an example of an outline of an earphone set according to the present embodiment. [Figure 4] FIG. 4 is a diagram illustrating an example of a hardware configuration of an information processing device included in the information processing system according to the present embodiment. [Diagram 5] FIG. 5 is a diagram for explaining an example of a stack point setting process in the information processing system according to the present embodiment. [Figure 6] FIG. 6 is a diagram for explaining an example of the process of acquiring electroencephalogram information in the information processing system according to the present embodiment. [Figure 7] FIG. 7 is a diagram for explaining an example of a process for creating a reframing sheet in the information processing system according to the present embodiment. [Figure 8]FIG. 8 is a diagram for explaining an example of a process for creating a reframing sheet in the information processing system according to the present embodiment. [Figure 9] FIG. 9 is a diagram for explaining an example of a process for creating a reframing sheet in the information processing system according to the present embodiment. [Figure 10A] FIG. 10A is a diagram for explaining an example of neurofeedback in the information processing system according to the present embodiment. [Figure 10B] FIG. 10B is a diagram for explaining an example of neurofeedback in the information processing system according to the present embodiment. [Figure 11] FIG. 11 is a diagram showing an example of subjective evaluation of work before and after neurofeedback. [Figure 12] FIG. 12 is a diagram showing an example of changes in the latent index before and after neurofeedback. [Figure 13] FIG. 13 is a diagram showing an example of attitude change toward a stuck point at work caused by neurofeedback. [Figure 14] FIG. 14 is a diagram showing an example of electroencephalogram information for each neurofeedback session. [Figure 15] FIG. 15 is a flowchart showing an example of a flow of reframing in the information processing system according to the present embodiment. [Figure 16] FIG. 16 is a diagram for explaining an example of changes in the degree of work distress and motivation due to reframing in the information processing system according to the present embodiment. [Figure 17] FIG. 17 is a diagram showing an example of a stack point setting screen in the information processing system according to the present embodiment. [Figure 18] FIG. 18 is a diagram showing an example of an action setting screen for actions for each JC skill in the information processing system according to the present embodiment. [Figure 19] FIG. 19 is a diagram showing an example of an evaluation screen for evaluating the degree of pain associated with work in the information processing system according to the present embodiment. [Figure 20] FIG. 20 is a diagram showing an example of a gamification result display screen in the information processing system according to the present embodiment. [Figure 21] FIG. 21 is a diagram showing an example of a gamification result display screen in the information processing system according to the present embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, embodiments of an information processing device, an information processing method, and a program will be described in detail with reference to the accompanying drawings.

[0012] Fig. 1 is a diagram showing an example of the configuration of an information processing system according to the present embodiment. As shown in Fig. 1, the information processing system 1 according to the present embodiment includes an earphone set 10, an information processing device 30, and a mobile terminal 50. The earphone set 10, the information processing device 30, and the mobile terminal 50 are connected to each other via a network N so as to be able to communicate with each other.

[0013] The earphone set 10 is an example of an earphone set that is worn by a user who is measuring brain waves as an electroencephalogram measuring device and has a bioelectrode provided in the ear canal. In the example shown in Fig. 1, the earphone set 10 is a neck-hanging type, but any earphone may be used as long as it is capable of sensing an electroencephalogram signal (an example of electroencephalogram information) from the ear canal. For example, the earphone set 10 may be an earphone set that acquires a reference signal from the earlobe, an earphone that acquires a reference signal or a ground signal from another position (another position in the ear canal), or a completely wireless earphone.

[0014] Also, the user may wear headgear that measures brain waves using the International 10 / 20 system as an electroencephalogram measuring device. Also, the electroencephalogram measuring device includes devices capable of measuring brain waves, such as a measuring device that uses scalp electrodes, a measuring device that measures brain activity using intracranial electrodes, a measuring device that measures brain activity using Functional Magnetic Resonance Imaging (fMRI), a measuring device that measures brain activity using Near-Infrared Spectroscopy, and the like.

[0015] 1, the earphone set 10 acquires electroencephalogram information from the ear canal and transmits the electroencephalogram information to the information processing device 30 or the mobile terminal 50 via the network N. The earphone set 10 may also perform a predetermined process on the electroencephalogram information and transmit it to the information processing device 30 or the mobile terminal 50. The predetermined process may include amplification, sampling, filtering, difference calculation, etc.

[0016] The information processing device 30 is, for example, a server, and calculates information indicating the user's emotion from electroencephalogram information measured by an electroencephalogram measuring device. For example, the information processing device 30 may obtain emotion information indicating the user's emotion using a model that extracts emotion-related information from electroencephalograms. The information processing device 30 may also improve the accuracy of the model by using learning data annotated by the user. The information processing device 30 may transmit the generated model to the mobile terminal 50.

[0017] The mobile terminal 50 is, for example, a processing terminal such as a mobile terminal held by a user, and sequentially acquires electroencephalogram information from the earphone set 10. The mobile terminal 50 inputs the sequentially acquired electroencephalogram information into a model to acquire emotion information indicating the emotion of the user.

[0018] When the emotion information satisfies a predetermined condition, the mobile terminal 50 selects content that adjusts the emotion of the user, and outputs the selected content to the earphone set 10. In the example shown in FIG. 1, the earphone set 10 is used as an output device, so the content is content that includes sound, but if an image output device is used as the output device, the content may include video, still images, animation, and the like. In addition, the mobile terminal 50 has a brain-machine interface function that estimates the user's emotion from the electroencephalogram information, executes processing to adjust the emotion, and operates equipment based on the electroencephalogram information.

[0019] This allows appropriate selection of content that adjusts the user's emotions according to the user's emotions. For example, the content includes at least one of music, voice, sound data, video, photos, animation, and games. In this embodiment, the content is preferably content that includes sound, and more preferably music.

[0020] 2 and 3 are diagrams for explaining an example of an outline of an earphone set according to the present embodiment. The earphone set 10 is not limited to the example shown in Fig. 2 and Fig. 3, and any earphones can be applied as long as they can sense brain waves from the ear canal and output to an external device.

[0021] 2, a pair of earphones 100R, 100L are connected to the neck strap 110 using a cable capable of signal communication, but may be connected using wireless communication. Hereinafter, RL will be omitted when there is no need to distinguish between left and right.

[0022] The neck hanging part 110 has a central member that runs along the back of the neck, and rod-shaped members (arms) 112R, 112L that are curved along both sides of the neck. Electrodes 122, 124 for sensing brainwave information are provided on the surface of the central member that is in contact with the neck on the back side. The electrodes 122, 124 are an electrode that is in earth contact and a reference electrode, respectively. This allows the electrodes 122, 124 to be spaced apart from the elastic electrodes provided on the ear tips of the earphones, as described later, making it possible to obtain brainwave information with high accuracy. The neck hanging part 110 may also have a processing unit that processes brainwave information and a communication device that communicates with the outside, but these processing units and communication units may be provided in the earphones 100.

[0023] In addition, the rod-shaped members 112R, 112L on both sides of the neck hanging part 110 are heavier at their tips than at their bases (the central member side), so that the electrodes 122, 124 are appropriately pressed against the neck of the wearer. For example, weights are provided at the tips of the rod-shaped members 112R, 112L. Note that the positions of the electrodes 122, 124 are not limited to these positions.

[0024] 3 may have an elastic member (e.g., urethane) 108 between the speaker 102 and the nozzle 104. By providing this elastic member 108, vibrations from the speaker 102 are less likely to be transmitted to the elastic electrode of the ear tip 106, and sound interference between the elastic electrode of the ear tip 106 and the speaker 102 can be prevented.

[0025] Furthermore, ear tip 106 including an elastic electrode is located at the sound guide port, but the elasticity of the elastic electrode itself makes it possible to prevent interference from sound vibrations. Also, by using an elastic material for the housing, this elastic material makes it difficult for sound vibrations to be transmitted to the elastic electrode of ear tip 106, making it possible to prevent interference from sound vibrations.

[0026] The earphone 100 may include an audio sound processor, and may use this audio sound processor to cut off sound signals below a certain frequency (e.g., 50 Hz) that corresponds to brainwave information. In particular, the audio sound processor cuts off sound signals below 30 Hz, which is a frequency band that is likely to show characteristics of brainwave information, but may also amplify sound signals with frequencies around 70 Hz in order to avoid impairing the bass sound.

[0027] This makes it possible to prevent interference between the sound signal and the brainwave information. Also, the audio sound processor may cut off a predetermined frequency only when the brainwave information is being sensed.

[0028] Furthermore, the ear tip 106 conducts brainwave information sensed from the ear canal to the contact of an electrode provided in the nozzle 104. The brainwave information is transmitted from the ear tip 106 to a biosensor inside the earphone 100 via the contact. The biosensor outputs the sequentially acquired brainwave information via a cable to a processing device provided in the neck hanging part 110, or transmits it to an external device. Furthermore, the ear tip 106 and the housing including the biosensor or the audio sound processor may be insulated.

[0029] Here, an example of the characteristics of the information processing system 1 according to the present embodiment will be described. The information processing system 1 according to the present embodiment has the following characteristics (1) and (2). (1) Instead of a work manager, a worker performs reframing on his / her own to change the way he / she perceives painful work. The information processing system 1 acquires the brain activity state (electroencephalogram information) of the worker before and after reframing using a wearable brain activity device (e.g., earphones 100), models the brain activity state of the worker, and provides neurofeedback of the positive state after reframing. This further increases the effect of reframing. (2) In addition, the information processing system 1 reframes the job and then links the worker’s ability to devise their own work (job crafting skills, hereafter referred to as JC skills) with the painful work, and implements these through gamification.

[0030] That is, the information processing system 1 according to the present embodiment allows a user to recognize and improve his / her own state by reframing a task that the user considers to be painful, thereby reducing the degree of pain from the task. Specifically, the information processing system 1 measures the brain activity state of the user with a measurement device, and models each individual (user) based on the measurement results (models a negative state, which is the brain activity state before reframing, and a positive state, which is the brain activity state after reframing, respectively). Next, the information processing system 1 performs neurofeedback to capture the painful task in a positive state, thereby enabling the user to normally view the painful task in a positive light, and further reducing the degree of pain. Furthermore, the information processing system 1 links the task (stuck point) that was painful before reframing to a job crafting skill so that the user can work on it while devising his / her own ideas, and by gamifying the linked stuck point, the user can view and perform the task in a more positive way.

[0031] Conventionally, no matter how much a person performs tasks that they find painful through gamification, the work itself remains painful and there is no effect of increasing intrinsic motivation for the work. Therefore, the information processing system 1 according to the present embodiment has been confirmed to be effective by practicing positive reframing and training modification by neurofeedback with the aim of "making work fun."

[0032] Specifically, the information processing system according to this embodiment provides the following advantages (1) to (3). (1) First, positive reframing helps you view work-related pain in a more positive light. (2) Neurofeedback reduces distress more than positive reframing alone. (3) As a result, self-perceived motivation for work (intrinsic motivation) increases and cognitive crafting abilities can be improved. Furthermore, by implementing gamification, it is also possible to obtain the following effect (4). (4) By performing the painful work through gamification and devising ways to do it, the relationship crafting and task crafting skills can be improved, and intrinsic motivation can be further increased. In gamification, points are added according to the work (tasks) performed by the user. This has the effect of encouraging continuity in the task.

[0033] 4 is a diagram showing an example of a hardware configuration of an information processing device included in the information processing system according to the present embodiment. In the present embodiment, the information processing device 30 is, for example, a server, and may be composed of one or more devices. The information processing device 30 processes electroencephalogram information, and analyzes the user's emotions from the electroencephalogram signal using, for example, a learning function of artificial intelligence.

[0034] Hereinafter, the information processing device 30 is also referred to as the server 30. The information processing device 30 is not limited to a server, and may be a general-purpose computer. The mobile terminal 50 may have the same hardware configuration as the information processing device 30.

[0035] The server 30 has one or more processors (e.g., CPU: Central Processing Unit) 310 or multiple network communication interfaces 320, memory 330, a user interface 350, and one or more communication buses 307 for interconnecting these components.

[0036] Server 30 may include, for example, a user interface 350 having a display device, a keyboard, and a mouse (or some other input device, such as a pointing device).

[0037] Memory 330 may be, for example, a high-speed random access memory, such as DRAM, SRAM, DDR RAM, or other random access solid-state storage device, or may be a non-volatile memory, such as one or more magnetic disk storage devices, optical disk storage devices, flash memory devices, or other non-volatile solid-state storage devices.

[0038] As another example, memory 330 may be one or more storage devices located remotely from processor 310. For example, memory 330 may store programs, modules, data structures, or a subset thereof.

[0039] The one or more processors 310 read and execute programs as necessary from the memory 330. For example, the one or more processors 310 may realize a stack point setting unit 311, a first electroencephalogram acquisition unit 312, a sheet creation unit 313, a second electroencephalogram acquisition unit 314, a model creation unit 315, a neurofeedback unit 316, and a gamification unit 317 by executing the programs stored in the memory 330.

[0040] In this embodiment, the stack point setting unit 311, the first brain wave acquiring unit 312, the sheet creating unit 313, the second brain wave acquiring unit 314, the model creating unit 315, the neurofeedback unit 316, and the gamification unit 317 are realized in the server 30, but at least one of the stack point setting unit 311, the first brain wave acquiring unit 312, the sheet creating unit 313, the second brain wave acquiring unit 314, the model creating unit 315, the neurofeedback unit 316, and the gamification unit 317 may be realized in the mobile terminal 50. In addition, the functions of the server 30 and the mobile terminal 50 may be realized in either the server 30 or the mobile terminal 50.

[0041] The stack point setting unit 311 is an example of a setting unit that sets a stack point. Here, a stuck point may be a short sentence expression that reflects your current dissatisfaction, belief, or preconception about your work that prevents you from reconsidering your work as enjoyable. Also, a stuck point may be a sentence expressed in extreme words (e.g., "never," "no one," "only") or responsibility (e.g., "should," "it's my fault," "it's his fault"). Also, a stuck point may be the work itself that you feel is painful, a belief, the timing at which you recognize the pain, etc.

[0042] For example, stuck points could be, "Work keeps coming down to me because the people who should do it don't," "I'm suffering because I'm only given subcontractor-like work," "It's hard because my group members don't seem to be on board with my suggestions," "No one helps me," "My work is meaningless and no one praises me," "My work is boring and my future won't change," or "I can't trust anyone, including my boss or colleagues, and they dislike me."

[0043] Fig. 5 is a diagram for explaining an example of a stack point setting process in the information processing system according to the present embodiment. In the present embodiment, the stack point setting unit 311 may display a stack point setting screen on the mobile terminal 50 as shown in Fig. 5. As shown in Fig. 5, the stack point setting screen may be a screen including candidates of stack points related to work-related dissatisfaction (for example, the situation or belief of the work-related difficulties you are currently feeling), the degree of distress, the frequency, the degree of unresolvedness, the degree of thinking that it cannot be resolved, and the total score thereof (degree of distress).

[0044] 5, the stack point setting screen has a field for inputting the stack point candidate with the largest total point among the stack point candidates input by the user, or an item (stack point candidate) that the user wants to change the way of thinking about, and the stack point setting unit 311 may set the stack point candidate input in the field as the stack point.

[0045] Returning to Fig. 4, the first electroencephalogram acquisition section 312 is an example of a first electroencephalogram acquisition section that acquires first electroencephalogram information before reframing from a measuring device such as the earphone set 10. Here, the first electroencephalogram information before reframing may be electroencephalogram information obtained while recalling a stuck point in work and repeatedly thinking about the mood or cause of dissatisfaction at that time for a predetermined period of time (e.g., two minutes).

[0046] Reframing also includes reinterpreting the stuck points. Reframing may also mean reinterpreting the work in a positive way, or generally changing the way the work is perceived (framed) and looking at the work from a different perspective. For example, reframing may involve reevaluating the stuck points to extract positive elements and planning an action plan (e.g., improvement measures) for the extracted elements. Here, the extracted positive elements may include "any positive impact on you," "something you can be grateful for," "something you have grown from that event," and "strengths you have gained."

[0047] 6 is a diagram for explaining an example of the process of acquiring electroencephalogram information in the information processing system according to the present embodiment. In the present embodiment, the first electroencephalogram acquiring section 312 may display an electroencephalogram information acquisition screen on the mobile terminal 50 as shown in FIG.

[0048] 6, the electroencephalogram information acquisition screen may include a field for inputting work-related stuck points to be reframed, and a message encouraging rumination on the stuck points (for example, "Recall these events and repeatedly think about the mood and causes of dissatisfaction at the time for two minutes.") The first electroencephalogram acquisition section 312 may acquire, as the first electroencephalogram information, the electroencephalogram information when the electroencephalogram information acquisition screen is displayed.

[0049] Returning to Fig. 4, sheet creation unit 313 acquires a reframing sheet (reframing information) used for reframing the user for the stuck point. In this embodiment, sheet creation unit 313 creates a reframing sheet. Here, the reframing sheet is a sheet used by the user for reframing the stuck point.

[0050] 7 to 9 are diagrams for explaining an example of a reframing sheet creation process in the information processing system according to the present embodiment. In the present embodiment, sheet creation unit 313 may display, on mobile terminal 50, a reframing sheet into which stuck points, reevaluation of stuck points, positive elements extracted from the reevaluation, and an action plan are input, as shown in FIG.

[0051] Then, the sheet creation unit 313 creates a reframing sheet including stuck points (e.g., "No one helps me"), reevaluation (e.g., "I get a report later on about what has been done"), positive elements (e.g., "I grow by working on my own"), and action plans (e.g., "Everyone voluntarily helps me with work") input by the user, as shown in Figures 8 and 9.

[0052] Returning to FIG. 4, the second electroencephalogram acquisition unit 314 is an example of a second electroencephalogram acquisition unit that acquires second electroencephalogram information after reframing from a measuring device such as the earphone set 10. In this embodiment, the second electroencephalogram acquisition unit 314 may display the reframing sheet created by the sheet creation unit 313 on the mobile terminal 50 and encourage the user to repeatedly think about reconsidering the stuck points or constructively planning a solution while looking at the reframing sheet for a predetermined time (e.g., 2 minutes). The second electroencephalogram acquisition unit 314 may acquire the electroencephalogram information during that time as the second electroencephalogram information after reframing. In addition, the second electroencephalogram acquisition unit 314 may acquire the degree of distress after reframing (e.g., the degree of distress, frequency, degree of unresolvedness, degree of thinking that it cannot be solved, and the total score thereof).

[0053] The model creation unit 315 is an example of a model creation unit that creates a model (reframing model) that predicts whether the user's electroencephalogram information is in a negative state or a positive state based on the first electroencephalogram information acquired by the first electroencephalogram acquisition unit 312 and the second electroencephalogram information acquired by the second electroencephalogram acquisition unit 314. In this embodiment, the model creation unit 315 learns (an example of creation) a decoder (reframing model) that predicts whether the user's electroencephalogram information is in a negative state or a positive state based on the first electroencephalogram information and the second electroencephalogram information. The model creation unit 315 may create a reframing model only in the case of the first reframing.

[0054] For example, the model creation unit 315 performs noise processing or preprocessing on each of the first electroencephalogram information and the second electroencephalogram information, and then learns a machine learning model (e.g., LASSO: Least Absolute Shrinkage and Selection Operator) that classifies the user's electroencephalogram information into a negative state or a positive state as an example of a decoder. According to the machine learning model (reframing model), it becomes possible to estimate the likelihood between a negative state and a positive state for the user's electroencephalogram information.

[0055] Here, the reframing model may be a trained model customized to the characteristics of the user's individual brain using the user's own electroencephalogram information. For example, the reframing model may be a reframing model including an inference program that trains electroencephalogram information using teacher data in which the state (e.g., emotional valence (positive or negative), arousal level) designated by the user himself / herself is used as a correct answer label when the electroencephalogram information is acquired, and infers the user's state from the electroencephalogram information.

[0056] The neurofeedback unit 316 performs neurofeedback to generate the second electroencephalogram information using the reframing model. Here, the neurofeedback may be trial and error training under a situation where the user's own electroencephalogram information can be fed back in real time by sound and video, etc., with the aim of being able to generate a desired electroencephalogram pattern (electroencephalogram information) by himself / herself. In other words, the neurofeedback may be outputting at least one of sound and video according to the emotion predicted by the reframing model based on the user's electroencephalogram information. The neurofeedback unit 316 may also perform neurofeedback when the pain level of the stuck point is equal to or higher than a threshold value.

[0057] Thus, in this embodiment, the neurofeedback unit 316 uses AI to learn and model the electroencephalogram information during reframing, and trains the person to generate second electroencephalogram information that he or she has reframed when work is difficult, etc. Through this training, the aim is to acquire the skills to positively reframe or change situations when daily work is difficult.

[0058] 10A and 10B are diagrams for explaining an example of neurofeedback in the information processing system according to the present embodiment. In the present embodiment, the neurofeedback unit 316 may provide feedback to the user that the second electroencephalogram information in the positive state is being obtained by warming, enlarging, or moving the color of the bar 1001 on the screen of the mobile terminal 50 as shown in FIG. 10A as the electroencephalogram information obtained from a measuring device such as the earphone set 10 approaches the second electroencephalogram information in the positive state while the user is looking at a work-related stuck point and a reframing sheet (for example, the reframing sheet in FIG. 10B). For example, the neurofeedback unit 316 may repeat the neurofeedback training four times for two minutes as one session.

[0059] FIG. 11 is a diagram showing an example of subjective evaluation of work before and after neurofeedback. Here, the subjective evaluation may be intrinsic motivation, cognitive crafting, and needs related to playful work. In FIG. 11, the vertical axis represents the subjective evaluation score, and the horizontal axis represents the score before (Pre) and after (Post) neurofeedback. As shown in FIG. 11, the scores of intrinsic motivation, cognitive crafting, and needs related to playful work are all higher after neurofeedback than before neurofeedback.

[0060] Fig. 12 is a diagram showing an example of changes in latent index before and after neurofeedback. In Fig. 11, the vertical axis represents the D score of the latent index, and the horizontal axis represents before (Pre) and after (Post) neurofeedback. As shown in Fig. 12, the D score of the latent index tends to increase before and after neurofeedback, but there is a large individual variability and no significant difference.

[0061] FIG. 13 is a diagram showing an example of attitude change toward a stuck point at work due to neurofeedback. In FIG. 13, the vertical axis represents the degree of distress toward a stuck point (e.g., "very painful," "very frequent," "degree of unresolved," "never able to be resolved"), and the horizontal axis represents the time before and after reframing (Pre, Post) and the number of neurofeedback sessions (NF1st to NF4th). As shown in FIG. 12, the degree of distress toward a stuck point is reduced by introducing reframing to a positive state. Furthermore, for the stuck points "very painful" and "very frequent," neurofeedback can reduce the degree of distress more than reframing, as shown in FIG. 12.

[0062] Fig. 14 is a diagram showing an example of electroencephalogram information for each neurofeedback session. In Fig. 14, the vertical axis represents electroencephalogram information, and the horizontal axis represents neurofeedback sessions (NF1st to NF4th). As shown in Fig. 14, from the third two-minute neurofeedback session, the electroencephalogram information was successfully shifted significantly toward a positive state.

[0063] In this way, by practicing reframing aimed at making work more enjoyable and neurofeedback, people can recognize and improve their own reactions, and reframe work-related pain in a positive way. Neurofeedback can also reduce pain more than reframing alone. As a result, people can increase their self-perceived motivation for work (intrinsic motivation) and improve their cognitive crafting abilities.

[0064] 4, the gamification unit 317 sets an action corresponding to each JC skill. After reframing, the gamification unit 317 links the JC skill with a painful task (stuck point) and implements an action corresponding to the JC skill linked to the stuck point through gamification.

[0065] Fig. 15 is a flow chart showing an example of a flow of reframing in the information processing system according to the present embodiment. Fig. 16 is a diagram for explaining an example of changes in work distress and motivation due to reframing in the information processing system according to the present embodiment. In Fig. 16, the vertical axis represents work motivation, and the horizontal axis represents work distress.

[0066] First, the stack point setting unit 311 sets a stack point based on an input from the user on the stack point setting screen (step S1501). Also, the neurofeedback unit 316 judges whether the total point (pain level) based on the input from the user on the stack point setting screen is equal to or greater than a threshold (step S1502).

[0067] If the degree of distress is less than the threshold (step S1502: No), the gamification unit 317 links the JC skill with the stack point and sets an action corresponding to the JC skill linked with the stack point (step S1503). After that, when the user practices the set action, the gamification unit 317 evaluates the degree of distress for the work based on the input from the user (step S1504).

[0068] On the other hand, if the pain level is equal to or greater than the threshold (step S1502: Yes), the sheet creation unit 313 judges whether or not this is the first reframing (step S1505). If this is the first reframing (step S1505: Yes), the first electroencephalogram acquirer 312 acquires the first electroencephalogram information before reframing (step S1509). Next, the sheet creation unit 313 acquires a reframing sheet (step S1506). In addition, the second electroencephalogram acquirer 314 acquires the second electroencephalogram information after reframing (step S1510).

[0069] Next, the model creation section 315 creates a reframing model based on the first electroencephalogram information before reframing acquired by the first electroencephalogram acquisition section 312 and the second electroencephalogram information after reframing acquired by the second electroencephalogram acquisition section 314 (step S1507). Furthermore, the neurofeedback section 316 performs neurofeedback based on the reframing model created by the model creation section 315 (step S1508), and proceeds to step S1503. As a result, as shown in Fig. 16, the user's degree of distress regarding work can be reduced and the user's motivation regarding work can be increased.

[0070] If it is determined in step S1505 that this is not the first reframing (step S1505: No), the neuro-feedback section 316 performs neuro-feedback based on the reframing model created in the first reframing (step S1508), and proceeds to step S1503.

[0071] Fig. 17 is a diagram showing an example of a stack point setting screen in the information processing system according to the present embodiment. In the present embodiment, the stack point setting unit 311 may display a stack point setting screen on the mobile terminal 50, in which a stack point and a pain level of the stack point can be input, as shown in Fig. 17. Then, when the pain level is equal to or higher than a threshold, the neurofeedback unit 316 performs neurofeedback.

[0072] Fig. 18 is a diagram showing an example of an action setting screen for an action for each JC skill in the information processing system according to the present embodiment. In the present embodiment, the neurofeedback unit 316 displays a skill list screen showing a list of JC skills on the mobile terminal 50 as shown in Fig. 18. Next, the neurofeedback unit 316 displays an action input screen for inputting an action for solving the stuck point for each JC skill displayed on the skill list screen as shown in Fig. 18. Then, the gamification unit 317 sets the action input on the action input screen as the action corresponding to the JC skill.

[0073] Fig. 19 is a diagram showing an example of an evaluation screen for evaluating the degree of pain for work in the information processing system according to the present embodiment. In the present embodiment, the gamification unit 317 may display a reevaluation screen on the mobile terminal 50, as shown in Fig. 19, in which the degree of pain for stuck points, the degree of resolution of the pain, the degree of implementation of the action, etc. can be input.

[0074] 20 and 21 are diagrams showing an example of a result display screen of gamification in the information processing system according to the present embodiment. In this embodiment, the gamification unit 317 may display on the mobile terminal 50 a result display screen in which a character of a kingdom or the like evolves according to a reduction rate of a pain level relative to a stack point based on a pain level or the like inputted on a reevaluation screen, as shown in FIG. 20. In addition, in this embodiment, the gamification unit 317 may display on the mobile terminal 50 a result display screen in which a crystal (for example, from bronze to diamond) according to the number of times an action is performed can be acquired for each JC skill to which an action is set, as shown in FIG. 21.

[0075] In this way, according to the information processing system 1 of this embodiment, by practicing reframing aimed at making work more enjoyable and by using neurofeedback, it becomes possible to reframe work-related pain in a positive way, and neurofeedback can reduce the level of pain more than reframing alone.

[0076] The program executed by the information processing device 30 of this embodiment is provided in a state where it is pre-installed in a ROM (Read Only Memory) or the like. The program executed by the information processing device 30 of this embodiment may be provided by being recorded in a computer-readable recording medium such as a CD-ROM, a flexible disk (FD), a CD-R, or a DVD (Digital Versatile Disk) in the form of an installable or executable file.

[0077] Furthermore, the program executed by the information processing device 30 of the present embodiment may be configured to be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network. Also, the program executed by the information processing device 30 of the present embodiment may be configured to be provided or distributed via a network such as the Internet.

[0078] The program executed by the information processing device 30 of this embodiment has a modular configuration including the above-mentioned units (stack point setting unit 311, first brain wave acquisition unit 312, sheet creation unit 313, second brain wave acquisition unit 314, model creation unit 315, neurofeedback unit 316, and gamification unit 317), and in terms of actual hardware, a processor 310 such as a CPU (Central Processing Unit) reads out the program from the above-mentioned ROM and executes it, thereby loading the above-mentioned units onto a main memory device, and the stack point setting unit 311, first brain wave acquisition unit 312, sheet creation unit 313, second brain wave acquisition unit 314, model creation unit 315, neurofeedback unit 316, and gamification unit 317 are generated on the main memory device.

[0079] For example, aspects of the present invention are as follows. <1> A first electroencephalogram acquisition unit that acquires first electroencephalogram information of a user before reframing with respect to a stack point; A second electroencephalogram acquisition unit that acquires second electroencephalogram information of the user after the reframing; a model creation unit that creates a model predicting whether the user's electroencephalogram information is in a negative state or a positive state based on the first electroencephalogram information and the second electroencephalogram information; a neurofeedback unit that performs neurofeedback to generate the second electroencephalogram information using the model; An information processing device comprising: <2> a gamification unit that sets an action corresponding to each job crafting skill, and after the reframing, links the job crafting skill to a stack point, and implements the action corresponding to the job crafting skill linked to the stack point through gamification. <1> The information processing device described in <3> The neurofeedback includes outputting at least one of a sound and an image corresponding to the emotion predicted by the model based on the user's electroencephalogram information. <1> or <2> The information processing device described in <4> The model creation unit creates the model only in the first reframing. <1> from <3> 13. The information processing device according to claim 12, <5> The neurofeedback unit performs the neurofeedback when the pain level of the stuck point is equal to or higher than a threshold. <4> The information processing device described in <6> An information processing method executed by an information processing device, acquiring first electroencephalogram information of the user before reframing to the stack point; acquiring second electroencephalogram information of the user after the reframing; creating a model for predicting whether the user's electroencephalogram information is in a negative state or a positive state based on the first electroencephalogram information and the second electroencephalogram information; performing neurofeedback using the model to generate the second electroencephalogram information; An information processing method comprising: <7> Computer, A first electroencephalogram acquisition unit that acquires first electroencephalogram information of a user before reframing with respect to a stack point; A second electroencephalogram acquisition unit that acquires second electroencephalogram information of the user after the reframing; a model creation unit that creates a model predicting whether the user's electroencephalogram information is in a negative state or a positive state based on the first electroencephalogram information and the second electroencephalogram information; a neurofeedback unit that performs neurofeedback to generate the second electroencephalogram information using the model; A program to make it function as such. [Explanation of symbols]

[0080] 1. Information Processing Systems 10 earphone sets 30 Information processing device 50 Mobile Devices 310 Processor 311 Stack point setting section 312 1st EEG Acquisition Unit 313 Sheet Creation Department 314 2nd EEG Acquisition Unit 315 Model Creation Department 316 Neurofeedback Department 317 Gamification Department 320 Network Communication Interface 330 Memory 350 User Interface [Prior art documents] [Patent documents]

[0081] [Patent Document 1] Patent Publication No. 2021-197141

Claims

1. A first electroencephalogram acquisition unit that acquires first electroencephalogram information of a user before reframing with respect to a stack point; A second electroencephalogram acquisition unit that acquires second electroencephalogram information of the user after the reframing; a model creation unit that creates a model predicting whether the electroencephalogram information of a user is in a negative state or a positive state based on the first electroencephalogram information and the second electroencephalogram information; a neurofeedback unit that performs neurofeedback to generate the second electroencephalogram information by using the model; An information processing device comprising:

2. The information processing device of claim 1, further comprising a gamification unit that sets an action corresponding to each job crafting skill, reframes the job crafting skill, links the job crafting skill to a stack point, and implements the action corresponding to the job crafting skill linked to the stack point through gamification.

3. The information processing device according to claim 1 , wherein the neurofeedback includes outputting at least one of a sound and an image corresponding to an emotion predicted by the model based on electroencephalogram information of the user.

4. The information processing apparatus according to claim 1 , wherein the model creation unit creates the model only in the case of a first reframing.

5. The information processing device according to claim 4 , wherein the neurofeedback section performs the neurofeedback when a pain level of the stuck point is equal to or higher than a threshold.

6. An information processing method executed by an information processing device, acquiring first electroencephalogram information of the user before reframing to the stack point; acquiring second electroencephalogram information of the user after the reframing; creating a model for predicting whether the user's electroencephalogram information is in a negative state or a positive state based on the first electroencephalogram information and the second electroencephalogram information; performing neurofeedback using the model to generate the second electroencephalogram information; An information processing method comprising:

7. Computer, A first electroencephalogram acquisition unit that acquires first electroencephalogram information of a user before reframing with respect to a stack point; A second electroencephalogram acquisition unit that acquires second electroencephalogram information of the user after the reframing; a model creation unit that creates a model predicting whether the electroencephalogram information of a user is in a negative state or a positive state based on the first electroencephalogram information and the second electroencephalogram information; a neurofeedback unit that performs neurofeedback to generate the second electroencephalogram information by using the model; A program to make it function as such.

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