JP7504376B2 - USER STATE DETERMINATION DEVICE, USER STATE DETERMINATION METHOD, PROGRAM, COMPUTER, AND USER STATE DETERMINATION DEVICE MANUFACTURING METHOD - Google Patents

Description

The present invention relates to a user status determination device, a user status determination method, a program, a computer, and a method for creating a user status determination device.

Conventionally, attention state determination systems that determine a user's attention state have been disclosed. For example, Patent Document 1 discloses an attention state determination system that measures a user's electroencephalogram signal and eye movement, and determines the user's attention state by using eye fixation related potentials (EFRPs) based on the start time of eye fixation from the measured eye movement.

Japanese Patent No. 5570386

However, the above technology analyzes brain waves when the eyes are fixed, so although it can be applied when the visual target is constantly moving, such as when a user is driving, it cannot be applied to continuous stimuli where the visual target or line of sight (eyes) does not move, such as when watching a screen.

The present invention has been made in consideration of the above problems, and its purpose is to provide a user state determination device, a user state determination method, a program, a computer, and a method for creating a user state determination device that can accurately determine the user state even when the visual target or line of sight (eyeball) is not moving, such as when watching a screen.

In one aspect of the present invention, in order to determine a user state, including the user's attention state or the degree of immersion, the user's brain activity state is measured, and when a blinking action of the user's eyes is detected, the user state is determined based on the brain activity state at the time of the detected blinking action.

According to the present invention, the user's state can be determined with high accuracy even when the visual target or line of sight is not moving.

FIG. 1 is a block diagram showing an example of a configuration of a user state determination device 100 according to the present embodiment. FIG. 2 is a diagram showing the relationship between eyeblink-evoked potential (EEP) and immersion state. FIG. 3 is a graph showing fluctuations in blink evoked potentials (EEP) after the blink time (0 ms) under high immersion, low immersion, and another condition set as a reference. FIG. 4 is a flowchart showing an example (Example 1) of a user state determination process in the user state determination device 100 of this embodiment. FIG. 5 is a flowchart showing an example (Example 2) of a user state determination process in the user state determination device 100 of this embodiment. FIG. 6 is a flowchart showing an example (Example 3) of a user state determination process in the user state determination device 100 of this embodiment.

The embodiment will be described with reference to the drawings. In the drawings, the same parts are given the same reference numerals and the description will be omitted. Note that, in the following, an example of application to a user (user) riding on a moving object during automatic driving will be described, but the present invention is not limited to this, and the user targeted by the present invention can be a human being in any state and performing any action.

(Configuration of the user state determination device)
Fig. 1 is a block diagram showing an example of the configuration of a user state determination device 100 according to the present embodiment. As shown in the block diagram of Fig. 1, the configuration of the user state determination device 100 to which the present embodiment is applied conceptually shows only a part of the configuration related to the present embodiment. In addition, when assuming a user during automatic driving, the user state determination device 100 may be installed at an arbitrary location in the vehicle, as an example, or the control unit 102 and the storage unit 102 may be installed at a remote location and communicate with a brain measurement unit 112, a blink detection unit 114, etc. in the vehicle via a communication network or the like.

In FIG. 1, the user state determination device 100 is generally configured to include a control unit 102 such as a CPU that provides overall control of the user state determination device 100, a brain measurement unit 112, a blink detection unit 114, and a memory unit 106 that stores various databases, etc., and these units are communicatively connected via any communication path. Here, the user state determination device 100 may be an ECU (engine control unit), a microcomputer, a personal computer, a server computer, etc.

The various databases and tables (e.g., personal database 106a and visual target specific database file 106b, etc.) stored in memory unit 106 are storage means such as small-capacity high-speed memory (e.g., cache memory) configured using SRAM (Static Random Access Memory) or fixed disk devices such as HDD (Hard Disk Drive) and SSD (Solid State Drive), and store various programs, tables, files, databases, etc. used for various processes.

Of these, the personal database 106a is a database of brain activity during blinking for each individual. As an example, the personal database 106a stores data showing the correlation between brain activity and the user state (degree of immersion, etc.) for a certain individual. For example, the correlation between the brain activity state (brain potential, etc.) and the user state (degree of immersion, etc.) may differ depending on the individual user while riding. The determination unit 102a, which will be described later, can accurately determine the user state from the brain activity state of a specific individual during blinking by referring to the personal database 106a. In addition, the learning unit 102b, which will be described later, may store the brain activity state and the user state of a certain individual in the personal database 106a in association with each other, or may learn the determination criteria for each individual (for example, the threshold value of the brain activity state for determining a high immersion state) by referring to the personal database 106a.

The database 106b for each visual target is a database of brain activity during blinking for each visual target. As an example, the personal database 106a stores brain activity and a user state (degree of immersion, etc.) in association with each visual target. For example, the correlation between the brain activity state (brain potential, etc.) and the user state (degree of immersion, etc.) may differ between a case where a user in a vehicle is watching a video or a car navigation screen and a case where the user is watching the environment around the vehicle. The determination unit 102a, which will be described later, can accurately determine the user state from the brain activity state at the time of blinking for a specific visual target by referring to the database 106b for each visual target. The learning unit 102b, which will be described later, may store the brain activity state and the user state in the database 106b for each visual target in association with each other, or may learn a judgment criterion for each individual (for example, a threshold value of the brain activity state for judging a high immersion state when watching a screen) by referring to the database 106b for each visual target.

The brain measurement unit 112 is a brain measurement means for measuring the user's brain activity state (brain potential, brain magnetic field, brain waves, etc.). The brain measurement unit 112 may be, for example, a magnetic field measurement means resulting from brain activity, a radio wave measurement means (Freer), a scalp surface potential measurement means, or may be what is called an electroencephalograph, magnetoencephalograph, or electroencephalograph. It is desirable for the brain measurement unit 112 to be capable of measurement with high time resolution. The brain measurement unit 112 is preferably a non-contact type, but may also be a contact type.

For example, the Neurobiomonitor headrest manufactured by Freer Logic may be used as the non-contact brain measurement unit 112 (http://freerlogic.com/products/hardware). The non-contact brain measurement unit 112 may also be an electroencephalograph or the like as described below (Patent No. 5981506) / (Patent Application No. 2019-201280) / (Takamasa Ando et al., Non-contact acquisition of brain function using a time-extracted compact camera, Scientific Reports | (2019) 9:17854 | https://doi.org/10.1038/s41598-019-54458-7). Also, for medical use, the in-vehicle brain measurement unit 112 may be configured using the magnetoencephalography system "RICOH MEG" (Magnetoencephalography system RICOH160-1 (Medical device certification number: 22100BZX00914000), https://jp.ricoh.com/release/2018/0709_1.html)

The blink detection unit 114 is a blink detection means that detects the blinking of the user's eyes. Although the blink detection unit 114 is illustrated as being in a separate housing from the brain measurement unit 112, this is not limited thereto and may be the same (hardware and/or software). For example, the blinking can be detected based on an electrooculogram (EOG: Electro Oculography) extracted from a signal from the brain measurement unit 112. The blink detection unit 114 may be realized as hardware and/or software. The blink detection unit 114 may be configured as part of the control unit 102.

As an example, the blink detection unit 114 may apply a blink potential removal technique of an electroencephalogram analysis system (BESA Research 7.0) to estimate a potential due to a blink based on a model, created in advance, of what potential is generated on the scalp due to a blink. The blink detection unit 114 may also detect the blinking action of the user's eyes using the techniques listed below.
Berg, P., and Scherg, M. A multiple source approach to the correction of eye artifacts, Electroenceph. clin. Neurophysiol., 1994, 90: 229-241.
Ille N., Berg P., and Scherg M. A Spatial Components Method for Continuous Artifact Correction in EEG and MEG. Biomed. Tech., 1997, 42 (suppl. 1): 80-83.
・Ille, N., Berg, P., Scherg, M. Artifact correction of the ongoing EEG using spatial filters based on artifact and brain signal topographies. J. Clin. Neurophysiol. 2002, 19: 113-124.
Uusitalo, M.A., Ilmoniemi, R.J. Signal-space projection method for separating MEG or EEG into components. Med. Biol. Eng. Comput., 1997, 35: 135-140.
http://wiki.besa.de/index.php?title=BESA_Research_Artifact_Correction

In FIG. 1, the control unit 102 is a processor such as a CPU that has a control program such as an OS (Operating System), a program that defines various processing procedures, and an internal memory for storing required data, and performs information processing to execute various processes using these programs. Functionally, the control unit 102 is configured to include a determination unit 102a and a learning unit 102b.

Among these, the determination unit 102a is a determination means for determining the user state (such as the user's attention state or the user's degree of immersion) based on the brain activity state at the time of the blinking action detected by the blink detection unit 114. Here, "at the time of the blinking action" may be "immediately after the blinking," "immediately after closing the eye for the blinking action," "immediately before the blinking action," "before and after the blinking action," "at the time of the blinking action," "the moment of the blinking action," "the period of the blinking action," or "the period from closing the eye for the blinking action to opening it completely." Note that even if the blinking action time detected by the blink detection unit 114 is a time point, the determination unit 102a may extract the brain activity state (brain potential, brain magnetic field, brain waves, etc.) for a certain time (period) before and after the time point or after (immediately after) the time point, and determine the user state based on the extracted brain activity state.

Here, in order to improve the accuracy of the determination, the determination unit 102a may calculate an average of the magnitude of brain activity during multiple blinks and determine the user state based on the average. For example, the determination unit 102a may obtain an eyeblink-evoked potential (EEP), which is a negative scalp potential that reflects a reset of the brain, by averaging electroencephalograms using a blink detected by the blink detection unit 114 as a trigger.

As an example, the determination unit 102a may determine the user state, including the user's attention state or the user's degree of immersion, based on the magnitude of brain activity during a blink detected by the blink detection unit 114. For example, the determination unit 102a may determine the user state as a low immersion state if the brain potential immediately after a blink is large, and may determine the user state as a high immersion state if the brain potential immediately after a blink is small. Here, FIG. 2 is a diagram showing the relationship between the eyeblink-evoked potential (EEP) and the immersion state. FIG. 3 is a graph showing the fluctuation of the eyeblink-evoked potential (EEP) after the blink (0 ms) in high immersion, low immersion, and another condition set as a reference.

It is known that blinking resets the brain by increasing the activity of the DMN (Default Mode Network: a network activated during a resting state) at the moment of blinking. Here, the blink evoked potential (EEP) can be obtained by averaging the brain waves using the blink as a trigger. As shown in Figures 2 and 3, when the user is immersed in a video, that is, when the degree of immersion is high, the degree of resetting the brain by blinking is shallow, so the blink evoked potential (EEP) (negative scalp potential reflecting the resetting of the brain) is small, and when the degree of immersion is low, the degree of resetting the brain by blinking is deep, so the blink evoked potential (EEP) is large. Therefore, the determination unit 102a can determine the user state as a low immersion state if the amount of brain activity is large based on the amount of brain activity at the time of blinking (for example, the maximum value of the brain waveform for a certain period immediately after the blink), and determine the user state as a high immersion state if the amount of brain activity immediately after the blink is small.

The determination unit 102a may also determine the user state based on a determination criterion for each individual regarding the brain activity state during a blinking action. Since the brain activity state during a blinking action varies between individuals, this allows the user state to be determined with high accuracy. As an example, the determination unit 102a may determine the user state by referring to the personal database 106a regarding the brain activity state during a blinking action. The determination unit 102a may also determine the user state according to the learning results of the learning unit 102b based on the personal database 106a (determination criteria such as a threshold value for the brain activity state to be determined as a high immersion state, etc.).

The determination unit 102a may also determine the user state based on a determination criterion for each visual target with respect to the brain activity state during the blinking action. Since the brain activity state varies depending on what the user is looking at when blinking, this allows the user state to be determined with high accuracy. As an example, the determination unit 102a may determine the user state by referring to the visual target-specific database 106b with respect to the brain activity state during the blinking action. The determination unit 102a may also determine the user state according to the learning results of the learning unit 102b based on the visual target-specific database 106b (determination criteria such as a threshold for the brain activity state to be determined as a highly immersive state, etc.).

The learning unit 102b is a machine learning means that learns criteria for determining the user state with respect to the brain activity state during a blinking action. The learning unit 102b may associate the brain activity state and the user state for a certain individual and store them in the personal database 106a, or may refer to the personal database 106a to learn the criteria for each individual (e.g., the threshold value of the brain activity state for determining a highly immersive state). The learning unit 102b may associate the brain activity state and the user state for each visual target and store them in the visual target-specific database 106b, or may refer to the visual target-specific database 106b to learn the criteria for each individual (e.g., the threshold value of the brain activity state for determining a highly immersive state when viewing a screen).

Here, the learning may be supervised learning, unsupervised learning, or reinforcement learning. Examples of learning algorithms that may be used include support vector machines (SVM), decision tree learning, neural networks (NN), genetic programming (GP), Bayesian networks, etc.

This completes the description of each component of the user state determination device 100 of this embodiment. Note that this embodiment does not necessarily have to be premised on the ECU or computer of a vehicle or the like functioning as the user state determination device 100 from the beginning. For example, even if the memory unit 106 does not have the personal database 106a or the visual target database 106b, the control unit 102 may create the personal database 106a or the visual target database 106b by storing data from the brain measurement unit 112, the blink detection unit 114, etc. in the memory unit 106. Similarly, even if the control unit 102 does not have the function of the determination unit 102a, the learning unit 102b may obtain a user state determination criterion by machine learning based on data stored in the memory unit 106, such as the personal database 106a and the visual target database 106b, thereby controlling the control unit 102 to realize the function as the determination unit 102a. Furthermore, even if the brain measurement unit 112 or the blink detection unit 114 is not connected to the control unit 102, a predetermined program or the like may be used to control the control unit 102 to connect to these peripheral devices. This makes it possible to create a user state determination device that can accurately determine the user state even when the visual target or line of sight (eyeball) is not moving, such as when watching a screen.

(User Status Determination Process)
Next, an example of a user state determination process in the user state determination device 100 of this embodiment configured as described above will be described in detail below with reference to Fig. 4 to Fig. 6. Fig. 4 is a flowchart showing an example (Example 1) of a user state determination process in the user state determination device 100 of this embodiment.

Example 1
As shown in FIG. 4, first, the brain measurement section 112 starts measuring the brain activity state of the user (step S01).

During EEG measurement (S02), when the blink detection unit 114 detects a blink (step S03, Yes), the determination unit 102a extracts EEG before and after the blink timing from the signal of the brain measurement unit 112 (step S04). For example, the determination unit 102a may extract the maximum value for a certain period of time (e.g., 100 ms) immediately after the blink as the amount of brain activity during the blink.

Then, the judgment unit 102a judges whether or not the extracted brain wave value exceeds a predetermined threshold (step S05). As an example, if the threshold is not exceeded (S05, No), it judges that the level of immersion is high (step S07), and if the threshold is exceeded, it judges that the level of immersion is low (step S06).

Then, the determination unit 102a outputs the determination result of the user's state of immersion (step S08) and ends the process (step S09).

In this way, it is possible to determine the degree of immersion in the visual target. Furthermore, when a non-contact brain measurement unit 112 is used, it is not necessary to wear an electrooculography measurement device or the like, which reduces inconvenience. Furthermore, it can be applied even to visual targets where the line of sight does not move, such as when looking at a screen installed inside the vehicle rather than at the area around the vehicle.

Example 2
A second example of the user state determination process in the user state determination device 100 of this embodiment will be described in detail below with reference to FIG.

Figure 5 is a flowchart showing an example (Example 2) of a user state determination process in the user state determination device 100 of this embodiment. Note that the flow of the process is similar to Example 1, so the following description will focus on the differences from Example 1.

In Example 2, in order to improve the accuracy of the judgment, the judgment unit 102a calculates the average amount of brain activity during multiple blinking actions and judges the user state based on the average amount.

That is, as shown in FIG. 5, the determination unit 102a repeats step S042, in which the brain waves at the timing of the blinking action are extracted from the signal of the brain measurement unit 112 and the values are added up, a required number of times (step S043), calculates the average amount of brain activity during the blinking action, and determines the degree of immersion based on the average amount of brain activity and a threshold value (steps S05 to S08).

This makes it possible to determine the degree of immersion in the visual target with greater accuracy than in Example 1.

Example 3
A third embodiment will be described below in detail with reference to FIG. 6 as an example of the user state determination process in the user state determination device 100 of the present embodiment.

Figure 6 is a flowchart showing an example (Example 3) of a user state determination process in the user state determination device 100 of this embodiment. Note that the flow of the process is similar to Examples 1 and 2, so the following description will focus on the parts that differ from Examples 1 and 2.

Assumed visual targets in an automobile are, for example, the vehicle's surrounding environment and information presentation devices (display screens such as televisions and car navigation systems), and the brain activity state at the time of blinking can vary depending on what the user is looking at. In this regard, in Example 3, in order to improve the accuracy of the determination in such cases, the learning unit 102b constructs a database 106b for each visual target that associates brain activity states with the user state, and the determination unit 102a aims to determine the user state with high accuracy by referring to the database 106b for each visual target.

6, the learning unit 102b stores the brain activity extracted by the determination unit 102a in step S04 in association with the immersion degree determination results determined by the determination unit 102a in steps S11 and S16 in the visual target database 106b (step S05). At that time, the learning unit 102b also stores information on the visual target determined in step S06 (in this case, information on whether the immersion target is the vehicle surroundings (S07) or the information presentation device (S12)) in association with the brain activity extracted by the determination unit 102a in step S04 in the visual target database 106b.

As a result, the learning unit 102b can perform supervised machine learning based on the visual target-specific database 106b to generate visual target-specific thresholds (S08, S13) as judgment criteria for the judgment unit 102a.

In this third embodiment, an example is described in which a database is constructed for each visual target and judgment criteria are generated for each visual target, but this is not limited to the above. A database (i.e., personal database 106a) may be constructed for each individual in a similar procedure, and judgment criteria for each individual may be generated.

As a result, it is possible to accurately determine the user state even if there is variation in the relationship between brain activity during blinking and immersion level for each visual object or each individual.

(Effects of this embodiment)
As described above, according to this embodiment, the following advantageous effects can be obtained.

In this embodiment, in order to determine the user state, including the user's attention state or the degree of immersion, the user's brain activity state is measured, and when the user's blinking action is detected, the user state is determined based on the brain activity state at the time of the detected blinking action.

This makes it possible to determine the user's state based on the brain activity state when the user blinks, without the requirement of eye movement as in conventional methods that use eye fixation-related potentials (EFRPs). Therefore, the user's state can be determined with high accuracy even when the visual target or line of sight (eyes) is not moving, such as when viewing a screen.

In addition, according to this embodiment, brain measurement detects brain activity using an electroencephalograph, magnetoencephalograph, or electroencephalograph, so the user's state can be determined with high accuracy based on electroencephalograms, brain magnetic fields, and brain potentials measured by sensors that can measure with high time resolution.

In addition, according to this embodiment, blinking is detected based on the electrooculogram (EOG) extracted from a brain measurement signal, so there is no need to provide a sensor for detecting blinking in addition to a sensor for brain measurement, and there is no need to wear an electrooculogram measuring device, which is less cumbersome and has excellent cost, etc.

In addition, according to this embodiment, the user state, including the user's attention state or the user's degree of immersion, is determined based on the magnitude of brain activity during a blink, so the user state can be determined with high accuracy based on the principle that the depth of the reset degree during a blink changes depending on the degree of immersion.

In addition, according to this embodiment, the user state is determined based on the average magnitude of brain activity during multiple blinks, so even if the brain activity state during a single blink is affected by noise or the like, the user state can be accurately determined based on the average.

In addition, according to this embodiment, the user state is determined based on the judgment criteria for each individual or each visual object regarding the brain activity state during the blinking action, so that the user state can be determined with high accuracy even if there is variation in the relationship between the amount of brain activity during blinking and the degree of immersion for each visual object or for each individual.

Other Embodiments
While the embodiments of the present invention have been described above, the present invention may be embodied in various different embodiments other than those described above within the scope of the technical idea described in the claims.

For example, the user state determination device 100 has been described as being configured as an integrated unit to perform processing in a stand-alone form, but this is not limited thereto, and the device may function as an external server or the like, perform processing in response to a request from an in-vehicle client terminal, and return the processing results to the in-vehicle client terminal.

Furthermore, among the processes described in the embodiments, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically using a known method.

In addition, the processing procedures, control procedures, specific names, registered data for each process, information including search conditions and other parameters, screen examples, and database configurations shown in the above documents and drawings may be changed as desired unless otherwise specified.

In addition, with respect to the user state determination device 100, each of the components shown in the figure is a functional concept, and does not necessarily have to be physically configured as shown in the figure. For example, the processing functions of each device of the user state determination device 100, particularly the processing functions performed by the control unit 102, may be realized in whole or in part by a processor such as a CPU (Central Processing Unit) and a program interpreted and executed by the processor, or may be realized as a hardware processor using wired logic. The program is recorded on a non-transient computer-readable recording medium containing programmed instructions for causing a computer to execute the method according to the present invention, as described below, and is mechanically read by the user state determination device 100 as necessary. That is, a computer program for giving instructions to the CPU in cooperation with an OS (Operating System) and performing various processes is recorded in a storage unit 106 such as a ROM or HDD (Hard Disk Drive). This computer program is executed by being loaded into RAM, and works with the CPU to form the control unit.

In addition, this computer program may be stored in an application program server connected to the user state determination device 100 via any network, and it is also possible to download all or part of it as needed.

The program according to the present invention may be stored on a computer-readable recording medium, or may be configured as a program product. Here, the term "recording medium" includes any "portable physical medium" such as a memory card, USB memory, SD card, flexible disk, magneto-optical disk, ROM, EPROM, EEPROM, CD-ROM, MO, DVD, and Blu-ray (registered trademark) Disc.

A "program" is a data processing method written in any language or description method, and may be in any format, such as source code or binary code. Note that a "program" is not necessarily limited to a single configuration, but also includes a distributed configuration of multiple modules or libraries, or a program that works in conjunction with a separate program, such as an OS (Operating System), to achieve its function. Note that the specific configuration for reading a recording medium in each device shown in the embodiments, the reading procedure, or the installation procedure after reading can use well-known configurations and procedures. The present invention may be configured as a program product in which a program is recorded on a non-transitory computer-readable recording medium.

The various databases stored in the memory unit 106 (personal database 106a, visual target database 106b, etc.) are storage devices such as memory devices such as RAM and ROM, fixed disk devices such as hard disks, flexible disks, and optical disks, and store various programs, tables, databases, and web page files used for various processes and website provision.

The user state determination device 100 may be configured as a known information processing device such as a personal computer, ECU, or workstation, or may be configured by connecting any peripheral device to the information processing device. The user state determination device 100 may also be realized by implementing software (including programs, data, etc.) that causes the information processing device to realize the method of the present invention.

Furthermore, the specific form of distribution and integration of the devices is not limited to that shown in the figures, and all or part of them can be functionally or physically distributed and integrated in any unit depending on various additions, etc., or depending on the functional load. In other words, the above-mentioned embodiments may be implemented in any combination, or the embodiments may be implemented selectively.

100 User state determination device 102 Control unit 102a Determination unit 102b Learning unit 106 Storage unit 106a Personal database 106b Visually recognized object database 112 Brain measurement unit 114 Blink detection unit

Claims (12)

A user state determination device that determines a user state including a user's attention state or a user's immersion level,
A brain measurement means for measuring a brain activity state of the user;
A blink detection means for detecting a blinking action of the user's eye;
A determination means for determining the user state based on the brain activity state at the time of the blink action detected by the blink detection means;
A user state determination device comprising: The user state determination device according to claim 1 ,
The brain measurement means includes:
The user state determination device is characterized in that the brain activity is detected by an electroencephalograph, a magnetoencephalograph, or an electroencephalograph. 3. The user state determination device according to claim 1,
The blink detection means includes:
The user state determination device is characterized in that the blinking action is detected based on an electrooculography extracted from a signal from the brain measurement means. 4. The user state determination device according to claim 1,
The determination means is
A user state determination device characterized by determining the user state, including the user's attention state or the user's degree of immersion, based on the magnitude of the brain activity during the blinking action. The user state determination device according to claim 4,
The determination means is
The user state determination device determines the user state based on an average magnitude of the brain activity during a plurality of blinking actions. The user state determination device according to any one of claims 1 to 5,
The determination means is
The user state determination device determines the user state based on an individual determination criterion for the brain activity state during the blinking action. 7. The user state determination device according to claim 1,
The determination means is
The user state determination device is characterized in that the user state is determined based on a determination criterion for each visual target with respect to the brain activity state during the blinking action. A user state determination method for determining a user state including a user's attention state or a user's immersion level, comprising:
A user state determination method characterized by measuring the user's brain activity state, and when a blinking action of the user's eyes is detected, determining the user state based on the brain activity state at the time of the detected blinking action. A program for causing a computer to execute a user state determination method for determining a user state, including a user's attention state or a user's degree of immersion,
A brain measurement step of measuring a brain activity state of the user;
A blink detection step of detecting a blinking action of the user's eye;
a determination step of determining the user state based on the brain activity state at the time of the blinking action detected in the blink detection step;
A program for causing a computer to execute the following. A user state determination device that determines a user state including a user's attention state or a user's immersion level,
A brain measurement means for measuring a brain activity state of the user;
A blink detection means for detecting a blinking action of the user's eye;
When connected to
A user state determination device that determines the user state based on the brain activity state at the time of the blinking action detected by the blink detection means. A user state determination device creation method for realizing, in a computer, a user state determination device that determines a user state, including a user's attention state or a user's immersion level, comprising:
A brain measurement means for measuring a brain activity state of the user;
A blink detection means for detecting a blinking action of the user's eye;
and controlling the connection of the
A step of controlling so that the user state is determined based on the brain activity state at the time of the blink action detected by the blink detection means;
A method for creating a user state determination device comprising: A program for realizing a user state determination device that determines a user state, including a user's attention state or a user's degree of immersion, in a computer, comprising:
A brain measurement means for measuring a brain activity state of the user;
A blink detection means for detecting a blinking action of the user's eye;
and controlling the connection of the
A step of controlling so that the user state is determined based on the brain activity state at the time of the blinking action detected by the blink detection means;
A program for causing a computer to execute a method including the steps of:

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