Control device by brain waves and application to video game device, arousal device, and lighting device

Description: TECHNICAL FIELD [Detailed description of the invention]

【0001】

[Industrial application field]

The present invention relates to an electroencephalogram control device that reflects an electroencephalogram state, and a game device, an awakening device, and a lighting device that use the control device to, for example, prevent a game or doze, or control lighting.

【0002】

[Conventional technology]

Many conventional game devices are equipped with a monitor for displaying images and a data input device for giving instructions on the progress of the game. In this case, the user usually enjoys the game by operating some data input device with his / her hand or foot to change the image on the monitor.

【0003】

For example, as an example of such a game device, FIG. 1 shows a racing device having a monitor, a steering wheel, an accelerator, a brake, and a seat.

【0004】

The following is a brief explanation of how to proceed with this game.

【0005】

First, when the user sits on the seat, the situation as if he / she is sitting on the driver's seat (e) of the racing car is displayed as an image (f) on the monitor (a) screen in front of him. After the user starts the game, the user controls the speed of the racing car by operating the accelerator (c) and the brake (d) with the foot, and controls the traveling direction of the racing car by operating the steering wheel (b) with the hand. While doing so, proceed through the course displayed on the monitor (a). And if the user mistakenly operates the steering wheel and jumps out of the course, the speed of the racing car will be extremely slow, and the speed will remain the same until returning to the course. (That is, the resistance value of the road surface outside the course is set considerably higher than that of the course part). In such a situation, when the user finishes turning the above-mentioned racing course a certain number of laps and reaches the goal, the time required from the start is displayed on the screen and the game ends.

【0006】

However, the series of animation images on the monitor of the racing game device includes preset racing course-related information (course shape, road surface resistance, etc.), the accelerator angle and handle angle of the racing car at that time, and It was realized by repeating image generation and image display based on the position and traveling direction of the racing car at high speed.

【0007】

Further, conventionally, there have been the following as a doze prevention device.

【0008】

First, FIG. 21 shows a doze prevention device that utilizes the movement of the user's head. In the figure, the angle sensor attached to the user's head, to detect the angle θ of the inclination direction p of the user's head with respect to the direction of gravity g (FIG. 21 (a)), the θ user of The head The tilt angle. Then, when the inclination angle is equal to or greater than the constant angle λ (angle threshold value) registered in the device in advance (Fig. 21 (b)), the fixed time (time) registered in the device in advance is also obtained. If more than the threshold value has passed, it is determined that the user is in a dozing state, and a buzzer is used to warn the user, for example. In other words, this was based on the empirical fact that the head tilts slightly when the user is awake and the head tilts significantly when the user is dozing.

【0009】

Next, FIG. 22 shows a doze prevention device for automobiles that utilizes the movement of the steering wheel. In the figure, the angle sensor is attached to the rotation axis of the steering wheel, and detects the rotation angle θ from the state where the steering wheel has an angle of zero (the state where the steering wheel is not turned: FIG. 22 (a)) while the user is driving a car. (Fig. 22 (b)). Then, when the rotation angle of the handle is the same (including zero angle) and a certain time (time threshold) or more registered in advance in the device has passed (that is, the movement of the handle has stopped for a certain time). If), the user was determined to be dozing and was warned by a buzzer, for example. In other words, this was based on the empirical fact that the user constantly moves the steering wheel a little when driving in the awake state, and the steering wheel stops moving completely when the user is dozing.

【0010】

Then, in the above two examples, if the user does not stop dozing even after a certain period of time has passed since the warning buzzer started to sound, it is judged that the user is deeply asleep and the volume of the warning buzzer is raised. I was taking appropriate measures.

【0011】

In addition, conventionally, when the illumination brightness is automatically adjusted, especially when the user tries to automatically adjust the illumination brightness according to his / her own consciousness level, the illumination brightness is switched by using the illumination having a timer function. This was done by the user setting the time in advance.

【0012】

For example, if you want to set the lighting brightness to low brightness until you go to bed and fall asleep, turn off the lighting during sleep, and switch the lighting brightness to high brightness after waking up, set the timer as follows and the user can set the timer. The illumination brightness was adjusted by operating it.

【0013】

(Setting 1) After the timer is differential, the illumination brightness is set to low brightness.

【0014】

(Setting 2) Set the lighting off time by predicting the sleep onset time (time required from bedtime to sleep onset).

【0015】

(Setting 3) Predict the sleep time (time required from falling asleep to waking up) and set the switching time of the illumination brightness to high brightness.

【0016】

However, here, going to bed means getting to sleep, and falling asleep means going to sleep.

【0017】

[Problems to be Solved by the Invention]

However, in the case of the game device as shown in the above conventional example, the control of the game is limited to the operation by the movement of a part of the body such as the hand and the foot, and the game can be experienced only with a mundane feeling. In particular, a large number of racing game devices such as those shown in the conventional examples are on the market, and although there are advances in video quality and operability, the real thrill of the game has reached a plateau.

【0018】

In addition, there has been no game device in which the brain wave state, which is one of the biological states of human beings, is reflected in the progress.

【0019】

Further, in the case of the racing game device shown in the conventional example, since the foot is used, it is impossible for the physically handicapped person with a disability to enjoy it.

【0020】

In addition, the doze prevention device shown in the above conventional example has the following drawbacks.

【0021】

First, when the doze prevention device shown in FIG. 21 is used, for example, when driving a car and the car is traveling on a long steep slope, the calculated tilt angle of the user's head becomes inaccurate, and the user In some cases, the warning buzzer did not sound even though the user was driving asleep, or on the contrary, the warning buzzer sounded even though the user was driving in an awake state. In addition, there are individual differences in the tilt angle of the user's head in the dozing state, and depending on the user, the tilt angle of the head does not exceed the registered fixed angle even if the user falls asleep, and a warning buzzer Was often not heard. Further, this doze prevention device has a drawback that it can be used only when the upper body of the user is upright, and cannot be used at all when the user is lying down.

【0022】

Further, in the doze prevention device for automobiles shown in FIG. 22, the user awakens when the vehicle operates normally when driving on a general roadway, but when a straight portion continues for a long distance as in a highway, for example. Even when driving in a state, the movement of the steering wheel stopped completely for a certain period of time or more, and the warning buzzer sometimes sounded.

【0023】

In addition, although the depth of human inemuri varies from person to person and varies depending on the situation, the time-based volume switching method as shown in the secondary treatment of the conventional example has a very high criterion for the user's sleep depth. It was ambiguous and sometimes inappropriate. For example, if the user falls asleep at a deep level of consciousness from an early stage, it is appropriate to sound a loud warning buzzer from the beginning, but this has not been achieved by the method in the conventional example.

【0024】

Further, in the case of the lighting control device shown in the above conventional example, the user predicts the sleep onset time and the sleep time based on experience and can and sets each switching time, but usually the human sleep onset time and the sleep time are not constant. However, there is a drawback that it lacks accuracy because it changes according to the physical condition at that time.

【0025】

For example, if the settings are made in this way, the lights may be turned off before the user has fallen asleep, or the user may have already fallen asleep but switched to low brightness, or the user may still be in low brightness. In many cases, the lights remained off even though they were awake. And, in such a case, there are many cases where electric power is wasted.

【0026】

In addition, if the user's bedtime differs from day to day, the time of falling asleep and the time of waking up also change, so there is a drawback that the settings must be reset each time.

【0027】

Moreover, it goes without saying that the settings made by one user cannot be used by others.

【0028】

The present invention has been made in view of the above conventional example, and a first object of the present invention is to provide a brain wave control device that performs processing according to a human state by processing and using a human brain wave signal. The second purpose is to provide a game device, an awakening device, and a lighting device using the game device.

【0029】

[Means for solving problems]

In order to achieve the first object, the electroencephalogram control device of the present invention has the following configuration.

【0030】

It has the maximum value among the brain wave input means for inputting the brain wave signal, the calculation means for calculating the spectrum for each frequency component of the brain wave signal input by the input means, and the spectrum for each frequency calculated by the calculation means. A determination means for determining a frequency component and a control means for controlling the next-stage processing based on the determination result by the determination means are provided.

【0031】

With this configuration, control can be performed according to the frequency component contained in the brain wave.

【0032】

More preferably, the frequency components are delta wave, theta wave, alpha wave and beta wave.

【0033】

With this configuration, it is possible to control whether the waveform of the brain wave is a delta wave, a theta wave, an alpha wave, or a beta wave.

【0034】

More preferably, the generation means for generating an image is further provided, and the next-stage processing is the generation of an image.

【0035】

With this configuration, it is possible to generate an image according to the frequency component contained in the brain wave.

【0036】

More preferably, the image is generated based on the instruction input means for inputting the instruction by the operator and the determination result by the instruction input means and the determination means clothing.

【0037】

With this configuration, an image is generated according to an instruction by an operator and an electroencephalogram.

【0038】

More preferably, the sound producing means for emitting a sound is further provided, and the next-stage processing is determining the volume of the sound emitted by the sound producing means.

【0039】

With this configuration, a volume sound corresponding to the frequency component contained in the brain wave is emitted.

【0040】

More preferably, the lighting means is further provided, and the next stage processing is the determination of the brightness by the lighting means.

【0041】

With this configuration, it illuminates with brightness according to the frequency component contained in the brain wave.

【0042】

Further, in order to achieve the second object, the game device of the present invention has the following configuration.

【0043】

A game device for running a vehicle on a screen, which is calculated by an electroencephalogram input means for inputting an electroencephalogram signal, a calculation means for calculating a spectrum of a brain wave signal input by the input means for each frequency component, and the calculation means. Of the spectrum for each frequency, the determination means for determining the frequency component having the maximum value, the instruction means for instructing the running state of the vehicle, the determination result by the determination means, and the instruction means are re-instructed. It includes a generation means for updating the state of the vehicle on the screen based on the traveling state and generating a new image, and a means for displaying the image generated by the generation means.

【0044】

With this configuration, the state of the vehicle on the screen is updated based on the operator's instruction and the brain wave, and the image is updated.

【0045】

Further, the awakening device of the present invention has the following configuration.

【0046】

It has the maximum value among the brain wave input means for inputting the brain wave signal, the calculation means for calculating the spectrum for each frequency component of the brain wave signal input by the input means, and the spectrum for each frequency calculated by the calculation means. It includes a determination means for determining a frequency component, a determination means for determining a volume based on a determination result by the determination means, and a means for emitting sound at a volume determined by the determination means.

【0047】

With this configuration, sound is emitted at a volume corresponding to the frequency component of the brain wave.

【0048】

Further, the lighting device of the present invention has the following configuration.

【0049】

It has the maximum value among the brain wave input means for inputting the brain wave signal, the calculation means for calculating the spectrum for each frequency component of the brain wave signal input by the input means, and the spectrum for each frequency calculated by the calculation means. It includes a determination means for determining a frequency component, a determination means for determining brightness based on a determination result by the determination means, and a means for emitting light with a brightness determined by the determination means.

【0050】

With this configuration, it illuminates with brightness according to the frequency component of the brain wave.

【0051】

[First Example]

First, in order to clarify the characteristics of this embodiment, the relationship between human brain waves and mental states will be briefly described.

【0052】

Human brain waves usually change in the frequency band of 0 to 30 Hz, and there are four types of characteristic frequencies in this frequency band as follows.

【0053】

1.5 ~ 3.5Hz band delta (δ) wave, 4.0 ~ 7.0Hz band Theta (θ) wave, 8.0 ~ 13.0Hz band Alpha (α) wave, 14.0 ~ 30.0Hz band Beta (β) wave And these four types of brain waves have the following characteristics related to the human mental state. Delta waves are unconscious or deep sleep, theta waves are drowsy or dreaming, alpha waves are relaxed and creatively awake, and beta waves are anxious and worried. It is said to appear mainly in a state of mental excitement. In other words, the level of low-frequency brain waves tends to increase as the human mental state stabilizes, and conversely, the level of high-frequency brain waves tends to increase as the human mental state becomes more excited. ..

【0054】

By the way, from such an explanation, it is easy to think that the brain wave state cannot be intentionally controlled by humans, but it is said that self-mental training gradually makes it possible to control it intentionally. There is. This means that, depending on training, humans can intentionally produce each characteristic waveform from delta waves to beta waves, even when they are awake. The device of this embodiment pays attention to the nature of such a waveform, and aims to reflect the human mental state in the progress of the game by changing the brain wave state by the user controlling his / her own mental state. There is.

【0055】

Hereinafter, the game device according to the first embodiment of the present invention will be described in detail with reference to the drawings.

【0056】

FIG. 2 is a block diagram showing a racing game device according to an embodiment of the present invention.

【0057】

In FIG. 2, the command input device 2 is an input device for inputting an instruction such as the start of a game, and a keyboard is used, for example.

【0058】

The data input device 3 is an input device for inputting course-related data, and a mouse is used, for example.

【0059】

The operation input device 4 is an input device for inputting the rotation angle of the handle, and for example, an angle sensor is used.

【0060】

The electroencephalogram input device 5 is an input device for inputting an electroencephalogram, and for example, an electroencephalograph is used.

【0061】

The arithmetic unit 6 performs arithmetic processing such as calculation of the brain wave state, a new position and direction of the racing car, and generation of a display image.

【0062】

The file device 7 is a device for storing course-related data (course data image, start initial position Ps (xs, ys), start initial direction γs, initial road surface resistance value μs, etc.) and various variables, such as an optical disk. A magnetic disk or the like is used.

【0063】

The display device 8 is a display device for displaying the generated image, and for example, a CRT monitor is used.

【0064】

The control device 1 controls a command input device 2, a data input device 3, an operation input device 4, an electroencephalogram input device 5, an arithmetic device 6, a file device 7, and a display device 8.

【0065】

The game device configured as described above will be described below according to the flow of data. A description of this process will be given later with reference to FIG.

【0066】

First, the game processing starts when the user presses a key on the keyboard which is the command input device 2. Next, the course-related data is input by the command of the control device 1, and the user inputs the course-related data with the data input device 3 such as a mouse by the method described later (detailed with reference to FIG. 4). Next, the variables representing the position and direction of the racing car are initialized. However, the position and direction of the racing car shall indicate the coordinates on the course data image in the course-related data and the direction seen from those coordinates. Then, using these variables, an initial image is generated by the method described later, and the display device 8 displays the image. Next, the race start standby state is set by the command of the control device 1, and the racing game is started when the user gives an instruction with the keyboard which is the command input device 2.

【0067】

Next, it is judged whether the current racing car has crossed the goal point, and if it has crossed, the required time is displayed on the display device 8 and then the game processing is finished. If not, the next state is set. move on. Then, the angle sensor, which is the operation input device 4, measures the rotation angle of the steering wheel according to the command of the control device 1. Further, according to the instruction of the control device 1, the arithmetic unit 6 calculates the electroencephalogram state value from the electroencephalogram spectrum data calculated by the method described later (detailed with reference to FIG. 11). Next, according to the command of the control device 1, the arithmetic unit 6 uses the rotation angle data, the brain wave state data, the course-related data, and the data of the position and direction of the racing car at that time to be used as a new position of the racing car by the method described later. Calculate the direction. Then, using the new position and direction data and the course-related data, a new display image is generated by the method described later (detailed with reference to FIG. 14). Then, the display device displays the generated image by the command of the control device 1. Next, the data of the current position and direction is updated with the data of the new position and direction, and the process returns to the judgment of whether or not the goal position has been exceeded again.

【0068】

Next, the details of the above description will be described, but the arrangement for convenience of description will be described.

【0069】

When the red, green, and blue data that make up each pixel of an image are represented by R, G, and B, respectively, and a certain color is represented, Colidentifier = (R value), (G value), (B value) It will be described as follows. However, identifier shall represent an identifier. Further, each component value is data that can be expressed in an 8-bit configuration, that is, 256 gradations, and the maximum brightness is 255 and the minimum brightness is 0. Further, it is assumed that the display device can display image data composed of such pixels. In addition, the pixel P at the position where the upper left point of the image is the origin and is advanced by x pixels to the right and y pixels downward is P (x, y) It will be represented by (Fig. 3). The above are the promises regarding images in the present embodiment, but the present invention is not limited to such designation.

【0070】

Hereinafter, (1), (2), (3), and (4) describe the main partial processing of the racing game, and (5) describes the entire game processing in detail.

【0071】

(1) Input of course-related data (Figs. 4 to 6) Next, the procedure for inputting course-related data will be described.

【0072】

Figure 4 is a flowchart showing the procedure for inputting course-related data. Hereinafter, the description will be given according to the data flow. Note that this flowchart is executed by the control device 1. The control device realizes the procedure of the flowchart by executing the program stored in RAM or the like. This is the same for all the flowcharts described below.

【0073】

Description of step C1 The control device 1 displays all the pixels of the screen of the display device 8, for example. ColZ = (100,100,100) Initialize with the color of. However, here, the vertical and horizontal sizes of the display device 8 are X pixels and Y pixels, respectively (Fig. 5 (a)). Description of step C2 By the command of the control device 1, the input of the diameter of the circular pointer corresponding to the course width is waited, and the user inputs the diameter d of the circular pointer by the command input device 2 such as a keyboard.

【0074】

Description of step C3 By the command of the control device 1, the drawing input state of the course is set, and the circular pointer with the diameter d specified in step C2 appears on the screen of the display device 8. Then, the user draws the course by moving the circular pointer on the screen with the data input device 3 such as a mouse. At this time, the pixels of the drawn locus portion are, for example, ColC = (255,255,255) The color is changed to (Fig. 5 (b), (c), (d)).

【0075】

Description of step C4 The start position is specified by the command of the control device 1, and an arrow-shaped pointer appears on the monitor. The user inputs the start position Ps (xs, ys) of the racing car by clicking on the course with the data input device 3 such as a mouse (Fig. 6 (e)).

【0076】

Description of step C5 The start direction is specified by the command of the control device 1, and the user specifies the start direction γs of the racing car with respect to the start position on the course by the data input device 3 such as a mouse on the monitor. However, this γs indicates the angle when viewed counterclockwise from the positive x-axis direction on the screen (Fig. 6 (f)).

【0077】

Description of step C6 By the command of the control device 1, the goal zone is specified and a square frame as shown in the figure appears on the display device 8 (Fig. 6 (g)). However, the length of one side of the frame (number of pixels) is set to be at least larger than the course width. The user moves this frame with a mouse or the like to specify a goal zone on the course. Then, for example, the color of the part where the square frame at the specified position and the course part specified in step C3 overlap. ColG = (255,0,0) Change to and make this area the goal zone. Then, the course data image is completed at this stage (Fig. 6 (h)).

【0078】

Description of step C7 By the command of the control device 1, the road surface resistance value input state is entered, and the user uses the data input device 3 such as a mouse to input each pixel of the course part (color is ColC part) and the goal part (color is ColG part). And the road surface resistance values μC, μZ corresponding to each pixel of the off-course part (the part whose color is ColZ), for example. μC = 0.05 μZ = 0.5 Enter as.

【0079】

Description of step C8 The control device 1 is in a command input waiting state, and the user is made to judge whether the current course-related data is good or bad, and if it is good, it is instructed to proceed to the next step, and if it is bad, it returns to step C1 and the course-related data is displayed. The command input device 2 gives an instruction to redo the input.

【0080】

Description of step C9 The control device 1 stores the image displayed on the screen of the display device 8 in the file device 7 as an image for course data. Similarly, the start position Ps, the start direction γs, and the road surface resistance values μC and μZ are also stored in the file device 7.

【0081】

The above-mentioned procedure for inputting course-related data is used in the game processing described later.

【0082】

(2) Calculation of EEG state values (Figs. 7 to 11) A spectrum for each frequency component of the electroencephalogram is used for the calculation of the electroencephalogram state value in this example. Therefore, before showing the flow of calculation of the electroencephalogram state value, a method of calculating the spectrum of the electroencephalogram by frequency component will be described.

【0083】

First, as shown in FIG. 7, the measuring unit 71 of the waveform input device 5 such as an electroencephalograph is attached to the head of the subject. Then, when the change in the potential between the electrodes A and B in the measuring unit with time is measured, a one-dimensional analog waveform signal as shown in FIG. 8 is obtained. Then, consider a case where, for example, a spectrum obtained by dividing a frequency band from 0 to F (Hz) into N frequency components is calculated from this analog waveform signal by a discrete Fourier transform (DFT). This DFT is a method usually used when decomposing a one-dimensional discrete signal into frequency components and analyzing it (FFT (First Fourier Transform) is well-known as a method for executing DFT with a small number of operations. ).

【0084】

Assuming that one sampling time of the electroencephalogram input device 5 is T, N / T = F (Equation-1) Is established. Here, if the sampling interval of the waveform input device is Δt, the number of inputs and the number of outputs in DFT are equal. Δt N = T (Equation-2) However, therefore, from these two formulas, Δt = 1 / F (Equation-3) It can be seen that Δt does not depend on the number of divisions N. Then, digital waveform data for each of N sampling intervals as shown in Fig. 9. v (t) = v (i · Δt) (i = 0,1,2,3, ..., N-1) (Equation-4) Then, the spectrum L (f) for each frequency component as shown in FIG. 10 can be calculated by the following formula by the DFT formula.

【0085】

[Number 1]

<img file="JPH07124331A_D0001.tif" />(Equation-5) Next, a method of calculating the electroencephalogram state value using the spectrum for each frequency component of the electroencephalogram described above will be described. FIG. 11 is a flowchart showing the calculation procedure of the electroencephalogram state value. Hereinafter, the description will be given according to the data flow.

【0086】

Description of step B1 The brain wave input device 5 converts the analog waveform data of the brain wave into digital waveform data v (i · Δt) (i = 0, ..., N-1) and inputs it.

【0087】

Description of step B2 Using the digital waveform data v (i · Δt) (i = 0, ..., N-1) input in step B1, the spectrum L (k / (Δt · N)) (k = 0) for each frequency component , ..., N-1) are calculated by the above method. However, N indicates the number of divisions of the frequency component, and is assumed to be input by the user during the game processing described later. Similarly, Δt is calculated by (Equation-3) using the maximum frequency F in the electroencephalogram spectrum input in the game processing described later.

【0088】

Here, for convenience, L (k / (Δt N)) = L'(k) And.

【0089】

Description of step B3 Of L'(k) (k = 1, ..., N-1), δmin k / (Δt N) &lt;δmax Let kdelta be k for which L'(k) is the maximum (that is, the maximum value in the delta wave) among k for which is satisfied. However, here (δmin, δmax) indicates the frequency band of the delta wave, which is input when the brain wave-related data in the game processing described later is input and is stored in the file device 7.

【0090】

Description of step B4 Of L'(k) (k = 1, ..., N-1), θmin k / (Δt N) &lt;θmax Let ktheta be the maximum value of L'(k) (that is, the maximum value in theta waves) among the k that holds. However, here, (θmin, θmax) indicates the frequency band of theta wave, which is input when the brain wave-related data in the game processing described later is input and is stored in the file device 7.

【0091】

Description of step B5 Of L'(k) (k = 1, ..., N-1), αmin k / (Δt N) &lt;αmax Calculates k for which L'(k) is the maximum (that is, the maximum value in the alpha wave) among k for which is satisfied, and stores it as kalpha in the file device 7. However, here (αmin, αmax) indicates the frequency band of the alpha wave, and it is assumed that it is input when the brain wave-related data is input in the game processing described later.

【0092】

Description of step B6 Of L'(k) (k = 1, ..., N-1), βmin k / (Δt N) &lt;βmax Let kbeta be k for which L'(k) is the maximum (that is, the maximum value in the beta wave) among k for which is satisfied. However, here (βmin, βmax) indicates the frequency band of the beta wave, and it is assumed that it is input when the brain wave-related data is input in the game processing described later.

【0093】

Description of step B7 Select the largest one from L'(kdelta), L'(ktheta), L'(kalpha), L'(kbeta) and perform the following processing.

【0094】

When L'(kdelta) is maximum: Set the EEG state value S to 1.

【0095】

When L'(ktheta) is maximum: Set the EEG state value S to 2.

【0096】

When L'(kalpha) is maximum: Set the EEG state value S to 3.

【0097】

When L'(kbeta)) is the maximum: Set the EEG state value S to 4.

【0098】

The procedure for calculating the electroencephalogram state value described above is used in the game processing described later.

【0099】

(3) Calculation of new position and direction of racing car (Figs. 12 and 13) Before describing the calculation method of the new position and direction of the racing car, the measurement method of the rotation angle ρ of the steering wheel will be described. FIG. 13 is a diagram showing a method of measuring the rotation angle of the handle. First, FIG. 13A shows a state in which the handle is not rotating. Then, the angle sensor attached to the center of the handle measures the rotation angle ρ as seen from the reference direction of speed measurement. If the rotation direction is clockwise, ρ is a positive number, and if it is counterclockwise, ρ is calculated. Let it be a negative number. For example, in the case of Fig. 13 (b), ρ is a positive number because it is rotated clockwise.

【0100】

Figure 12 shows the calculation of the new position and direction of the racing car.

【0101】

The position and direction of the racing car at a certain point in time during the game were calculated by P (x, y) and γ, respectively, the angle of rotation of the steering wheel at this time was ρ, and the brain wave state was calculated by the procedure of S ((2)). The new position and direction (position and direction in the next state) are P'(x', y') and γ', respectively. First, using ρ and γ, γ'is γ'= γ + ρ It shall be calculated by. In addition, this calculation formula is set so that the traveling direction at a certain point in time and the rotation angle of the steering wheel are reflected in the new traveling direction. Then, each component of P'(x', y') is determined by the new direction γ', the road surface resistance value μ (P) at the position P, and the electroencephalogram state value S. x'= int (x + S / μ (P) cosγ') y'= int (y + S / μ (P) sinγ') It shall be calculated by. However, int (x) is a function that truncates the decimal point of x. Here, since the distance between points P and P'is S / μ (P), the distance between these two points is directly proportional to the electroencephalogram state value S (and inversely proportional to the road surface resistance value, that is, high). The higher the frequency brain wave level, the faster the speed (that is, the greater the distance between the current position and the new position), and when it is off course, it is much faster than when it is on course. It is set to be slower (that is, the distance between the current position and the new position is smaller).

【0102】

The new position and direction calculation method for the racing car described above will be used in the game processing described later.

【0103】

(4) Generation of display image (Figs. 14 to 17) The image displayed on the display device 8 is generated by the method shown in the flow of FIG. 14 depending on the course data image and the position and direction of the racing car.

【0104】

Hereinafter, the description will be given according to the flow of processing.

【0105】

Description of step G1 A partial image is cut out from the course data image by the following method.

【0106】

FIG. 15 is a diagram showing a method of cutting out a partial image from the course data image. However, in the figure, a part of the course data image is visible, and it is composed of a course portion 152 and an off-course portion 151.

【0107】

First, consider a straight line g that passes through the position P (x, y) and is orthogonal to the traveling direction vector in this figure. However, this traveling direction vector is assumed to mean an arbitrary vector whose starting point is P and which is an angle γ formed with the x-axis. Of the two points on this straight line g whose distance from the point P is w / 2, the point on the left side is A and the point on the right side is B when facing the direction of travel from P. Then, the points where the points A and B are translated by the distance h in the traveling direction are defined as the points D and C, respectively. Here, if the coordinates of point A, point B, point C, and point D are A (xA, yA), B (xB, yB), C (xC, yC), D (xD, yD), respectively, each coordinate value is, xA = int (x + w / 2 cosγ) yA = int (y + w / 2 sinγ) xB = int (xw / 2 cosγ) yB = int (yw / 2 sinγ) xC = int (xB + h sin γ) yC = int (yB + h cosγ) xD = int (xA + h sin γ) yD = int (yA + h cosγ) It is calculated by. Then, the area of this quadrangle ABCD is cut out as a partial image (Fig. 16 (a)).

【0108】

Description of step G2 The process of deformation processing of the partial image obtained in step G1 is shown in FIGS. 16 and 17.

【0109】

First, let M be the midpoint of the line segment AB in the partial image obtained in the figure, and let A'and B'be the points where the distance to M is d / 2 on the line segments AM and BM, respectively (Fig. 16). (b)). Here, the length of the line segment A'B is d. First, the first deformation is performed so that the length of the line segment A'B'of the trapezoid A'B'CD is w, and the image of FIG. 16 (c) is obtained. Next, the image is subjected to a second transformation such that the horizontal direction is X pixels and the vertical direction is Y / 2 pixels (X and Y indicate the number of horizontal and body pixels of the display device 8, respectively). ), And obtain the image of FIG. 17 (d).

【0110】

Description of step G3 Generate a background image with the same number of pixels in the vertical and horizontal directions as the display device 8, and set the colors of all the pixels, for example. ColB = (0,0,255) Initialize with (Fig. 17 (e)).

【0111】

Description of step G4 The deformed image obtained in step G2 is combined with the background image obtained in step G3 as shown in FIG. 17 (f) to obtain a display image.

【0112】

The display image generation procedure described above is used in the game processing described later.

【0113】

(5) Game processing (Fig. 18) Next, the game processing in this embodiment will be described.

【0114】

FIG. 18 is a flowchart showing the game processing in this embodiment.

【0115】

Hereinafter, the processing method will be described in detail according to the data flow.

【0116】

Description of step S1 The control device 1 puts the data input device 3 in the data input waiting state, and the user passes through the data input device 3 to each frequency band (δmin, δmax), (θmin, θmin,) of the delta wave, theta wave, alpha wave, and beta wave. θmax), (αmin, αmax), (βmin, βmax) (unit of each value is Hz), maximum frequency F (Hz) in the brain wave spectrum, frequency division number N (pieces) of the brain wave, horizontal and vertical of the display device 8. After inputting the number of pixels X (pixels) and Y (pixels), store them in file 7.

【0117】

Description of step S2 The control device 1 issues a command to the arithmetic unit 6, causes the sampling interval Δt of the waveform input device to be calculated by (Equation -3), and stores it in the file device 7.

【0118】

Description of step S3 The control device 1 puts the data input device 3 in the course-related data input waiting state, and when the user inputs the course-related data by the method described above, stores the data input device 3 in the file device 7. The details are as explained in (1).

【0119】

Description of step S4 By the command of the control device 1, the coordinate data P (x, y) indicating the position of the racing car and the traveling direction γ are initially set by the start position data Ps (xs, ys) in the course-related data and the start direction vector γs, respectively. To become. In other words x xs y ys γ γs And.

【0120】

Description of step S5 By the command of the control device 1, the arithmetic unit 6 determines whether or not the position of the racing car is in the goal zone. That is, if the point P (x, y) on the course data image is included in the pixel group that is ColG on the course data image, the process proceeds to step 10, and if not, the process proceeds to the next step. ..

【0121】

Description of step S6 By the instruction of the control command 1, the angle sensor which is the operation input device 4 measures the rotation angle ρ of the handle and stores it in the file device 7.

【0122】

Description of step S7 According to the instruction of the control device 1, the arithmetic unit 6 calculates the electroencephalogram state value S according to the procedure described in (2) and stores it in the file device 7.

【0123】

Description of step S8 According to the command of the control device 1, the arithmetic unit 6 changes the state of the racing car at that time, that is, the position P (x, y), the direction γ, the road surface resistance value μ (P) at this position, the rotation angle ρ of the steering wheel, and the brain wave. Using the state S, the new position P'(x', y') and direction γ'of the racing car are calculated by the procedure described in (3) and stored in the file device 7.

【0124】

Description of step S9 According to the instruction of the control device 1, the arithmetic unit 6 generates a display image by the above-mentioned method using P'(x', y') and γ'calculated in step S6, and stores the display image in the file device 7.

【0125】

Description of step S10 According to the instruction of the control device 1, the display device 8 displays the display image in the file device 7 generated in step S8. This step is described in detail as (4).

【0126】

Description of step S11 At the instruction of the controller 1, the arithmetic unit 6 updates the current position P (x, y) and the direction γ to the new position P'(x', y') and the direction γ', that is, x x' y y' γ γ' And proceed to step S5.

【0127】

Description of step S12 The control device 1 causes the arithmetic unit 6 to calculate the elapsed time from the start, displays it on the display device 8, and then ends the process.

【0128】

According to the procedure described above, the game device of this embodiment calculates a spectrum for each frequency component from the waveform data of the user's brain wave, and uses the result to give an instruction to the progress of the game. It will be a game device with a completely new taste, which is different from a game device that uses only a part of the human body such as legs.

【0129】

As a result, the mental state of the user is directly reflected in the progress of the game, so that the sense of unity with the game is deepened and the degree of fun is dramatically increased.

【0130】

Furthermore, there is an additional advantage that the user can perform self-mental training (self-mind training) while enjoying the game.

【0131】

Further, for example, if the speed is controlled by brain waves in the racing game shown in the conventional example, it is not necessary to use the legs, so that even a physically handicapped person with a disability can enjoy it.

【0132】

[Second Example]

As a second embodiment, an awakening device using brain waves, that is, a doze prevention device will be described.

【0133】

The relationship between human brain waves and the level of consciousness is as described in the first embodiment, but will be briefly described in order to clarify the characteristics of this embodiment.

【0134】

Human brain waves usually change in the frequency band of 0 to 30 Hz, and there are four types of characteristic frequencies in this frequency band as follows.

【0135】

1.5 ~ 3.5Hz band delta (δ) wave, 4.0 ~ 7.0Hz band Theta (θ) wave, 8.0 ~ 13.0Hz band Alpha (α) wave, 14.0 ~ 30.0Hz band Beta (β) wave And these four types of brain waves have the following characteristics related to the level of human consciousness. Delta waves are unconscious or deep sleep, theta waves are drowsy or dreaming, alpha waves are vaguely awake, and beta waves are focused or mental. It is said that it appears in a clearly awake state like when you are active. That is, the lower the frequency brain wave level tends to become stronger as the human consciousness level tends to stabilize, and conversely, the higher frequency brain wave level tends to become stronger as the human consciousness level moves toward the concentration direction. An object of the present invention is to reflect the human consciousness level in the adjustment of the volume of the warning buzzer by using such human brain waves.

【0136】

Hereinafter, examples of the present invention will be described in detail with reference to the drawings.

【0137】

FIG. 19 shows an embodiment of the present invention.

【0138】

The data input device 191 is an input device for inputting data, and a keyboard is used, for example.

【0139】

The electroencephalogram input device 192 is an input device for inputting an electroencephalogram, and for example, an electroencephalograph is used.

【0140】

The command input device 193 is an input device for giving an instruction to the control device, and a mouse is used, for example.

【0141】

The display device 195 is for displaying input data and input commands, and for example, a CRT is used.

【0142】

The file device 196 is a file device for storing data input by the subject, digital electroencephalogram data of the user, and calculated spectrum data, and a non-volatile memory such as a magnetic disk is used.

【0143】

The arithmetic unit 197 performs arithmetic processing for volume selection.

【0144】

For the sound output device 198, for example, a buzzer is used.

【0145】

The control device 194 controls a data input device 191, a waveform input device 192, a command input device 193, a display device 195, a file device 196, an arithmetic device 197, and a sound output device 198.

【0146】

The doze prevention device configured as described above will be described below according to the flow of data.

【0147】

First, the user assigns a buzzer volume corresponding to each consciousness level by the data input device 191. Then, the waveform input device 192 A / D-converts the analog waveform data of the user's brain wave sent at a fixed time, and the obtained digital waveform data is stored in the file device 196. Then, based on this digital waveform data, the spectrum for each frequency component is calculated by the method described later and stored in the file device 196. Then, using this result, the arithmetic unit 197 selects the buzzer volume corresponding to the consciousness level at that time from the buzzer volume assigned to the user, and the volume of the sound output device 198 is switched to the selected volume.

【0148】

Next, a method of calculating the spectrum of the brain wave by frequency component will be described.

【0149】

First, as shown in FIG. 7, the measuring unit 71 of a waveform input device such as an electroencephalograph is attached to the user's head. Then, when the potential difference between the electrodes A and B with respect to time is measured, a one-dimensional analog waveform signal as shown in FIG. 8 is obtained. Then, consider a case where, for example, a spectrum obtained by dividing a frequency band from 0 to F (Hz) into N frequency components is calculated from this analog waveform signal by a discrete Fourier transform (DFT). This DFT is a method usually used when decomposing a one-dimensional discrete signal into frequency components and analyzing it (FFT (First Fourier Transform) is well-known as a method for executing DFT with a small number of operations. ).

【0150】

First, assuming that one sampling time of the waveform input device 192 is T, N / T = F (Equation-6) Is established. Here, if the sampling interval of the waveform input device 192 is Δt, the number of inputs and the number of outputs in the DFT are equal. Δt N = T (Equation-7) However, therefore, from these two formulas, Δt = 1 / F (Equation-8) It can be seen that Δt does not depend on the number of divisions N. Then, digital waveform data for each of N sampling intervals as shown in Fig. 9. v (t) = v (i · Δt) (i = 0,1,2,3, ..., N-1) (Equation-9) Then, the spectrum L (f) for each frequency component as shown in FIG. 10 can be calculated by the following formula by the DFT formula.

【0151】

[Number 2]

<img file="JPH07124331A_D0002.tif" />(Equation-10) The method of calculating the spectrum for each frequency component based on the waveform data of the electroencephalogram described above is used in the doze prevention process described later.

【0152】

Next, the doze prevention treatment in this embodiment will be described.

【0153】

FIG. 20 is a flowchart showing the doze prevention process in this embodiment.

【0154】

Hereinafter, the processing method will be described in detail according to the data flow.

【0155】

Description of step S201 The control device 194 puts the command input device 193 in the command input waiting state, and when the user issues a command to newly input various data and assign the buzzer volume to each consciousness level, the process proceeds to the next step S202 and is not performed. After issuing the command (that is, the previous various data stored in the file device 196 and the assignment of the buzzer volume to each consciousness level are also used this time), the process proceeds to step S204.

【0156】

Description of step S202 The control device 194 puts the data input device 191 in a data input waiting state, and the user can use the delta wave, theta wave, alpha wave, and beta wave frequency bands (δmin, δmax), (θmin, θmax), (αmin, αmax). , (Βmin, βmax), the maximum frequency value p (Hz) in the spectrum of the brain wave, the number of frequency divisions N (pieces) of the brain wave, and the command reception standby time s (seconds) are input, and then stored in the file device 196.

【0157】

Description of step S203 The control device 194 puts the data input device 191 in the input waiting state, and the user sets the buzzer volume corresponding to each consciousness level, for example. Buzzer volume for delta wave Loud volume Theta wave buzzer volume Medium volume Alpha wave buzzer volume low volume Beta wave buzzer volume Volume zero (silence) Set as. Then, these data are stored in the file device 196.

【0158】

Description of step S204 The control device 194 issues a command to the arithmetic unit 197 to calculate the sampling interval Δt of the waveform input device 192 by (Equation -8).

【0159】

Description of step S205 The control device 194 causes the waveform input device 192 to measure N brain waves at a sampling interval Δt, and the digital waveform data of the obtained brain waves v (t) = v (i · Δt) (i = 0, ..., Store N-1) in file device 196.

【0160】

Description of step S206 The control device 194 uses the digital waveform data v (i · Δt) (i = 0, ..., N-1) in the file device 196 to obtain a spectrum for each frequency component according to (Equation -10) and the above method. L (k / (Δt · N)) (k = 0, ..., N-1) is calculated by the arithmetic unit 197 and stored in the file device 196.

【0161】

Here, for convenience, L (k / (Δt N)) = L'(k) And.

【0162】

Description of step S207 The control device 194 is in the L'(k) (k = 1, ..., N-1) in the file device 196. δmin k / (Δt N) &lt;δmax Let L'(k) calculate the maximum k (that is, the maximum value in the delta wave) among the k that holds, and store it as kdelta in the file device 196.

【0163】

Description of step S208 The control device 194 is in the L'(k) (k = 1, ..., N-1) in the file device 196. θmin k / (Δt N) &lt;θmax Let L'(k) calculate the maximum k (that is, the maximum value in theta wave) among the k that holds, and store it as ktheta in the file device 196.

【0164】

Description of step S209 The control device 194 is in the L'(k) (k = 1, ..., N-1) in the file device 196. αmin k / (Δt N) &lt;αmax Let L'(k) calculate the maximum k (that is, the maximum value in the alpha wave) in the k that holds, and store it in the file device 196 as kalpha.

【0165】

Description of step S210 The control device 194 is in the L'(k) (k = 1, ..., N-1) in the file device 196. βmin k / (Δt N) &lt;βmax Is satisfied, L'(k) is made to calculate the maximum k (that is, the maximum value in the beta wave) in the arithmetic unit 197, and it is stored in the file device 196 as kbeta.

【0166】

Description of step S211 The control device 194 causes the arithmetic unit 197 to select the largest one among L'(kdelta), L'(ktheta), L'(kalpha), and L'(kbeta), and performs the following processing.

【0167】

-When L'(kdelta) is maximum: Set the selected volume as the volume for delta waves.

【0168】

-When L'(ktheta) is maximum: Set the selected volume as theta wave volume.

【0169】

-When L'(kalpha) is maximum: Set the selected volume as the alpha wave volume.

【0170】

-When L'(kbeta) is maximum: Set the selected volume as the volume for delta waves.

【0171】

Description of step S212 The control device 194 switches the buzzer volume of the output device 198 to the selected volume in step S211.

【0172】

Description of step S213 The control device 194 puts the command input device 193 in the input waiting state for a certain period of time s, ends the process if the user sends a process end command within that time, and returns to step S205 otherwise.

【0173】

As described above, according to the present embodiment, the spectrum for each frequency component is calculated from the waveform data of the user's brain wave, and the result is used to assign the spectrum to each consciousness level in advance from the volume at that time. By selecting the volume corresponding to the user's identification status and sounding the warning buzzer at the selected volume, the volume of the warning buzzer can be adjusted to reflect the user's level of consciousness, that is, the depth of sleep. Equipment can be provided.

【0174】

As a result, the situation in which the user is placed (whether the user is upright or lying down, the inclination angle of the road when the user is driving a car, etc.) and the characteristics of each user when sleeping (user when sleeping). It is possible to accurately determine the user's dozing state and sound the warning buzzer at an appropriate volume without being affected by the tilt angle of the head and the depth of sleep.

【0175】

[Third Example]

As a third embodiment, a lighting control device that controls the brightness of lighting using brain waves will be described.

【0176】

First, in order to clarify the characteristics of this embodiment, the relationship between human brain waves and the level of consciousness will be briefly described.

【0177】

Human brain waves usually change in the frequency band of 0 to 30 Hz, and there are four types of characteristic frequencies in this frequency band as follows.

【0178】

1.5 ~ 3.5Hz band delta (δ) wave, 4.0 ~ 7.0Hz band Theta (θ) wave, 8.0 ~ 13.0Hz band Alpha (α) wave, 14.0 ~ 30.0Hz band Beta (β) wave And these four types of brain waves have the following characteristics related to the level of human consciousness. Delta waves are unconscious or deep sleep, theta waves are drowsy or dreaming, alpha waves are vaguely awake, and beta waves are focused or mental. It is said that it appears in a clearly awake state like when you are active. That is, the lower the frequency brain wave level tends to become stronger as the human consciousness level tends to stabilize, and conversely, the higher frequency brain wave level tends to become stronger as the human consciousness level moves toward the concentration direction. An object of the present invention is to reflect the level of human consciousness in the extension of illumination brightness by using such human brain waves.

【0179】

Hereinafter, examples of the present invention will be described in detail with reference to the drawings.

【0180】

FIG. 23 shows a third embodiment of the present invention.

【0181】

The data input device 231 is an input device for inputting data, and a keyboard is used, for example.

【0182】

The waveform input device 232 is an input device for inputting an electroencephalogram, and for example, an electroencephalograph is used.

【0183】

The command input device 233 is an input device for giving an instruction to the control device, and a mouse is used, for example.

【0184】

The display device 235 is for displaying input data and input commands, and for example, a CRT is used.

【0185】

The file device 236 is a file device for storing data input by the subject, digital electroencephalogram data of the user, and calculated spectrum data, and a non-volatile memory such as a magnetic disk is used.

【0186】

The arithmetic unit 237 performs arithmetic processing for selecting the brightness.

【0187】

As the illuminating device 238, for example, a fluorescent lamp is used.

【0188】

The control device 234 controls the data input device 231, the waveform input device 232, the command input device 233, the display device 235, the file device 236, the arithmetic unit 237, and the lighting device 238.

【0189】

The lighting control device configured as described above will be described below according to the flow of data.

【0190】

First, the user uses the data input device 231 to adjust the illumination brightness corresponding to each consciousness level. Then, the waveform input device 232 A / D-converts the analog waveform data of the user's brain wave sent at a fixed time, and the obtained digital waveform data is stored in the file device 236. Then, based on this digital waveform data, the spectrum for each frequency component is calculated by the method described later and stored in the file device 236. Then, using this result, the arithmetic unit 237 selects the brightness corresponding to the consciousness level at that time from the brightness assigned by the user, and the brightness of the lighting device 238 is switched to the selected brightness.

【0191】

Next, a method of calculating the spectrum of the brain wave by frequency component will be described.

【0192】

First, as shown in FIG. 7, the measuring unit 71 of a waveform input device such as an electroencephalograph is attached to the user's head. Then, when the potential difference between the electrodes A and B with respect to time is measured, a one-dimensional analog waveform signal as shown in FIG. 8 is obtained. Then, consider a case where, for example, a spectrum obtained by dividing a frequency band from 0 to F (Hz) into N frequency components is calculated from this analog waveform signal by a discrete Fourier transform (DFT). This DFT is a method usually used when decomposing a one-dimensional discrete signal into frequency components and analyzing it (FFT (First Fourier Transform) is well-known as a method for executing DFT with a small number of operations. ).

【0193】

First, assuming that one sampling time of the waveform input device 232 is T, N / T = F (Equation-11) Is established. Here, if the sampling interval of the waveform input device 232 is Δt, the number of inputs and the number of outputs in DFT are equal. Δt N = T (Equation-12) However, therefore, from these two formulas, Δt = 1 / F (Equation-13) It can be seen that Δt does not depend on the number of divisions N. Then, digital waveform data for each of N sampling intervals as shown in Fig. 9. v (t) = v (i · Δt) (i = 0,1,2,3, ..., N-1) (Equation-14) Then, the spectrum L (f) for each frequency component as shown in FIG. 10 can be calculated by the following formula by the DFT formula.

【0194】

[Number 3]

<img file="JPH07124331A_D0003.tif" />(Equation-15) The method of calculating the spectrum for each frequency component based on the waveform data of the electroencephalogram described above is used in the lighting control process described later.

【0195】

Next, the lighting control process in this embodiment will be described.

【0196】

FIG. 24 is a flowchart showing the lighting control process in this embodiment.

【0197】

Hereinafter, the processing method will be described in detail according to the data flow.

【0198】

Description of step S241 When the control device 234 puts the command input device 233 in the command input waiting state and gives a command to newly input various data and assign the brightness to each consciousness level, the control device 234 proceeds to the next step S242 and does not perform the command input device 234. That is, the process proceeds to step S244 after issuing the command (the allocation of brightness to each of the previous various data and each awareness level stored in the file device 236 is also used this time).

【0199】

Description of step S242 The control device 234 puts the data input device 231 in the data input waiting state, and the user can use the delta wave, theta wave, alpha wave, and beta wave frequency bands (δmin, δmax), (θmin, θmax), (αmin, αmax). , (βmin, βmax) After inputting the maximum frequency value p (Hz) in the spectrum of the brain wave, the number of frequency divisions of the brain wave N (pieces), and the command reception standby time s (seconds), store them in the file device 236.

【0200】

Description of step S243 The control device 234 puts the data input device 231 in the input waiting state, and the user sets the illumination brightness corresponding to each consciousness level, for example. Brightness for delta wave Zero brightness (off) Brightness for theta waves Weak brightness Alpha wave brightness strong brightness Beta wave brightness High brightness Set as. Then, these data are stored in the file device 236.

【0201】

Description of step S244 The control device 234 issues a command to the arithmetic unit 237 to calculate the sampling interval Δt of the waveform input device 232 according to (Equation -13).

【0202】

Description of step S245 The control device 234 causes the waveform input device 232 to measure N brain waves at a sampling interval Δt, and the digital waveform data of the obtained brain waves v (t) = v (i · Δt) (i = 0, ..., Store N-1) in file device 236.

【0203】

Description of step S246 The control device 234 uses the digital waveform data v (i · Δt) (i = 0, ..., N-1) in the file device 236 to obtain a spectrum by frequency component according to (Equation -15) and the method described above. L (k / (Δt · N)) (k = 0, ..., N-1) is calculated by the arithmetic unit 237 and stored in the file device 236.

【0204】

Here, for convenience, L (k / (Δt N)) = L'(k) And.

【0205】

Description of step S247 The control device 234 is in the L'(k) (k = 1, ..., N-1) in the file device 236. δmin k / (Δt N) &lt;δmax Let L'(k) calculate the maximum k (that is, the maximum value in the delta wave) among the k that holds, and store it as kdelta in the file device 236.

【0206】

Description of step S248 The control device 234 is in the L'(k) (k = 1, ..., N-1) in the file device 236. θmin k / (Δt N) &lt;θmax The arithmetic unit 237 is made to calculate the k that becomes the maximum (that is, the maximum value in theta wave) in L'(k) among the k that holds, and it is stored in the file device 236 as ktheta.

【0207】

Description of step S249 The control device 234 is in the L'(k) (k = 1, ..., N-1) in the file device 236. αmin k / (Δt N) &lt;αmax Let L'(k) calculate the maximum k (that is, the maximum value in the alpha wave) in the k that holds, and store it in the file device 236 as kalpha.

【0208】

Description of step S250 The control device 234 is in the L'(k) (k = 1, ..., N-1) in the file device 236. βmin k / (Δt N) &lt;βmax Is satisfied, L'(k) is made to calculate the maximum k (that is, the maximum value in the beta wave) in the arithmetic unit 237, and it is stored in the file device 236 as kbeta.

【0209】

Description of step S251 The control device 234 causes the arithmetic unit 237 to select the largest one among L'(kdelta), L'(ktheta), L'(kalpha), and L'(kbeta), and performs the following processing.

【0210】

-When L'(kdelta) is maximum: Set the selected brightness as the brightness for delta waves.

【0211】

-When L'(ktheta) is maximum: Set the selected brightness as the theta wave brightness.

【0212】

-When L'(kalpha) is maximum: Set the selected brightness as the brightness for alpha waves.

【0213】

-When L'(kbeta) is maximum: Set the selected brightness as the brightness for delta waves.

【0214】

Description of step S252 The control device 234 switches the illumination brightness to the selected brightness in step S251.

【0215】

Description of step S253 The control device 234 puts the command input device 233 in the input waiting state for a certain period of time s, ends the lighting control process if the user sends a process end command within that time, and returns to step S245 otherwise.

【0216】

As described above, according to the present embodiment, the spectrum for each frequency component is calculated from the waveform data of the user's brain wave, and the result is used to assign the luminance to each consciousness level in advance at that time point. By selecting the brightness corresponding to the user's identification state and setting it as the lighting brightness, it is possible to provide an unprecedented lighting control device capable of adjusting the lighting brightness by accurately reflecting the user's consciousness level.

【0217】

The present invention may be applied to a system composed of a plurality of devices or a system composed of one device. Needless to say, the present invention can also be applied when it is achieved by supplying a program to a system or an apparatus.

【0218】

[Effect of the invention]

As described above, according to the electroencephalogram control device according to the present invention, there is an effect that processing according to a human state can be performed by processing and using a human electroencephalogram signal.

【0219】

[Simple explanation of drawings]

[Figure 1]

It is a figure which shows an example of the conventional game apparatus (racing game apparatus).

[Figure 2]

It is a block diagram which shows the game apparatus of 1st Example.

[Fig. 3]

It is a figure which shows the expression method of the coordinate of a pixel in an image.

[Fig. 4]

It is a flowchart of a course-related data input method.

[Fig. 5]

It is the first figure which showed the course-related data input method.

[Fig. 6]

It is the second figure which showed the course-related data input method.

[Fig. 7]

It is a figure which showed the state of the electroencephalogram input.

[Fig. 8]

It is a figure which showed the display example of the electroencephalograph.

[Fig. 9]

It is a figure which showed the A / D conversion of the waveform data of an electroencephalogram.

[Fig. 10]

It is a figure which showed the example of the spectrum by frequency component obtained by the discrete Fourier transform.

[Fig. 11]

It is a flowchart which shows the calculation of the electroencephalogram state value.

[Fig. 12]

It is a figure which showed the method of determining a new position and direction of a racing car.

[Fig. 13]

It is the figure which showed the positive-negative relationship between the rotation direction of a handle, and ρ.

[Fig. 14]

It is a flowchart which shows the generation process of a display image.

[Fig. 15]

It is a figure which showed the image cut area on the course data image.

[Fig. 16]

It is the first figure which showed the image processing method.

[Fig. 17]

It is the 2nd figure which showed the image processing method.

[Fig. 18]

It is a flowchart which shows the game processing in 1st Example.

[Fig. 19]

It is a block diagram which shows the doze prevention device of 2nd Example.

[Fig. 20]

It is a flowchart which shows the doze prevention processing of 2nd Example.

[Fig. 21]

It is a figure which showed an example of the doze prevention device using the movement of a user's head.

[Fig. 22]

It is a figure which showed an example of the doze prevention device using the movement of the steering wheel of an automobile.

[Fig. 23]

It is a block diagram which shows the lighting control device of 3rd Example.

[Fig. 24]

It is a flowchart which shows the lighting control processing of 3rd Example.

[Explanation of symbols]

1 controller, 2 Command input device, 3 data input device, 4 operation input device, 5 EEG input device, 6 Arithmetic logic unit, 7 Control unit, 8 It is a display device.