JP2007144112A - Sleep treatment apparatus, brain wave activating method using brain wave induction method, and subliminal learning system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To apply brain wave during sleep for long time by using of a brain wave induction method to the brain wave induction apparatus. <P>SOLUTION: The brain wave induction method enhances the real efficiency of the brain wave induction apparatus, and while the frequency band areas having wave lengths of 1-60 seconds for adding resting intervals are made complex to the frequency for the brain wave induction, the resting intervals and the frequency for the brain wave induction shift relatively large and repeat at the specified frequency band area corresponding to the elapsed time, and furthermore, the specified frequency band area shifts relatively small at the each repeat. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an electroencephalogram guidance system.

Devices that induce sleep are effective for sleep disorders, autonomic dysfunction, or depression. There are various induction methods by light stimulation and relaxation, and it is a system that induces to a sleepable state by releasing the tension of the living body to some extent, but it cannot directly correct and induce the electroencephalogram.
In modern psychiatric hospitals, there are few cases where these guidance devices are effectively used, and for sleep disorders, the use of neurological drugs such as sleeping pills is the mainstream, or depression or schizophrenia is used in stimulating devices. As a result, it was not possible to defer advanced science to psychiatric care because only electroshock therapy is generally performed in Japan. Therefore, with regard to the brain wave during sleep, a method and technique for effectively stimulating the brain wave for a long period of time have been required.
As ergonomic knowledge, there is 1 / f fluctuation theory which is said to affect the natural environment and human rhythm. This is said to have a healing effect due to subtle changes and deviations in the regular rhythm.

JP, 2005-292215, A High-speed learning system and storage medium for learning JP 2004-133362 A Learning system JP 2003-135767 A Japanese Patent Publication No. H06-85804 JP06-0642908 EEG Induction Device Special H07-012376 EEG induction device Special H06-026593 low frequency treatment device JP H04-347171 EEG induction device Special H07-90019 Sleep stage monitoring device JP2003-339674 SLEEP STAGE ESTIMATION DEVICE AND DEVICE USING SIGNAL OUTPUT FROM SLEEP STAGE ESTIMATION DEVICE JP H02-98368 SLEEP INDUCING DEVICE Japanese Patent Publication H05-056902 Sleep State Change Detection Device and Sleep State Control Device

  The bioelectric stimulation device and the low-frequency treatment device may not be effective when used for a long time because the monotonous mechanical pattern and rhythm may cause discomfort and fatigue.

  This problem seems to be related to systems and devices in general that interfere with human perception, but in particular, the mechanism of the device and frequencies up to 0.4Hz-48Hz that interfere with human brain waves are likely to be affected.

  In addition, it was necessary to mitigate the above problem by using 1 / f fluctuation theory for the device, but it is generally in the research stage and seems to be an incomplete theory.

  By the way, the electroencephalogram guidance apparatus solves the above problem by biofeedback the detected electroencephalogram and filtering a specific frequency band.

  In addition, in the subliminal learning system, it was necessary to devise a way to increase learning motivation and concentration by stimulating various brain waves. The same applies to the sleep introduction device. For this reason, it was considered difficult to put various therapeutic devices related to the mind and nerves into practical use.

  In other words, the conventional method cannot directly correct and correct the electroencephalogram. Therefore, various devices have to be applied to increase the completeness of electroencephalogram induction.

Accordingly, the present invention provides an electroencephalogram induction method for electroencephalogram induction and a system thereof.
The present inventors have surprisingly found a method for inducing a brain wave during sleep for a long time by using an electroencephalogram guidance method for an electroencephalogram guidance device.

That is, the present invention
An electroencephalogram induction method for increasing the actual efficiency of the electroencephalogram induction device,
A frequency band having a wavelength of 1 second to 60 seconds for adding a pause interval to a frequency for inducing brain waves is combined,
The frequency for the pause interval and the electroencephalogram induction further changes relatively in accordance with the elapsed time in a specific frequency band, and repeats.
The specific frequency band further relates to an electroencephalogram guidance method characterized in that the specific frequency band is relatively small even at each repetition.

-The therapeutic effects of bioelectric stimulation devices and low frequency treatment devices can be applied to the head for a long time.
-In the electroencephalogram induction device, the actual efficiency can be sustained for a long time. In addition, by correcting brain waves in the sleep state, it becomes possible to treat all illnesses related to the mind and nerves.
-It is possible to activate the brain as a result by performing the electroencephalogram guidance over the entire electroencephalogram band.
-It can be applied as a substitute for the conventional 1 / f fluctuation effect.
-The subliminal effect can be amplified in the subliminal system.

Specific examples of the present invention will be described below.

  FIG. 1 shows an example used in a system or the like that requires a time interval related to perception. In each step a-e and rest period f, it is shown that the interval is gradually increased in order to activate the electroencephalogram. The effect of this method is similar to the 1 / f fluctuation theory, but it is possible to reduce the stress compared to the conventional monotonous stimulus by incorporating it not only in the time interval but also in various scenes. For example, when applied to an α wave in an electroencephalogram induction device, it is considered that the actual efficiency of electroencephalogram induction is increased by changing and changing the place where only 10 Hz is normally used within a band from 8 to 13 Hz. Furthermore, it is possible to activate the brain as a result by performing the electroencephalogram guidance over the entire electroencephalogram band.

In addition, the rest interval is preferably equal to or less than the respiration rate predicted according to the electroencephalogram. Since the respiration rate per minute is generally 12 to 20 in normal times, the composite wave is 1/5 Hz to 1/3 Hz or less. Is used. In video and the like, it seems to be effective for amplifying continuous subliminal effects. As a specific example, in the learning process in the learning system, even when the pause time f continues five times due to the subliminal effect (amplification) of the learning process ae, the actual efficiency seems to be sustained. Furthermore, by implementing the above-described electroencephalogram induction, three synergistic effects such as electroencephalogram induction, subliminal effect, and 1 / f fluctuation effect (electroencephalogram induction method) can be expected. (See Example 3)

  Similarly, when the process of about 20 seconds shown in FIG. 1 is continuously repeated for 90 minutes, it is desirable to have a different change every time.

  For example, in order to bring out an effect of 20%, if the first is 20 seconds (because 20 seconds is the maximum value in the electroencephalogram induction method), 90 seconds later is 16 seconds, in proportion to the passage of time. An effect that activates the electroencephalogram can be obtained by subtle changes. The most appropriate amount of effect is that it does not change too much, is monotonous, and is not easily conscious. (See Example 7) In FIGS. 3 and 6, it is shown that the frequency band changes with each iteration.

Next, a specific example in which the electroencephalogram guidance method is used in a subliminal learning system will be described.
For example, for the purpose of learning English words, in the learning process ae shown in FIG. 1, ab is a translated sentence, c is an English word, d is an example, and e is a display of all images displayed up to ad. Do. When the English word is “speed”, a and b are “speed, speed, and quick”, c is “speed”, d is “speed up speed increases”, and e is all of these.

  Here, ab is the first stage for displaying the associative source image, cd is the second stage for displaying the associative destination image and its additional information, e is a display for review, and each of these steps Is to amplify the subliminal effect by providing the pause time f.

  Further, in the learning step a-d, brain wave induction is performed by blinking the background together with the image display.

  As long as the format of the image can be expressed, it can be an image in addition to a character string, or it can be added with sound, and when there are multiple association source images or association destination images for one learning image May be continuously displayed in synchronism with the electroencephalogram induction frequency.

  The learning system according to the above is also possible by a general method. However, it is necessary to give subtle changes to the a-f time and the electroencephalogram frequency little by little because it is easy to get bored with a monotonous rhythm only by repeating these learning processes. It is possible with the 1 / f fluctuation theory, but especially in the EEG guidance method, the learning process ab is for recognizing an image, and the learning process cd is for learning. Should be decided. That is, regardless of the order of the process ae of one learning image, the learning process cd is at least in the middle of the alpha wave with the highest wavelength, and the learning process ab is for transitioning to a lower wavelength. It seems to be more appropriate as a learning effect. At this time, the relational expression between each process and the frequency becomes c> d> e> a> b, but especially e may be ignored because it is a review process.

  In addition, when determining the frequency for inducing brain waves, the use of θ waves may make you sleepy. Therefore, it is possible to use the δ wave or the α wave low band instead, but this problem can be avoided if the user sufficiently sleeps. Further, there is a problem that flickering occurs depending on the specifications of the display terminal.

FIG. 2 is an example of a waveform of an electroencephalogram induction method, and shows a composite wave of an electroencephalogram and an electroencephalogram induction execution time. In the subliminal learning system, the non-execution time of the electroencephalogram induction also serves as an amplification of the subliminal effect.

  The following is a description of problems in conducting brain wave guidance during sleep and the brain wave guidance system.

  The state of brain waves during sleep from sleep to wake up is a stage where deep sleep and shallow sleep are repeated about 5 times, and one stage takes about 90 minutes, and REM sleep for shallow sleep Non-REM sleep for deep sleep is configured at a ratio of about 1: 4, and in the REM sleep stage that appears during stage repetition, physical activity increases rapidly, and the respiratory rate increases with EEG in general Known to.

  In mental illness, recovery may be delayed or worsened due to poor sleep state, which may contribute to the etiology. It is considered that treatment can be performed by correcting the transition of the electroencephalogram during sleep to a normal range using the device.

  Specifically, it is necessary to devise an ergonomic rhythm for the pulse wave for brain wave induction, not only using the frequency for stimulating the brain wave.

  Now, an ergonomic rhythm is shown as a specific example.

  First, regarding the duration of EEG induction, if the pause time is fixed or if there is no pause time, it may be perceived as an unbearable rhythm immediately after EEG induction begins, and the 1 / f fluctuation theory is used. Even if it exists, the effect required for ideal sleep induction cannot be obtained because it is theoretically incomplete in the first place.

  Therefore, the interval between EEG induction pauses is determined by combining frequencies that are less than or equal to the approximate value of the respiratory rate that is related to the EEG frequency. The execution time of the electroencephalogram induction becomes more fatigued as the frequency for the electroencephalogram becomes higher. Therefore, the execution interval should be determined so as not to cause continuous stimulation in addition to the above condition of the respiration rate or less. In addition, the respiratory rate during sleep is about 0.2 Hz during non-REM sleep and about 0.4 Hz during REM sleep, but it can be further reduced to 1/2 if it is applied to each of EEG induction time and rest time. good. (See Example 7)

  Next, problems during non-REM sleep are shown.

  In general, the average ratio of REM sleep to non-REM sleep is about 1: 4, but in REM sleep, REM sleep suddenly starts from the deepest sleep state of non-REM sleep. The sleep induction time must actually vary. Rather, in non-REM sleep, it is desirable that the effect amount of electroencephalogram induction be minimized and taken longer to induce REM sleep naturally.

  In addition, at the start of EEG induction of REM sleep, there is a possibility of sleep disturbance due to random timing. Therefore, it is possible to ergonomically reduce the transition of the previous electroencephalogram frequency by inheriting it directly to the pause interval or the composite wave. That is, since the brain wave immediately before REM sleep is about 0.5 Hz (delta wave low band), the frequency for the composite wave immediately after REM sleep is preferably about 0.5 Hz or about 0.25 Hz.

  Therefore, it can be considered that the brain wave induction during substantial REM sleep may be 1: 7 ± 2 assuming the first half of the lag.

In addition, as the sleep time elapses, the arousal level gradually increases, so the transition of the electroencephalogram frequency and the respiratory frequency must increase as a whole.
FIG. 3 shows the transition of the dominant brain wave for actually inducing the brain wave during sleep and the pause interval, and the band of the pause interval is about 0.01-0.3 Hz.

  An electroencephalogram treatment apparatus may be accompanied by peculiar fatigue by using it too frequently. This is the same for music, as if you get tired of listening to the same music every day.

  Therefore, in order to prevent the sleep effect from remarkably deteriorating, it is necessary to incorporate a slightly different change from day to day and refrain from daily use.

  Tables 1 and 2 below show the EEG start point frequency, EEG arrival frequency, pause interval start point frequency, pause interval end point frequency, stage time (REM Sleep time).

The electroencephalogram induction uses a frequency determined by an electroencephalogram induction method, but the means should not specify any one of electrical stimulation, optical stimulation, and acoustic stimulation.
For example, in an electroencephalogram treatment apparatus, the electroencephalogram induction medium and the part to be applied to the human body should be determined according to the symptom and diseased part within the effective range of the electroencephalogram induction apparatus, and head and light stimulation induction are not necessarily suitable. Considering the case of chronic diseases and neurological symptoms, it can be recovered from an abnormal state by performing it around the most suitable living body part.

  Moreover, since the response of the light stimulus to the living body is slow, the actual efficiency seems to be significantly reduced when the frequency becomes a high frequency such as a β wave.

  By the way, there are α waves, β waves, and γ waves in the brain wave at the time of awakening.・ It is generally known that the situation is frustrating.

  Among them, the γ wave has the highest arousal level. Therefore, when waking up, it is possible to activate the electroencephalogram as a result by stimulating all the way up to γ wave to α wave. FIG. 6 shows an execution interval for activating the electroencephalogram when the electroencephalogram is about 47.8 Hz-7.4 Hz and the frequency for the respiration rate is about 0.4-0.1 Hz. (In addition, the overall frequency decreases with each iteration, and the highest value after 3 minutes is because the frequency transition is repeated.)

  In an actual electroencephalogram induction device, the characteristics and voltage used of each means are different. Therefore, when the electroencephalogram induction device is directly controlled by a pulse wave from a computer, it is necessary to devise the waveform or pulse width.

  Next, points to be noted when using each means will be described.

  1. The treatment site when electrical stimulation is used for electroencephalogram induction seems to be effective on the neck and back, or the nasal bone and its surroundings. The effect of attaching the conductors symmetrically to the human body is relatively low. Since the effective voltage of electrical stimulation is 40 volts ± 20 volts, a bias voltage of about 20 volts is added, or 1/3 of the maximum output is added to the height of the waveform. The pulse width is 100 ± 50 μsec. The actual efficiency of EEG induction is the highest.

  2. The effect of light stimulation may be low because it cannot be seen that the high frequency of the β wave or higher is blinking. At low frequencies, the effect is almost lost when the light lighting time is constant, so the lighting time must be determined from the ratio to the rest time. When using an LED, the effective voltage is about 4 ± 2 volts, so a bias voltage of about 2 volts is added, or 1/3 of the maximum output is added to the height of the waveform. The actual efficiency of EEG induction is the second highest if it is less than β waves.

  3. When sonic stimulation is used for brain wave induction, one pulse wave corresponds to two sound wave waveforms, and therefore, a half pulse wave or a sawtooth wave is used. Other than that, there is a method of generating an interference frequency within an effective electroencephalogram induction range by causing interference between two different relatively high frequencies. This method can also be realized by program software of a general-purpose computer. Moreover, it is appropriate that the sound volume is about the ambient sound.

  4). Light flashing stimulation using a display terminal is generally designed to have a display update frequency of around 60 Hz, so that there is a problem that flickering occurs depending on the frequency for flashing in the background. To solve this problem, select the frequency list that is divisible from the update frequency (30, 20, 15, 12, 10, .. for 60Hz) and the one closest to the frequency required for EEG induction. There is a way. As other methods, it is necessary to tune the update frequency itself as in the ninth embodiment or to provide a separate electroencephalogram induction device.

(The artificial intelligence system (extended) shown below is a medium for performing data analysis and calculation, and is a construction method that can be reproduced on a computer. Is also feasible.)

  FIG. 4 is a method for calculating effective brain wave guidance from the change in dominant brain waves necessary for the living body in brain wave guidance. When the artificial intelligence system learns, the relationship between the brain wave and the time axis is actually easy to understand. Each process is shown in FIG.

  First, input the change a of the dominant brain wave over time within a range that can be understood from general knowledge, and make up the unclear part by connecting the dominant brain waves before and after smoothly with a curve to create a prototype b of the brain wave induction pattern .

  Next, the electroencephalogram guidance device is tried during sleep, and when there is discomfort or awakening during this time, the time d1 is recorded as failure information d, and the wavelength at that time is changed and the process is temporarily terminated. Furthermore, when failure information d2 is generated by the next trial, the wavelength is appropriately changed to d1 if it is earlier than failure information d1, and to d2 if it is later. By repeating this method, it is possible to induce a change in dominant brain wave that is necessary for the living body for a long time.

  In addition, the electroencephalogram immediately after waking up is still asleep, and a final induction step with a wavelength level higher than the α wave should be provided in order to promote an appropriate arousal state. In the final induction stage, it is desirable that γ waves, β waves, and α waves are stimulated uniformly.

  In addition, continuous stimulation of the brain wave by the brain wave guidance device causes a burden on the nerve and causes discomfort, so this problem can be solved by providing a resting time in synchronization with the interval of breathing movement so as not to cause much stress. It is necessary to avoid it. More strictly speaking, if the breathing motion cannot be predicted, an interval equal to or less than the breathing rate is used. FIG. 6 shows an execution interval for activating the electroencephalogram by uniformly performing electroencephalogram induction when waking up. During sleep, it must also be considered that breathing and heart rate change greatly during REM sleep and non-REM sleep. FIG. 7 shows the transition of the electroencephalogram and the pause interval actually derived using this method.

  When using the artificial intelligence system using the above method, after learning the dominant brain wave during sleep and its time from the subject at the basic system stage, it moves to the artificial intelligence system expansion type and actually If the subject feels uncomfortable or awakens during guidance using the guidance device, the switch such as a push button is expanded as guidance failure information (which is considered to be an action error in brain wave observation and brain wave guidance). It must be self-correcting in preparation for the observation equipment on the side. Further, when learning sufficient for prediction is completed, it is possible to simulate one or more types of long-term ideal electroencephalogram guidance patterns, and the system can be shifted to a small computer with a simplified system.

Further, in order to further improve the guidance accuracy, for example, there is a method of adjusting the actual efficiency disparity due to individual differences in advance by adding attribute information for each subject such as age, average sleep time, and usage frequency to the learning element. is there.

  The appropriate rest interval of EEG induction is originally best synchronized with the biorhythm of the human body, so instead of simulating the respiratory frequency and EEG transition, a means to detect the respiratory rate (or respiratory movement) It is more desirable to use to predict the most appropriate electroencephalogram. In addition, since it is possible to predict the timing at which REM sleep starts from the detected respiratory rate, by incorporating this into the electroencephalogram treatment apparatus, for example, a method without the lag of Example 4 is also possible. It is done.

  In multimedia, it is produced based on a frequency that humans can perceive. For example, in the case of movie film, 24 Hz, and in the case of music, if the quarter note is 1 second, the 32nd note is 8 Hz.

  However, it can be said that the actual update interval slightly exceeds the perceivable range because it is difficult to withstand flicker and fatigue when the frequency is close to the electroencephalogram. This is because the brain wave is temporarily corrected by interfering with the brain wave, but the update frequency is constant, resulting in fatigue.

  As another method for preventing interference with the electroencephalogram, it is also possible to synchronize (feed back) the dominant electroencephalogram with the detected electroencephalogram (electroencephalogram filter). For example, in the case of a television set, it is possible to achieve power saving and high luminance by detecting and synchronizing a dominant brain wave where it is currently updated at 60 Hz. In the case of classical music as well, it seems that there is a relaxation effect by changing the tempo appropriately to bring about changes in the brain waves.

  In addition, there is a problem that it is theoretically difficult to completely synchronize the low frequency with the electroencephalogram (biofeedback). Therefore, for example, when a dominant brain wave is detected every other minute, an intermediate technical method that encompasses human perception and theoretical synchronization by using a brain wave induction method to widen the frequency band. Is the method. For example, when the dominant electroencephalogram is 10 Hz, it has an update frequency that changes at 11-9 Hz using the electroencephalogram guidance method.

  A device using this technical method is useful not only for a display terminal having an update frequency but also for detecting a dominant brain wave with a music playback device or the like to change the playback speed. Moreover, it can also be used for an artificial vision device that converts an image into sound waves for obtaining from the auditory sense.

  The artificial perception apparatus receives the “conversion source information” on the video screen, performs the “conversion to frequency band” process, and outputs the “sound wave waveform”, thereby obtaining video information from the auditory sense.

  The feature of the present invention is mainly a conversion processing method, which is an artificial visual device that is applied to an internal program of a computer, and an artificial hearing device that can obtain sound wave information from vision by reversing the flow of the processing There is.

Therefore, the present invention provides a waveform conversion algorithm and an apparatus thereof that have the effects of the invention by acquiring a video screen, converting it to a low-frequency-high frequency (formula AC), and outputting it. Specifically, a waveform (1/20 milliseconds = 20 kHz, 1 millisecond = 1 kHz) with a high frequency corresponding to the color information in FIG. 10 is generated and output, and the number of the color information in FIG. Correspondingly, continuous processing is performed at a mid-range frequency (about 120 Hz in the case of 0.1 / 12 seconds) assuming the pitch (16-1.6 kHz) in FIG. 11 and is actually applied to an artificial visual device. The update interval is set as a low frequency (0.1 second = 10 Hz).

(Formula A) Low frequency ≒ EEG band for perception (0.5-48Hz, preferably 4-23Hz)
(Formula B) Mid frequency ≒ Band for pitch (16-1.6kHz)
(Formula C) High frequency <audible band (20-20KHz)

  Further, in the waveform conversion for a single color at a high frequency shown in FIG. 10, the saturation is generated as the number of waves, the hue is generated as the level of the wave (strength), and the first part of the waveform height is according to the lightness It is possible to generate only with a specific saturation or hue, and furthermore, the three elements for waveform conversion should not specify color information or color space, but human beings. This is because it should be determined engineeringly, and color space cannot be said to be in a complete research stage. This waveform conversion corresponds to waveform synthesis by an oscillator and its filter in a synthesizer, or a pedal portion of a piano.

  The reason why the middle frequency is a band having a change in pitch is to devise color information (especially the horizontal axis position) to make it easier to perceive, and the low frequency is just an update interval. Therefore, it can be said that the core part of the present invention is a waveform conversion method for converting color information into a waveform at a high frequency.

  Waveform conversion in the artificial visual device is, for example, if the color information is 12 on both the left and right sides, the mid-range frequency is 12 gradations. If the deviation difference at this time is doubled, it becomes 12 scales for one octave just like a keyboard.

  By the way, the synthesizer is a device that synthesizes and outputs a frequency of a pitch corresponding to 12 scales, but has a function that can perform timbre processing in addition to automatic performance and sound intensity. Specifically, the timbre is determined by synthesizing a waveform that is an element of the timbre with the frequency of the pitch. In other words, even if an arbitrary waveform is synthesized with a frequency of 16-1.6 kHz used for the pitch, it can be devised so as not to affect the pitch. This kind of tone processing can be obtained in the same way by pressing a piano pedal.

  Now, in the artificial visual apparatus, the sound and the timbre can be discriminated in this way, thereby converting the sound into an audible sound wave. For example, when converting the color information for 8 dots on the video screen into sound, the player plays in order from the sound of the sound to the sound one octave above (assuming the black keyboard is ignored).

  At this time, Doremifasolaside corresponds to eight pieces of color information. Furthermore, the intensity of the sound changes according to the hue, and can be expressed by making it as small as pianissimo if it is blue, or as strong as an accent if it is white or yellow. The timbre processing described above can be used to express brightness, saturation, and the like. Specifically, a waveform that can be synthesized as a timbre is generated at a high frequency, and the waveform is output based on the frequency for the pitch. That is, the output of the middle frequency is not simply a sine wave or a pulse wave, but an output interval of a waveform generated by a high frequency. (For example, if only lightness such as a monochrome image is converted instead of hue and tone, it is not necessary to generate a waveform with a high frequency.)

In the same way, it means an update interval for the above-described conversion process even at a low frequency. For example, it is a frequency for continuously converting video to sound waves by providing an update interval of 60 Hz as in a television.
Therefore, the relational expression 1-2 on the time axis of each frequency is theoretically established. For example, if the mid-frequency is a 12-tone (12) keyboard, the low-frequency must be at least the required length x 12 times to distinguish one pitch, and this is converted to frequency (Hertz) Then, formula 1 is inevitably established. The relational expression between the middle frequency and the high frequency can be expressed by Equation 2.

(Formula 1) Low frequency ≤ Average value of mid frequency ÷ Number of color information (Formula 2) Maximum value of mid frequency ≤ High frequency ÷ Maximum value of brightness (resolution)

  That is, the number of color information can be added by lowering the low frequency and resolution. Actually, it is necessary to set the update interval low in order to convert more color information in consideration of the audible range, and it seems that the α wave low range of the electroencephalogram is suitable as an artificial perception device. In addition, convenience is enhanced by automatically increasing or decreasing according to the situation. In the future, users will be able to hear the scales in a capacity-like manner (like a musician), so the conversion range is expanded by including the vertical axis so that the keyboard increases by one octave. It can be expected that the visual information can be recognized.

The artificial hearing device is an inverse application of the waveform conversion algorithm of the present invention. In other words, if the law for converting light to sound waves is ergonomic based on artificial intelligence reasoning, it can be reversibly adapted to other uses.
In addition, an artificial hearing device specialized in the formant frequency for analyzing voiceprints is considered to be able to distinguish human voices from information obtained from vision.

For example, in order to display 12 full-color LEDs, the pitch of 12 gradations is analyzed from the input sound wave. At this time, since human perception is low frequency, the information of the dimension which was not heard at all appears in front of the eye by updating it with the frequency of the low band and further corresponding to the left and right sound waves. If a total of 24 full-color LEDs are attached to the edge of the glasses, it is expected that it will be closer to practical use, but it may be a color liquid crystal screen. (In a CPU medium with low waveform analysis accuracy, it is necessary to omit waveform analysis at high frequencies and replace the hue of the mid frequency with lightness.)
In addition to the method using a spectrum analyzer and an oscilloscope, there is a method for realizing the analysis method by calculating from sound data using a computer. For example, it can be calculated as a wavelength component from the number of waves included in a certain time, an average value, and a total value. In the color output stage, it is desirable to convert to an ergonomic color space, for example, Munsell color space.

  Since the low frequency for the update interval shown in Example 11-12 is based on the brain wave, if the low frequency is modulated in order to detect and synchronize the dominant brain wave, the brain wave of the user is obtained. Accordingly, the most appropriate low frequency can be derived.

  In addition, as this related technology, there is an electroencephalogram guidance device that filters a detected electroencephalogram with a specific frequency for an α wave, and performs bioconversion by optical conversion. In other words, it is considered technically possible to apply biofeedback technology and an electroencephalogram guidance method for activating electroencephalogram to the update interval of the artificial visual device and the artificial auditory device.

The electroencephalogram guidance method can be used by being used in a system and apparatus that require a time interval related to perception.

It is a conceptual diagram of the element in a subliminal learning system. It is a composite waveform diagram of an electroencephalogram frequency and a respiratory frequency. It is a transition figure of the rest interval by the electroencephalogram in a sleep treatment device, and a compound wave. It is a line diagram showing a method for calculating EEG during sleep. It is a conceptual diagram of the element in a subliminal learning system. This is an execution interval for activating the electroencephalogram. It is an imaginary view of an artificial visual device. It is an imaginary view of a handy type artificial visual device. It is the figure which showed the state of the conversion range in a video screen. It is a figure which converts color information into the waveform of a high frequency band. It is a figure of the modulation frequency of the mid range distributed to right and left.

Explanation of symbols

10 Subliminal learning system
11 Dictionary database
12 EEG induction (and EEG activation method)
13 Subliminal effect
14 1 / f fluctuation effect (and EEG activation method)
20 Image learning (by subliminal display and electroencephalograph)
21 Data selection (learned input, reset, and split dictionary database)
DESCRIPTION OF SYMBOLS 1 Main body 2 Small camera 3 Small speaker 4 Pointing device 5 Pad 6 Small terminal device 010 Video screen 011 Waveform conversion range 012 Center of waveform conversion range AC Color information arranged on the left side ac Color information arranged on the right side

The present invention relates to an electroencephalogram induction method, a sleep treatment apparatus, a subliminal learning system, and an electroencephalogram activation method.

Devices that induce sleep are effective for sleep disorders, autonomic dysfunction, or depression. There are various induction methods by light stimulation and relaxation, and it is a system that induces a state where it is possible to sleep by releasing the tension of the living body to some extent .
However, in modern psychiatric hospitals, there are few cases where these induction devices are used effectively, and the use of nervous system drugs such as sleeping pills is the mainstream for sleep disorders, or depression or schizophrenia is used in stimulating devices. As a result, it is not possible to say that advanced science is obsessed with psychiatric treatment , especially for electroencephalograms during sleep. method of inducing, and the technology Ru required der. _
As ergonomic knowledge, there is 1 / f fluctuation theory which is said to affect the natural environment and human rhythm. This is said to have a healing effect due to subtle changes and deviations in the regular rhythm.

JP, 2005-292215, A High-speed learning system and storage medium for learning JP 2004-133362 A Learning system JP 2003-135767 A Japanese Patent Publication No. H06-85804 JP06-0642908 EEG Induction Device Special H07-012376 EEG induction device Special H06-026593 low frequency treatment device JP H04-347171 EEG induction device Special H07-90019 Sleep stage monitoring device JP2003-339674 SLEEP STAGE ESTIMATION DEVICE AND DEVICE USING SIGNAL OUTPUT FROM SLEEP STAGE ESTIMATION DEVICE JP H02-98368 SLEEP INDUCING DEVICE Japanese Patent Publication H05-056902 Sleep State Change Detection Device and Sleep State Control Device Japanese Patent Laid-Open No. 2005-87572

  The bioelectric stimulation device and the low-frequency treatment device may not be effective when used for a long time because the monotonous mechanical pattern and rhythm may cause discomfort and fatigue.

This problem seems to be due to the fact that the frequency of 0.4Hz-48Hz vaguely induces the frequency tracking response of the brain in the internal period of the system and device that affects human perception.

In addition, it was necessary to alleviate the above problem by using 1 / f fluctuation theory for the device, but this is generally an incomplete theory at the research stage , and it has obtained sufficient effects in the technical field of electroencephalogram induction. It is not done.

In other electroencephalogram guidance apparatuses, bio-feedback of the detected electroencephalogram is attempted , and a specific frequency band is filtered to solve the above problem .

In addition, in the subliminal learning system, devices for introducing sleep are also applied to mental nerves such as sleep disorders for the same reason, as it is necessary to devise ways to increase learning motivation and concentration by stimulating various brain waves. It is difficult to obtain various therapeutic effects.

  In other words, the conventional method cannot directly correct and correct the electroencephalogram. Therefore, various devices have to be applied to increase the completeness of electroencephalogram induction.

Therefore, the present invention provides an electroencephalogram induction method, a sleep treatment apparatus using the electroencephalogram induction method, a subliminal learning system, and an electroencephalogram activation method .
Surprisingly, the inventor of the present invention is similar to 1 / f fluctuation by adding the EEG-induced frequency transition and the change in each repetition to the internal period of the electroencephalogram guidance device and the device acting on human perception. It was found that the effect can be obtained.

That is, the present invention
In a device that affects human perception,
An electroencephalogram activation method applied to an internal cycle to activate an arbitrary electroencephalogram band of a user,
The frequency of EEG induction is a means of repeating at least one type of EEG band from δ wave, θ wave, α wave, β wave, γ wave,
A means for taking into account the rest period using a respiratory cycle corresponding to maintaining the affinity to the human body for the electroencephalogram induction, or a cycle less than that,
Means for taking into account the change in the electroencephalogram band so that the frequency change path of the electroencephalogram induction is different for each iteration,
EEG activation method characterized by comprising
About.

-The therapeutic effects of bioelectric stimulation devices and low frequency treatment devices can be applied to the head for a long time.
-In the electroencephalogram induction device, the actual efficiency can be sustained for a long time. In addition, by correcting brain waves in the sleep state, it becomes possible to treat all illnesses related to the mind and nerves.
-It is possible to activate the brain as a result by performing the electroencephalogram guidance over the entire electroencephalogram band.
-It can be applied as a substitute for the conventional 1 / f fluctuation effect.
-The subliminal effect can be amplified in the subliminal system.

Specific examples of the present invention will be described below.

FIG. 1 shows an example used in a system or the like that requires a time interval related to perception. In each step ae and rest period f, it is shown that the interval is gradually increased to activate the electroencephalogram. The effect of this method is to similar to 1 / f fluctuation theory, not only the time interval, by applying against various configurations according to the brain wave inducing psychological stress compared to conventional monotonous stimuli Can be reduced. For example, when applied to the α wave of an electroencephalogram guidance device , it is considered that the actual efficiency of electroencephalogram induction is increased by changing the transition of the α wave from 8 to 13 Hz in the entire band , where 10 Hz is normally used repeatedly. Furthermore, it is possible to activate the brain as a result by performing the electroencephalogram guidance over the entire electroencephalogram band.

In addition, the rest interval is preferably the respiration rate predicted according to the electroencephalogram or less , and since the respiration rate per minute is generally 12 to 20 in normal times, the composite wave is from 1/5 Hz. Use 1 / 3Hz or less.
Also, this effect seems to be effective for amplifying a continuous subliminal effect due to an image or the like . As a specific example, in the learning process in the learning system, even when the pause time f is continued five times due to the subliminal effect (amplification) of the learning process ae, the actual efficiency is maintained and the above-described brain wave induction is further performed. By doing so, we can expect three synergistic effects of brain wave induction and 1 / f fluctuation similar effect. _ (See Example 3)
In other words, the affinity for the human body is maintained by adding transition intervals and pause intervals based on the respiratory cycle to the EEG induction frequency, and the EEG induction effect can be improved by changing the transition path at each iteration. It can last for a long time.

  Similarly, when the process of about 20 seconds shown in FIG. 1 is continuously repeated for 90 minutes, it is desirable to have a different change every time.

  For example, in order to bring out an effect of 20%, if the first is 20 seconds (because 20 seconds is the maximum value in the electroencephalogram induction method), 90 seconds later is 16 seconds, in proportion to the passage of time. An effect that activates the electroencephalogram can be obtained by subtle changes. The most appropriate amount of effect is that it does not change too much, is monotonous, and is not easily conscious. (See Example 7) In FIGS. 3 and 6, it is shown that the frequency band changes with each iteration.

Next, a specific example in which the electroencephalogram guidance method is used in a subliminal learning system will be described.
For example, for the purpose of learning English words, in the learning process ae shown in FIG. 1, ab is a translated sentence, c is an English word, d is an example, and e is a display of all images displayed up to ad. Do. When the English word is “speed”, a and b are “speed, speed, and quick”, c is “speed”, d is “speed up speed increases”, and e is all of these.

  Here, ab is the first stage for displaying the associative source image, cd is the second stage for displaying the associative destination image and its additional information, e is a display for review, and each of these steps Is to amplify the subliminal effect by providing the pause time f.

  Further, in the learning step a-d, brain wave induction is performed by blinking the background together with the image display.

  As long as the format of the image can be expressed, it can be an image in addition to a character string, or it can be added with sound, and when there are multiple association source images or association destination images for one learning image May be continuously displayed in synchronism with the electroencephalogram induction frequency.

The learning system according to the above is also possible by a general method. However, simply repeating these learning steps makes it easy to get tired of the monotonous rhythm, so it is necessary to give subtle changes to the af time and the electroencephalogram frequency little by little. It is possible with 1 / f fluctuation theory, but in the present invention, it specializes in the electroencephalogram induction action, the learning process ab is for recognizing the image, and the learning process cd is for learning, so depending on the occasion Therefore, the frequency band of the electroencephalogram should be determined. That is, regardless of the order of the process ae of one learning image, the learning process cd is at least in the middle of the alpha wave with the highest wavelength, and the learning process ab is for transitioning to a lower wavelength. It seems to be more appropriate as a learning effect. At this time, the relational expression between each process and the frequency becomes c>d>e>a> b, but especially e may be ignored because it is a review process.

  In addition, when determining the frequency for inducing brain waves, the use of θ waves may make you sleepy. Therefore, it is possible to use the δ wave or the α wave low band instead, but this problem can be avoided if the user sufficiently sleeps. Further, there is a problem that flickering occurs depending on the specifications of the display terminal.

FIG. 2 is an example in which a half sine wave is combined with the electroencephalogram induction, and shows the implementation time of the electroencephalogram induction and its pause interval . In the subliminal learning system, the pause interval also serves as an amplification of the subliminal effect.

  The following is a description of problems in conducting brain wave guidance during sleep and the brain wave guidance system.

  The state of brain waves during sleep from sleep to wake up is a stage where deep sleep and shallow sleep are repeated about 5 times, and one stage takes about 90 minutes, and REM sleep for shallow sleep Non-REM sleep for deep sleep is configured at a ratio of about 1: 4, and in the REM sleep stage that appears during stage repetition, physical activity increases rapidly, and the respiratory rate increases with EEG in general Known to.

  In mental illness, recovery may be delayed or worsened due to poor sleep state, which may contribute to the etiology. It is considered that treatment can be performed by correcting the transition of the electroencephalogram during sleep to a normal range using the device.

  Specifically, it is necessary to devise an ergonomic rhythm for the pulse wave for brain wave induction, not only using the frequency for stimulating the brain wave.

  Now, an ergonomic rhythm is shown as a specific example.

  First, regarding the duration of EEG induction, if the pause time is fixed, or if there is no pause time, it may be perceived as an unbearable rhythm immediately after the start of EEG induction, and the 1 / f fluctuation theory is used. Even if it exists, the effect required for ideal sleep induction cannot be obtained because it is theoretically incomplete in the first place.

Therefore, the interval between EEG induction pauses is determined by combining frequencies that are less than or equal to the approximate value of the respiratory rate that is related to the EEG frequency. Since the duration of EEG induction becomes more fatigued as the frequency for EEG increases, the interval should be determined so that it does not result in continuous stimulation in addition to the above conditions of the respiratory cycle or less. It is. In addition, the respiratory cycle during sleep is about 0.2 Hz during non-REM sleep and about 0.4 Hz during REM sleep. good. (See Example 7)

  Next, problems during non-REM sleep are shown.

In general, the average ratio of REM sleep to non-REM sleep is about 1: 4, but in REM sleep, it starts suddenly from the deepest sleep state of non-REM sleep. This time lag must be assumed so that the sleep induction time actually fluctuates. That means
In non-REM sleep, it is desirable to take a longer interval between EEG induction pauses and induce REM sleep naturally.

Moreover, at the time of starting REM sleep induction, a random change in the electroencephalogram induction period may impair the affinity to the human body and cause sleep disturbance. For this reason, it is possible to reduce psychological stress ergonomically and maintain affinity by inheriting the transition of the previous electroencephalogram frequency as it is in the pause interval or the composite wave. That is, since the electroencephalogram immediately before REM sleep is about 0.5 Hz (delta wave low range), it is preferable that the pause interval at the start of REM sleep starts from about 0.5 Hz to about 0.25 Hz.

Thus, brain wave-inducing at the time of real REM sleep is assumed to the first half of the time lag, 1: 7 can be considered to be a ± 2 any good.

In addition, as the sleep time elapses, the arousal level gradually increases, so the transition of the electroencephalogram frequency and the respiratory frequency must increase as a whole.
In other words, in order to change the electroencephalogram induction and the respiratory cycle to change differently at each repetition, the frequency of δ wave induction immediately before REM sleep and the frequency of the pause interval immediately after REM sleep are approximated and δ wave induction By taking the pause interval longer than the respiratory cycle, the affinity of brain wave induction is maintained for each sleep stage repetition, and the sleep interval is specialized.
FIG. 3 shows the transition of the dominant brain wave for actually inducing the brain wave during sleep and the pause interval, and the band of the pause interval is about 0.01-0.3 Hz.

  An electroencephalogram treatment apparatus may be accompanied by peculiar fatigue by using it too frequently. This is the same for music, as if you get tired of listening to the same music every day.

  Therefore, in order to prevent the sleep effect from remarkably deteriorating, it is necessary to incorporate a slightly different change from day to day and refrain from daily use.

The following Table 1 and Table 2 show the state of each frequency and the induction time of non-REM sleep and REM sleep at every hour of stage repetition on the 1st and 7th days.

The electroencephalogram induction uses a frequency determined by an electroencephalogram induction method, but the means should not specify any one of electrical stimulation, optical stimulation, and acoustic stimulation.
For example, in an electroencephalogram treatment apparatus, the electroencephalogram induction medium and the part to be applied to the human body should be determined according to the symptom and diseased part within the effective range of the electroencephalogram induction apparatus, and head and light stimulation induction are not necessarily suitable. Considering the case of chronic diseases and neurological symptoms, it can be recovered from an abnormal state by performing it around the most suitable living body part.

  Moreover, since the response of the light stimulus to the living body is slow, the actual efficiency seems to be significantly reduced when the frequency becomes a high frequency such as a β wave.

  By the way, there are α waves, β waves, and γ waves in the brain waves at awakening. Of these, α waves are in a relaxed and concentrated state, β waves are in a normal living state or in a killed state, and γ waves are excited.・ It is generally known that the situation is frustrating.

  Among them, the γ wave has the highest arousal level. Therefore, when waking up, it is possible to activate the electroencephalogram as a result by stimulating all the way up to γ wave to α wave. FIG. 6 shows an execution interval for activating the electroencephalogram when the electroencephalogram is about 47.8 Hz-7.4 Hz and the frequency for the respiration rate is about 0.4-0.1 Hz. (In addition, the overall frequency decreases with each iteration, and the highest value after 3 minutes is because the frequency transition is repeated.)

  In an actual electroencephalogram induction device, the characteristics and voltage used of each means are different. Therefore, when the electroencephalogram induction device is directly controlled by a pulse wave from a computer, it is necessary to devise the waveform or pulse width.

The waveform using the frequency of brain wave induction including the respiration rate in the present invention may not be a strict pulse wave or sine wave. Next, points to be noted when using each means will be described.

  1. The treatment site when electrical stimulation is used for electroencephalogram induction seems to be effective on the neck and back, or the nasal bone and its surroundings. The effect of attaching the conductors symmetrically to the human body is relatively low. Since the effective voltage of electrical stimulation is 40 volts ± 20 volts, a bias voltage of about 20 volts is added, or 1/3 of the maximum output is added to the height of the waveform. The pulse width is 100 ± 50 μsec. The actual efficiency of EEG induction is the highest.

  2. The effect of light stimulation may be low because it cannot be seen that the high frequency of the β wave or higher is blinking. At low frequencies, the effect is almost lost when the light lighting time is constant, so the lighting time must be determined from the ratio to the rest time. When using an LED, the effective voltage is about 4 ± 2 volts, so a bias voltage of about 2 volts is added, or 1/3 of the maximum output is added to the height of the waveform. The actual efficiency of EEG induction is the second highest if it is less than β waves.

  3. When sonic stimulation is used for brain wave induction, one pulse wave corresponds to two sound wave waveforms, and therefore, a half pulse wave or a sawtooth wave is used. Other than that, there is a method of generating an interference frequency within an effective electroencephalogram induction range by causing interference between two different relatively high frequencies. This method can also be realized by program software of a general-purpose computer. Moreover, it is appropriate that the sound volume is about the ambient sound.

  4). Light flashing stimulation using a display terminal is generally designed to have a display update frequency of around 60 Hz, so that there is a problem that flickering occurs depending on the frequency for flashing in the background. To solve this problem, select the frequency list that is divisible from the update frequency (30, 20, 15, 12, 10, .. for 60Hz) and the one closest to the frequency required for EEG induction. There is a way. As other methods, it is necessary to tune the update frequency itself as in the ninth embodiment or to provide a separate electroencephalogram induction device.

(The artificial intelligence system shown below is a medium for data analysis and calculation, and is a construction method that can be reproduced on a computer. In practice, it can be realized without the artificial intelligence system by following the steps below. .)

  FIG. 4 is a method for calculating effective brain wave guidance from the change in dominant brain waves necessary for the living body in brain wave guidance. When the artificial intelligence system learns, the relationship between the brain wave and the time axis is actually easy to understand. Each process is shown in FIG.

  First, input the change a of the dominant brain wave over time within a range that can be understood from general knowledge, and make up the unclear part by connecting the dominant brain waves before and after smoothly with a curve to create a prototype b of the brain wave induction pattern .

  Next, the electroencephalogram guidance device is tried during sleep, and when there is discomfort or awakening during this time, the time d1 is recorded as failure information d, and the wavelength at that time is changed and the process is temporarily terminated. Furthermore, when failure information d2 is generated by the next trial, the wavelength is appropriately changed to d1 if it is earlier than failure information d1, and to d2 if it is later. By repeating this method, it is possible to induce a change in dominant brain wave that is necessary for the living body for a long time.

  In addition, the electroencephalogram immediately after waking up is still asleep, and a final induction step with a wavelength level higher than the α wave should be provided in order to promote an appropriate arousal state. In the final induction stage, it is desirable that γ waves, β waves, and α waves are stimulated uniformly.

  In addition, continuous stimulation of the brain wave by the brain wave guidance device causes a burden on the nerve and causes discomfort, so this problem can be solved by providing a resting time in synchronization with the interval of breathing movement so as not to cause much stress. It is necessary to avoid it. More strictly speaking, if the breathing motion cannot be predicted, an interval equal to or less than the breathing rate is used. FIG. 6 shows an execution interval for activating the electroencephalogram by uniformly performing electroencephalogram induction when waking up. During sleep, it must also be considered that breathing and heart rate change greatly during REM sleep and non-REM sleep. FIG. 7 shows the transition of the electroencephalogram and the pause interval actually derived using this method.

In the case of using the artificial intelligence system using the above method, the dominant brain wave during sleep and its time are learned from the subject in the initial stage , and in the next stage, guidance is actually performed using the brain wave guidance device. If the subject feels uncomfortable or awakens during the course, the transition path of EEG guidance is corrected using switch inputs such as push buttons as guidance failure information (which is considered to be an action error in EEG observation and EEG guidance). There must be. Moreover, when learning sufficient for prediction is completed, it is possible to simulate one or more types of long-term ideal electroencephalogram guidance patterns, and it is possible to move to a small computer with a simplified artificial intelligence system. .

  Further, in order to further improve the guidance accuracy, for example, there is a method of adjusting the actual efficiency disparity due to individual differences in advance by adding attribute information for each subject such as age, average sleep time, and usage frequency to the learning element. is there.

The appropriate rest interval for EEG induction is essentially the most appropriate to synchronize with the biorhythm of the human body, so in addition to the method of simulating the respiratory frequency and EEG transition, it is a means to detect the respiratory rate (or respiratory action) It is more desirable to predict the most appropriate electroencephalogram using. In addition, since it is possible to predict the timing at which REM sleep starts from the detected respiration rate, it is considered that a method that does not assume the time lag of Example 4, for example, is possible by incorporating this into the electroencephalogram treatment apparatus. .

  In multimedia, it is produced based on a frequency that humans can perceive. For example, in the case of movie film, 24 Hz, and in the case of music, if the quarter note is 1 second, the 32nd note is 8 Hz.

However, since the same frequency as the electroencephalogram band is accompanied by unbearable flicker and fatigue, the actual display terminal update period and the frequency for reproducing the waveform of music, etc., are slightly beyond the perceivable range. It can be said that there is. This is because the brain wave is temporarily corrected by interfering with the brain wave, but the update frequency is constant, resulting in fatigue.

As another method for preventing the interference with the electroencephalogram, it is possible to synchronize ( electroencephalogram feedback) with the detected dominant electroencephalogram (electroencephalogram filter). For example, in the case of a television , it is possible to achieve power saving and high luminance by detecting and synchronizing the dominant brain wave where it is currently updated at 60 Hz. In the case of classical music as well, it seems that there is a relaxation effect by changing the tempo appropriately to bring about changes in the brain waves.

Therefore, for the problem that it is theoretically difficult to completely synchronize the low frequency with the electroencephalogram (biofeedback) , for example, when the dominant electroencephalogram is detected every minute, the above electroencephalogram induction method is applied here. By taking a wider frequency band, it is possible to realize an intermediate technical method that encompasses human perception period and theoretical synchronization.
For example, the update cycle changes at 11-9 Hz, and the psychological stress due to flickering is reduced by the change path changing every repetition.

  This effect could be exhibited particularly in the reproduction of multimedia in which the update period is relatively low and interferes with the α wave band.

In addition, this internal cycle is inherently able to maintain the most appropriate update cycle if it is modulated so as to detect and synchronize the dominant brain wave of the user . For the frequency, the detected brain wave is replaced with an electroencephalogram stimulation means of an electroencephalogram induction device that biofeeds back in a specific frequency band for α-wave amplification , and then the music playback speed is changed or two as shown in FIG. It is also applied as an internal period of a sound wave visualization device that obtains from sound by converting a dimensional image into sound waves.

The electroencephalogram activation method can be used by being applied to an internal cycle of a device that affects human perception and an electroencephalogram induction device .

It is a figure which shows the space | interval of the rest time using the respiratory cycle which concerns on one Example of this invention. FIG. 4 is a composite waveform diagram of an electroencephalogram frequency and a respiratory frequency according to an embodiment of the present invention . It is a figure which shows transition of the rest time using the electroencephalogram induction frequency in the sleep treatment apparatus which concerns on one Example of this invention, and a respiratory period thru | or the period below it. It is a figure which shows the transition path | route calculation method of the electroencephalogram induction frequency in all the sleep stages based on one Example of this invention. It is a conceptual diagram which shows amplifying a learning effect in the subliminal learning system which concerns on one Example of this invention . It is a figure which shows the electroencephalogram activation system which stimulates the electroencephalogram band of the alpha-gamma wave based on one Example of this invention . 1 is an imaginary view of an apparatus to which an electroencephalogram activation method and a sound wave visualization method according to an embodiment of the present invention are applied .

Explanation of symbols

10 Subliminal learning system
11 Dictionary database
12 EEG induction (and EEG activation method)
13 Subliminal effect
14 1 / f fluctuation effect (and EEG activation method)
20 Image learning (by subliminal display and electroencephalograph)
21 Data selection (learned input, reset, and split dictionary database)
1 Main Body 2 Small Camera 3 Small Speaker 4 Pointing Device 5 Pad

Claims (55)

An electroencephalogram induction method for increasing the actual efficiency of the electroencephalogram induction device,
A frequency band having a wavelength of 1 second to 60 seconds for adding a pause interval to a frequency for inducing brain waves is combined,
The frequency for the pause interval and the electroencephalogram induction further changes relatively in accordance with the elapsed time in a specific frequency band, and repeats.
The electroencephalogram induction method characterized in that the specific frequency band further changes relatively small at each repetition. In systems and devices with an update rhythm of 48Hz-0.01Hz,
An electroencephalogram guidance method for the update rhythm to change differently every repetition,
The update rhythm changes according to the frequency changing from the start point to the end point,
An electroencephalogram guidance method characterized in that the frequency transition is repeated from the starting frequency when it reaches the end point. In systems and devices with an update rhythm of 48Hz-0.01Hz,
An electroencephalogram guidance method for the update rhythm to change differently every repetition,
The update rhythm changes according to the frequency changing from the start point to the end point,
When the frequency transition reaches the end point, it repeats from the starting frequency,
Furthermore, the electroencephalogram guidance method is characterized by taking into account the transition for changing the frequency of the starting point and the ending point in each iteration. In systems and devices with an output frequency of 48Hz-0.5Hz and an update rhythm of 0.5Hz-0.01Hz,
It is an electroencephalogram induction method for different changes for each repetition with respect to an output frequency of 48 Hz-0.5 Hz and an update rhythm of 0.5 Hz-0.01 Hz,
The change difference is different depending on the frequency transition from the start point to the end point, and repeats from the start point frequency when the end point frequency is reached,
Further, the electroencephalogram guidance method is characterized in that the frequency of the start point and the end point is taken into account for the change to be different even at each iteration. In a system and its device with an update interval of 48Hz-0.01Hz,
An electroencephalogram induction method for differentiating changes every repetition with respect to the frequency for electroencephalogram induction or the update interval,
The change difference is a change difference due to the transition for activating the electroencephalogram, and when it reaches outside the allowable range, it returns to the starting position within the allowable range and repeats,
Furthermore, the electroencephalogram guidance method characterized by taking into account the transition for different changes in each iteration. An electroencephalogram induction method for increasing the actual efficiency of the electroencephalogram induction device,
While combining the frequency for taking into account the rest interval below the respiration rate to the frequency for electroencephalogram induction,
An electroencephalogram guidance method characterized by taking into account transitions for the pause interval and the electroencephalogram induction frequency to be different for each pause interval. An electroencephalogram induction method for increasing the actual efficiency of the electroencephalogram induction device,
While combining the frequency for taking into account the rest interval below the respiration rate to the frequency for electroencephalogram induction,
The frequency for inducing the pause interval and the electroencephalogram is repeated within a specific frequency band range, taking into account the transition to be different for each pause interval,
Furthermore, similarly, the specific frequency band range also takes into account transitions that are different for each repetition. An electroencephalogram induction method for increasing the actual efficiency of the electroencephalogram induction device,
While combining the frequency below the respiration rate to provide a pause interval with the frequency for EEG induction,
The frequency below the respiration rate and the frequency for the electroencephalogram induction are different wavelengths for each electroencephalogram induction, gradually lowering over a specific required time, and repeating,
Furthermore, the specific time required and the overall frequency take into account changes that are different even at each iteration, and an electroencephalogram guidance method characterized by the above. It is an electroencephalogram induction method that has a relaxing effect by using it in systems and devices that interfere with perception,
For the time interval of each step that interferes with perception, a frequency for adding a pause interval equal to or less than the respiration rate is used,
Furthermore, the frequency takes into account the transition to be different for each process,
The electroencephalogram guidance method characterized in that the transition for different steps is repeated within a specific band range or with a specific required time. It is an electroencephalogram guidance method that has a subliminal effect amplification and relaxation effect by using it in a subliminal learning system,
The update interval (or process interval) that interferes with perception uses a frequency for adding a pause interval less than the respiration rate, and
The frequency below the respiration rate has a transition change to be different for each process,
The transitional change repeats within a specific bandwidth range or takes a specific duration,
Further, the electroencephalogram guidance method is characterized in that a transitional change is taken into account because the specific bandwidth range or the specific required time is different even in each iteration. An electroencephalogram induction method for increasing the actual efficiency of the electroencephalogram induction device,
In addition to the frequency for brain wave induction, combined with a frequency band of 0.4 Hz or less to add a pause interval,
The pause interval and the frequency for brain wave induction change and change in proportion to the elapsed time,
Furthermore, an electroencephalogram guidance method characterized by repetition within a specific frequency band. An electroencephalogram induction method for increasing the actual efficiency of the electroencephalogram induction device,
In addition to the frequency for brain wave induction, combined with a frequency band of 0.4 Hz or less to add a pause interval,
The pause interval and the frequency for brain wave induction change and change in proportion to the elapsed time,
Further, the electroencephalogram guidance method characterized in that the transition change is repeated at a specific required time. In systems and devices that interfere with perception,
It is an electroencephalogram induction method that activates the electroencephalogram by changing each time using a wavelength of 0.5-48 Hz, or an update (process) interval of 0.5 Hz to 0.01 Hz,
The electroencephalogram guidance method characterized in that the transitional change returns to the starting wavelength (or starting point interval) for repetition when reaching outside the allowable range. In systems and devices that interfere with perception,
It is an electroencephalogram induction method that activates the electroencephalogram by changing each time using a wavelength of 0.5-48 Hz, or an update (process) interval of 0.5 Hz to 0.01 Hz,
The transition change, when reaching outside the allowable range, returns to the starting wavelength (or starting point interval) to repeat,
Further, the electroencephalogram guidance method characterized in that the allowable range changes in every repetition. An electroencephalogram induction method for increasing the actual efficiency of the electroencephalogram induction device,
Combined with a frequency band of 0.4 Hz or less to provide a pause interval for the frequency for brain wave induction,
The electroencephalogram induction method, wherein the pause interval and the frequency for electroencephalogram induction have different wavelengths for each electroencephalogram induction and have changed over a specific required time. An electroencephalogram induction method for increasing the actual efficiency of the electroencephalogram induction device,
Combined with a frequency band of 0.4 Hz or less to provide a pause interval for the frequency for brain wave induction,
The frequency for the pause interval and the frequency for the electroencephalogram induction are different wavelengths for each electroencephalogram induction, change over a specific required time, and repeat,
Furthermore, the specific time required and the overall frequency take into account a transitional change for different iterations, and an electroencephalogram induction method. It is an electroencephalogram guidance method that has a relaxing effect by using it for all systems and devices that interfere with perception,
The interval that interferes with perception uses a frequency band of 0.4 Hz to 0.1 Hz for adding a pause interval,
The pause interval changes every time,
Further, the electroencephalogram induction method, wherein the transition is repeated within a specific band range. It is an electroencephalogram guidance method that has a relaxing effect by using it for all systems and devices that interfere with perception,
The interval that interferes with perception uses a frequency band of 0.4 Hz to 0.1 Hz for adding a pause interval,
The pause interval changes every time,
Furthermore, the transition repeats in a specific band,
Further, the electroencephalogram induction method characterized in that the specific band changes with each repetition. It is an electroencephalogram guidance method that has a subliminal effect amplification and relaxation effect by using it in a subliminal learning system,
The time interval of the process that interferes with perception uses a frequency of 1/5 Hz to 1/3 Hz to account for a pause interval with a subliminal effect,
The time interval of the process takes into account the transition to be different for each process,
Furthermore, the transition repeats in a specific band,
Further, the electroencephalogram induction method characterized in that the specific band changes with each repetition. An electroencephalogram induction method for activating an electroencephalogram in a subliminal learning system using electroencephalogram induction,
While combining the frequency band from 1 / 5Hz to 1 / 3Hz to provide a pause interval with a subliminal effect on the frequency for EEG induction,
The frequency for the pause interval and the frequency for the electroencephalogram induction are different wavelengths for each electroencephalogram induction, change over a specific required time, and repeat,
Furthermore, the specific time required and the overall frequency take into account a transitional change for different iterations, and an electroencephalogram induction method. The electroencephalogram induction method is
For the frequency transition from γ wave to α wave for brain wave stimulation,
Compounding the frequency transitioning within the range of 0.4Hz to 0.1Hz for the pause interval,
The frequency transition repeats after a time lapse of 50 ± 20 seconds,
Furthermore, an electroencephalogram guidance method characterized by the frequency band changing with each iteration. The electroencephalogram induction method is
For the frequency band of γ wave to α wave for brain wave stimulation,
Combine frequency bands in the range of 0.9Hz-0.04Hz for pause intervals,
The electroencephalogram stimulation and the pause interval change and change over a required time of 60 ± 40 seconds, and further,
Furthermore, the electroencephalogram induction method characterized in that the frequency band or the passage of time has changed during each iteration. A method using a composite wave to activate the electroencephalogram,
The composite wave is
A frequency A transitioning from a high γ wave region to a low α wave region for brain wave induction;
Using a frequency B that transitions from 0.4 Hz to 0.1 Hz for the pause interval,
The transition of the frequency AB takes 45 seconds ± 15 seconds and repeats,
Furthermore, an electroencephalogram guidance system characterized by using subtraction to take into account changes even at each iteration. An electroencephalogram induction method using a composite wave for conducting electroencephalogram induction during sleep for a long time,
The composite wave is
A frequency A that changes from an alpha wave to a delta wave (0.5 Hz) for brain wave induction;
Using a frequency B that transitions from 0.5Hz to 0.01Hz for the pause interval,
The transition of the frequency AB takes a time of 80 ± 10 minutes in one stage and is repeated up to 6 times.
Furthermore, an electroencephalogram guidance method characterized by taking into account changes in the stage at each iteration. An electroencephalogram induction method using a composite wave for activating the electroencephalogram,
The composite wave is
Frequency band A around the β wave for brain wave induction,
While using a frequency band B of 0.85 ± 0.75Hz for the pause interval,
The composite wave takes 60 ± 40 seconds and changes and repeats,
Furthermore, an electroencephalogram guidance method characterized by a change of 6 ± 4% in order to take into account the changes that are different in each iteration. An electroencephalogram induction method using a composite wave for long-term electroencephalogram induction during sleep,
The composite wave is
A frequency A that transitions from α wave for cerebral wave induction to δ wave low region (0.5 Hz),
Using a frequency B that transitions from 0.5Hz to 0.01Hz for the pause interval,
The transition of the frequency A-B arrives in a time required for 80 ± 20 minutes in one stage and repeats up to 6 times,
Furthermore, an electroencephalogram guidance method characterized by taking into account changes in the stage at each iteration. An electroencephalogram treatment device equipped with electroencephalogram guidance means for sleeping,
In addition to outputting brain wave A using the brain wave guiding means, the frequency A that transitions from the α wave for brain wave induction to the δ wave low band (0.5 Hz),
The electroencephalogram induction output has a pause interval by combining the frequency B transitioning from 0.5 Hz to 0.01 Hz,
The transition of the frequency AB is repeated up to 6 times taking 80 ± 20 minutes at a time, and the frequency AB is further added every 6 ± 2%. EEG treatment device. The electroencephalogram treatment apparatus comprises an electroencephalogram guidance means, a CPU main body and its internal program,
The internal program is
The brain wave induction means outputs a brain wave induction frequency of γ-α waves to the brain wave induction means,
The brain wave induced output is:
While having a downtime by using the frequency of 0.4Hz-0.1Hz,
The pause time and the frequency for brain wave induction change in proportion to the time lapse of 50 ± 30 seconds and repeat in a specific range,
Further, the electroencephalogram treatment apparatus is characterized in that the specific range takes into account a transition for different changes at each iteration. The electroencephalogram treatment apparatus comprises an electroencephalogram guidance means, a CPU main body and its internal program,
The internal program includes a frequency for electroencephalogram induction,
Combine frequency to use rest time below respiration rate,
Output to the brain wave guiding means,
further,
The frequency for the pause time and the electroencephalogram induction has a transitional change to be different for each repetition,
The transition change repeats in a specific wavelength band, and
Furthermore, the specific waveband is an electroencephalogram treatment apparatus characterized by taking into account a transitional change for differently changing every repetition. The electroencephalogram treatment apparatus comprises an electroencephalogram guidance means, a CPU main body and its internal program,
The internal program outputs a pulse wave of β-δ waves to the electroencephalogram guiding means,
The pulse wave is
It is a composite waveform by combining a frequency band of 0.5-0.01 Hz for using a rest time less than the respiration rate with respect to the frequency for inducing the electroencephalogram,
The pause time and the frequency for brain wave induction change over the duration of the stage of 80 ± 20 minutes,
The transition change repeats for a maximum of 6 stages,
Furthermore, the electroencephalogram treatment apparatus is characterized in that the frequency band changes in each iteration. The electroencephalogram treatment apparatus comprises an electroencephalogram guidance means, a CPU main body and its internal program,
The internal program outputs a pulse wave of β-δ waves to the electroencephalogram guiding means,
The pulse wave is
It is a composite waveform by combining a frequency band of 0.5-0.01 Hz for using a rest time less than the respiration rate with respect to the frequency for inducing the electroencephalogram,
The pause time and the frequency for brain wave induction change over the duration of the stage of 80 ± 20 minutes,
The transition change repeats for a maximum of 6 stages,
In addition, the frequency band changes and changes with each iteration,
The electroencephalogram inducing means comprises an output terminal capable of connecting a plurality of photostimulators, sonic stimulators, and electrical stimulators,
An electroencephalogram treatment apparatus comprising a voltage / current amplification circuit for receiving the pulse wave and processing and outputting the waveform into a waveform suitable for each stimulation apparatus. A learning system including a display terminal having a constant update interval,
The learning system includes a learning process program and a dictionary database in an internal storage,
The dictionary database has a plurality of learning image information consisting of association source image data, association destination image data, additional information,
The learning process program is an internal program for a learning process corresponding to the learning image information,
The first stage displays the association source image information,
In the second stage, the association destination image information is displayed,
The third stage displays the association source image information, the association destination image information, and the additional information,
The subliminal learning system is characterized by using a pause interval for amplifying the subliminal effect and an electroencephalogram guidance method for changing the execution time of each learning step. A learning system including a display terminal having an update interval of 24 Hz or more,
The learning system includes a learning process program and a dictionary database in an internal storage,
The dictionary database has a plurality of learning image information consisting of association source image data, association destination image data, additional information,
The learning process program is an internal program for a learning process corresponding to the learning image information,
The first stage displays the association source image information,
In the second stage, the association destination image information is displayed,
The third stage displays the association source image information, the association destination image information, and the additional information,
In addition, it has a pause interval for amplifying the subliminal effect and a blinking background screen for brain wave induction,
A subliminal learning system using an electroencephalogram guidance method for changing and changing the pause interval and blinking speed. A learning system including a display terminal having an update interval of 0.5 Hz or more,
The learning system includes a learning process program and a dictionary database in an internal storage,
The dictionary database has a plurality of learning image information consisting of association source image data, association destination image data, additional information,
The learning process program is an internal program for a learning process corresponding to the learning image information,
The first step displays the association source image information,
The second stage displays the association destination image information,
The third stage displays the association source image information, the association destination image information, and the additional information,
In the first stage and the second stage,
It has a pause interval for amplifying the subliminal effect and a blinking background screen using the frequency for brain wave induction,
A subliminal learning system using an electroencephalogram guidance method for changing and changing the pause interval and the blinking. A learning system,
With a pause interval to amplify the subliminal effect and a light flashing stimulus for brain wave induction,
27. A subliminal learning system using the electroencephalogram guidance method according to any one of claims 1-26, wherein the pause interval and the frequency of the light blinking stimulus change and change. A learning system,
While having an execution interval of the learning process and an electroencephalogram induction means for electroencephalogram induction,
27. A subliminal learning system using the electroencephalogram guidance method according to any one of claims 1-26, wherein the execution interval and the electroencephalogram induction frequency change and change. 36. A subliminal learning system according to any of claims 32-35,
The first stage and the second stage are each performed twice,
The frequency for inducing the electroencephalogram is that the first phase is around the θ wave, the second phase is around the δ wave, the second phase is around the β wave, and the second phase is around the α wave. A characteristic subliminal learning system. 36. A subliminal learning system according to any of claims 32-35,
The first stage and the second stage are each performed twice,
The frequency for the electroencephalogram induction is:
A subliminal learning system characterized by transition changes in the order of the first stage of the second stage, the second stage of the second stage, the first stage of the first stage, and the second stage of the first stage. 36. A subliminal learning system according to any of claims 32-35,
The first stage and the second stage are each performed twice,
In the interval of each step and the frequency for the electroencephalogram induction, the order for transition change is as follows:
A subliminal learning system characterized in that the first stage of the second stage, the second stage of the second stage, the first stage of the first stage, and the second stage of the first stage. In the learning step, when any one of the association source image data and the association destination image data is plural, the images are sequentially and continuously displayed in synchronization with a frequency for brain wave induction. 36. A subliminal learning system according to any of claims 32-35. 36. The subliminal learning system according to claim 32, wherein the additional information is further displayed in the second round of the second stage. An electroencephalogram guidance apparatus using the electroencephalogram guidance method according to any one of claims 1 to 26 as an internal algorithm. An electroencephalogram guidance program using the electroencephalogram guidance method according to any one of claims 1 to 26 as an internal algorithm in a system that interferes with perception. The electroencephalogram treatment apparatus includes an electroencephalogram simulator system that simulates an electroencephalogram during sleep based on artificial intelligence reasoning, and an electroencephalogram induction means.
The brain wave simulator system is
An electroencephalogram treatment apparatus using the electroencephalogram guidance method according to any one of claims 1-26 as an internal algorithm. The electroencephalogram treatment apparatus further includes means for detecting a respiratory rate,
45. The electroencephalogram treatment apparatus according to claim 27, wherein the change transition of the frequency band is changed according to a dominant electroencephalogram predicted from a respiratory rate. The electroencephalogram treatment apparatus further includes means for detecting a respiratory rate,
45. The electroencephalogram treatment apparatus according to claim 27, wherein the pause interval is synchronized with the respiration rate. The artificial visual apparatus includes means for converting and outputting sound waves for audible sound from a video screen or the like, means for detecting dominant brain waves,
The update interval for converting to sound waves has a relatively large change to synchronize with the dominant brain wave,
Furthermore, the artificial vision apparatus characterized by using the electroencephalogram guidance method according to any one of claims 1 to 26 for having a relatively small change. The artificial hearing device includes means for converting and outputting sound information to color information for vision, and means for detecting dominant brain waves,
The update interval for converting and outputting to the color information has a relatively large change to synchronize with the dominant brain wave,
Furthermore, the artificial vision apparatus characterized by using the electroencephalogram guidance method according to any one of claims 1 to 26 for having a relatively small change. A system having an update interval of 0.5-48 Hz for perception, further comprising means for detecting dominant brain waves,
The update interval has a relatively large change to synchronize with the dominant electroencephalogram,
Furthermore, the biofeedback system using the electroencephalogram guidance method according to any one of claims 1-26 for having a relatively small change. A system having an update interval of 0.5-48 Hz for perception, further comprising means for detecting dominant brain waves,
The update interval has a relatively large change to synchronize with the dominant electroencephalogram,
Furthermore, the biofeedback system using the electroencephalogram guidance method according to any one of claims 1 to 26 for an internal program for having a relatively small change. A display device having an update interval of 0.5-48 Hz, further comprising means for detecting dominant brain waves,
The update interval has a relatively large change to synchronize with the dominant electroencephalogram,
Furthermore, the biofeedback system using the electroencephalogram guidance method according to any one of claims 1-26 for having a relatively small change. 36. The subliminal learning system according to claim 32, wherein the electroencephalogram induction further includes an electroencephalogram induction device as a means. The electroencephalogram treatment apparatus according to any one of claims 27 to 35 and 47 to 51, wherein the electroencephalogram induction comprises any one of a sound wave generator, a light flashing stimulator, and an electrical stimulator. And subliminal learning system, artificial visual device, and biofeedback system. The frequency for the pause interval uses a sine wave or a triangular wave for smoothly changing the output amount, and
In addition, the minimum output amount to guarantee the actual efficiency of the electroencephalogram induction device is taken into account (or the minimum output amount by combining with the pulse wave)
52. The electroencephalogram treatment device, subliminal learning system, artificial vision device, and biofeedback system according to any one of claims 27-35 and 47-51. The frequency for the pause interval uses a sine wave or a triangular wave for smoothly changing the output amount, and
27. The electroencephalogram guidance method according to claim 1, wherein a pulse wave for ensuring the minimum output amount is synthesized.