KR20170096276A

KR20170096276A - Study condition control mehtod using brain wave

Info

Publication number: KR20170096276A
Application number: KR1020160017330A
Authority: KR
Inventors: 송지성; 박수조; 전민승; 안호정; 김효선; 김민규
Original assignee: 한양대학교 에리카산학협력단; 송지성; 김민규; 안호정; 김효선; 박수조; 전민승
Priority date: 2016-02-15
Filing date: 2016-02-15
Publication date: 2017-08-24

Abstract

The present invention provides a learning environment control method which can improve concentration using brainwaves. The learning environment control method using brainwaves according to one aspect of the present invention comprises the following: a brainwave receiving step of receiving brainwaves; a brainwave analysis step of classifying and extracting types of brainwaves according to the frequency from the received brainwaves; a syncing step of recognizing the brainwave change and waiting for an electronic device to be controlled by the brainwaves; and a color temperature control step of determining users concentration according to the change of brainwaves and changing the color temperature of the illumination. According to the present invention, the concentration of a user can be improved by controlling the color temperature, illumination, and sound waves according to the change of brainwaves.

Description

{STUDY CONDITION CONTROL MEHTOD USING BRAIN WAVE}

The present invention relates to a learning environment control method, and more particularly, to a learning environment control method using an EEG.

Generally, brain waves are biological signals that directly or indirectly reflect human consciousness or unconscious state, and refers to a wavelength having a frequency of 30 Hz or less with a potential difference of tens of microvolts measured in all regions of human scalp.

These EEGs are classified into a delta wave, a theta wave, an alpha wave, a beta wave, and a gamma wave by frequency band. Delta waves are typically EEG waves with a frequency of less than 4 Hz and are typical of normal sleep states. Theta waves are those with frequencies in the range of 4 to 8 Hz and are often present when the state is mentally disturbed or distracted, often in adolescents with learning disabilities .

The alpha wave is an electroencephalogram with a frequency of about 8 to 12 Hz, which is generally stable when the mental state is stable, and the eye is closed and taking a relaxed psychological state. Alpha waves also occur when there is a high degree of concentration to separate from the surrounding situation, or when psychological stabilization has occurred due to meditation. Gamma wave is an EEG having a frequency of 30 to 50 Hz and appears in an excited state.

Beta waves refer to the EEG with a frequency of about 12 to 30 Hz, which is mainly observed when a little tension or attention is paid. Beta waves are widespread throughout the brain when exercising, learning, or performing tasks. The beta wave is divided into an SMR wave having a frequency of 12 to 15 Hz, an intermediate beta wave having a frequency of 15 to 18 Hz, and a high-beta wave having a frequency of 20 Hz or more. Beta waves are more stressful when exposed to stress such as anxiety or tension.

When attention is paid, SMR wave appears. When concentrated and normal activities are performed, middle beta waves with a frequency of 15 to 18 Hz appear in the left brain and Kobe beat exceeding 20 Hz appears when tension and anxiety continue.

The present invention provides a learning environment control method capable of improving concentration using brain waves.

A learning environment control method using EEG according to an aspect of the present invention includes a step of receiving an EEG receiving EEG, an EEG analysis step of classifying and extracting EEG types according to a frequency from a received EEG, And a color temperature control step of determining a user's concentration according to the change of brain waves and changing a color temperature of the illumination.

In addition, the sinking step may include a picture display step of displaying a picture on the display.

In addition, the sinking step may include a brain wave change recognition step of recognizing a change of a user's brain wave appearing according to a picture display.

Further, in the EEP change recognition step, it can be determined that there is a sink doctor when the intensity of the setter becomes lower and the intensity of the SMR wave and the middle beta wave become higher.

Also, the EEG recognizing step can determine that there is a sink doctor when the intensity of the alpha wave is decreased in the right hemisphere and the alpha wave is not changed in the left hemisphere.

In addition, the sinking step may include a sink signal generating step of, when the user's brain wave change coincides with a preset pattern, transmitting a pairing signal to the electronic device to wait for the electronic device to receive the driving signal.

In addition, the color temperature control step may include a concentration determination step of determining a degree of concentration of the user.

In addition, the concentration determination step may determine that the user is concentrating when both the SMR wave and the intermediate beater increase and the increase amount of the SMR wave is larger than the increase amount of the middle beta wave.

Also, the concentration determination step may divide the degree of learning concentration by dividing the sum of the output value of the SMR wave and the output value of the middle beta wave by the output value of the three waves.

The color temperature adjusting step may include a color temperature changing step for increasing the color temperature of the illumination when the concentration is decreased.

Also, when it is determined that the color temperature changing step is in the concentrated state, the color temperature of the illumination can be controlled to 5500K to 6500K.

Also, when it is determined that the color temperature changing step is a rest state, the color temperature of the illumination can be controlled to 3000K to 4000K.

In addition, the environmental control method may further include a step of adjusting illuminance of the illumination, and the illuminance adjusting step may increase the illuminance when the concentration is decreased.

Further, when it is determined that the illuminance control step is in the concentrated state, the illuminance of the illumination can be controlled from 750 lux to 850 lux.

In addition, the environment control method may further include a background sound wave adjusting step of adjusting a background sound wave according to a change in brain waves.

In addition, the background sound wave adjusting step may generate a true sound wave having a frequency of 1 Hz to 1 kHz when the Kobe beat is increased while the concentration is maintained.

In addition, the background sound wave adjusting step may generate a sound wave having a frequency of a frequency band lower than the audible frequency.

As described above, according to the present invention, it is possible to improve the concentration by controlling the color temperature, illumination, and sound waves according to the change of EEG.

1 is a diagram showing a space in which a learning environment control system according to the present invention is installed.
2 is a block diagram illustrating a learning environment control system using EEG according to a first embodiment of the present invention.
FIG. 3 is a flowchart for explaining a learning environment control method using an EEG according to the first embodiment of the present invention.
4 is a block diagram of a learning environment control system using EEG according to a second embodiment of the present invention.
5 is a flowchart for explaining a learning environment control method using an EEG according to a second embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily carry out the present invention. The present invention can be variously modified and may have various embodiments, and specific embodiments will be described in detail with reference to the drawings. It should be understood, however, that the invention is not intended to be limited to the particular embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

Terms including ordinals, such as first, second, etc., may be used to describe various elements, but the elements are not limited to these terms. The terms are used only for the purpose of distinguishing one component from another.

For example, without departing from the scope of the present invention, the first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component. And / or < / RTI > includes any combination of a plurality of related listed items or any of a plurality of related listed items.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries are to be interpreted as having a meaning consistent with the contextual meaning of the related art and are to be interpreted as either ideal or overly formal in the sense of the present application Do not.

FIG. 1 is a diagram showing a space in which a learning environment control system according to the present invention is installed, and FIG. 2 is a configuration diagram illustrating a learning environment control system using an EEG according to a first embodiment of the present invention.

1 and 2, the learning environment control system 100 using the EEG according to the first embodiment includes an EEG reception unit 110, an EEG analysis unit 120, a sink unit 130, (140), and a background sound wave controller (150).

The EEG receiving unit 110 receives the EEG transmitted from the EEG device 20. The EEG receiving unit 110 can receive EEG signals from the EEG measuring device 20 by wireless communication.

The EEG device 20 attaches a plurality of electrodes to the scalp of the user 10 and receives the user's brain waves through the electrodes. For example, a ground electrode among a plurality of electrodes is disposed at the center of a user's scalp, and a right-brain electrode and a left-brain electrode are attached to the scalp of the user on both sides thereof. At this time, the EEG device selects and measures EEG for the frontal region of the user except the EEG or the frontal region. The EEG device 20 may be in the form of a headset, a band, or a hat.

The EEG analyzing unit 120 classifies and extracts the types of EEG according to frequencies from the received EEG. The EEG analysis unit 120 extracts the alpha waves, the SMR waves, the middle beta waves, the high beta waves, the seta waves, and the gamma waves from the received EEG. The EEG analysis unit 120 includes an amplification module 121, a filter module 123, and an AD conversion module 125.

The amplification module 121 has an amplifier therein and amplifies the brain waves of several tens of μV to tens of mV received by the brain wave receiving unit 110 through the amplifier to 3 to 5 V to facilitate the analysis of the received brain waves.

The filter module 123 includes a plurality of analog filters to filter various noise included in the brain waves amplified by the amplification module 121. At this time, the filter is composed of a high pass filter, a band pass filter, a band stop filter, and a low pass filter. Such a high-pass filter primarily removes noise due to DC voltage, respiration, body movement, eye blinking, and the like, and the band-pass filter filters the EEG having a frequency band range to be measured. The band-stop filter removes noise due to the power supply of 50Hz or 60Hz, and the low-pass filter limits the width of the brain waves to prevent distortion and prevents distortion occurring when the brain waves are restored. The A / D conversion module 125 digitizes the EEG in the analog state extracted through the filter module 123.

The sync unit 130 recognizes the EEG changes and waits for the electronic apparatus to be controlled by the EEG. The sync unit 130 may include a character display module 131, a brain wave change recognition module 132, and a sync signal generation module 133.

The character display module 131 displays characters on the display, but displays moving characters. The brain wave change recognition module 132 recognizes a change in the user's brain wave that appears according to the display of characters. When a user recognizes a moving character, eye movement occurs and the intensity of the delta wave increases, and the intensity of the SMR wave increases in the process of reading the character. Accordingly, when the intensity of the delta wave increases and the intensity of the SMR wave increases, the EEG recognizing module 132 can determine that there is a sinking intention.

In addition, the appearance of alpha waves in the process of recognition of letters and pictures is different. During the linguistic task, the intensity of the alpha waves decreases in the left hemisphere, there is no change in the alpha waves in the right hemisphere, While performing spatial tasks, the intensity of the alpha wave is decreased in the right hemisphere and there is no change in the alpha wave in the left hemisphere. The EEG recognizing module 132 determines that there is a sink doctor when the intensity of the alpha wave is decreased in the left hemisphere and the alpha wave is not changed in the right hemisphere. The sink signal generation module 133 transmits the sink signal to the electronic device, and switches to the standby state so that the electronic device can receive the drive signal.

The color temperature controller 140 includes a concentration determining module 141 and a color temperature changing module 142 for determining a concentration of a user according to a change in brain waves and changing a color temperature of the illumination 50.

The concentration determination module 141 recognizes that both the SMR wave and the intermediate beater increase, and that the increase amount of the SMR wave is larger than the increase amount of the middle beta wave and that the concentration is concentrated. In the learning state, both the SMR wave and the middle beta wave increase, and the increase of the SMR wave is larger than the increase of the middle beta wave by recognizing and thinking of the character. The concentration determination module 141 recognizes this state as a state in which the user is concentrated. In the present description, the amount of increase in all kinds of brain waves is measured by a voltage.

The concentration determining module 141 can quantize and store the concentration, and a value obtained by dividing the sum of the output value of the SMR wave and the output value of the middle beta wave by the output value of the three wave is defined as the learning concentration. A high concentration means that the user is immersed in study, and a low concentration of learning means that the user is in a learning state but distracted.

In the state of concentration on learning, the decrease of the cetapha reflecting the level of unconsciousness increases, the SMR wave which means the attention power around the periphery, and the middle beta wave which means the immersion concentration power that is immersed in one object. Therefore, the degree of concentration of the user in the learning state can be grasped more clearly by calculating the learning concentration as described above.

The color temperature change module 142 controls the color temperature of the illumination 50 to 5500K to 6500K when the concentration state is determined to be concentrated, and increases the color temperature of the illumination when the concentration is lowered. The color temperature for general household activities is known to be about 4600K. If you increase the color temperature, you can improve the concentration by increasing the SMR wave. In particular, if the color temperature is maintained at 5500K to 6500K, the EEG occurring at the time of concentration due to the color temperature can be further strengthened.

On the other hand, the color temperature changing module 142 reduces the color temperature of the illumination 50 when it is determined to be in the rest state, and controls the color temperature of the illumination 50 to 3000K to 4000K in the rest state. Reducing the color temperature can increase the alpha wave and relax the tension.

The background sound wave controller 150 controls the generation of sound waves according to the change of brain waves. The background sound wave controller 150 can generate a true sound wave having a frequency of 1 Hz to 1 kHz when the Kobe beat is increased while the concentration is maintained.

The background sound wave control unit 150 includes a stress determination unit 151 for determining whether Kobe beat increases or not and a sound wave output unit 152 for generating a true sound wave having a frequency of 50 Hz to 1 KHz when Kobe beat increases . The sound waves may be output through the speaker 40. [

The sound wave output unit 152 can reduce the frequency of the sound wave when the Kobe beat increases in the state where the concentration is maintained and the background sound wave control unit adjusts the frequency of the sound wave having the frequency of 1 Hz to 30 Hz .

The background sound wave controller 150 can generate a U wave having a large amplitude and a long wavelength and a low frequency. U wave is a sound wave like wave sound. When the background sound wave controller 150 generates a sound wave having a low frequency, a mid-wave wave having a frequency of 10 Hz to 12 Hz can be derived. Mead Alpha is an EEG that improves study efficiency and relieves stress.

Hereinafter, a learning environment control method using the EEG according to the first embodiment of the present invention will be described with reference to FIG. FIG. 3 is a flowchart for explaining a learning environment control method using an EEG according to the first embodiment of the present invention.

1 to 3, a learning environment control method using an EEG according to the first embodiment includes EEG reception step S101, EEG analysis step S102, Sink step S103, S104), and a background sound wave adjusting step (S105).

The EEG reception step (S101) receives the EEG transmitted from the EEG device (20). The EEG receiving step (S101) can receive brain waves from the EEG device 20 by wireless communication.

The EEG analysis step (S102) classifies and extracts the kinds of EEG according to the frequency from the received EEG. The EEG analysis unit 120 extracts the alpha waves, the SMR waves, the middle beta waves, the high beta waves, the seta waves, and the gamma waves from the received EEG. The EEG analysis step (S102 includes an amplification step, a filtering step, and an AD conversion step).

In the amplification step, an amplifier is provided, and the received EEG analysis is facilitated by amplifying the brain waves of several tens of μV to several tens of mV received by the EEG receiving unit 110 through an amplifier to 3 to 5V.

The filtering step includes a plurality of analog filters to filter various noise included in the brain waves amplified by the amplification module 121. At this time, the filter is composed of a high pass filter, a band pass filter, a band stop filter, and a low pass filter. Such a high-pass filter primarily removes noise due to DC voltage, respiration, body movement, eye blinking, and the like, and the band-pass filter filters the EEG having a frequency band range to be measured. The band-stop filter removes noise due to the power supply of 50Hz or 60Hz, and the low-pass filter limits the width of the brain waves to prevent distortion and prevents distortion occurring when the brain waves are restored. The AD conversion step digitizes the EEG signal extracted through the filtering step.

The sync step S103 recognizes the EEG changes and waits for the electronic apparatus to be controlled by the EEG. The sinking step S103 may include a character displaying step, a brain wave change recognizing step, and a sink signal generating step.

The character display step displays a character on the display, but displays the character to be moved. The step of recognizing the EEG changes recognizes the change of the user's brain waves appearing according to the display of the characters. When a user recognizes a moving character, eye movement occurs and the intensity of the delta wave increases, and the intensity of the SMR wave increases in the process of reading the character. Thus, when the intensity of the delta wave is increased and the intensity of the SMR wave is increased, it can be judged that there is a sink doctor.

In addition, the appearance of alpha waves in the process of recognition of letters and pictures is different. During the linguistic task, the intensity of the alpha waves decreases in the left hemisphere, there is no change in the alpha waves in the right hemisphere, While performing spatial tasks, the intensity of the alpha wave is decreased in the right hemisphere and there is no change in the alpha wave in the left hemisphere. In the EEG phase recognition step, we think that there is a sink doctor when the intensity of the alpha wave is decreased in the left hemisphere and the alpha wave is not changed in the right hemisphere. In the sink signal generating step, the sync signal is transmitted to the electronic device, and the electronic device switches to the standby state so that the drive signal can be received.

The color temperature control step (S104) includes determining concentration of the user according to the change of brain waves, changing the color temperature of the illumination 50, and determining the concentration of the user.

In the concentration determination stage, both the SMR wave and the middle beat peak are increased, and the increase in the SMR wave is detected as being larger than the increase in the middle beta wave and it is recognized that the concentration is concentrated. In the learning state, both the SMR wave and the middle beta wave increase, and the increase of the SMR wave is larger than the increase of the middle beta wave by recognizing and thinking of the character. Thus, the concentration determination step recognizes such a state as a state in which the user is concentrated. In the present description, the amount of increase in all kinds of brain waves is measured by a voltage.

In the concentration determination step, the concentration can be quantified and stored. The value obtained by dividing the sum of the output value of the SMR wave and the output value of the middle beta wave by the output value of the half wave is defined as the learning concentration. A high concentration means that the user is immersed in study, and a low concentration of learning means that the user is in a learning state but distracted.

When it is determined that the color temperature changing step is a concentrated state, the color temperature of the illumination 50 is controlled to be in the range of 5500K to 6500K, and when the concentration is lowered, the color temperature of the illumination is increased. The color temperature for general household activities is known to be about 4600K. If you increase the color temperature, you can improve the concentration by increasing the SMR wave. In particular, if the color temperature is maintained at 5500K to 6500K, the EEG occurring at the time of concentration due to the color temperature can be further strengthened.

On the other hand, when the color temperature changing step is determined to be in the rest state, the color temperature of the illumination 50 is reduced. In the rest state, the color temperature of the illumination 50 is controlled to 3000K to 4000K. Reducing the color temperature can increase the alpha wave and relax the tension.

The background sound wave controlling step (S105) controls the generation of sound waves in accordance with the change of the brain waves. The background sound wave adjusting step (S105) can generate a true sound wave having a frequency of 1 Hz to 1 kHz when the kobe beat is increased while the concentration is maintained.

The background sound wave control step S105 may include a stress determination step for determining whether Kobe beat is increased or a sound output step for generating a true sound wave having a frequency of 50 Hz to 1 kHz when Kobe beat increases. The sound waves may be output through the speaker 40. [

The sound wave output stage can reduce the frequency of the sound wave when the Kobe beat increases while the concentration is maintained and the background sound wave controller can generate a sound wave having a frequency of 1 Hz to 30 Hz have.

The background sound wave control step can generate a U wave having a large amplitude and a long wavelength and a low frequency. U wave is a sound wave like wave sound. When the background sound wave controller 150 generates a sound wave having a low frequency, a mid-wave wave having a frequency of 10 Hz to 12 Hz can be derived. Mead Alpha is an EEG that improves study efficiency and relieves stress.

Hereinafter, a learning environment control system using an EEG according to a second embodiment of the present invention will be described with reference to FIG. 4 is a block diagram of a learning environment control system using EEG according to a second embodiment of the present invention.

4, the learning environment control system 200 using the EEG according to the second embodiment includes an EEG receiving unit 210, an EEG analysis unit 220, a sink unit 230, a color temperature control unit 240 A background sound wave controller 250, and an illumination controller 260.

The EEG receiving unit 210 receives the EEG transmitted from the EEG device 20. The EEG receiving unit 210 can receive EEG signals from the EEG measuring device 20 by wireless communication.

The EEG analyzing unit 220 classifies and extracts the EEG types according to the frequency from the received EEG. The EEG analysis unit 220 extracts the alpha waves, the SMR waves, the middle beta waves, the high beta waves, the seta waves, and the gamma waves from the received EEG. The EEG analysis unit 220 includes an amplification module 221, a filter module 223, and an AD conversion module 225.

The amplification module 221 includes an amplifier and amplifies the brain waves of several tens of microvolts to several tens of millivolts received by the EEG receiver 210 through the amplifier to 3 to 5 V to facilitate the analysis of the received brain waves.

The filter module 223 includes a plurality of analog filters to filter various noise included in the brain waves amplified by the amplification module 221. At this time, the filter is composed of a high pass filter, a band pass filter, a band stop filter, and a low pass filter. Such a high-pass filter primarily removes noise due to DC voltage, respiration, body movement, eye blinking, and the like, and the band-pass filter filters the EEG having a frequency band range to be measured. The band-stop filter removes noise due to the power supply of 50Hz or 60Hz, and the low-pass filter limits the width of the brain waves to prevent distortion and prevents distortion occurring when the brain waves are restored. The AD conversion module 225 digitizes the EEG in the analog state extracted through the filter module 223.

The sync unit 230 recognizes the EEG change and waits for the electronic device to be controlled by the EEG. The sync unit 230 may include a character display module 231, a brain wave change recognition module 232, and a sync signal generation module 233.

The character display module 231 displays characters on the display, but displays moving characters. The brain wave change recognition module 232 recognizes the change of the user's brain waves appearing according to the display of the characters. When a user recognizes a moving character, eye movement occurs and the intensity of the delta wave increases, and the intensity of the SMR wave increases in the process of reading the character. Accordingly, when the intensity of the delta wave increases and the intensity of the SMR wave increases, the brain wave change recognition module 232 can determine that there is an intention to sink.

In addition, the appearance of alpha waves in the process of recognition of letters and pictures is different. During the linguistic task, the intensity of the alpha waves decreases in the left hemisphere, there is no change in the alpha waves in the right hemisphere, While performing spatial tasks, the intensity of the alpha wave is decreased in the right hemisphere and there is no change in the alpha wave in the left hemisphere. The EEG recognizing module 232 determines that there is a sink doctor when the intensity of the alpha wave is decreased in the left hemisphere and the alpha wave is not changed in the right hemisphere. The sink signal generation module 233 transmits the sink signal to the electronic device and switches to the standby state so that the electronic device can receive the driving signal.

The color temperature control unit 240 includes a concentration determination module 241 and a color temperature variation module 242. The concentration determination module 241 determines a user's concentration according to a change in brain waves and changes a color temperature of the illumination 50.

The concentration determination module 241 recognizes that both the SMR wave and the intermediate beater increase, and that the increase amount of the SMR wave is larger than the increase amount of the middle beta wave, and concentrates the detection. In the learning state, both the SMR wave and the middle beta wave increase, and the increase of the SMR wave is larger than the increase of the middle beta wave by recognizing and thinking of the character. The concentration determination module 241 recognizes this state as a state in which the user is concentrated. In the present description, the amount of increase in all kinds of brain waves is measured by a voltage.

The concentration determining module 241 can quantify and store the concentration. The value obtained by dividing the sum of the output value of the SMR wave and the output value of the middle beta wave by the output value of the three waves is defined as the learning concentration. A high concentration means that the user is immersed in study, and a low concentration of learning means that the user is in a learning state but distracted.

The color temperature variation module 242 controls the color temperature of the illumination 50 to 5500K to 6500K when the concentration state is determined to be in a concentrated state, and increases the color temperature of the illumination when the concentration is lowered. The color temperature for general household activities is known to be about 4600K. If you increase the color temperature, you can improve the concentration by increasing the SMR wave. In particular, if the color temperature is maintained at 5500K to 6500K, the EEG occurring at the time of concentration due to the color temperature can be further strengthened.

On the other hand, the color temperature changing module 242 decreases the color temperature of the illumination 50 when it is judged to be in the rest state, and controls the color temperature of the illumination 50 to 3000K to 4000K in the rest state. Reducing the color temperature can increase the alpha wave and relax the tension.

The background sound wave controller 250 controls the generation of sound waves according to the change of brain waves. The background sound wave controller 250 can generate a true sound wave having a frequency of 1 Hz to 1 kHz when the Kobe beat is increased while the concentration is maintained.

The background sound wave control unit 250 includes a stress determination unit 251 for determining whether the Kobe beat wave increases or not and a sound wave output unit 252 for generating a true sound wave having a frequency of 1 Hz to 1 KHz when the Kobe beat wave increases . The sound waves may be output through the speaker 40. [

The sound wave output unit 252 can reduce the frequency of the sound wave when the Kobe beat increases in a state where the concentration is maintained and the background sound wave control unit adjusts the sound wave having a frequency in the range of 1 Hz to 30 Hz .

The background sound wave controller 250 can generate a U wave having a large amplitude and a long wavelength and a low frequency. U wave is a sound wave like wave sound. When the background sound wave controller 250 generates a sound wave having a low frequency, it is possible to derive a mid-wave wave having a frequency of 10 Hz to 12 Hz. Mead Alpha is an EEG that improves study efficiency and relieves stress.

The illuminance adjusting unit 260 increases the illuminance of the illumination when the concentration is lowered. When it is determined that the illuminance adjusting unit 260 is in the concentrated state, the illuminance of the illuminance can be controlled from 750 lux to 850 lux. Generally, as the illuminance increases, the intensity of the SMR wave can be increased to induce concentration.

Hereinafter, a learning environment control method using an EEG according to a second embodiment of the present invention will be described with reference to FIG. 5 is a flowchart for explaining a learning environment control method using an EEG according to a second embodiment of the present invention.

Referring to FIGS. 4 and 5, the learning environment control method using EEG according to the second embodiment includes EEG reception step S201, EEG analysis step S202, Sink step S203, S204), illumination adjustment (S205), and background sound wave adjustment (S206).

The EEG receiving step (S201) receives the EEG transmitted from the EEG device (20). The EEG receiving step (S201) can receive brain waves from the EEG measuring device 20 by wireless communication.

The EEG analysis step (S202) classifies and extracts the types of EEG according to frequencies from the received EEG. The EEG analysis unit 120 extracts the alpha waves, the SMR waves, the middle beta waves, the high beta waves, the seta waves, and the gamma waves from the received EEG. The EEG analysis step S202 includes an amplification step, a filtering step, and an AD conversion step.

The sink step S203 recognizes the EEG change and waits for the electronic device to be controlled by the EEG. The sinking step S203 may include a character displaying step, a brain wave change recognizing step, and a sink signal generating step.

The color temperature control step S204 includes determining the concentration of the user according to the change of the EEG, changing the color temperature of the illumination 50, and determining the concentration and the color temperature.

The background sound wave adjusting step (S206) controls the generation of sound waves according to the change of brain waves. The background sound wave adjusting step (S206) can generate a true sound wave having a frequency of 1 Hz to 1 kHz when the kobe beat is increased while the concentration is maintained.

The illumination adjustment step (S205) increases the illuminance of the illumination when the concentration is lowered. When it is determined that the illumination adjustment step S205 is in the concentrated state, the illuminance of the illumination can be controlled from 750 lux to 850 lux (luz). Generally, as the illuminance increases, the intensity of the SMR wave can be increased to induce concentration.

The background sound wave adjusting step S206 may include a stress determination step of determining whether Kobe beat is increased or a sound output step of generating a true sound wave having a frequency of 50 Hz to 1 kHz when Kobe beat increases. The sound waves may be output through the speaker 40. [

As described above, preferred embodiments of the present invention have been disclosed in the present specification and drawings, and although specific terms have been used, they have been used only in a general sense to easily describe the technical contents of the present invention and to facilitate understanding of the invention , And are not intended to limit the scope of the present invention. It is to be understood by those skilled in the art that other modifications based on the technical idea of the present invention are possible in addition to the embodiments disclosed herein.

100, 200: learning environment control system
110, 210: EEG receiver
120 and 220: EEG analysis unit
130, and 230:
140, 240: Color temperature control unit
150, 250: background sound wave control unit

Claims

An EEG receiving step of receiving an EEG;
An EEG analysis step of classifying and extracting the kinds of EEG according to frequencies from the received EEG;
A sink step of recognizing an EEG change and waiting for an electronic device to be controlled by an EEG; And
A color temperature control step of determining the user's concentration according to the change of brain waves and changing the color temperature of the illumination;
And controlling the learning environment using the EEG.

The method according to claim 1,
Wherein the sink step includes a picture display step of displaying pictures on a display.

3. The method of claim 2,
Wherein the sink step includes an EEG change recognition step of recognizing a change of a user's EEG appearing according to a display of a picture.

The method of claim 3,
Wherein the step of recognizing the EEG changes determines that there is a sink physician when the intensity of the SETA wave is low and the intensity of the SMR wave and the middle beta wave is high.

The method of claim 3,
Wherein the step of recognizing the EEG includes determining that there is a sink physician when the intensity of the alpha wave in the right hemisphere decreases and the alpha wave in the left hemisphere does not change.

The method of claim 3,
Wherein the sinking step includes transmitting a pairing signal to the electronic device when the user's brain wave change coincides with the preset pattern, and waiting for the electronic device to receive the driving signal. Learning environment control method.

The method according to claim 1,
Wherein the color temperature control step includes a concentration determination step of determining a degree of concentration of a user.

8. The method of claim 7,
Wherein the concentration determining step determines that the user is concentrating when both the SMR wave and the middle beat increase and the increase amount of the SMR wave is larger than the increase amount of the middle beta wave.

8. The method of claim 7,
Wherein the concentration determining step divides the sum of the output value of the SMR wave and the output value of the middle beta wave into output values of the three waves to quantify the degree of learning concentration.

10. The method of claim 9,
Wherein the color temperature controlling step includes a color temperature changing step of increasing the color temperature of the illumination when the concentration is decreased.

11. The method of claim 10,
Wherein the color temperature changing step controls the color temperature of the illumination to be in the range of 5500K to 6500K when it is determined that the color temperature is in the concentrated state.

12. The method of claim 11,
Wherein the color temperature changing step controls the color temperature of the illumination to be 3000K to 4000K when it is determined that the color temperature changing step is in the rest state.

11. The method of claim 10,
Wherein the environment control method further includes a step of adjusting the illuminance of the illumination, and the step of adjusting the illuminance increases the illuminance when the concentration is decreased.

14. The method of claim 13,
Wherein the illuminance control step controls the illuminance of the illumination from 750 lux to 850 lux when it is determined that the illuminance is concentrated.

The method according to claim 1,
Wherein the environment control method further includes a background sound wave adjusting step of adjusting a background sound wave according to a change in brain waves.

The method according to claim 1,
Wherein the background sound wave adjusting step generates a true sound wave having a frequency of 1 Hz to 1 kHz when the Kobe beat is increased while the concentration is maintained.

The method according to claim 1,
Wherein the background sound wave adjusting step generates a sound wave having a frequency of a frequency band lower than the audible frequency.