KR101664023B1 - Electronic equipment control device using brain wave - Google Patents

Abstract

The present invention provides an electronic apparatus driving apparatus capable of driving an electronic apparatus using brain waves.
According to one aspect of the present invention, there is provided an apparatus for driving an electronic device using an EEG, the apparatus including an EEG receiver for receiving an EEG; a EEG analyzing unit for classifying and extracting EEGs according to frequencies from received EEGs; A pattern storage module for storing a pairing pattern for connection and a driving pattern for driving the electronic device, a pairing determination module for determining whether a change in the brain waves coincides with a pairing pattern, And a drive pattern determination module that determines whether or not the EEG changes coincide with each other, and the drive pattern includes a plurality of drive patterns.

Description

TECHNICAL FIELD [0001] The present invention relates to an electronic device driving apparatus using an electroencephalogram (EEG)

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to an electronic device driving apparatus, and more particularly, to an electronic device driving apparatus 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. The delta wave is a brain wave with a frequency of less than 4Hz and typically appears in a normal sleep state. Theta wave is an EEG having a frequency of about 4 to 8 Hz, which is mainly observed when the state is disturbed or distracted. .

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 an electronic apparatus driving apparatus capable of driving an electronic apparatus using brain waves.

According to one aspect of the present invention, there is provided an apparatus for driving an electronic device using an EEG, the apparatus comprising: an EEG receiver for receiving an EEG; a EEG analyzing unit for classifying and extracting EEGs according to frequencies from received EEGs; A pattern storage module for storing a pairing pattern for connection and a driving pattern for driving the electronic device, a pairing determination module for determining whether a change in the brain waves coincides with a pairing pattern, And a drive pattern determination module that determines whether the change in the EEG signal coincides with each other.

Here, the drive pattern determination module may determine that the patterns match if the increase and decrease of the alpha waves are repeated twice within the set time period.

In addition, the driving pattern judging module determines patterns of activity when the activity of the left parietal lobe is increased and the activity of the left / right frontal lobe is lowered in the determination of the activity change of the alpha wave twice or more within a preset time It can be judged.

In addition, the drive pattern determination module may determine that the patterns match when the increase of the SMR wave and the middle beta wave is repeated twice within a predetermined period.

The pattern storage module stores different primary and secondary patterns. The pattern comparison module includes a primary pattern determination module for determining whether the received EEG coincides with the primary pattern, And a secondary pattern determination module that determines whether or not they match with each other.

In addition, the primary pattern determination module may include a first matching signal generation unit for indicating that patterns match if the received EEG coincides with a primary pattern, and a second matching signal generation unit for indicating inconsistency when the received EEG mismatches with the primary pattern 1 error signal generation unit.

The secondary pattern determination module determines the secondary pattern only when the primary pattern determination module determines that the patterns match, and when the received EEG coincides with the secondary pattern, 2 match signal generating unit and a second error signal generating unit for indicating inconsistency when the received EEG does not coincide with the second pattern.

The EEG analysis unit may further include an amplification module for receiving the received EEG signal.

The EEG analyzing unit may further include a filter module for removing noise included in an EEG signal and an AD change module for converting an analog signal into a digital signal.

The EEG analyzing unit may further include a Fourier transform unit for Fourier transforming the EEG data converted into digital data and separating the received EEG into sinusoidal waves.

As described above, according to the present invention, an electronic device can be driven according to a change in brain waves. In addition, it is possible to drive the electronic device by confirming the user's intention more accurately according to the generation of the question, the affirmation of the question, and the judgment of the negative intention.

1 is a block diagram illustrating an electronic device driving apparatus using an EEG according to a first embodiment of the present invention.
2 is a flowchart illustrating a method of driving an electronic device using an EEG according to the first 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.

1 is a block diagram illustrating an electronic device driving apparatus using an EEG according to a first embodiment of the present invention.

Referring to FIG. 1, an electronic device driving apparatus 200 using an EEG according to the first embodiment includes an EEG receiving unit 210, an EEG analyzing unit 220, a pattern storing module 231, a pairing determining module 233, and pattern determination modules 235, 237.

The EEG receiving unit 210 attaches a plurality of electrodes to the user's scalp 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 receiving unit 210 selects and receives brain waves for the frontal region of the user 10 except the EEG or the frontal lobe. The EEG receiving unit 210 may have a band shape and may include a hat 20. The EEG receiving unit 210 may be an electrode connected to a smart phone and a data cable.

The EEG analyzing unit 220 classifies and extracts EEG types according to frequencies from the EEG received from the received EEG, and extracts alpha waves, beta waves, seta waves, delta waves, and gamma waves from the received EEG. The EEG analysis unit 220 includes an amplification module 221, a filter module 223, an A / D conversion module 225, and a Fourier transform module 227.

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 A / D conversion module 224 digitizes the EEG in the analog state extracted through the filter module 223. The Fourier transform module 227 performs Fourier transform on the EEG-converted EEG data and separates the received EEG into sinusoidal waves.

The pairing determination module 233, the primary pattern determination module 235 and the secondary pattern determination module 237 compares the increase and decrease of the alpha wave, beta wave, theta wave, and gamma wave among the EEG signals, The change is compared with the pre-stored pattern to judge whether or not the pattern matches.

The pattern storage module 231 stores a predetermined EEG pattern. The pattern storage module stores a pairing pattern for connection with an electronic device and a driving pattern for driving the electronic device. The driving pattern includes a primary pattern and a secondary pattern, and the primary pattern and the secondary pattern are formed in different patterns and are sequentially judged. The EEG change pattern may be composed of a change pattern of an alpha wave, a change pattern of an SMR wave, a change pattern of a middle beta wave, a change pattern of a high beta wave, a change pattern of a setta wave, a change pattern of a gamma wave, or a combination thereof.

The pairing determination module 233 includes a pairing pattern search unit 233a, a pairing signal generation unit 233b, and a pairing display unit 233c. The pairing pattern search unit 233a searches the pattern storage module 231 for the occurrence of an EEG coinciding with an EEG pattern stored in a pairing pattern. The pairing pattern is formed by an EEG pattern generated during an operation for intensively watching one place . That is, when the user keeps watching the TV, a change of the brain waves occurs, and the pairing pattern search unit 233a detects the change of the brain waves.

The pairing signal generating unit 233b transmits the pairing signal to the electronic device, and switches the electronic device to the standby state so that the electronic device can receive the driving signal. The pairing display unit 233c uses a sound or an LED lamp to inform that the pairing is being executed. Therefore, the user can confirm that the device can be driven according to his / her intention and take the thought or action for the generation of brain waves.

The primary pattern determination module 235 determines whether or not the primary pattern stored in the pattern storage module 231 and the received EEG change match. The primary pattern determination module 235 determines whether there is a discrepancy when the received EEG signal is inconsistent with the primary pattern and the first matching signal generation unit 235a that indicates that the patterns coincide when the received EEG coincides with the primary pattern And a first error signal generation unit 235b.

When a match signal is generated in the first match signal generating unit 235a, the user can perform an action of generating a second pattern. If an error signal is generated in the first error signal generating unit 235b, It is possible to judge again by performing an action of generating a difference pattern.

The secondary pattern determination module 237 determines the secondary pattern only when the primary pattern determination module 235 determines that the patterns coincide with each other and determines the secondary pattern stored in the pattern storage module 231, And judges whether or not the changes coincide with each other. The secondary pattern determination module 237 determines whether or not the received EEG signal matches the secondary pattern to indicate that the patterns match, and a disagreement when the received EEG signal is inconsistent with the secondary pattern And a second error signal generation unit 237b.

When the coincidence signal is generated in the second coincidence signal generating unit 237a, the user can confirm that the normal EEG has been generated and authenticated. If an error signal is generated in the second error signal generating unit 237b, It is possible to judge again by performing an action of generating a difference pattern.

2 is a flowchart illustrating a method of driving an electronic device using an EEG according to the first embodiment of the present invention.

Referring to FIG. 5, the electronic device driving method using the EEG according to the first embodiment includes an EEG reception step S201, an EEG analysis step S202, a pairing determination step S203, a primary pattern determination step S204), and a secondary pattern determination step (S205).

The EEG receiving step (S201) is performed by the EEG receiving unit 210, attaches a plurality of electrodes to the user's scalp, 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 receiving step (S201) may receive EEG for the frontal region of the user, such as brain waves, or EEG for regions other than the frontal lobe.

The EEG receiving unit 210 may have a band shape and a hat shape. The EEG receiving unit 210 may be an electrode connected to a smart phone and a data cable.

The EEG analysis step (S202) classifies and extracts the types of EEG according to frequency from the EEG received from the received EEG, and extracts alpha, beta, ceta, delta, and gamma waves from the received EEG. The EEG analysis step S202 includes an amplification step, a filtering step, an AD conversion step and a Fourier transform step.

The amplifying step is performed by the amplifying module 221 and amplifies the brain waves of several tens of μV to tens of mV received by the EEG receiving unit 210 to 3 to 5 V by using an amplifier.

The filtering step is performed by the filter module 223 and filters various noise included in the EEG amplified by using a plurality of analog filters. In this case, the filter may be a high pass filter, a band pass filter, a band stop filter, or a low pass filter. The filtering step includes a high-pass filtering step of first removing noise due to DC voltage, respiration, body motion, eye blinking, and the like using a high-pass filter, and an EEG And a band pass filtering step of filtering the received signal.

In the filtering step, a band-stop filtering step of removing noise due to power supply of 50 Hz or 60 Hz using a band-stop filter and a bandpass filtering of a low-pass filter are used to prevent distortion, And a low-pass filtering step for preventing the low-pass filter.

The A / D conversion step digitizes the EEG in the analog state using the A / D conversion module 225. In the Fourier transform step, the digital EEG data is Fourier transformed to separate the received EEG into sinusoidal waves.

The pairing determination step (S203) is performed by the pairing determination module 233 and includes a pairing pattern search step, a pairing signal generation step, and a pairing display step.

In the matching pattern searching step, whether a pairing pattern is generated or not is detected in the pattern storing module 231 to determine whether an EEG coincides with an EEG pattern stored in a pairing pattern. The pairing pattern can be formed by an EEG pattern generated during an operation of concentrating on one place. That is, when the user keeps watching the TV, a change in the brain waves occurs, and the pairing pattern detection step detects the change in the brain waves.

In the pairing signal generation step, the pairing signal is transmitted to the electronic device, and the electronic device switches to the standby state so that the electronic device can receive the driving signal. The pairing display step uses a sound or an LED lamp to indicate that the pairing is being executed.

The primary pattern determination step S204 is performed by the primary pattern determination module 235 and determines whether the primary pattern stored in the pattern storage module 231 is consistent with the received brain waves.

The primary pattern determination step S204 includes a first matching signal generation step for indicating that the patterns coincide when the received EEG coincides with the primary pattern and a first matching signal generation step for generating a disagreement when the received EEG does not coincide with the primary pattern 1 error signal generation step.

The secondary pattern determination step S205 determines the secondary pattern only when it is determined that the patterns match in the primary pattern determination step S204. The secondary pattern determination step S205 determines the secondary pattern stored in the pattern storage module 231, And judges whether or not the changes coincide with each other. The second pattern determination step S205 includes a second coincidence signal generation step of indicating that the patterns coincide when the received EEG coincides with the second pattern, a second coincidence signal generation step of generating a coincidence signal when the received EEG does not coincide with the second pattern 2 error signal generation step.

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.

200: Electronic device driving device
210: EEG receiver
220: EEG analysis unit
221: Amplification module
223: Filter module
223: AD conversion module
227: Fourier transform module
231: Pattern storage module
233: Pairing decision module
233a: Pairing Pattern Retrieval
233b: Pairing signal generating unit
233c: Pairing display unit
235: primary pattern determination module
235a: first match signal generation unit
235b: first error signal generation unit
237: Secondary pattern determination module
237a: second primary signal generating unit
237b: second error signal generation unit

Claims (10)

An EEG receiving unit attached to the user and receiving an EEG;
An EEG analyzing unit for classifying and extracting EEG according to frequency from the received EEG; And
A pattern storage module for storing a pairing pattern for connection between an EEG and an electronic device and a driving pattern for driving the electronic device;
A pairing judgment module for judging whether the change of the brain waves coincides with the pairing pattern; And
And a drive pattern determination module for determining whether or not the received pattern changes with the drive pattern stored in the pattern storage module,
Wherein the drive pattern comprises a plurality of drive patterns,
The pattern storage module stores different primary patterns and secondary patterns. The pattern comparison module includes a primary pattern determination module for determining whether the received EEG coincides with the primary pattern, and a primary pattern determination module for determining whether the received EEG matches the secondary pattern Wherein the primary pattern determination module includes a first matching signal generation unit for indicating that patterns match if the received EEG coincides with a primary pattern, And a first error signal generation unit for indicating a discrepancy when there is a discrepancy, wherein the secondary pattern determination module determines a secondary pattern only when the primary pattern determination module determines that the pattern matches, A second coincidence signal generating unit for indicating that the patterns coincide when the EEG coincides with the second pattern, and a second error signal generating unit for indicating inconsistency when the received EEG does not coincide with the second pattern Wherein the electronic device is an electronic device using an EEG.
The method according to claim 1,
Wherein the drive pattern determination module determines that the patterns match if the increase and decrease of the alpha waves are repeated twice within a predetermined period.
The method according to claim 1,
The driving pattern judging module judges that the pattern matches when the pattern of the activity of the left parietal lobe is increased and the activity of the left / right frontal lobe is lowered twice or more within a predetermined time Wherein the electronic device is an electronic device using an EEG.
The method according to claim 1,
Wherein the drive pattern determination module determines that the pattern matches when the increase of the SMR wave and the middle beta wave is repeated twice within a preset period.
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