KR20170026880A

KR20170026880A - Smart phone application and smart phone pairing apparatus using using brain wave

Info

Publication number: KR20170026880A
Application number: KR1020150122603A
Authority: KR
Inventors: 송지성; 박수조; 지영현; 안정기; 최용준; 송상호
Original assignee: 한양대학교 에리카산학협력단; 송지성; 송상호; 안정기; 최용준; 박수조; 지영현
Priority date: 2015-08-31
Filing date: 2015-08-31
Publication date: 2017-03-09
Also published as: KR101831757B1

Abstract

The present invention provides a smartphone application and a smartphone pairing device using an EEG that can easily operate a smartphone using an EEG by pairing a smartphone with an EEG.
The smartphone application using EEG according to an aspect of the present invention includes an EEG analysis module for classifying and extracting EEGs according to frequencies from received EEG waves and a rule analyzing module for recognizing changes in EEGs and determining whether they match the pre- Module, a pairing execution module for executing an interaction between the brain wave and the smartphone, and a smartphone driving module for executing a command for driving the smartphone according to a change in the brain wave signal.

Description

TECHNICAL FIELD [0001] The present invention relates to a smart phone pairing apparatus and a smart phone pairing apparatus,

The present invention relates to a smartphone application and a smartphone pairing apparatus, and more particularly, to a smartphone application and a smartphone pairing apparatus using brain waves.

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.

An object of the present invention is to provide a smartphone pairing apparatus using an EEG capable of pairing a brain wave with a smartphone to drive a smartphone using brain waves.

The smartphone application using EEG according to an aspect of the present invention includes an EEG analysis module for classifying and extracting EEGs according to frequencies from received EEG waves and a rule analyzing module for recognizing changes in EEGs and determining whether they match the pre- Module, a pairing execution module for executing an interaction between the brain wave and the smartphone, and a smartphone driving module for executing a command for driving the smartphone according to a change in the brain wave signal.

The smartphone driving module includes a command storage unit for storing command signals input to the smartphone in a time zone, an EEG pattern for executing a command stored in a predetermined time range, And a habit instruction deciding unit for comparing the habit instruction deciding unit.

The command storage unit may store a command signal and an EEG pattern for executing the command signal.

The habit command deciding unit sequentially compares the input EEG signal with the EEG pattern stored in the first time range, the second time range and the third time range, and the first time range is smaller than the second time range, The third time range is made larger than the second time range.

The habit command deciding unit may compare an input EEG signal with an EEG pattern for executing an instruction stored in the first time range and generate an EEG pattern for executing the stored EEG pattern and the stored command within the first time range Comparing the inputted EEG pattern with an EEG signal for executing a command stored in the second time range if the EEG pattern does not coincide with the inputted EEG pattern, It is possible to compare the input brain wave signal with the brain wave pattern for executing the command stored in the third time range.

According to another aspect of the present invention, there is provided an apparatus for pairing a smartphone using an EEG, including an EEG receiving unit attached to a user and receiving an EEG, a EEG transmitting unit for transmitting received EEG to a smart phone, And a pairing module for executing interlocking between the brain waves and the smartphone and a module for executing the smartphone according to the change of the brain wave signal. And a smartphone application module that executes a command to execute the command.

Here, the smartphone application may include a pairing strength indicator for indicating the intensity of the received EEG signal.

The rule determination module may include a first pattern determiner for comparing the first EEG pattern with the received EEG to determine whether they match.

The rule determination module may include a second pattern determiner for comparing the second EEG pattern with the received EEG to determine whether they match.

In addition, the rule determination module may include a third pattern determiner for comparing the third EEG pattern with the received EEG to determine coincidence.

In addition, the first EEG pattern may include a step of increasing an alpha wave, a step of decreasing an alpha wave and an increase of a beta wave, a step of decreasing a beta wave and increasing an alpha wave.

In addition, the second EEG pattern may include a step of increasing delphas, a step of decreasing a delta wave, and a step of increasing a beta wave.

In addition, the third EEG pattern may be a change of EEG caused by the movement of the eye.

In addition, the first EEG pattern may be a change of EEG caused by the movement of the mouth.

In addition, the second brain wave pattern may be a change in brain waves caused by movement of a hand.

In addition, the smartphone driving module may include a command storage unit for storing command signals input to the smartphone in a time zone, an EEG pattern for executing commands stored in a predetermined time range, And a habit command decision unit for comparing the signals.

The habit command deciding unit sequentially compares the input EEG signal with the EEG pattern stored in the first time range, the second time range and the third time range, and the first time range is smaller than the second time range, The third time range may be larger than the second time range.

Also, the first time range may be 30 minutes, the second time range may be 1 hour, and the third time range may be 3 hours.

As described above, according to the present invention, it is possible to pair the EEG and the smartphone more easily. In addition, it is possible to quickly operate the smartphone using the brain wave by comparing the driving command and the brain wave pattern habitually performed according to time.

FIG. 1 is an explanatory diagram showing a smartphone pairing apparatus using brain waves according to an embodiment of the present invention.
2 is a block diagram of a smartphone pairing apparatus using brain waves according to an embodiment of the present invention.
3 is a flowchart illustrating a smartphone pairing method according to an embodiment of the present invention.
4 is a diagram illustrating a pairing intensity indicator according to an embodiment of the present invention.
5 is a diagram for explaining EEG patterns.

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 is to be understood, however, that the invention is not to be limited to the specific 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 view showing a living room to which an electronic apparatus driving apparatus according to the present invention is applied, and FIG. 2 is a configuration diagram illustrating an electronic apparatus driving apparatus using an EEG according to a first embodiment of the present invention.

1 and 2, the smartphone pairing apparatus 100 using the EEG according to the first embodiment includes an EEG receiving unit 110, an EEG transmitting unit 120, and a smartphone application 130 do. The smartphone application 130 includes an EEG analysis module 131, a pairing strength indicator 133, a rule determination module 132, a pairing execution module 134, and a smartphone driver module 135.

The EEG receiving unit 110 comprises an apparatus for receiving an EEG attached to a user. The EEG receiving unit 110 may attach a plurality of electrodes to the scalp of the user 10 and receive the brain waves of the user 10 through the electrodes. In addition, the brain-wave receiving unit 110 can indirectly measure brain waves using ultraviolet rays, infrared rays, or the like. The EEG receiving unit 110 may be a headphone 20, a hair band, or a pair of glasses, and may be a hat. The EEG receiving unit 110 may be an electrode connected to a smart phone and a data cable. The brain-wave transmitting unit 120 transmits brain waves to the smartphone 30 using wired / wireless communication.

The smartphone application 130 analyzes the received EEG, performs pairing with the smartphone 30, receives the EEG in the paired state, and drives the smartphone 30.

The EEG analysis module 131 classifies and extracts the EEG according to the frequency from the received EEG. Extracts alpha waves, beta waves, theta waves, delta waves, and gamma waves from the received EEG. The EEG analysis module 131 includes an amplification unit 131a, a filter unit 131b, and an AD conversion unit 131c.

The amplification unit 131a has an internal amplifier and amplifies the brain waves of several tens of μV to several 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 unit 131b includes a plurality of analog filters to filter various noise included in the brain waves amplified by the amplification unit 131a. 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 unit 131c digitizes the brain waves in the analog state extracted through the filter unit 131b.

4 is a diagram illustrating a pairing intensity indicator according to an embodiment of the present invention.

Referring to FIGS. 2 and 4, the pairing intensity display unit 133 displays the intensity of the received EEG signal. The pairing intensity display section 133 displays the pairing intensity so that the color is filled in accordance with the intensity of the brain waves on the figure indicating the shape of the human head.

5 is a view showing EEG patterns.

Referring to FIG. 2 and FIG. 5, the rule determination module 132 determines whether or not it matches the pre-stored EEG rules. The rule determination module 132 compares the first EEG pattern with the received EEG to determine whether they match or not. The first pattern determiner 132a compares the second EEG pattern with the received EEG, A second pattern determiner 132b, and a third pattern determiner 132c for comparing the third EEG pattern with the received EEG to determine whether they match.

Here, the first EEG pattern may include a step of increasing the alpha wave, a step of decreasing the alpha wave and an increase of the beta wave, a step of decreasing the beta wave and an increase of the alpha wave. That is, the first EEG pattern may have a pattern in which the alpha wave is increased, the alpha wave is decreased, the beta wave is increased, then the beta wave is decreased and the alpha wave is increased.

The second EEG pattern may include a step in which delphas are increased, a step in which the delta wave is decreased and a beta wave is increased. The third EEG pattern is a change in the EEG caused by the movement of the eye. When the eyes move or frown, a unique pattern of EEG changes appears, and the third pattern determiner 132c determines whether such a change occurs.

In addition, the first EEG pattern can be formed by a change in the EEG caused by the movement of the mouth, and the second EEG pattern can be formed by the change in the EEG caused by the movement of the hand.

The rule determination module 132 determines whether the second EEP pattern matches if the first EEP pattern matches, and determines whether the third EEP pattern matches if the second EEP pattern coincides.

The pairing execution module 134 performs an interlocking operation between the EEG and the smartphone 30 when it is determined that the EEG patterns coincide with each other, thereby preparing to receive a driving command by the EEG.

The smartphone driving module 135 executes a command for driving the smartphone according to the change of the brain wave signal. The smartphone driving module 135 includes an instruction storage unit 135a and a habit instruction deciding unit 135b.

The command storage unit 135a stores command signals input to the smartphone 30 for each time slot, and also stores a command signal and an EEG pattern for executing the command signal. The EEG pattern that executes the command signal may be an EEG pattern generated when the user desires to execute the command, and may be an EEG pattern that is intentionally generated.

The habit command deciding unit 135b sequentially compares the inputted EEG signal with the EEG pattern stored in the first time range, the second time range and the third time range. Wherein the first time range is less than the second time range, the third time range is greater than the second time range, the first time range may be 30 minutes, the second time range may be one hour, The time range may be 2 hours.

The habit command deciding unit 135b compares the input EEG signal with the EEG pattern for executing the command stored in the first time range and compares the inputted EEG pattern with the EEG pattern for executing the stored command stored in the first time range If the input EEG pattern and the EEG pattern for executing the stored command stored in the second time range do not coincide with each other, the third time range And compares the inputted EEG signal.

When the smartphone 30 is driven using the brain waves, only the commands stored in the brain wave pattern can be executed. However, in the case of many stored EEG patterns, searching and executing an exact matching EEG pattern not only takes a long time, but also has a problem in that it is difficult to search for an identical EEG. However, since users tend to execute a specific instruction at a specific time, the instruction to be executed by the user is stored for 24 hours, and the EEG pattern of the frequently executed instruction is compared with the input EEG pattern at the same time, . According to this, the drive command can be executed more quickly.

3 is a flowchart illustrating a smartphone pairing method according to an embodiment of the present invention.

Referring to FIGS. 2 and 3, the smartphone pairing method according to the present embodiment includes an EEG reception step S101, an EEG transmission step S102, an EEG analysis step S103, a rule determination step S104, Step S105, displaying the pairing strength (S106), determining a habit command (S107), and command driving step (S108).

The EEG receiving step S101 receives the user's brain waves using the EEG receiving unit 110 having the EEG sensor. The EEG transmission step (S102) transmits the EEG received through the wire / wireless communication method to the smartphone.

The EEG analysis step (S103) classifies and extracts EEGs according to frequencies from the received EEG. In the step of analyzing EEG waves (S103), the received EEG is amplified and filtered to extract the alpha waves, beta waves, theta waves, delta waves, and gamma waves from the received EEG.

The rule determination step (S104) includes a first pattern determination step of comparing the first EEP pattern and the received EEPROM to determine whether they match or not, a second pattern determination step of comparing the second EEP pattern with the received EEPROM, And a judgment step. In addition, the rule determining step may further include a third pattern determining step of comparing the third EEG pattern with the received EEG to determine whether the third EEG pattern matches or not.

The first pattern determining step may determine whether or not an EEG caused by the mouth motion exists, and the second pattern determining step may determine whether EEG caused by the hand motion is present. In addition, the third pattern determination step determines whether or not an EEG caused by eye movement exists.

In the pairing execution step S105, when it is determined that the EEG patterns are coincident, the EEPROM is interlocked with the smartphone 30 to prepare to receive a driving command by the EEPROM.

The pairing strength display step (S106) displays the intensity of the received EEG signal. The pairing intensity display step (S106) displays the pairing intensity so that colors are filled in accordance with the intensity of the brain waves on the figure indicating the shape of the human head.

The habit command decision step S107 compares the inputted EEG signal with the EEG pattern stored in the first time range, the second time range and the third time range. Wherein the first time range is smaller than the second time range and the third time range is greater than the second time range. Also, the first time range may be 30 minutes, the second time range may be 1 hour, and the third time range may be 3 hours.

The habit command decision step S107 compares the input EEG signal with the EEG pattern for executing the command stored in the first time range and compares the input EEG pattern with the EEG pattern for executing the stored command stored in the first time range The EEPROM compares the inputted EEG pattern with the EEG pattern for executing the stored command stored in the second time range. If the EEG pattern does not coincide with the inputted EEG pattern, And compares the inputted EEG signal with the EEG pattern that executes the command stored within the time range.

In the command driving step S108, when an EEG signal coinciding with the EEG pattern of the command signal stored in the time range described above is input, the command driving step executes an instruction to drive the smart phone according to the EEG signal change.

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: Smartphone pairing device
110: EEG receiver
120: EEG transmission unit
130: Smartphone application
131: EEG analysis module
131a:
131b:
131c: AD conversion section
132: Rule Judgment Module
132a: a first pattern determination unit
132b: the second pattern determiner
132c: the third pattern determination unit
133: Strength indicator
134: Pairing execution module
135: Smartphone-powered module
135a: command storage unit
135b: habit command deciding unit
20: Headphones
30: Smartphone

Claims

An EEG analysis module for classifying and extracting EEG according to frequencies from the received EEG; and a rule decision module for recognizing the change of the EEG and determining whether the EEG matches the previously stored EEG rules.
A pairing execution module for executing an interaction between an EEG and a smartphone; And
A smartphone driving module for executing a command for driving a smartphone according to an EEG signal change;
And a smartphone application using the EEG.

The method according to claim 1,
The smartphone driving module includes a command storage unit for storing command signals input to a smart phone in a time zone, an EEG pattern for executing commands stored in a predetermined time range, and an input EEG signal And a habit instruction deciding unit for comparing the haptic command and the haptic command.

3. The method of claim 2,
Wherein the command storage unit stores a command signal and a brain wave pattern for executing the command signal.

The method of claim 3,
Wherein the habit instruction deciding unit sequentially compares the EEG pattern stored in the first time range, the second time range and the third time range with the inputted EEG signal, the first time range being smaller than the second time range, Wherein the third time range is greater than the second time range.

5. The method of claim 4,
Wherein the habit instruction deciding unit compares an input EEG signal with an EEG pattern for executing an instruction stored in the first time range, and if the EEG pattern for executing the stored instruction stored in the first time range does not match And comparing the inputted EEG pattern with an EEG signal for executing a command stored in the second time range, and if the input EEG pattern does not coincide with the EEG pattern executing the stored command stored in the second time range, And comparing the input EEG signal with an EEP pattern for executing an instruction stored in the third time range.

An EEG receiving unit attached to the user and receiving an EEG;
A brain wave transmission unit for transmitting the received brain waves to a smartphone; And
An EEG analysis module for classifying and extracting EEGs according to frequency from the received EEG, a rule determination module for determining whether the EEG changes are recognized by recognizing the change of the EEG, and a pairing execution module for executing interlocking between the EEG and the smartphone And a smartphone application module for executing a command for driving a smartphone according to a change in an EEG signal;
And a controller for controlling the pairing of the smartphone using the EEG.

The method according to claim 6,
Wherein the smartphone application includes a pairing intensity indicator for displaying the intensity of the received EEG signal.

The method according to claim 6,
Wherein the rule judging module includes a first pattern determiner for comparing the first EEG pattern with the received EEG to determine whether they match or not.

9. The method of claim 8,
Wherein the rule judging module includes a second pattern determiner for comparing the second EEG pattern with the received EEG to determine whether they match or not.

10. The method of claim 9,
Wherein the rule judging module includes a third pattern determiner for comparing the third EEG pattern with the received EEG to determine whether they match or not.

11. The method of claim 10,
Wherein the first EEG pattern includes steps of increasing alpha waves, decreasing alpha waves and increasing beta waves, decreasing beta waves, and increasing alpha waves. .

12. The method of claim 11,
Wherein the second EEG pattern includes a step of increasing delphas, a step of decreasing delta waves, and a step of increasing beta waves.

13. The method of claim 12,
Wherein the third EEG pattern is a change in EEG caused by movement of the eye.

14. The method of claim 13,
Wherein the first EEG pattern is a change in EEG caused by movement of the mouth.

15. The method of claim 14,
Wherein the second EEG pattern is a change in EEG caused by movement of a hand.

The method according to claim 6,
The smartphone driving module includes a command storage unit for storing command signals input to a smart phone in a time zone, an EEG pattern for executing commands stored in a predetermined time range, and an input EEG signal And a habit command deciding unit for comparing the haptic command and the haptic command.

17. The method of claim 16,
Wherein the command storage unit stores a command signal and a brain wave pattern for executing the command signal together.

18. The method of claim 17,
Wherein the habit instruction deciding unit sequentially compares the EEG pattern stored in the first time range, the second time range and the third time range with the inputted EEG signal, the first time range being smaller than the second time range, And the third time range is greater than the second time range.

19. The method of claim 18,
Wherein the habit instruction deciding unit compares an input EEG signal with an EEG pattern for executing an instruction stored in the first time range, and if the EEG pattern for executing the stored instruction stored in the first time range does not match And comparing the inputted EEG pattern with an EEG signal for executing a command stored in the second time range, and if the input EEG pattern does not coincide with the EEG pattern executing the stored command stored in the second time range, And comparing the input EEG signal with an EEP pattern for executing a command stored in a third time range.

20. The method of claim 19,
Wherein the first time range is 30 minutes, the second time range is 1 hour, and the third time range is 3 hours.