KR20160095252A - Electronic equipment control device using positive or negative brain wave - Google Patents

Abstract

The present invention provides an electronic device driving apparatus capable of driving an electronic device by using a brain wave. According to an aspect of the present invention, the electronic device driving apparatus using a brain wave includes: a brain wave receiving unit attached to a user to receive a brain wave; a brain wave analyzing unit classifying the brain wave based on a frequency from the received brain wave and extracting the brain wave; a pattern comparing unit comparing a change in the extracted brain wave with a prestored pattern to determine whether or not the change in the extracted brain wave corresponds to the prestored pattern; and a drive determining unit generating a question and determining a positive or negative intention for the question to generate a drive signal of the electronic device.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to an apparatus for driving an electronic device using positive or negative brain waves,

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 positive or negative 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.

The present invention provides an electronic apparatus driving apparatus capable of driving an electronic apparatus using positive or negative brain waves.

According to an aspect of the present invention, there is provided an apparatus for driving an electronic device using an EEG, the EEG apparatus including an EEG receiver for receiving an EEG, a EEG analyzing unit for classifying and extracting EEG according to a frequency from received EEG, A pattern comparing unit for comparing the stored pattern with a previously stored pattern, and a drive determining unit for generating a question and generating a driving signal of the electronic device by determining whether the question is affirmative or negative.

The pattern comparison unit may include a pattern storage module in which a pairing pattern for connection with an electronic device and a drive pattern for driving the electronic device are stored.

The pattern comparison unit may include a pairing determination module that determines that a change in brain waves matches a pairing pattern.

The pairing determination module includes a pairing pattern search unit for searching for whether a pairing pattern is generated, and a pairing signal generation unit for transmitting a pairing signal to the electronic device when the pairing pattern is generated to wait for the electronic device to receive a drive signal can do.

The pairing determination module may include a pairing display unit for notifying that the pairing is being performed using a sound or an LED lamp.

The pattern comparison unit may include a drive pattern determination module that determines whether the received pattern changes with the drive pattern stored in the pattern storage module.

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 period of stunning.

The driving determination unit may include a question generation module for generating and displaying a question and a judgment module for determining the generation of positive EEG or negative EEG for the question.

The positive decision module uses the synchronization rate, which is a variable indicating the direction of rotation in the phase space consisting of the EEG components measured at two places and a variable indicating the degree of simultaneous increase or decrease of EEG measured at two places, You can judge a doctor or a negative opinion.

로 정의되며, 여기서, 상기 s1과 s2는 두 위치에서 측정된 뇌파 신호, 상기 H(x)는 x가 음수이거나 0일 때에는 0, 양수일 때는 1의 값을 갖는 스텝 함수, 및 상기 w는 동기율을 계산하는 구간 크기로 이루어질 수 있다.The synchronization rate

(X) is a step function having a value of 0 when x is negative or 0, and a positive value when x is positive, and w is a step function having a synchronization rate And the size of the interval for calculating the distance.

로 정의되며, 여기서 상기 P(t)는 편향성, 상기 벡터 s는 s1과 s2로 이루어진 2차원 벡터, 상기 단위 벡터 θ는 s1과 s2로 이루어지는 위상공간에서의 원점을 중심으로 시계 반대 방향으로 회전하는 방향의 단위 벡터로 이루어질 수 있다.The bias

, Wherein P (t) is biased, the vector s is a two-dimensional vector consisting of s1 and s2, and the unit vector [theta] is rotated counterclockwise about the origin in the phase space consisting of s1 and s2 Direction unit vector.

The drive determination unit may include a drive signal generation module that generates an ON signal for activating the electronic device or an OFF signal for deactivating the electronic device.

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 view showing a living room to which an electronic apparatus driving apparatus according to the present invention is applied.
2 is a block diagram illustrating an electronic device driving apparatus using an EEG according to a first embodiment of the present invention.
3 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.

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, an electronic device driving apparatus 100 using an EEG according to the first embodiment includes an EEG receiving unit 110, an EEG analyzing unit 120, a pattern comparing unit 130, And a drive determination unit 140.

The electronic device driving apparatus 100 using the EEG according to the first embodiment is configured such that the user 10 is sitting on a couch in a living room or a living room or the like and uses the hat 20 equipped with an EEG detector, , A lamp, an audio, and so on.

The EEG receiving unit 110 attaches a plurality of electrodes to a 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 110 selects and receives EEG for the region excluding the EEG or the frontal lobe of the frontal region of the user 10. [ The EEG receiving unit 110 may be formed in a band shape and may include a cap 20. The EEG receiving unit 110 may be an electrode connected to a smart phone and a data cable.

The EEG analyzing unit 120 classifies and extracts EEG types according to frequency from 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 120 includes an amplification module 121, a filter module 123, an AD conversion module 125, and a Fourier transformation module 127.

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 124 digitizes the EEG in the analog state extracted through the filter module 123. The Fourier transform module 127 performs Fourier transform on the EEG-converted EEG data and separates the received EEG into sinusoidal waves.

The pattern comparison unit 130 compares the increase / decrease of the alpha wave, beta wave, theta wave, and gamma wave among the EEG signals, and compares the extracted EEG changes with pre-stored patterns to determine coincidence. The pattern comparison unit 130 includes a pattern storage module 131, a pairing determination module 133, and a drive pattern determination module 135.

The pattern storage module 131 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 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.

For example, when a number is counted from 1 to 10 in the head, and when a national anthem is called into the head, different brain waves are generated. The pattern of change of the brain waves is stored in the pattern storage module 131. In addition, patterns of EEG that change when eyes are closed and patterns of EEG that change when recognizing characters or pictures are stored in the pattern storage module. The pattern is set such that the same pattern is repeated at least twice during a predetermined time, and the time can be set in various ranges from 1 second to 1 minute. (Judges contrast)

The pairing determination module 133 includes a pairing pattern search unit 133a, a pairing signal generation unit 133b, and a pairing display unit 133c. The pairing pattern search unit 133a searches the pattern storage module 131 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, the illumination, etc., a change of the brain waves occurs, and the pairing pattern search unit 133a detects the change of the brain waves. When one spot is concentrated, the intensity of the SMR wave and the middle beta wave increases and the intensity of the setta wave decreases. When the change of the EEG wave occurs, the pairing pattern search unit 133a determines that the pairing pattern exists.

The pairing signal generating unit 133b 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 133c informs that the pairing is being executed using a sound or an LED lamp. 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 drive pattern determination module 135 determines whether the drive pattern stored in the pattern storage module 131 matches the change of the received EEG. The driving pattern determination module 135 determines that the patterns match when the increase and decrease of the alpha waves are repeated twice or more within the stunning period. When the user repeats the operation of closing and closing the eyes at intervals of 3 seconds, the alpha wave increases in the closed eye and the alpha wave decreases in the closed eye. The change pattern of the alpha wave is stored in the pattern storage module 131, The drive pattern determination module 135 can determine whether the pattern matches.

The driving determination unit 140 includes a question generation module 141, a determination module 142, and a driving signal generation module 143. The question generation module 141 generates a question by displaying a character on the screen or generating a sound. The question may be answered by asking whether or not the device should be operated.

The positive decision module 142 diagnoses the occurrence of positive EEG or negative EEG for the question. Since the change of the beta wave in the negative EEP is more obvious than the positive EEP, the positive decision module 142 can judge whether or not the EEP of the EEG occurs. In addition, the aptitude determination module 142 calculates the temporal and spatial correlation of brain waves to determine whether they are positive brain waves or negative brain waves. The affirmative decision module 142 can determine the positive and negative by calculating the bias and the synchronization rate and using it as a logical decision variable of the neural network. Here, the bias refers to the direction of rotation in the phase space composed of EEG components measured at two places, and the synchronization rate is a variable indicating the degree of simultaneous increase or decrease of EEG measured at two places.

로 정의되며, 여기서, 상기 s1과 s2는 두 위치에서 측정된 뇌파 신호, 상기 H(x)는 x가 음수이거나 0일 때에는 0, 양수일 때는 1의 값을 갖는 스텝 함수, 및 상기 w는 동기율을 계산하는 구간 크기이다.The synchronization rate

(X) is a step function having a value of 0 when x is negative or 0, and a positive value when x is positive, and w is a step function having a synchronization rate .

로 정의되며, 여기서 상기 P(t)는 편향성, 상기 벡터 s는 s1과 s2로 이루어진 2차원 벡터, 상기 단위 벡터 θ는 s1과 s2로 이루어지는 위상공간에서의 원점을 중심으로 시계 반대 방향으로 회전하는 방향의 단위 벡터이다. On the other hand,

, Wherein P (t) is biased, the vector s is a two-dimensional vector consisting of s1 and s2, and the unit vector [theta] is rotated counterclockwise about the origin in the phase space consisting of s1 and s2 Direction unit vector.

The positive decision module 142 determines the positive and negative by assigning the synchronization rate and bias to the variables of the classification method such as the neural network and the linear decision function. The synchronization rate and bias can be used individually, and both variables can be input. The neural network consists of a multilayer perceptron with an input layer, a hidden layer, and a node level output layer, and is already learned for logic judgment.

The drive signal generation module 143 generates a drive signal for switching the electronic device to the ON state when it is determined in the affirmative determination module 142 to be affirmative. The driving signal generation module 143 may generate infrared rays, and may transmit signals through wireless communication such as Bluetooth or Wi-Fi.

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

1 and 3, a method of driving an electronic device using an EEG according to the first embodiment includes EEG reception step S101, EEG analysis step S102, pairing determination step S103, A step S104, a question generating step S105, and a judgment step S106.

The EEG receiving step S101 is performed by the EEG receiving unit 110 and attaches a plurality of electrodes to the user's scalp to receive 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 (S101) can receive the EEG for the frontal region of the user and the EEG for the region excluding the frontal lobe.

The EEG receiving unit 110 may have a band shape and a hat shape. The EEG receiving unit 110 may be an electrode connected to a smart phone and a data cable.

The step of analyzing EEG (S102) classifies and extracts the types of EEG according to frequencies from the EEG received from the received EEG, and extracts the alpha waves, beta waves, theta waves, delta waves, and gamma waves from the received EEG. The EEG analysis step S102 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 121 and amplifies the brain waves of several tens of μV to tens of mV received by the EEG receiving unit 110 to 3 to 5 V by using an amplifier.

The filtering step is performed by the filter module 123 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 125. In the Fourier transform step, the digital EEG data is Fourier transformed to separate the received EEG into sinusoidal waves.

The pairing determination step (S103) is performed by the pairing determination module 133 and includes a pairing pattern search step, a pairing signal generation step, and a pairing display step.

In the matching pattern searching step, whether or not a pairing pattern is generated is searched for in the pattern storage module 131 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 drive pattern determination step (S104) is performed by the drive pattern determination module 135 and determines whether the drive pattern stored in the pattern storage module 131 matches the change of the received EEG. The drive pattern determination step (S104) determines that the patterns match if the increase and decrease of the alpha waves are repeated two or more times within the set period. When the user repeats the operation of closing and closing the eyes at intervals of 3 seconds, the alpha wave increases in the closed eye and the alpha wave decreases in the closed eye. The change pattern of the alpha wave is stored in the pattern storage module 131, The drive pattern determination step (S104) can determine whether or not such patterns match.

The question generating step S105 is performed by the question generating module 141 and generates a question by displaying a character on the screen or generating a sound. The question may be answered by asking whether or not the device should be operated.

The affirmative judgment step (S106) diagnoses the occurrence of positive EEG or negative EEG for the question. Since the change of the beta wave in the negative EEG rather than the positive EEG is clear, the positive judgment step (S106) can judge whether or not the negative pattern of the EEG occurs. In the affirmative decision step (S106), the temporal and spatial correlation of brain waves is calculated to determine whether the brain waves are positive or negative. In the affirmative decision step S106, positive and negative can be judged by calculating the bias and synchronization rate and using it as a logic decision variable of the neural network. Here, the bias refers to the direction of rotation in the phase space composed of EEG components measured at two places, and the synchronization rate is a variable indicating the degree of simultaneous increase or decrease of EEG measured at two places.

로 정의되며, 여기서, 상기 s1과 s2는 두 위치에서 측정된 뇌파 신호, 상기 H(x)는 x가 음수이거나 0일 때에는 0, 양수일 때는 1의 값을 갖는 스텝 함수, 및 상기 w는 동기율을 계산하는 구간 크기이다.The synchronization rate

(X) is a step function having a value of 0 when x is negative or 0, and a positive value when x is positive, and w is a step function having a synchronization rate .

로 정의되며, 여기서 상기 P(t)는 편향성, 상기 벡터 s는 s1과 s2로 이루어진 2차원 벡터, 상기 단위 벡터 θ는 s1과 s2로 이루어지는 위상공간에서의 원점을 중심으로 시계 반대 방향으로 회전하는 방향의 단위 벡터이다. On the other hand,

, Wherein P (t) is biased, the vector s is a two-dimensional vector consisting of s1 and s2, and the unit vector [theta] is rotated counterclockwise about the origin in the phase space consisting of s1 and s2 Direction unit vector.

In the affirmative decision step (S106), positive and negative are determined by assigning the synchronization rate and bias to the variables of the classification method such as the neural network and the linear decision function. The synchronization rate and bias can be used individually, and both variables can be input. The neural network consists of a multilayer perceptron with an input layer, a hidden layer, and a node level output layer, and is already learned for logic judgment.

And the positive determination step generates a drive signal for switching the electronic device to the ON state when it is determined to be positive.

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: Electronic device driving device
110: EEG receiver
120: EEG analysis unit
121: Amplification module
123: Filter module
125: AD conversion module
127: Fourier transform module
130: pattern comparison unit
131: Pattern storage module
133: Pairing decision module
133: Detection of pairing patterns
133b: Pairing signal generating unit
133c: Pairing display unit
135: drive pattern determination module
140:
141: Question Generation Module
142:
143: drive signal generating module

Claims (11)

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;
A pattern comparing unit for comparing the extracted EEG changes with pre-stored patterns to determine whether they match or not; And
Generating a driving signal of the electronic device by generating a question and judging whether the question is affirmative or negative;
And an electronic device driving unit for driving the electronic device using the EEG.
The method according to claim 1,
Wherein the pattern comparison unit includes a pattern storage module storing a pairing pattern for connection with an electronic device and a drive pattern for driving the electronic device.
3. The method of claim 2,
Wherein the pattern comparison unit includes a pairing determination module for determining that a change in brain waves coincides with a pairing pattern.
3. The method of claim 2,
The pairing determination module includes a pairing pattern search unit for searching for whether a pairing pattern is generated, and a pairing signal generation unit for transmitting a pairing signal to the electronic device when the pairing pattern is generated to wait for the electronic device to receive a drive signal Wherein the electronic device is an electronic device using an EEG.
3. The method of claim 2,
Wherein the pairing determination module comprises a pairing display unit for informing that the pairing is being performed using a sound or an LED lamp.
3. The method of claim 2,
Wherein the pattern comparison unit includes a drive pattern determination module for determining whether a received pattern change is in agreement with a drive pattern stored in the pattern storage module.
The method according to claim 1,
Wherein the drive determining unit includes a question generating module for generating and displaying a question and an aptitude determining module for determining occurrence of a positive EEG or negative EEG for a question.
The method according to claim 1,
The positive decision module uses the synchronization rate, which is a variable indicating the direction of rotation in the phase space consisting of the EEG components measured at two places and a variable indicating the degree of simultaneous increase or decrease of EEG measured at two places, Wherein the controller determines whether a doctor or a physician is negative.
9. The method of claim 8,
The synchronization rate

Lt; / RTI >
Here, s1 and s2 are EEG signals measured at two positions, H (x) is a step function having a value of 0 when x is negative or 0, and 1 when it is positive, and w is a step function calculating a synchronization rate Wherein the electronic apparatus is a portable electronic apparatus.
9. The method of claim 8,
The bias

Lt; / RTI >
Here, the P (t) is biased, the vector s is a two-dimensional vector composed of s1 and s2, and the unit vector [theta] is a unit vector in a direction rotating in the counterclockwise direction about the origin in the phase space consisting of s1 and s2 Wherein the electronic device is an electronic device using an EEG.
8. The method of claim 7,
Wherein the drive determining unit includes a drive signal generating module for generating an ON signal for activating the electronic device or an OFF signal for deactivating the electronic device.

Images