KR101648120B1 - Eeg-based neurofeedback method and apparatus for emotion regulation training - Google Patents

Abstract

The neurofeedback method based on the EEG for emotion regulation training according to the present invention includes the steps of expressing an emotional stimulus for inducing an emotional response of an EEG, measuring a multi-channel EEG that changes through the emotional stimulus, Calculating a gamma power value for each channel for each of the converted brain signal data; calculating a gamma power value for each channel based on the received brain signal data; And converting the gamma power value of the selected channel among the channels into an emotion control index and displaying the result on the monitor.

Description

[0001] EEG-BASED NEUROFEEDBACK METHOD AND APPARATUS FOR EMOTION REGULATION TRAINING [0002]

The present invention relates to an EEG-based neurofeedback technique, and more particularly, to a method and apparatus for emotion regulation training by measuring emotion control effect from EEG instead of functional magnetic resonance imaging (fMRI) Based neurofeedback method and apparatus for realizing the same.

As is well known, neurofeedback techniques for emotion regulation have been developed primarily using functional magnetic resonance imaging (fMRI) techniques.

Here, the functional magnetic resonance imaging (fMRI) technique has a merit that it can measure the degree of activation of each brain region in detail. In particular, the sub-cortical region in which the emotional regulation effect in the brain can be confirmed is relatively accurately There are advantages to be able to measure.

However, the conventional functional magnetic resonance imaging (MRI) technique has a disadvantage that the user has to use the MRI scanner inconveniently, and the time resolution rate is relatively low to be optimized for real-time neurofeedback.

Korean Patent Publication No. 2009-0071508 (Published on 2009. 07. 01)

The present invention proposes a system capable of effectively realizing emotional adjustment training by measuring the emotion regulation effect from EEG instead of fMRI and providing it as a real-time neuro feedback form.

The present invention is based on the cognitive reappraisal technique in the emotion regulation method and suggests a system that can display the emotion regulation effect in real time through the gamma power in the frontal lobe among the EEG characteristics.

The present invention relates to a method and apparatus for real-time emotion control using a frontal gamma wave in consideration of the characteristics in which a subject's own emotion is suppressed, maintained and increased in a given emotional stimulus so that the corresponding frontal gamma power is decreased, We propose a neuro feedback system.

According to an aspect of the present invention, there is provided a method for generating an EEG, the method comprising: expressing an emotional stimulus for inducing an emotional response of an EEG according to an aspect; measuring and transmitting multi-channel EEG changing through the emotional stimulus; A process of receiving and processing the EEG of the channel and converting it into brain signal data for each channel; calculating a gamma power value for each channel for each converted brain signal data; The present invention provides a brain-wave-based neurofeedback method for emotional adjustment training, which includes converting a power value into an emotion control index and displaying it on a monitor.

The process of exposing the emotional stimulus of the present invention may include a process of selecting any one of a plurality of preset types of stimuli and a process of extracting an emotional stimulus corresponding to the selected stimulus type from the stimulus DB .

The emotion stimulation of the present invention can be repeatedly expressed by a predetermined number of times defined by the user.

The EEG according to the present invention may be a potential difference generated in the frontal region scalp and may be transmitted as a wireless or wired signal.

The gamma power value of the present invention may be calculated using any one of a Short-Time Fourier Transform, a Wavelet Transform, a Hilbert Transform, and an Empirical Mode Decomposition .

The emotion control index of the present invention can be displayed in real time on the monitor in the form of a bar graph or a line graph.

The emotional adjustment indicator of the present invention can be displayed on the monitor with a history of previous emotion adjustment indicator values.

In the present invention, when the number of the selected channels is plural, the average value of the gamma power of a plurality of channels may be calculated and converted to the emotion control index.

According to another aspect of the present invention, there is provided a stimulus DB in which data on a predetermined plurality of types of stimuli are stored and a stimulus stimulus in which one or more of the plurality of stimulus types is selected to induce an emotional response of an EEG A brain wave signal measuring unit for measuring multi-channel brain waves changing through the emotional stimulus to be displayed, an EEG signal transmitting unit for transmitting the measured multi-channel brain waves through a wireless or wired signal, An EEG signal processor for receiving the multi-channel EEG signals and converting them into brain signal data for each channel, a gamma-wave extractor for calculating a gamma power value for each channel for each converted brain signal data, And a emotion control neurofeedback control unit for converting the gamma power value of the selected channel into an emotion control indicator and displaying it on a monitor EEG Neurofeedback provides a device for controlled based training.

The brain wave measurement sensor unit of the present invention can measure the brain waves generated in the frontal lobe.

The EEG sensor of the present invention may use a dry or wet electrode.

The EEG signal transmitting unit of the present invention may transmit the EEG signal as a wireless or wired signal.

The EEG signal processing unit of the present invention may convert the brain waves received in the multi-channel form into brain signal data for each channel.

The gamma-wave extracting unit of the present invention may extract the gamma-ray using one of the short-time Fourier transform, the Wavelet transform, the Hilbert transform, and the empirical mode decomposition. The gamma power value can be calculated.

The emotion regulation neuro feedback control unit of the present invention may display the emotion regulation index in real time on the monitor in the form of a bar graph or a line graph.

The emotional adjustment neuro feedback control unit of the present invention may display the emotional adjustment indicator on the monitor together with a history of previous emotional adjustment indicators.

The emotion regulation neuro feedback control unit of the present invention may calculate an average value of a plurality of channels of gamma power when the selection channels are plural and switch to the emotion regulation index.

The present invention measures multi-channel EEG changes through emotion stimulation to induce an emotional response of EEG, converts it into brain signal data for each channel, The gamma power value is calculated and the gamma power value of the selected channel among the channels is switched to the emotion control indicator and displayed on the monitor so that the user can realize the emotion control training optimized for the real time neuro feedback without entering the MRI scanner have.

Further, the neurofeedback apparatus based on the EEG according to the present invention can be effectively adapted to a depression treatment program, a post-traumatic stress treatment program, and the like.

1 is a block diagram of an EEG-based neurofeedback apparatus for emotion regulation training according to the present invention.
FIG. 2 is a flowchart illustrating a main process of processing neurofeedback for emotion control training based on brain waves according to the present invention.

First, the advantages and features of the present invention, and how to accomplish them, will be clarified with reference to the embodiments to be described in detail with reference to the accompanying drawings. While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, but, on the contrary, It will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

In the following description of the present invention, detailed description of known functions and configurations incorporated herein will be omitted when it may make the subject matter of the present invention rather unclear. It is to be understood that the following terms are defined in consideration of the functions of the present invention, and may be changed according to intentions or customs of a user, an operator, and the like. Therefore, the definition should be based on the technical idea described throughout this specification.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 is a block diagram of an EEG-based neurofeedback apparatus for emotion regulation training according to the present invention.

Referring to FIG. 1, an EEG-based neurofeedback apparatus according to the present invention includes a data storage unit 110, an emotion stimulation control unit 120, an EEG sensor 130, an EEG signal transmitting unit 140, A gamma-ray extractor 160, and an emotion-controlled neurofeedback controller 170, as shown in FIG.

First, the data storage unit 110 may include a stimulus DB 112 and an information DB 114. Stimulus information (stimulus data) for generating various types of emotion set in advance is stored in the stimulus DB 112 Such stimuli can be classified into various types, such as, for example, photographic images, audiovisual videos, tactile stimuli, auditory stimuli, and the like. Here, each stimulus is assigned a balance and an arousal value, and the range of the balance and arousal value can be defined, for example, between 0 and 7.

The emotion control index information converted from the gamma power values calculated for each channel may be transmitted from the emotion control neuro feedback controller 170 to be described later and stored in the information DB 114 in the data storage unit 110. [

Next, the emotional stimulation control unit 120 controls the stimulation response of the emotional exercise training participant through the neurofeedback (that is, the emotional response of the emotional adjustment exercise participant through the neurofeedback) Alternatively, one or more functions may be selected and displayed (expressed) in an emotion stimulus (e.g., a photograph image, an audiovisual moving image, a tactile stimulus, an auditory stimulus, etc.). Here, the selection of the kind of the emotion stimulus can be performed randomly (randomly) or in a predetermined order.

The presentation time (or presentation time) of the emotion stimulus can be defined (set) by the user and can be changed depending on the type of the stimulus. For example, it can be defined that the photographic image is expressed (expressed) in 2-5 seconds, the moving image is 3-30 seconds, the tactile stimulus is 1-5 seconds, and the auditory stimulus is 3-30 seconds.

Also, the idle time between stimulations can be defined (set) by the user in a range of a few seconds, and the number of times of presentation (presentation) of the emotion stimulus can be defined (set) by the user or automatically determined by the training protocol have.

Meanwhile, the EEG sensor 130 measures a multi-channel EEG that changes through emotion stimulation displayed under the control of the emotion stimulation controller 120, for example, measures a brain wave generated at the frontal lobe For example, a dry or wet electrode may be used as the EEG sensor unit 130. [ Here, the brain waves may mean, for example, a potential difference generated in the scalp area of the frontal region.

The EEG signal transmitting unit 140 processes (e.g., computes, amplifies, filters, etc.) EEG signals of multiple channels (multiple channels centered on the frontal lobe) measured through the EEG sensor unit 130, The EEG signal transmitting unit 140 may be provided with a wireless or wireless transmission system. Here, the transmitted brain signal may be ADC processed digital data.

Next, the EEG signal processing unit 150 receives multi-channel EEG transmitted from the EEG signal transmitting unit 140 in a wireless or wired manner, demodulates the EEG signals into original signals before being modulated, processes the demodulated brain signals for each channel For example, buffering of brain signal data, elimination of brain wave noise, and the like, into brain signal data.

Meanwhile, the gamma-ray extracting unit 160 acquires the converted brain signal data transmitted from the EEG signal processing unit 150 in real time and calculates a gamma power value for each channel (for example, several to several tens of channels) And calculating the gamma wave power value from the brain signal of each channel for each cycle). Here, the acquisition rate of the brain signal data acquired in real time may vary depending on the sampling rate in the EEG sensor 130, for example, in the range of 128 samples / s to 1000 samples / s .

More specifically, the gamma-ray extracting unit 160 temporarily stores the brain signals of each channel acquired in real time in a corresponding buffer of a predetermined size (the number of buffers and the number of channels are the same) The mobile station reads the stored radio signal data and then uses any one of a Short-Time Fourier Transform, a Wavelet Transform, a Hilbert Transform, and an Empirical Mode Decomposition The power of the gamma wave is calculated for each channel.

As an example, if a short-term Fourier transform is applied to the power calculation of a gamma wave, the size of the buffer can be determined according to the specification defined by the user. For example, it may be set in the range of about 0.5-1 second have.

The period of reading the data in the buffer to calculate the power of the gamma wave can be defined according to the specification of the short-term Fourier transform. For example, it may be set in the range of about 0.1-0.5 seconds depending on the purpose of the system.

In addition, the frequency band corresponding to the gamma wave can be defined by the user. According to the precedent studies related to emotion regulation, the appropriate range of about 30-50 Hz can be considered.

The window function to be applied to the data in the short term Fourier transform specification can be defined by the user. For example, a Hamming window or a Hanning window can be applied, and the short-term Fourier transform specification, Gamma wave power calculation period, gamma frequency band, window function, etc. can be designated by the user when designing the gamma wave extraction module.

As an example, the gamma wave extracting unit 160 can calculate the gamma wave power as an example of the following module operation.

Number of EEG channels = 20

Sampling rate = 500 samples / s

Buffer size = 0.5s = 250 samples

Gamma power calculation period = 0.1s = 50 samples

Gamma wave frequency band = 30 - 50Hz

In the above case, 20 brain signal values are input from 20 channels every 1/500 s = 2ms, and a maximum of 250 samples are stored in a buffer corresponding to each channel (20 buffers in total) After the first 250 samples are stored in the buffer, the data samples stored in the current buffer are sampled every 0.1 second. After applying the short-term Fourier transform technique, power values corresponding to 30 to 50 Hz are extracted and the average value is sent to the emotion- (170).

In this case, 200 samples are duplicated between the 250 samples used for the current calculation and the 250 samples used for the next calculation, and this calculation process is performed simultaneously for each buffer.

Next, the emotion regulation neural feedback controller 170 switches the gamma power value of the selected channel among the channels to the emotion control index and displays it on the monitor, that is, A gamma power value of a given channel is obtained and a gamma power value of a channel (s) preset by the user is selected from among gamma power values of all given channels or an average value of gamma power values of a selected channel when a plurality of selected channels are obtained And the ability to switch gamma power values to emotion control indicators according to user-specified options. Here, the converted emotion control index may be stored in the information DB 114 in the data storage unit 110.

The emotion control neural feedback controller 170 acquires the baseline power value from the information DB 114 and outputs the gamma power value (or the gamma power value) from the emotion stimulation control unit 120 when the stimulus state input value is E (Emotion) The averaged value), and the baseline-processed gamma power value can be switched to the emotion control index according to the option specified by the user. Of course, when the stimulation state input value transmitted from the emotion stimulation control unit 120 is N (Neutral), the gamma power value (or an average thereof) is stored in the information DB 114 as a baseline power value.

Here, the options of the user emotion control index include 1) a power value (no additional conversion process), 2) a scale value (for example, a value between -1 and 1 by substituting a value within a predetermined maximum and minimum value range And 3) a discrete integer value (the power value is replaced with the closest integer and scaling is applied to the emotion control level).

Also, the user interface design that displays the emotion control index on the monitor (screen) can be configured as desired by the user, for example, the emotion control index can be displayed in real time in the form of a bar graph or a line graph, Can be displayed (displayed) on the monitor together.

Also, if necessary, an evaluation input interface may be provided on the screen so that the participant can directly and personally evaluate the emotional response experienced before he / she has a rest period after the stimulus presentation. In this case, the evaluation unit inputs the balance and awakening value of the stimulus And the input time is given in the range of a few seconds and can be presented to be evaluated, for example, at a 5-point or 7-point scale.

Therefore, while the emotion stimulation is being displayed (presented), the emotion control index (neurofeedback emotion control index) output from the emotion control neuro feedback control unit 170 is simultaneously displayed on the screen, so that the participant adjusts the emotional reaction by itself Control effects can be observed through neurofeedback. At this time, the neurofeedback emotion control indicator may be set to be displayed on the screen even during the resting period, at which time the participant can help to turn his or her emotional reaction back to normal.

As an example, the emotion control neural feedback controller 170 may generate an emotion control index as an example of the following module operation.

Example of Module Behavior

Number of EEG channels = 20

Select channel = F3, Fz

Gamma power calculation period = 0.1s

Stored baseline power value = 10

Emotional adjustment index maximum / minimum = 10 / -10

Stimulus state input value = E

Emotional Adjustment Indicator Option = Scale Value

Emotional Adjustment Index Display Option = Line Graph

In the above case, 20 gamma power values are received from the gamma wave extracting unit 160 every 0.1 second, and power values corresponding to the channel indices F3 and Fz are selected to obtain two power average values For example, if the average value is calculated to be 14.78, the base line power value of 10 is subtracted from the information DB 114, and the base line processed value 4.78 is divided by the maximum value of 10 to obtain 0.478, This value (0.478) is displayed on the monitor as a line graph with the existing emotion control indicator history, in which case the line graph is updated every 0.1 second on the monitor.

Next, a series of processes for providing neurofeedback for emotion control training using the neurofeedback apparatus based on the EEG according to the present embodiment having the above-described configuration will be described in detail.

FIG. 2 is a flowchart illustrating a main process of processing neurofeedback for emotion control training based on brain waves according to the present invention.

2, the emotion stimulation control unit 120 selects one or more than one of a plurality of stimulation types stored in the stimulation DB 112 to induce an emotional response of a participant in emotion regulation training through neurofeedback (Step 202). ≪ / RTI >

Here, the emotional stimulus may be, for example, a photograph image, an audiovisual moving image, a tactile stimulus, an auditory stimulus, and the like. The selection of the type of emotion stimulus may be random (random) or may proceed in a predetermined order. In addition, the presentation (presentation) time of emotional stimuli can be defined (set) by the user, for example, 2-5 seconds for photographic images, 3-30 seconds for moving images, 1-5 seconds for tactile stimuli, 3 -30 seconds, and so on.

Next, the EEG sensor 130 measures multi-channel EEGs that change through emotion stimulation expressed in accordance with the control from the emotion stimulation controller 120, for example, measures the EEG occurring at the frontal lobe, (Step 204). Here, the brain waves may mean, for example, a potential difference generated in the scalp area of the frontal region.

In response, the EEG signal transmitting unit 140 performs processing such as computation, amplification, filtering, and the like on the measured multi-channel (multi-channel centered at the frontal lobe) transmitted from the EEG sensor unit 130 Modulated into a wireless or wired signal and transmitted (transmitted) to the EEG signal processing unit 150 (step 206).

Then, the EEG signal processing unit 150 demodulates the multi-channel EEG transmitted by radio or wire to the original signal before modulation, processes the demodulated brain signals for each channel (for example, buffering of brain signal data, Brain wave noise elimination, etc.), converts it into brain signal data, and transmits it to the gamma wave extracting unit 160 (step 208).

Next, the gamma wave extracting unit 160 acquires the converted brain signal data transmitted from the EEG signal processing unit 150 in real time and calculates a gamma power value for each channel (for example, several to several tens of channels) (The gamma wave power value is calculated from the brain signal of each channel per cycle) and then transmitted to the emotion regulation neural feedback controller 170 (step 210). Here, the acquisition rate of the brain signal data may vary depending on the sampling rate of the EEG sensor 130, for example, it may have a range of 128 samples / s to 1000 samples / s.

Here, the power calculation of the gamma wave for each channel can be performed using any one of, for example, short-term Fourier transform, wavelet transform, Hilbert transform, or empirical mode decomposition.

Thereafter, the emotion regulation neural feedback controller 170 obtains a gamma power value for each channel transmitted at every predetermined period from the gamma wave extractor 160, obtains a gamma power value for each given channel, The average gamma power value obtained by obtaining the average value of the gamma power values of the selected channel when a plurality of selected channels are selected is displayed on the monitor on the monitor in accordance with the option specified by the user (Step 212).

Here, the emotion control indicator can be displayed in real time on the monitor in the form of a bar graph or a line graph, and can be displayed on the monitor together with a history of previous emotion control indicators.

When the stimulus state input value transmitted from the emotion stimulation control unit 120 is E (Emotion), the emotion control neuro feedback control unit 170 subtracts the baseline power value from the gamma power value (or its average value) The baseline processed gamma power value is converted to an emotion control indicator according to the option specified by the user. Of course, when the stimulation state input value transmitted from the emotion stimulation control unit 120 is N (Neutral), the gamma power value (or its average value) is stored in the information DB 114 as a baseline power value.

It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the present invention as defined by the following claims. It is easy to see that this is possible. That is, the embodiments disclosed in the present invention are not intended to limit the scope of the present invention but to limit the scope of the present invention.

Therefore, the scope of protection of the present invention should be construed in accordance with the following claims, and all technical ideas within the scope of equivalents should be interpreted as being included in the scope of the present invention.

110: Data storage unit 120: Emotion stimulation control unit
130: EEG sensor part 140: EEG signal transmission part
150: EEG signal processing unit 160: Gamma wave extracting unit
170: emotion regulation neurofeedback control section

Claims (17)

A process of expressing an emotional stimulus for inducing an emotional response of an EEG,
Measuring and transmitting multi-channel EEGs that change through the emotional stimulus to be displayed;
Receiving and processing the transmitted multi-channel EEG signals into brain signal data for each channel;
Calculating a gamma power value for each of the converted brain signal data,
A process of converting the gamma power value of the selected channel among the channels into the emotion control index according to the predefined option and displaying it on the monitor
/ RTI >
The pre-
A power value, a scale value converted into a value between -1 and 1 by replacing the power value with a value within a predetermined maximum and minimum value range, a discrete integer that displays the power value as the emotion control level by applying scaling after replacing the power value with the closest integer Containing a value
Brain - based neurofeedback method for emotion regulation training.
The method according to claim 1,
Wherein the step of displaying the emotional stimulus comprises:
Selecting one of a plurality of preset types of stimuli;
A process of fetching and expressing the emotion stimulus corresponding to the selected type of stimulation from the stimulation DB
A neurofeedback method based on EEG for emotional adjustment training.
3. The method of claim 2,
The emotion stimulation may include:
It is repeatedly displayed as many times as the preset number defined by the user
Brain - based neurofeedback method for emotion regulation training.
The method according to claim 1,
The EEG includes:
The frontal area is the potential difference
Brain - based neurofeedback method for emotion regulation training.
5. The method of claim 4,
The EEG includes:
Transmitted as a wireless or wired signal
Brain - based neurofeedback method for emotion regulation training.
The method according to claim 1,
The gamma power value,
Is calculated using any one of a short-time Fourier transform, a wavelet transform, a Hilbert transform, and an empirical mode decomposition.
Brain - based neurofeedback method for emotion regulation training.
The method according to claim 1,
The emotional adjustment index includes:
Displayed in real time on the monitor in the form of a bar graph or a line graph
Brain - based neurofeedback method for emotion regulation training.
8. The method of claim 7,
The emotional adjustment index includes:
Displayed on the monitor with a history of previous emotion control indicator values
Brain - based neurofeedback method for emotion regulation training.
The method according to claim 1,
In the displaying step,
Calculating a mean value of gamma power of a plurality of channels when the number of the selected channels is plural, and switching to the emotion control index
Brain - based neurofeedback method for emotion regulation training.
A stimulus DB in which data for a plurality of preset types of stimuli are stored,
An emotion stimulation control unit for selecting one or more of the plurality of stimulation types to express an emotional stimulus in order to induce an emotional response of an EEG;
A brain wave measuring sensor unit for measuring multi-channel brain waves that change through the emotional stimulus,
An EEG signal transmitting unit for transmitting the multi-channel EEG measured as a wireless or wired signal,
An EEG signal processing unit for receiving the transmitted EEG signals and converting them into brain signal data for each channel;
A gamma wave extracting unit for calculating a gamma power value for each of the converted brain signal data,
The emotion control neurofeedback control unit for converting the gamma power value of the selected channel among the channels into the emotion control index according to the predefined option,
Lt; / RTI >
The pre-
A power value, a scale value converted into a value between -1 and 1 by replacing the power value with a value within a predetermined maximum and minimum value range, a discrete integer that displays the power value as the emotion control level by applying scaling after replacing the power value with the closest integer Containing a value
Neuro - feedback device based on EEG for emotion regulation training.
11. The method of claim 10,
The EEG sensor unit includes:
Measuring the EEG occurring in the frontal lobe
Neuro - feedback device based on EEG for emotion regulation training.
11. The method of claim 10,
The EEG sensor unit includes:
Using dry or wet electrodes
Neuro - feedback device based on EEG for emotion regulation training.
11. The method of claim 10,
The EEG signal transmitter includes:
And transmitting the brain waves as wireless or wire signals
Neuro - feedback device based on EEG for emotion regulation training.
11. The method of claim 10,
The gamma-
The gamma power value is calculated using any one of a Short-Time Fourier Transform, a Wavelet Transform, a Hilbert Transform, and Empirical Mode Decomposition
Neuro - feedback device based on EEG for emotion regulation training.
11. The method of claim 10,
Wherein the emotion control neuro feedback control unit comprises:
The emotion control indicator is displayed on the monitor in real time in the form of a bar graph or a line graph
Neuro - feedback device based on EEG for emotion regulation training.
16. The method of claim 15,
Wherein the emotion control neuro feedback control unit comprises:
Wherein the emotional adjustment indicator is displayed on the monitor together with a history of previous emotional adjustment indicators
Neuro - feedback device based on EEG for emotion regulation training.
11. The method of claim 10,
Wherein the emotion control neuro feedback control unit comprises:
Calculating a mean value of gamma power of a plurality of channels when the number of the selected channels is plural, and switching to the emotion control index
Neuro - feedback device based on EEG for emotion regulation training.

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