KR20090016893A - Eeg-training based on aging-parameter of brain function - Google Patents

Abstract

A training method using aging-parameter of brain function is provided to prevent aging of brain function by building aging index of brain wave. A biofeedback training method uses brain wave. In spectrum transformed to frequency domain through a system for measuring electroencephalogram of a subject, the spectrum designates peak frequencies(PF) of frequency domain of 6~13Hz as an aging index determining a biological function aging of brain. The aging index is applied to standards of a biofeedback training, and converts peak frequencies of frequency domain of 6~13Hz into SEF-A%(Spectral Edge Frequency) index, MEF(Median Frequency) index or MF(Mean Frequency) index.

Description

EEG training method using brain function aging indicators {EEG-Training based on Aging-Parameter of Brain Function}

The present invention is to determine the biological function of the brain in the peak frequency (PF) of the frequency range of 6 ~ 13Hz in the spectrum transformed into the frequency space through the brain wave measurement of the subject for the purpose of slowing or improving the brain function decline due to aging Designated as an aging indicator, and relates to an EEG training method using the brain function aging indicator, characterized in that to apply the aging indicator as a criterion of biofeedback training.

EEG training is commonly known as neurofeedback, also known as brainwave biofeedback, in which the trainee can identify specific EEG indicators related to brain conditions in real-time by visual or auditory methods. It is a training method that effectively induces the volunteer's voluntary efforts to change.

This training was first introduced in the 1970s and has been gradually applied until recently, and the medical community has been attracting attention as a representative non-pharmaceutical brain function treatment and hyperstimulation method with few side effects.

More specifically, it corresponds to behavioral cognitive therapy for the purpose of acquiring autonomous control ability of specific bioregulatory indicators, and the biofeedback device used for this training is a kind of mirror that accurately reflects the user's own bioregulatory indicators. It acts as a simple tool.

This is because we need a biofeedback device that acts as a bio-mirror in order to acquire autonomous control, just as we need to know exactly how we look in the mirror every time we can correct our clothes. At the time of biofeedback training, it is possible to accurately identify the state of the bioregulatory indicators at every moment, so that the user can try to correct the indicators in the target direction. Through such repeated efforts, the user learns the voluntary control sensation of the bioregulatory indicators, and finally, the self-controlling ability to the target direction can be learned.

The results of autonomous control efforts of bioregulatory indicators that are attempted by the user at every moment during biofeedback training are objectively evaluated through changes in the bioregulatory indicators, and are delivered to the user in a positive or negative response form. You will continue to try to maintain your control efforts, or to strengthen them, a little more. On the contrary, if a negative response is received to the user's adjustment efforts, the user tries to obtain a positive response by correcting the adjustment effort method in a manner different from the one just performed. At this time, the result of the user's efforts is delivered to the user in real time through the response function, and the user adjusts to the target direction while acquiring a sense of how to adjust his condition repeatedly until a satisfactory positive response is reached. Gradually increase your ability.

Since the autonomous control ability of these desired bioregulatory indicators is a result of repeated cycles between the user's voluntary effort and immediate evaluation (response) of the effort, it is called biofeedback training and the user has his own treatment. There is a feature that requires an active participant role.

The following describes the response function of the biofeedback device in more detail.

Visual response is usually preferred when you open your eyes and perform biofeedback training.However, if the training is more effective when the eyes are closed, such as relaxation effort, the user will not be able to see the visual response screen. The same auditory response function is used to determine the level of bioregulatory indicators.

The visual response screen presented to the user may be given as an absolute value, a bar graph, a static picture, or a dynamic image, and the numerical or histogram type visual response may be a more quantitative measure of his / her biomarker level. User's favorite form of response, funny picture or dynamic video form, user's preference for boredom.

In other words, if the biocontrol indicator increases as a result of voluntary efforts of the user, the value of the biofeedback response screen changes to a large number, the height of the bar graph increases, the shape of the face is frowned, or the face changes from smiling to dynamic. By showing that the arrows flying toward the center gradually closer to the central goal, the user is to make sure that their efforts are going well in the target direction and play an implicit cheering role to make more efforts in that direction.

Conversely, if the user's bioregulatory indicators are lowered, the response screen will give negative responses such as low numbers, short bar graphs, frowns, and arrows moving off targets. It is an implicit advice to try again in the direction.

The auditory response function specifies the target value (threshold value), and if the current bioregulatory indicator value is above the target value, the response sound is 'ding dong' and the user adjusts the direction in the correct direction even when the user closes his eyes. It makes it easy to know whether you are doing this.

On the other hand, EEG-Training is an important part of the success of the training, which EEG-Training Indicators should be used according to the training purpose. It has been mainly performed for the purpose of improving left and right brain balance function. For example, when training for the purpose of improving the concentration function, training is mainly performed to increase the power or amplitude of the beta wave region, which is an EEG analysis index having a positive correlation with the concentration function. It is also used as a low-beta wave range (12-15 Hz), or a medium-beta wave range (15-18 Hz). On the other hand, training is conducted to reduce the power and amplitude values of theta wave area, which is a negative EEG analysis index that has a negative correlation with the concentration function, but recently, these two values are combined to reflect the ratio of beta to theta (TBR, Theta). -Beta Ratio.'Training methods to increase the analytical index are preferred.

However, with the recent increase in the elderly population, anxiety about dementia, a representative senile brain function disorder, has been increasing rapidly.However, EEG training that can improve the rate of brain function decline while directly controlling the quantitative value of biological aging of the brain There is no situation yet.

It is an object of the present invention to provide an EG training method using aging indicators to prevent aging of brain functions by building aging indicators of brain waves to prevent and improve brain function decline due to aging.

The purpose of the present invention as described above is to specify the peak frequency (PF) of the frequency domain of 6 ~ 13Hz in the spectrum transformed into the frequency space through the EEG measurement of the subject as an aging indicator for determining the biological functional aging of the brain, the aging It is achieved by the EEG training method using the brain function aging indicator, characterized in that the indicator is applied as a criterion of biofeedback training.

EEG training method using the brain function aging indicator according to the present invention is effective in preventing dementia and improves the rate of brain function decline by directly controlling the quantitative value of biological functional aging of the brain.

Most of the EEG rhythms that appear in the alpha rhythm band are generated by the network between the thalamus and the cerebral cortex and are controlled by cholinergic neurons in the brain stem. As aging progresses, the probability of this cholinergic damage increases and this leads to a decrease in brain function. This level of brain function can be confirmed through changes in brain waves.

EEG's unique rhythm is spontaneous brain flies appearing to everyone in a stable state. The thalamus of the brain is the main source and serves as a pacemaker for brain flies. As shown in the graph of FIG. 1, the EEG is shown in the form of the highest peak (hereinafter, eigenrhythm peak frequency) around 10 Hz in the spectral distribution of the steady state EEG.

For normal adults, the eigenrhythm peak frequency is high and pointed at around 10 Hz (± 2 Hz) or higher, but as the brain's biological function ages, the corresponding rhythm peak frequency (PF) is increased as shown in FIGS. , Peak Frequency) shows a tendency to gradually go down.

Therefore, the eyelids can set the steady state rhythm peak frequency (PF) as an aging indicator that reflects brain aging, and when used in biofeedback training, direct neurophysiological-based anti-aging training can be performed. .

In other words, the trainees are provided with information related to the eigenrhythm peak frequency in real-time feedback method, and the trainees are focused, awakened, and relaxed on their spontaneous brain state change efforts to slow or improve the decrease of this number. Or try different forms of meditation. If such an increase results from such an effort, the training proceeds in such a way that the trainee is presented with a reward signal informing the trainee to continue the effort.

Accordingly, the present invention is a biofeedback training method using brain waves, aging to determine the biological function aging of the brain in the peak frequency (PF) of the frequency range of 6 ~ 13Hz in the spectrum transformed into the frequency space through the brain wave measurement of the subject Designated as an indicator, it characterized in that the aging indicator is applied as a standard of biofeedback training.

In addition, the aging indicator of the present invention converts the peak frequency (PF) of the frequency range of 6 ~ 13Hz to the SEF-A% (Spectral Edge Frequency) indicator in the spectrum transformed into the frequency space through the EEG measurement of the subject, or MEF It may be made by converting into a (Median Frequency) indicator or a MF (Mean Frequency) indicator.

In the present invention, the brain wave measurement of the subject is preferably measured at the frontal or frontal lobe. The eigenrhythms of EEG appearing in the alpha rhythm band are most preferred in terms of convenience of training because the frontal lobe has no hairs and easy attachment of EEG electrodes. The laryngeal lobe has better eigenrhythm peak frequency than other parts. As it appears, it is a preferred site for accuracy.

Herein, the aging index according to the present invention is defined as a standard for biofeedback training. As shown in FIGS. 1 to 5, the peak frequency (PF) of the frequency domain of 6 to 13 Hz in the spectrum transformed into the frequency space is It is well known to show a slower frequency according to the deterioration of brain function or cognitive function due to biological aging. Especially, senile dementia is less than 8Hz, which shows relatively slower peak frequency (PF) than normal people of the same age. This is due to the fact that the longer the duration of disease or the more severe the symptoms, the slower.

That is, the peak frequency (PF) is in the frequency range of 10Hz or higher for normal adults under 40s, the peak frequency (PF) is near 9.6Hz for normal adults in the 50s, and the peak frequency (PF) is around 9.2Hz for normal adults in the 60s. The peak frequency (PF) was found to be around 8.5 Hz in normal 70s and the peak frequency (PF) was below 8 Hz in senile dementia patients.

Therefore, for example, if you want to conduct biofeedback training for normal adults under 40 years old, the peak frequency (PF) in the frequency range of 10Hz is applied as a criterion for biofeedback anti-aging and improvement training. Displaying peak frequency (PF) in the frequency domain may provide biofeedback training for aging by indicating a predetermined visual or auditory response that requires more effort.

Meanwhile, the present invention refers to the SEF-A% (Spectral Edge Frequency) in which the eigenrhythm peak frequency value is indirectly reflected, and refers to the frequency up to A% of the total wave when the sum of the power of the EEG signal is accumulated from 0 Hz. Alternatively, MEF (Median Frequency) and MF (Mean Frequency) indicators can be used as aging indicators. These indicators are sensitive to whether the value distribution is biased toward a relatively high frequency or a low frequency in a designated frequency region in the spectrum, and has a positive correlation with the rhythm peak frequency (PF). have. Meanwhile, the indicators known as MEF and MF are included in the SEF-A% index as SEF-50% and SEF-Mean%, respectively. Therefore, only the method of calculating the SEF index will be described.

A cumulative spectrum graph can be obtained by first adding the values from the lowest frequency value to the highest frequency value in the designated frequency region of the spectrum. In this graph, the maximum value means the total cumulative value, and if the scale is adjusted to correspond to the value of 100% for convenient calculation, the graph form is as follows. The 'SEF-A%' indicator is defined as the frequency value at the point where the value corresponds to A% in this cumulative spectrum.

For example, in the case of SEF-50%, it is determined by the frequency value when the value is 50% in the cumulative spectrum, which is called the center frequency or median frequency (MEF) because it means the center value in the spectral distribution. Also called.

The SEF-A% index can be extracted using the same procedure as long as the time series data is transformed into frequency space, such as amplitude spectrum, amplitude density spectrum, power density spectrum, and wavelet spectra, as well as the power spectrum of EEG. It has a similar meaning.

For reference, EEG training is recommended to be performed 2-3 times a week. Through repeated training, the weight change of the cranial nerve cell synaptic connection is induced in the desired direction, and thus the brain function change can be achieved to the target level. It is known as a training method that is implemented based on the principle.

1 is a graph showing the peak frequency (PF) that a normal adult under 40 in the frequency domain occurs,

Figure 2 is a graph showing the peak frequency (PF) that occurs in the normal 50s adult in the frequency domain,

3 is a graph showing the peak frequency (PF) that occurs in the 60s normal adult in the frequency domain,

4 is a graph showing the peak frequency (PF) that occurs in the 70s normal adult in the frequency domain,

5 is a graph showing the peak frequency (PF) that occurs in elderly dementia patients in the frequency domain,

FIG. 6 is a graph showing SEF-A% (Spectral Edge Frequency) indexes using the cumulative graph of FIG. 1.

Claims (3)

In the biofeedback training method using brain waves, The peak frequency (PF) in the frequency range of 6 to 13 Hz in the spectrum transformed into the frequency space through the EEG measurement of the subject is designated as an aging index for discriminating biological aging of the brain, and the aging index is used as a standard for biofeedback training. EEG training method using the brain function aging indicators, characterized in that applied. The method of claim 1, The aging indicator converts the peak frequency (PF) in the frequency range of 6 to 13 Hz into the SEF-A% (Spectral Edge Frequency) index in the spectrum transformed into the frequency space through the EEG measurement of the subject, or the MEF (Median Frequency) index. , Or EEG training method using the brain function aging indicator, characterized in that made by converting to MF (Mean Frequency) indicator. The method according to claim 1 or 2, EEG measurement of the subject EEG training method using the brain function aging indicator, characterized in that made in the frontal or occipital lobe region.

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