WO2014175684A1

WO2014175684A1 - Apparatus and method for inducing sleep by using neurofeedback

Info

Publication number: WO2014175684A1
Application number: PCT/KR2014/003615
Authority: WO
Inventors: 인호; 이헌정; 이정빈
Original assignee: 고려대학교 산학협력단
Priority date: 2013-04-26
Filing date: 2014-04-24
Publication date: 2014-10-30
Also published as: KR20140128018A; KR101552515B1

Abstract

An apparatus and a method for inducing sleep using neurofeedback are disclosed. The method for inducing sleep measures the brain wave pattern of a user by using a brain wave measuring means, differentiates the sleep and wakeful states of the user by comparing the measured brain wave pattern and a previously stored brain wave pattern according to the state of the human body, and applies a sleep-inducing stimulus to the user if the sleep and wakeful states correspond to a sleepy pattern as the result of the differentiation.

Description

Sleep Induction Device and Method Using Neurofeedback

The present invention relates to sleep induction technology, in particular, using a neurofeedback technology to measure and predict the brain waves appearing when sleepy patients with insomnia, to record the device, method and method for helping to easily enter the sleep It is about the medium.

Insomnia complains of difficulty in starting or maintaining sleep, or sleep that is not rejuvenated. It is known that 27% of the modern adult population experiences temporary insomnia and 9% experience chronic insomnia.

There are many causes of insomnia, but psychological behavioral reactions to irregular stress are one of the main causes of insomnia. Problems caused by insomnia cause various kinds of accidents and physical functions such as depression, anxiety, and psychiatric problems such as manic depression, cardiovascular system, and immune system abnormalities. It is very difficult to arithmetically calculate the direct and indirect social burdens of insomnia, but it is difficult to reduce the labor force due to insomnia, increase medical use, decrease cognitive function and the resulting traffic accidents, industrial accidents and other accidents, and other physical diseases and depression. Considering the increasing incidence of mental illness, the social burden is expected to be astronomical. However, the current treatment of insomnia has a number of problems.

The most commonly used sleeping pills prescriptions are easy to sleep, but have side effects. In other words, resistance and dependence occur, and the prescription dose is gradually increased and the drug is difficult to break. In addition, the symptoms of accompanying sleep apnea worsen, causing side effects of the cardiovascular system, increasing daytime memory problems, and increasing the risk of falling and taking over medications such as binge eating, violent behavior, and suicide. May occur.

For this reason, the sleep medicine community recommends nonpharmacological cognitive behavior therapy (CBT) as the first recommended treatment for insomnia. In other words, it is a treatment method that helps sleep sleep by solving insomnia patients' chronic beliefs about sleep, excessive expectation, worry, wrong sleeping habits, irregular sleep schedules and hyperalgesia and tension. CBT consists of sleep hygiene education, sleep restraint therapy, stimulation restraint therapy, cognitive therapy, and relaxation therapy. It changes thoughts and behavior through repetitive education and training. The problem with CBT, however, is that it takes a lot of time and money to treat. Many times you will need to meet with a specialist, be educated and corrected.

The core of the CBT treatment process is to create an insomnia that causes insomnia, a relaxation state to calm down and sleep. Therefore, if a method is developed to effectively accomplish this, it will provide a breakthrough in the treatment of insomnia.

In the past, the development of several tools has been attempted under similar thinking. Previously, a therapeutic device using neuro-feedback has been proposed, which is a relaxation training through the feedback of EEG, which relaxes the usual anxiety and tension and does not bring the device to actual sleep. In addition, a device has been developed for synchronizing EEG through external stimulation, but this also is not a method for giving insomnia patients direct feedback to sleep and has not been scientifically proven to be effective. "Understanding and clinical application of Neurofeedback (Park, Hyung-bae, Plastic Hair, Korean Psychiatric Association, 2006)" outlines the possibility that neurofeedback can be used for various disorders including sleep disorders.

Therefore, there is a need for a technical means capable of stably inducing sleep of an insomnia patient directly and effectively using such neurofeedback.

The technical problem to be solved by the present invention is to prevent the side effects of the conventional prescription of sleeping pills for the treatment of insomnia patients, and in the application of non-pharmacologic cognitive behavioral therapy training that is used in conventional insomnia treatment method using neurofeedback actually This is not an application in sleep situations, so in an actual sleep situation, the effort to get this sleep rather solves the problem that can cause sleep arousal and lead to brain arousal, allowing insomnia patients to sleep directly in bed. It is intended to overcome the limitation of not presenting a therapeutic method that can induce or respond appropriately to the condition of the patient.

In order to solve the above technical problem, a sleep induction method according to an embodiment of the present invention, measuring the brain wave pattern of the user using the brain wave measuring means; Determining the sleep arousal state of the user by comparing the measured EEG pattern with an EEG pattern according to a pre-stored human state; And if the sleep wakeup state corresponds to a sleepiness pattern, applying a sleep induction stimulus to the user.

Sleep guidance method according to an embodiment, the step of continuously recording the EEG pattern measured from the user from the sleepiness pattern to the sleep pattern over time; And extracting an EEG immediately before the user becomes sleepy from the recorded EEG pattern and updating the drowsiness pattern to learn an EEG pattern capable of predicting sleepiness in response to the personal characteristics of the user. .

In the sleep induction method according to an embodiment, after the sleep induction stimulus is applied, judging the sleep arousal state of the user by measuring the brain wave pattern of the user and comparing the brain wave pattern according to a pre-stored human state ; And if the sleep wakeup state corresponds to the sleep state as a result of the trial, continuously reducing the sleep induction stimulus applied to the user over time.

Sleep induction method according to an embodiment, measuring the sleep state, the duration of each sleep state and sleep depth of the user while varying the application conditions of the sleep induction stimulation; And recommending a condition for applying a sleep-induced stimulus to the user, which may provide the best sleep quality by evaluating sleep quality based on the measurement result.

On the other hand, the following provides a computer-readable recording medium recording a program for executing the above-described sleep induction method on a computer.

In order to solve the above technical problem, the sleep induction apparatus according to an embodiment of the present invention, pre-store the EEG pattern according to the human state, including the brain wave of the general state, sleepiness immediately before sleep and brain wave of the sleep state An EEG pattern storage unit; An EEG measuring unit attached to a user's forehead or scalp and measuring an EEG pattern of the user using an electric field; A discriminating unit for determining the sleep arousal state of the user by comparing the measured EEG pattern with an EEG pattern according to the pre-stored human state; And a sleep feedback unit configured to apply a sleep-induced stimulus to the user when the sleep wakeup state corresponds to a sleepiness pattern.

Sleep induction apparatus according to an embodiment, EEG recording unit for continuously recording the EEG pattern measured from the user over the sleep pattern from the sleep pattern over time; And a pattern learning unit configured to learn an EEG pattern capable of predicting sleepiness in response to an individual characteristic of the user by extracting an EEG immediately before the user becomes sleepy by updating the drowsiness pattern from the recorded EEG pattern. Can be.

In the sleep induction apparatus according to an embodiment, after the sleep induction stimulus is applied, the determination unit measures the EEG pattern of the user through the EEG measurement unit and the EEG according to the human state previously stored in the EEG pattern storage unit By judging the sleep wakeup state of the user by comparing with the pattern, and when the sleep wakeup state corresponds to the sleep state as a result of the trial, the sleep feedback unit continues the sleep induction stimulus applied to the user over time. Can be reduced.

Sleep induction apparatus according to an embodiment, by measuring the sleep state, the duration of each sleep state and sleep depth of the user while varying the application conditions of the sleep-induced stimulation through the EEG measurement unit, based on the measurement result It may further include an evaluation unit for recommending the conditions for applying the sleep-induced stimulation that can provide the best sleep quality by evaluating the sleep quality to the user.

Embodiments of the present invention can induce a natural sleep by the patient himself without causing tension or arousal by giving feedback stimulation to the insomnia patient who is difficult to fall asleep to create and maintain the brain wave state before going to sleep without drug treatment, measured from the patient By continuously learning patterns and stimuli that can induce sleep based on sleepiness patterns, it is possible to treat insomnia optimized for the patient's condition.

1 is a flowchart illustrating a method of inducing sleep using neurofeedback according to an exemplary embodiment of the present invention.

2 is a flowchart illustrating a method of learning an EEG pattern optimized for a user by using an EEG record in a sleep induction method according to an embodiment of the present invention.

3 is a flowchart illustrating a method of adjusting a sleep stimulation stimulus according to a sleep state of a user in a sleep induction method according to an embodiment of the present invention.

4 is a flowchart illustrating a method of providing an optimal sleep-induced stimulus by evaluating sleep quality according to various conditions in the sleep-induction method according to an embodiment of the present invention.

5 is a block diagram illustrating an apparatus for inducing sleep using neurofeedback according to an exemplary embodiment of the present invention.

[Description of the code]

500: sleep induction device

10: pattern storage unit

20: EEG measuring unit

30: determination unit

40: sleep feedback unit

50: EEG record

60: pattern learning unit

70: evaluation unit

Sleep induction method using a neurofeedback according to an embodiment of the present invention, measuring the brain wave pattern of the user using the brain wave measuring means; Determining the sleep arousal state of the user by comparing the measured EEG pattern with an EEG pattern according to a pre-stored human state; And if the sleep wakeup state corresponds to a sleepiness pattern, applying a sleep induction stimulus to the user.

Before describing the embodiments of the present invention, the overview of neurofeedback technology and the problems presented by the insomnia treatment technology utilizing the same are discussed, followed by an overview of the technical means employed by the embodiments of the present invention to solve these problems. To introduce.

Published in 1929 by Hans Berger (1873–1941), Germany, EEG is an important biosignal of human brain activity. EEG is divided into delta waves (1-4 Hz), theta waves (4-8 Hz), alpha waves (8-13 Hz), beta waves (13-30 Hz), and gamma waves (30-120 Hz), depending on the state of mental activity. Delta waves are brain waves that occur in deep sleep, theta waves are brain waves that occur in normal sleep conditions, and basic brain waves when dreaming. Alpha waves are brain waves that occur when you are resting. Strong when there is. Beta waves, like learning, are brain waves that occur when the brain is doing some mental work. Gamma waves are brain waves that occur when cognitive action occurs by combining information scattered in various parts of the brain.

Brain waves are either fast or slow in response to this normal mental activity. If not, it means that your brain is functioning abnormally. In other words, since normal brains and abnormal brains have distinct features in brain waves, brain waves may be measured to determine whether there are abnormal brains.

In general, the functions of the body, which the autonomic nervous system controls like the rhythm of the brain, are known to be out of our control. But in the 1950s, Dr. Miller of Yale University in the United States discovered that muscles that are involuntary (involuntary muscles) or the autonomic nervous system, such as muscles of the intestines or heart, can be controlled by our will, depending on conditions. Biofeedback is the technology that controls our involuntary muscles or autonomic nervous system. In particular, the biofeedback technology that controls brain waves is called neurofeedback by combining neuro-prefixed neuro.

The discovery of neurofeedback dates back to 1934, when Dr. Matthew and Adrian of Cambridge University, England, built electroencephalograms to measure brain waves. One day, I measured the brainwaves and tried to make a sound from the speaker only when the alpha wave came out. Then I noticed that alpha waves became stronger and stronger. This is the principle of neurofeedback.

By measuring your brainwaves and telling you that a specific brainwave has occurred, the brain automatically enhances that brainwave. This is like the conditional reflection that Dr. Pavlov discovered. If you feed a dog while feeding it, you will drool later. If you look at the food, the drooling brain's unconditional reflex circuit is connected with a bell to create a conditional society. Repeating this reinforces the newly created conditional reflection circuit, which makes it a habit. Then you will be drooling. In this way, every time a specific brain wave comes out, the brain develops a circuit by the brain wave, and if repeated over time, the circuit is strengthened and the specific brain wave increases.

In 1958, Dr. Joe Kamiya of the University of Chicago, U.S.A., was the first to experiment with changes in the state of mind by adjusting brain waves in accordance with the principle of neurofeedback. This experiment shows that brain waves can be controlled by will, which can't be arbitrarily controlled. It is the first neurofeedback experiment in the true sense.

In 1971, Dr. Barry Sturman of UCLA in the United States succeeded in treating epilepsy with neurofeedback using SMR waves (12-16 Hz brain waves from the sensory cortex of the brain). This is the first time in the world to apply neurofeedback to disease treatment. In 1976, Dr. Ruba of Tennessee, USA, reported a successful example of treating ADD and ADHD with neurofeedback using SMR and beta waves.

In 1979, Dr. Davidson of the United States found that when the alpha-wave balance between the left and right brains is broken, depression occurs. EEG findings of so-called emotional disorders have been discovered. In 1995, Dr. Rosenfeld reported successful experiments in treating depression through neurofeedback training, which balances the alpha wave of the left and right brain. In 1989, Dr. Pennyston and Kulkoski reported that neurofeedback training in patients with alcoholism or post-traumatic stress disorder (PTSD) was effective in treating them.

Meanwhile, the conventional insomnia treatment method using the neurofeedback technology proposes a method of training to induce relaxation state through usual training. However, even with this training, actual sleep is a different situation. Rather, a lack of sufficient relaxation training can lead to anxiety resulting in brain arousal. . This is because sleep controlled by autonomic nerves cannot be controlled by conscious sleep. Therefore, it is necessary to give feedback to the person who goes to sleep through neurofeedback about the change of brain wave caused by autonomic nerve.

In addition, the conventional insomnia treatment method of synchronizing the EEG by stimulating the frequency at a certain time interval to induce sleep has been attempted, but induction of sleep by the phenomenon called electroencephalography lacks the scientific basis, the stimulation rather patients It can also trigger arousal. Therefore, the present invention aims to suggest a means for treating insomnia that can lead the patient to a comfortable sleep state by using neurofeedback technology without such side effects.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, in the following description and the accompanying drawings, detailed descriptions of well-known functions or configurations that may obscure the subject matter of the present invention will be omitted. In addition, it should be noted that like elements are denoted by the same reference numerals as much as possible throughout the drawings.

1 is a flowchart illustrating a method of inducing sleep using neuro feedback according to an embodiment of the present invention, which includes the following steps.

In operation S110, the sleep induction apparatus measures an EEG pattern of a user using an EEG measurement means. Before going to sleep, the user first prepares to measure the electric field generated from the user's brain by wearing an EEG measuring means on the forehead or scalp, which is easy to measure EEG.

In operation S120, the sleep inducing apparatus determines the sleep arousal state of the user by comparing the brain wave pattern measured through operation S110 with an brain wave pattern according to a pre-stored human state. In other words, it compares the currently measured user's brain waves with various brain wave patterns that may appear in humans and examines the current state of the user. Here, the EEG pattern according to the pre-stored human state preferably includes at least a general state EEG, a sleepy EEG before sleep and an EEG of the sleep state, if necessary, human EEG pattern according to a more various state It may also include.

As a result of the determination of step S130, if the sleep awakening state corresponds to the sleepiness pattern, the process proceeds to step S140. If the current brain wave does not correspond to the sleepiness pattern, the process returns to step S110 to repeat the EEG pattern measurement.

In operation S140, the sleep inducing device applies a sleep inducing stimulus to the user. That is, since the current user is sleepy, the user may induce sleep by utilizing a sleep induction stimulation provided in advance. Here, the sleep induction stimulus may be utilized by an acoustic stimulus (for example, may be a sound signal or music) or a light stimulus (for example, a lamp or an illumination effect) for inducing a user's sleep. Can be.

2 is a flowchart illustrating a method of learning an EEG pattern optimized for a user by using an EEG record in a sleep induction method according to an embodiment of the present invention. Prior to the sleep induction method may further include the following steps.

In operation S210, the sleep induction apparatus continuously records the EEG pattern measured from the user over time from the sleepiness pattern to the sleep pattern. The sleep pattern to be recorded in step S210 may be the brain wave of the user according to the feedback process receiving the sleep-induced stimulation described above with reference to FIG. 1. In addition, recording of the sleep pattern may be performed periodically or repeatedly, thereby obtaining more reliable samples.

In operation S220, the apparatus for inducing sleep extracts the brainwaves immediately before the user becomes sleepy from the brainwave patterns recorded through the operation S210 and updates the sleepiness pattern to predict sleepiness in response to the personal characteristics of the user. To learn. In other words, in step S220, the sleepy brainwave pattern immediately before sleep is used as a basic data for generating a sleepy brainwave model for predicting sleep. The sleepy brainwave model generated in this way can be used to predict a sleep state in advance without a process of comparing the measured brainwave patterns, thereby enabling sleepiness determination and sleep prediction optimized for the user more quickly.

After the above process, the step S110 of FIG. 1 is performed to perform a series of sleep induction methods, and by using the updated drowsiness pattern, a quick sleep feedback (sleep induction stimulation is estimated by predicting that the currently measured user enters the sleep soon. I mean you can

3 is a flowchart illustrating a method of adjusting a sleep stimulation stimulus according to a user's sleep state in the sleep induction method according to an embodiment of the present invention. The following steps may be further included in the sleep induction method. Here, in order to avoid duplication of description, the description will focus on the process after the step of applying the sleep induction stimulus (step S140).

If the sleep induction stimulus is applied through the process before the step S140 and the sleep feedback is started, the user does not participate in the feedback at all, and the sleep induction device directly adjusts the sleep induction stimulation according to the user's brain waves, thereby achieving natural sleep induction. Is done.

In operation S310, the sleep induction apparatus measures an EEG pattern of a user using an EEG measuring means. In other words, while providing sleep feedback through the previous process in step S310 it will continuously monitor the brain waves of the user.

In operation S320, the sleep induction apparatus re-determines the sleep awakening state of the user by comparing the brain wave pattern measured through the operation S310 with an brain wave pattern according to a pre-stored human condition.

In step S330, if the sleep awakening state corresponds to the sleep state as a result of the trial, step S340 is entered. Otherwise, the process returns to step S310 to repeat the measurement of the EEG pattern.

In operation S340, the sleep inducing device continuously reduces the sleep inducing stimulus applied to the user over time. That is, if it is determined that the user is getting a stable sleep, it is desirable to gradually reduce the sleep feedback (for example, to reduce the volume of the sound signal that induces sleep or to diminish the brightness of the lamp). In the long run, feedback can be adjusted while the brainwave is measured until the user has a good night's sleep, and finally the feedback and the brainwave measurement can be completely terminated.

4 is a flowchart illustrating a method of providing an optimal sleep stimulation stimulus by evaluating sleep quality according to various conditions in a sleep induction method according to an embodiment of the present invention. The following steps may be further included in the sleep induction method. Here, in order to avoid duplication of description, the description will focus on the process after the step of applying the sleep induction stimulus (step S140).

In operation S410, the sleep inducing apparatus measures the sleep state, the duration of each sleep state, and the sleep depth of the user while changing various application conditions of the sleep induction stimulus. The conditions for applying the sleep-induced stimulus may be variously combined within these ranges by setting a range of suitable variables in humans through experiments in advance. For example, the intensity, tempo, duration, etc. of the sound signal may be such variables, and the brightness or change of the lamp may also be variables.

That is, in step S410 it is used as a basis for finding a more advantageous sleep-induced stimulation by measuring the signs of the user's sleep through the brain waves in accordance with the change in the conditions of applying the sleep-induced stimulation.

In operation S420, the sleep inducing apparatus evaluates sleep quality based on the measurement result of operation S410. By quantitatively representing the quality of sleep according to the combination of the conditions for applying the sleep-induced stimulus, it is possible to find the condition for applying the induced stimulus that can induce the highest level of sleep.

Here, a variety of technical means can be used to quantitatively evaluate the quality of sleep, for example, by examining the sleep EEG data in the EEG recording device, the deep sleep EEG band (1Hz to 4Hz) of the total EEG data You can quantify whether you are occupying (%), or, conversely, how much awakening wave (8Hz or higher) is occupying all the EEG data.

Through this, the sleep induction device according to the embodiment of FIG. 4 may recommend the condition for applying the sleep induction stimulus to provide the best sleep quality to the user.

FIG. 5 is a block diagram illustrating a sleep induction apparatus 500 using neuro feedback according to an embodiment of the present invention, and illustrates the sleep induction method described above with reference to FIGS. to be. Here, the operation of each component will be described generally by focusing on the connection relationship between the components.

The pattern storage unit 10 is configured to prestore at least three EEG patterns according to a human state, including an EEG in a general state, an EEG in a sleepy state just before sleep, and an EEG in a sleep state, and may store various types of electronic data. It can be implemented with a recording device. This is a configuration provided to compare the EEG patterns of the general sleep disorder patients, it can be modified and developed into a pattern more suitable for the patient using the sleep induction device 500 according to the present embodiment by being updated through continuous EEG measurement.

The EEG measuring unit 20 is attached to the user's forehead or scalp and measures the EEG pattern of the user using an electric field. The EEG measuring unit 20 is formed in any one of a band form, hairpin form, sticker form and is attached adjacent to the user's forehead or scalp to continuously measure the EEG until the user wakes up from sleep. It plays a role. The EEG measurement unit 20 may be implemented in a form that does not cause a user's rejection or disturbs sleep so that the EEG can be measured without any inconvenience even when the user is lying down.

The determination unit 30 determines the sleep awakening state of the user by comparing the brain wave pattern measured by the brain wave measuring unit 20 with the brain wave pattern according to the human state previously stored in the pattern storage unit 10. The determination unit 30 analyzes the measured EEG data, removes noise, and determines which sleep arousal stage the user is currently located in.

The sleep feedback unit 40 applies a sleep induction stimulus to the user when the sleep awakening state corresponds to a drowsiness pattern as a result of the determination through the determination unit 30. Here, the sleep-induced stimulation, it is preferable to include any one of the acoustic stimulation or light stimulation for inducing the user's sleep, any stimulus to help sleep can be utilized as a sleep induction stimulation. This allows the user to naturally enter the sleep state without any special awareness of the sleep induction process, without training or tension or arousal to sleep.

On the other hand, after the sleep-induced stimulus is applied, the determination unit 30 measures the brain wave pattern of the user through the brain wave measuring unit 20 to the human state previously stored in the pattern storage unit 10. The sleep arousal state of the user can be judged by comparing with the EEG pattern. Then, when the sleep wakeup state corresponds to the sleep state as a result of the trial, the sleep feedback unit 40 may continuously reduce the sleep induction stimulus applied to the user over time.

In addition, the sleep guidance apparatus 500 of FIG. 5 may further include an EEG recording unit 50 and a pattern learning unit 60 according to implementation and utilization needs.

The EEG recording unit 50 continuously records the EEG pattern measured from the user in accordance with time from the sleepiness pattern to the sleep pattern, and the user or doctor can freely set the measurement time and period. In addition, if the purpose of inducing sleep other than the above diagnostic purpose is achieved, the quality of sleep when the user wakes up may be evaluated, and then the recorded data may be deleted to back up the data or to free up storage space. .

The pattern learner 60 extracts and collects an EEG immediately before the user becomes sleepy from the EEG pattern recorded in the EEG recorder 50 to update the drowsiness pattern to predict sleepiness in response to the personal characteristics of the user. Can learn EEG patterns.

Furthermore, the sleep guidance apparatus 500 of FIG. 5 may further include an evaluation unit 70 according to implementation and utilization needs. The sleep induction apparatus 500 according to an embodiment may measure the sleep state, the duration of each sleep state, and the sleep depth of the user while varying the application condition of the sleep induction stimulus through the EEG measurement unit 20. have. Then, the evaluator 70 recommends to the user an application condition of the sleep-induced stimulus that can provide the best sleep quality by evaluating the sleep quality based on the measurement result through the EEG recorder 50 or Therefore, the user can make changes to the period or pattern of EEG measurement that is more suitable for the user.

Meanwhile, embodiments of the present invention can be implemented by computer readable codes on a computer readable recording medium. The computer-readable recording medium includes all kinds of recording devices in which data that can be read by a computer system is stored.

Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disks, optical data storage devices, and the like, which may also be implemented in the form of carrier waves (for example, transmission over the Internet). Include. The computer readable recording medium can also be distributed over network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion. And functional programs, codes and code segments for implementing the present invention can be easily inferred by programmers in the art to which the present invention belongs.

The present invention has been described above with reference to various embodiments thereof. Those skilled in the art will understand that the present invention can be implemented in a modified form without departing from the essential features of the present invention. Therefore, the disclosed embodiments should be considered in descriptive sense only and not for purposes of limitation. The scope of the present invention is shown in the claims rather than the foregoing description, and all differences within the scope will be construed as being included in the present invention.

According to the embodiments of the present invention described above, by giving a feedback stimulus to make the insomnia patient who is difficult to fall asleep before making a sleep without medication, the patient can induce natural sleep without causing tension or arousal state. In addition, it is possible to treat insomnia optimized for the patient's condition by continuously learning the patterns and stimuli that can induce sleep based on the sleepiness pattern measured from the patient. In particular, the sleep induction technology adopted by the embodiments of the present invention provides feedback that means that the brain wave condition corresponding to the drowsiness pattern in the brain wave should be maintained as it is while the patient relaxes. It is effective in treating insomnia because it induces people to fall asleep naturally.

Claims

Measuring an EEG pattern of a user using an EEG measuring means;

Determining the sleep arousal state of the user by comparing the measured EEG pattern with an EEG pattern according to a pre-stored human state; And

And applying a sleep induction stimulus to the user when the sleep awakening state corresponds to a sleepiness pattern.
The method of claim 1,

The EEG pattern according to the pre-stored human state,

Sleep induction method comprising a brain wave in a general state, sleepiness immediately before sleep and brain wave in the sleep state.
The method of claim 1,

Continuously recording the EEG pattern measured from the user over time from a sleepiness pattern to a sleep pattern; And

Learning the EEG pattern which can predict the sleepiness in response to the personal characteristics of the user by extracting the EEG immediately before the user is sleepy from the recorded EEG pattern to update the sleepiness pattern; .
The method of claim 1,

Judging the sleep arousal state of the user by measuring the brain wave pattern of the user and comparing the brain wave pattern according to a pre-stored human state after the sleep induction stimulus is applied; And

If the sleep wakeup state corresponds to a sleep state as a result of the trial, continuously reducing a sleep-induced stimulus applied to the user as time passes.
The method of claim 1,

The sleep induction stimulation,

Sleep induction method comprising any one of an acoustic stimulation or a light stimulation for inducing the user's sleep.
The method of claim 1,

Measuring a sleep state, a duration of each sleep state, and a sleep depth of the user while varying an application condition of the sleep induction stimulus; And

Recommending to the user an application condition of a sleep-induced stimulus that can provide the best sleep quality by evaluating sleep quality based on the measurement result.
Measuring an EEG pattern of a user using an EEG measuring means;

Determining the sleep arousal state of the user by comparing the measured EEG pattern with an EEG pattern according to a pre-stored human state; And

And when the sleep arousal state corresponds to a sleepiness pattern, applying a sleep-inducing stimulus to the user as a result of the determination; recording a program for executing the sleep-inducing method in a computer.
A pattern storage unit pre-stores an EEG pattern according to a human state including an EEG in a general state, an EEG in a sleepy state just before sleep, and an EEG in a sleep state;

An EEG measuring unit attached to a user's forehead or scalp and measuring an EEG pattern of the user using an electric field;

A discriminating unit for determining the sleep arousal state of the user by comparing the measured EEG pattern with an EEG pattern according to the pre-stored human state; And

And a sleep feedback unit configured to apply a sleep induction stimulus to the user when the sleep awakening state corresponds to a sleepiness pattern.
The method of claim 8,

The brain wave measuring unit,

Sleep induction device, characterized in that formed in the form of any one of a band form, hairpin form, sticker form adjacent to the forehead or scalp of the user.
The method of claim 8,

An EEG recording unit for continuously recording the EEG pattern measured from the user over time from sleepiness patterns to sleep patterns; And

A pattern learning unit configured to learn an EEG pattern capable of predicting sleepiness in response to an individual characteristic of the user by extracting an EEG immediately before the user becomes sleepy by updating the drowsiness pattern from the recorded EEG pattern guide.
The method of claim 8,

After the sleep induction stimulus is applied, the determination unit measures the brain wave pattern of the user through the brain wave measuring unit and compares the sleep arousal state of the user by comparing the brain wave pattern according to the human state previously stored in the pattern storage unit. Judging,

When the sleep wakeup state as a result of each trial, the sleep feedback unit, the sleep induction device, characterized in that to continuously reduce the sleep-induced stimulation applied to the user over time.
The method of claim 8,

The sleep induction stimulation,

Sleep induction device comprising any one of a sound stimulus or a light stimulation for inducing the user's sleep.
The method of claim 8,

Measuring the sleep state, the duration of each sleep state and the sleep depth of the user while varying the application conditions of the sleep-induced stimulation through the EEG measurement unit,

And an evaluator for recommending a condition for applying a sleep-induced stimulus to the user that can provide the best sleep quality by evaluating sleep quality based on the measurement result.