KR102461705B1 - Method for providing information on brain health status of child young people and apparatus executing the method - Google Patents

Abstract

Disclosed are a method for providing information on brain health status of children and adolescents, and an apparatus for performing the same. A method for providing information on brain health status of children and adolescents according to an embodiment of the present invention includes: acquiring EEG data of a state in which a task of reference children and adolescents is performed; Calculating and storing average related information of EEG data according to at least one of gender and age of reference children and adolescents using the obtained EEG data; acquiring EEG data of a state in which a task of the person to be measured is performed; extracting average related information of EEG data corresponding to the gender and age of the subject; Comparing the EEG data of the subject and the average related information of the extracted EEG data; and checking the brain health state of the subject according to the comparison result.

Description

METHOD FOR PROVIDING INFORMATION ON BRAIN HEALTH STATUS OF CHILD YOUNG PEOPLE AND APPARATUS EXECUTING THE METHOD

An embodiment of the present invention relates to a technology for providing information on a brain health state.

The continuous recording of potential fluctuations between two points on the scalp caused by the electrical activity of the brain is called an EEG. EEG is a biosignal that reflects the state of human consciousness, and research is being conducted to measure the mental health state of a subject using EEG.

Korean Patent Publication No. 10-2012-0106339 (September 26, 2012)

An embodiment of the present invention is to provide a method for diagnosing a brain health state of children and adolescents capable of diagnosing a brain health state of a subject using EEG information of reference children and adolescents, and an apparatus for performing the same.

In a method for diagnosing brain health conditions of children and adolescents according to an exemplary embodiment, in the apparatus for diagnosing brain health conditions, first EEG data in a state in which a task of reference children and adolescents is not performed and second EEG data in a state in which a task is performed obtaining each of the In the brain health condition diagnosis apparatus, the average related information of the first EEG data and the second EEG data according to at least one of gender and age of the reference children and adolescents using the acquired first EEG data and second EEG data calculating and storing average-related information, respectively; acquiring, by the apparatus for diagnosing a brain health state, first EEG data in a state in which a task is not performed and second EEG data in a state in which a task is performed, respectively; extracting, in the apparatus for diagnosing a brain health state, average-related information of the first EEG data and average-related information of the second EEG data corresponding to the gender and age of the person to be measured; In the brain health condition diagnosis apparatus, the first EEG data of the person to be measured and average related information of the first EEG data are compared, and the second EEG data of the person to be measured and the mean related information of the second EEG data are compared. to do; and diagnosing, in the brain health state diagnosis apparatus, the brain health state of the measured subject according to the comparison result.

The task for obtaining the second EEG data is a suppression power (NoGo Suppression) task, a reflection power (NoGo Monitoring) task, a task performance (P3b) task, a waiting condition task performance (Cue P3) task, a preparation capability (CNV) task, It may include at least one of an adaptive ability (Novelty) task and an Ignore task.

The average related information of the first EEG data includes at least one of an average value of the amplitude of the first EEG, a standard deviation of the size of the first EEG, and an average development curve for each age of the first EEG size and the average-related information of the second EEG data, the average value of the amplitude of the second EEG, the average value of the latency of the second EEG, the standard deviation of the size of the second EEG, the second It may include at least one of a standard deviation of the latency of the EEG, an average development curve for each age of the magnitude of the second EEG, and an average development curve for each age of the latency of the second EEG.

The first EEG data includes at least one of a delta wave, theta wave, an alpha wave, a sensor motor rhythm (SMR), a beta wave, and a high beta wave, and the step of diagnosing the brain health state of the person to be measured includes: The method may include determining whether the person to be measured is deficient in a neurotransmitter according to a result of comparing the first EEG data of the person to be measured and the average related information of the first EEG data.

The method may further include generating, in the brain health condition diagnosis apparatus, prescription information according to the type of the deficient neurotransmitter and the degree of the deficiency when the neurotransmitter of the subject is deficient.

The second EEG data is, the subject's suppression power (NoGo Suppression) task, reflective power (NoGo Monitoring) task, task performance (P3b) task, atmospheric condition task performance (Cue P3) task, preparation capability (CNV) task, adaptation It is data on EEG measured while performing at least one of a Novelty task and an Ignore task, and the diagnosing of the brain health state of the person to be measured includes the second EEG data of the person to be measured and the It may include the step of confirming the frontal lobe development state of the subject according to the comparison result of the average related information of the second EEG data.

As a result of the check, if there is an abnormality in the developmental state of the frontal lobe of the person to be measured, the method may further include generating, in the brain health state diagnosis apparatus, prescription information according to the ability to have the abnormality and the degree of the abnormality.

According to another exemplary embodiment, a method for diagnosing a brain health state of children and adolescents includes: acquiring, in an apparatus for diagnosing a brain health state, EEG data of a state in which a task of reference children and adolescents is performed; calculating and storing, in the apparatus for diagnosing brain health, average related information of EEG data according to at least one of gender and age of the reference children and adolescents using the obtained EEG data; obtaining, in the brain health condition diagnosis apparatus, EEG data in a state in which a task of the person to be measured has been performed; extracting, in the apparatus for diagnosing a brain health condition, average related information of EEG data corresponding to the gender and age of the person to be measured; comparing, in the apparatus for diagnosing brain health conditions, average related information of the EEG data of the subject and the extracted EEG data; and diagnosing, in the brain health state diagnosis apparatus, the brain health state of the measured subject according to the comparison result.

The task for obtaining the EEG data includes a NoGo Suppression task, a NoGo Monitoring task, a task performance (P3b) task, a waiting condition task performance (Cue P3) task, a preparation capability (CNV) task, an adaptive capability. It may include at least one of a (Novelty) task and an Ignore task.

The average-related information of the EEG data includes an average value of the amplitude of the EEG, an average value of the latency of the EEG, a standard deviation of the size of the EEG, a standard deviation of the latency of the EEG, the size of the EEG It may include at least one of an average development curve for each age, and an average development curve for each age of the latency of the EEG.

The EEG data is, the target person's suppression power (NoGo Suppression) task, reflective power (NoGo Monitoring) task, task performance (P3b) task, atmospheric condition task performance (Cue P3) task, preparation capability (CNV) task, adaptive capability ( Novelty) task and data on EEG measured while performing at least one of an Ignore task, and the step of diagnosing the brain health state of the person to be measured includes: It may include the step of confirming the frontal lobe development state of the subject according to the comparison result of the average-related information.

As a result of the check, if there is an abnormality in the developmental state of the frontal lobe of the person to be measured, the method may further include generating, in the brain health state diagnosis apparatus, prescription information according to the ability to have the abnormality and the degree of the abnormality.

An apparatus according to an exemplary embodiment includes one or more processors; Memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the program comprising: first EEG data in a state in which a task of the subject is not performed; and acquiring each of the second brain wave data in a state in which the task is performed; extracting the average-related information of the first EEG data and the average-related information of the second EEG data corresponding to the gender and age of the person to be measured, respectively; comparing the first EEG data of the person to be measured and the average related information of the first EEG data, and comparing the second EEG data of the person to be measured and the average related information of the second EEG data; and instructions for executing the step of diagnosing the brain health state of the subject according to the comparison result.

The task for obtaining the second EEG data is a suppression power (NoGo Suppression) task, a reflection power (NoGo Monitoring) task, a task performance (P3b) task, a waiting condition task performance (Cue P3) task, a preparation capability (CNV) task, It may include at least one of an adaptive ability (Novelty) task and an Ignore task.

The program, in the step of diagnosing the brain health state of the person to be measured, confirming the frontal lobe development state of the person to be measured according to the comparison result of the second EEG data of the person to be measured and the average related information of the second EEG data It may include instructions for executing a step.

The program may include instructions for further executing the step of generating prescription information according to the ability to have the abnormality and the degree of the abnormality when, as a result of the confirmation, there is an abnormality in the developmental state of the frontal lobe of the person to be measured.

An apparatus according to another exemplary embodiment includes one or more processors; Memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the program comprising: acquiring EEG data in a state in which a task of a subject has been performed ; extracting average related information of EEG data corresponding to the gender and age of the subject; comparing the EEG data of the subject and the average related information of the extracted EEG data; and diagnosing the brain health state of the subject according to the comparison result.

The task for obtaining the EEG data includes a NoGo Suppression task, a NoGo Monitoring task, a task performance (P3b) task, a waiting condition task performance (Cue P3) task, a preparation capability (CNV) task, an adaptive capability. It may include at least one of a (Novelty) task and an Ignore task.

In the step of diagnosing the brain health state of the person to be measured, the program executes the step of confirming the frontal lobe development state of the person to be measured according to the comparison result of the average related information of the EEG data of the person to be measured and the extracted EEG data It may contain instructions for

The program may include instructions for further executing the step of generating prescription information according to the ability to have the abnormality and the degree of the abnormality when, as a result of the confirmation, there is an abnormality in the developmental state of the frontal lobe of the person to be measured.

An embodiment of the present invention compares the first EEG of the subject with the average related information of the first EEG data of reference children and adolescents whose gender and age correspond to the subject, and diagnoses whether the subject has a neurotransmitter deficiency. Depending on the type and degree of deficiency of the neurotransmitter, it is possible to provide a solution suitable for it.

In addition, by comparing the average related information of the second EEG of the subject and the second EEG data of reference children and adolescents whose gender and age are matched with the subject, the prefrontal executive state (or developmental state) of the subject can be diagnosed. , it will be possible to provide a solution suitable for the ability and degree of abnormality in the development of the frontal lobe.

1 is a block diagram showing the configuration of an apparatus for diagnosing brain health conditions according to an exemplary embodiment;
FIG. 2 is a diagram for explaining tasks for measuring a second EEG in a system for diagnosing a brain health condition according to an exemplary embodiment; FIG.
3 is a flowchart illustrating a method for diagnosing a brain health state according to an exemplary embodiment;
4 is a graph showing the average development curve of the second EEG according to the inhibitory force task (NoGo Suppression) in an exemplary embodiment;
5 is a graph showing the average development curve of the second EEG according to the reflexive task (NoGo Monitoring) in the exemplary embodiment;
6 is a graph showing the average development curve of the second brain wave according to the task performance (P3b) task in the exemplary embodiment;
7 is a graph showing the average development curve of the second brain wave according to the atmospheric condition task performance (Cue P3) task in an exemplary embodiment;
8 is a graph showing the average developmental curve for the second brain wave according to the preparation capacity (CNV) task in an exemplary embodiment;
9 is a graph showing the average development curve of the second brain wave according to the adaptive ability (Novelty) task in an exemplary embodiment;
10 is a graph showing the average development curve of the second EEG according to the Ignore task in an exemplary embodiment;
11 is an illustration of a computing environment including an example computing device suitable for use in example embodiments.

Hereinafter, specific embodiments of the present invention will be described with reference to the drawings. The following detailed description is provided to provide a comprehensive understanding of the methods, apparatus, and/or systems described herein. However, this is merely an example and the present invention is not limited thereto.

In describing the embodiments of the present invention, if it is determined that the detailed description of the known technology related to the present invention may unnecessarily obscure the gist of the present invention, the detailed description thereof will be omitted. And, the terms to be described later are terms defined in consideration of functions in the present invention, which may vary according to intentions or customs of users and operators. Therefore, the definition should be made based on the content throughout this specification. The terminology used in the detailed description is for the purpose of describing embodiments of the present invention only, and should in no way be limiting. Unless explicitly used otherwise, expressions in the singular include the meaning of the plural. In this description, expressions such as “comprising” or “comprising” are intended to indicate certain features, numbers, steps, acts, elements, some or a combination thereof, one or more other than those described. It should not be construed to exclude the presence or possibility of other features, numbers, steps, acts, elements, or any part or combination thereof.

In the following description, the terms "transmission", "communication", "transmission", "reception" and other similar meanings of a signal or information are not only directly transmitted from one component to another component, but also a signal or information This includes passing through other components. In particular, to “transmit” or “transmit” a signal or information to a component indicates the final destination of the signal or information and does not imply a direct destination. The same is true for "reception" of signals or information. In addition, in this specification, when two or more data or information are "related", it means that when one data (or information) is acquired, at least a part of other data (or information) can be acquired based thereon.

Also, terms such as first and second may be used to describe various components, but the components should not be limited by the terms. The above terms may be used for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, a first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component.

1 is a block diagram showing the configuration of an apparatus for diagnosing brain health conditions according to an exemplary embodiment.

Referring to FIG. 1 , the brain health state diagnosis apparatus 100 may include an EEG measuring unit 102 , a data processing unit 104 , a database 106 , and a diagnosis module 108 .

The brain health condition diagnosis apparatus 100 may be implemented as one device, but some components may be implemented in another device (or implemented as another device). For example, the EEG measuring unit 102 , the data processing unit 104 , and the diagnostic module 108 may be implemented as one device, and the database 106 may be implemented as an external server. The database 106 may be a cloud-based server. In addition, the EEG measuring unit 102 may be implemented as a separate device, and the data processing unit 104 and the diagnostic module 108 may be implemented as a single device. In this case, the data processing unit 104 may acquire the EEG data from the EEG measurement unit 102 by wire or wirelessly.

The brain health state diagnosis apparatus 100 measures a first EEG when a task is not performed and a second EEG when a task is performed for children and adolescents, respectively, and first EEG data for each gender and age Mean related information of (eg, mean value of EEG size, standard deviation of EEG size, average development curve of EEG size, etc.) and average related information of second EEG data (eg, EEG amplitude (Amplitude) and EEG latency) (Latency), standard deviation of EEG size and EEG latency, average development curve of EEG size and EEG latency, etc.) is calculated and converted into a database.

Next, the brain health state diagnosis apparatus 100 relates the first EEG and the second EEG of the person to be measured (the adolescent who wants to diagnose the brain health condition) to the average of pre-stored EEG data corresponding to the gender and age of the child and adolescent. By comparing with the information, it is possible to diagnose the brain health state of the subject.

Hereinafter, the configuration and operation of the brain health condition diagnosis apparatus 100 will be described in detail.

The EEG measuring unit 102 measures the first EEG from the scalp of children and adolescents. The first EEG is an EEG measured in a state in which children and adolescents do not perform tasks (ie, in a natural state). The EEG measuring unit 102 may measure the amplitude (Amplitude) of the first EEG. The first EEG includes a delta wave, theta wave, an alpha wave, a sensor motor rhythm (SMR), a beta wave, a high beta wave, and the like according to a frequency. Delta waves are brain waves with a frequency of 0.5 to 4 Hz, and appear in a state of deep sleep. Theta wave is an EEG with a frequency of 4 to 7 Hz, and appears in a sleepy state, a distracted state, or a daydream state. Alpha waves are brain waves with a frequency of 8 to 12 Hz, and appear when external concentration is loose in a relaxed state. SMR (Sensory Motor Rhythm) is an EEG with a frequency of 12 to 15 Hz, and appears when you maintain concentration while not moving. Beta waves are brain waves with a frequency of 15 to 18 Hz, and appear when thinking and maintaining concentration in an active state. High beta waves are brain waves with a frequency of 18 Hz or higher, and appear in a state of tension or anxiety.

In addition, the EEG measuring unit 102 measures the second EEG from the scalp of children and adolescents. The second EEG is an EEG measured while the children and adolescents performed the task. The EEG measuring unit 102 measures the amplitude (Amplitude) of the second EEG and the time (Latency) from the generation of the second EEG to the maximum amplitude of the second EEG (hereinafter, may be referred to as latency). can do.

Specifically, the EEG measurement unit 102 allows children and adolescents to suppress (NoGo Suppression) task, reflective power (NoGo Monitoring) task, task performance (P3b) task, atmospheric condition task performance (Cue P3) task, preparation ability (CNV) ) task, adaptive ability (Novelty) task, ignorance (Ignore) task, etc. to perform tasks, in the state that each task is performed, it is possible to measure the EEG (ie, the second EEG) of children and adolescents. A detailed description of each task will be described later with reference to FIG. 2 .

The EEG measuring unit 102 may measure the first EEG and the second EEG for male and female children and adolescents of various age groups (eg, 6 to 17 years old), respectively. In this case, the EEG measuring unit 102 may measure the first EEG and the second EEG for children and adolescents (hereinafter, may be referred to as “reference children”) in normal brain health. In this case, the measured first EEG data and the second EEG data are used as reference EEG data. The EEG measuring unit 102 may be made in a form that can be worn on the head of the person to be measured. The EEG measuring unit 102 may amplify the EEG signal measured from the scalp of the person to be measured and remove noise.

The data processing unit 104 receives the first EEG data and the second EEG data from the EEG measurement unit 102 . In addition, the data processing unit 104 receives the reference body information of children and adolescents (eg, the sex of the person to be measured, the age of the person to be measured, etc.). The reference body information of children and adolescents may be input from a user interface (not shown). The data processing unit 104 includes first EEG data (eg, delta wave, theta wave, alpha wave, SMR (Sensory Motor Rhythm), beta wave, high beta wave, etc. ) can be calculated as the mean and standard deviation. In addition, the data processing unit 104 is based on the second EEG data according to at least one of gender and age group of children and adolescents (eg, deterrence task, reflex task, task performance task, atmospheric condition task performance task, preparation ability task, adaptation It is possible to calculate the average and standard deviation of the brain wave data measured when performing the ability task, the neglect task, etc.).

The data processing unit 104 may calculate an average development curve of the first EEG data according to the sex and age of the reference children and adolescents. In this case, the data processing unit 104 may calculate an average development curve according to each indicator (eg, delta wave, theta wave, alpha wave, SMR, beta wave, high beta wave, etc.) of the first EEG data. In addition, the data processing unit 104 may calculate an average development curve of the second EEG data according to the sex and age of the reference children and adolescents. At this time, the data processing unit 104 is each task index of the second EEG data (eg, deterrence task, reflex task, task performance task, atmospheric condition task performance task, preparation ability task, adaptive ability task, ignorance task, etc.) It is possible to calculate the average development curve according to

The database 106 may include a first database 106 - 1 and a second database 106 - 2 . The first database 106 - 1 may store the first EEG data measured by the EEG measuring unit 102 . The first database 106 - 1 may store the average and standard deviation of the first EEG data according to at least one of gender and age. The first database 106 - 1 may store the average development curve of the first EEG data according to gender and age. The second database 106 - 2 may store the second EEG data measured by the EEG measuring unit 102 . The second database 106 - 2 may store the average and standard deviation of the second EEG data according to at least one of gender and age. The second database 106 - 2 may store the average development curve of the second EEG data according to gender and age.

The diagnosis module 108 may measure the first EEG of the person to be measured for diagnosing the brain health state through the EEG measuring unit 102 . The diagnosis module 108 compares the first EEG data of the person to be measured with the average related information of the pre-stored first EEG data corresponding to the gender and age of the person to be measured, and determines the brain health state (or degree of brain development) of the person to be measured. can be detected. For example, the diagnosis module 108 may detect the brain health state of the person to be measured by comparing the average development curve of the first EEG data and the pre-stored first EEG data.

In an exemplary embodiment, the diagnostic module 108 compares the first EEG data of the person to be measured with the average value of the pre-stored first EEG data or the average development curve of the first EEG data to compare the neurotransmitter (for example, , dopamine, norepinephrine, GABA, serotonin, etc.) can be detected. When the neurotransmitter deficiency is predicted, the diagnostic module 108 may provide a solution according to the degree of the neurotransmitter deficiency. For example, if the subject is predicted to have dopamine deficiency, the diagnostic module 108 prescribes drugs that enhance dopamine (eg, vitamins, minerals, herbs, etc.) or prescribe neurofeedback training that enhances dopaminergic circuits. can do.

The diagnosis module 108 may measure the second EEG of the person to be measured for diagnosing the brain health state through the EEG measuring unit 102 . The diagnosis module 108 compares the second EEG data of the person to be measured and the average related information of the second EEG data stored in advance corresponding to the gender and age of the person to be measured to determine the brain health state (or degree of brain development) of the person to be measured. can be detected. For example, the diagnosis module 108 may detect the brain health state of the person to be measured by comparing the average development curve of the second EEG data and the pre-stored second EEG data.

In an exemplary embodiment, the diagnosis module 108 compares the second EEG data of the subject with the average value of the second EEG data stored in advance or the average development curve of the second EEG data to compare the subject's frontal lobe development state (or frontal lobe execution) condition) can be diagnosed. The diagnosis module 108 may provide a solution for the development of the frontal lobe when the prefrontal developmental state of the subject does not reach the average.

FIG. 2 is a diagram for explaining tasks for measuring a second EEG in the brain health condition diagnosis system according to an exemplary embodiment.

Referring to FIG. 2 , two stimulations (eg, a picture or a photograph) may be given to the subjects at a predetermined time interval (eg, 1000 ms). The first stimulus and the second stimulus can each be viewed for 100 ms. There may be a time interval of 300 ms before the first stimulus is given. Subjects are trained to press the button if the first stimulus is an animal (A) and the second stimulus is also an animal (A), and if the first stimulus is an animal (A) and the second stimulus is a plant (P), the button You can be educated not to enjoy the

Here, the NoGo Suppression task can measure the EEG according to the subject's response while showing the animal (A) as the first stimulus and the plant (P) as the second stimulus. At this time, the subjects should not enjoy the button when the plant (P) comes out as the second stimulus.

The NoGo Monitoring task measures EEG according to the self-recognition of the subject while performing the NoGo Suppression task. That is, when the subject was shown the plant (P) as the second stimulus, the EEG was generated according to the recognition of whether he or she acted correctly (ie, did not enjoy the button) or acted wrongly (ie, when the button was pressed). will measure

The task performance (P3b) task can measure the EEG according to the subject's response while showing the animal (A) as the first stimulus and the animal (A) as the second stimulus. At this time, the subjects must press the button when the animal (A) comes out as the second stimulus.

The atmospheric condition task performance (Cue P3) task can measure EEG according to the subject's response when the animal (A) is shown as the first stimulus. That is, when the atmospheric condition task performance task shows the animal (A) as the first stimulus, the EEG of the subjects immediately following the first stimulus is measured.

The readiness capability (CNV) task shows the animal (A) as the first stimulus and can measure the EEG of the subjects ready for the second stimulus accordingly. That is, the subjects are in a state to respond to the second stimulus when the animal (A) is shown as the first stimulus. The preparatory ability task shows the animal (A) as the first stimulus, It is possible to measure the brain waves of the subjects just before the reaction.

In the adaptive ability (Novelty) task, when a sound was played while showing a plant (P) as the first stimulus and a new picture (eg, a person) not mentioned during the pre-training as the second stimulus, the subjects' responses EEG can be measured according to

When the Ignore task shows a plant (P) as the first stimulus and also shows a plant (P) as the second stimulus, the brain wave according to the responses of the subjects can be measured.

3 is a flowchart illustrating a method for diagnosing a brain health state according to an exemplary embodiment. In the illustrated flowchart, the method is described by dividing the method into a plurality of steps, but at least some of the steps are performed in a different order, are performed together in combination with other steps, are omitted, are performed in sub-steps, or are not shown. One or more steps may be added and performed. In addition, according to an embodiment, one or more steps not shown in the method may be performed together with the method.

Referring to FIG. 3 , the EEG measuring unit 102 measures the first EEG when the task is not performed on children (ie, reference children and adolescents) in normal brain health ( S101 ). For example, the EEG measuring unit 102 may measure a delta wave, theta wave, an alpha wave, a sensor motor rhythm (SMR), a beta wave, a high beta wave, and the like of reference children and adolescents. The EEG measuring unit 102 may measure the amplitude (Amplitude) of the first EEG and the time (Latency) from the generation of the first EEG to the maximum amplitude of the first EEG.

Next, the EEG measuring unit 102 measures the second EEG when the task is performed on the reference children and adolescents (S103). For example, the EEG measurement unit 102 is a reference task for children and adolescents, a suppression power (NoGo Suppression) task, a reflexive power (NoGo Monitoring) task, a task performance (P3b) task, a waiting condition task performance (Cue P3) task, preparation ability The second EEG may be measured when the (CNV) task, the adaptive ability (Novelty) task, and the Ignore task are performed. The EEG measuring unit 102 may measure the amplitude (Amplitude) of the second EEG and the time from the generation of the second EEG to the maximum amplitude of the second EEG (Latency).

Next, the data processing unit 104 calculates the average of the first EEG data and the average of the second EEG data according to at least one of gender and age of the reference children and adolescents (S 105). For example, the data processing unit 104 may calculate an average of the first EEG data according to the sex and age of the reference children and adolescents and store the average in the database 106 . The data processing unit 104 may calculate an average of the second EEG data according to the sex and age of the reference children and adolescents and store it in the database 106 . The data processing unit 104 may also calculate a standard deviation of the first EEG data and a standard deviation of the second EEG data. In addition, the data processing unit 104 may calculate the average development curve of the first EEG data and the average development curve of the second EEG data according to the sex and age of the reference children and adolescents, respectively.

Next, the EEG measuring unit 102 measures the first EEG when the task is not performed and the second EEG when the task is performed for the subject (children and adolescents who want to diagnose a brain health condition), respectively. (S 107).

Next, the diagnosis module 108 extracts the average of the first EEG data corresponding to the gender and age of the subject from the database 106 ( S109 ).

Next, the diagnosis module 108 compares the average of the first EEG data of the subject with the extracted first EEG data to determine whether there is a deficiency in the neurotransmitter of the subject (S 111 ). As a result of checking in step S 111 , if there is a deficiency in the neurotransmitter of the test subject, the diagnosis module 108 generates prescription information according to the type and degree of the deficiency of the neurotransmitter ( S 113 ).

Next, the diagnosis module 108 extracts an average of the second EEG data corresponding to the gender and age of the subject from the database 106 (S115).

Next, the diagnosis module 108 compares the average of the second EEG data and the extracted second EEG data of the subject to determine whether there is an abnormality in the prefrontal executive state (or the prefrontal development state) of the subject (S 117 ) ). As a result of checking in step S117, if there is an abnormality in the frontal lobe execution state of the subject, the diagnosis module 108 generates prescription information according to the ability and the abnormality in which the abnormality occurs (S119).

4 is a graph showing the average development curve of the second EEG according to the inhibitory force task (NoGo Suppression) in an exemplary embodiment. Figure 4 (a) is a graph showing the average development curve for the amplitude (Amplitude) of the second brain wave according to the inhibitory task, Figure 4 (b) is the latency of the second brain wave according to the inhibitory task (Latency) It is a graph showing the average development curve. Here, the x-axis represents the age of reference children and adolescents, and the y-axis represents the standardized average value.

Referring to (a) of FIG. 4 , it can be seen that the average value of the size of the second EEG according to the inhibitory task increases as the age of the reference children and adolescents increases. In (a) of FIG. 4 , the graph SG 1 is a graph showing the magnitude of the second EEG according to the inhibitory force task. Here, the x-axis represents time (ms), and the y-axis represents potential (µV). The magnitude of the second EEG according to the inhibitory force task may mean a maximum amplitude value in the graph SG 1 .

Referring to (b) of FIG. 4 , it can be seen that the average latency of the second EEG according to the inhibition task decreases as the age of the reference children and adolescents increases. In (b) of FIG. 4 , the graph SG 2 is a graph showing the latency of the second EEG according to the inhibitory force task. Here, the x-axis represents time (ms), and the y-axis represents potential (µV). The latency of the second EEG according to the restraining force task may mean a period from the time of the reaction of the reference children and adolescents to the appearance of the maximum amplitude.

5 is a graph showing the average development curve of the second EEG according to the reflexive task (NoGo Monitoring) in an exemplary embodiment. Figure 5 (a) is a graph showing the average development curve for the amplitude (Amplitude) of the second brain wave according to the reflex task, Figure 5 (b) is the latency of the second brain wave according to the reflex task task It is a graph showing the average development curve. Here, the x-axis represents the age of reference children and adolescents, and the y-axis represents the standardized average value.

Referring to (a) of FIG. 5 , it can be seen that the average value of the size of the second EEG according to the reflexive task is constant from the age of 7 to 12 of the reference children and adolescents, and then increases from the age of 13 or more. In (a) of FIG. 5 , the graph SG 3 is a graph showing the magnitude of the second EEG according to the reflexive task. Here, the x-axis represents time (ms), and the y-axis represents potential (µV). The magnitude of the second EEG according to the reflective force task may mean a maximum amplitude value in the graph SG 3 .

Referring to (b) of FIG. 5 , it can be seen that the average latency of the second EEG according to the reflexive task decreases as the age of the reference children and adolescents increases. In (b) of FIG. 5 , the graph SG 4 is a graph showing the latency of the second EEG according to the reflexive task. Here, the x-axis represents time (ms), and the y-axis represents potential (µV). The latency of the second EEG according to the reflexive task may mean a period from the reaction time of the reference children and adolescents to the appearance of the maximum amplitude.

6 is a graph showing the average development curve of the second brain wave according to the task performance (P3b) task in an exemplary embodiment. Figure 6 (a) is a graph showing the average development curve for the magnitude (Amplitude) of the second brain wave according to the task performance task, Figure 6 (b) is the latency of the second brain wave according to the task performance task (Latency) It is a graph showing the average development curve for Here, the x-axis represents the age of reference children and adolescents, and the y-axis represents the standardized average value.

Referring to (a) of Figure 6, it can be seen that the average value of the size of the second EEG according to the task performance task increases from the age of 7 to 8 of the reference children and adolescents, and decreases slightly as the age increases from the age of 9. . In (a) of FIG. 6 , the graph SG 5 is a graph showing the magnitude of the second EEG according to the task performance task. Here, the x-axis represents time (ms), and the y-axis represents potential (µV). The magnitude of the second EEG according to the task performance task may mean a maximum amplitude value in the graph SG 5 .

Referring to (b) of FIG. 6 , the average value of the latency of the second EEG according to the task performance task increases until the age of 7 to 8 years of age of the reference children and adolescents, decreases until the age of 9 to 13, and then increases again after the age of 14 can be seen doing In (b) of FIG. 6 , the graph SG 6 is a graph showing the latency of the second EEG according to the task performance task. Here, the x-axis represents time (ms), and the y-axis represents potential (µV). The latency of the second EEG according to the task performance task may mean a period from the reaction time of the reference children and adolescents to the appearance of the maximum amplitude.

7 is a graph showing the average development curve of the second brain wave according to the atmospheric condition task performance (Cue P3) task in an exemplary embodiment. Figure 7 (a) is a graph showing the average development curve for the amplitude (Amplitude) of the second EEG according to the atmospheric condition task performance task, Figure 7 (b) is the second EEG according to the atmospheric condition task performance task A graph showing the average development curve for latency. Here, the x-axis represents the age of reference children and adolescents, and the y-axis represents the standardized average value.

Referring to (a) of FIG. 7 , it can be seen that the average value of the size of the second EEG according to the task performance task in the atmospheric condition increases from the age of 7 to 9 of the reference children and adolescents, and decreases as the age increases from the age of 10. . In (a) of FIG. 7 , the graph SG 7 is a graph showing the magnitude of the second EEG according to the atmospheric condition task performance task. Here, the x-axis represents time (ms), and the y-axis represents potential (µV). The magnitude of the second EEG according to the atmospheric condition task performance task may mean a maximum amplitude value in the graph SG 7 .

Referring to (b) of FIG. 7 , it can be seen that the average value of the latency of the second EEG according to the task performance task in the atmospheric condition increases somewhat as the age of the reference children and adolescents increases. However, it can be seen that the average value of the latency of the second EEG according to the task performance task in the atmospheric condition does not have a significant difference according to the age. In (b) of FIG. 7 , the graph SG 8 is a graph showing the latency of the second EEG according to the atmospheric condition task performance task. Here, the x-axis represents time (ms), and the y-axis represents potential (µV). The latency of the second EEG according to the task performance task in the atmospheric condition may mean a period from the reaction time of the reference children and adolescents to the appearance of the maximum amplitude.

8 is a graph illustrating an average developmental curve for a second brain wave according to a preparation capacity (CNV) task in an exemplary embodiment. Here, the x-axis represents the age of reference children and adolescents, and the y-axis represents the standardized average value. In the case of the second EEG according to the preparatory ability task, the area ( area) is calculated.

Referring to FIG. 8 , it can be seen that the average value of the area of the second EEG according to the preparation ability task varies greatly according to the age of the reference children and adolescents. That is, it can be seen that the average value of the area of the second EEG according to the preparation ability task increases until the age of 7 to 9, decreases until the age of 10 to 13, and increases again until the age of 14 to 16 of the reference children and adolescents. In FIG. 8 , the graph SG 9 is a graph showing an area below the reference potential based on the reference potential for the second EEG according to the preparation ability task. Here, the x-axis represents time (ms), and the y-axis represents potential (µV).

9 is a graph showing the average development curve of the second EEG according to the adaptive ability (Novelty) task in an exemplary embodiment. Figure 9 (a) is a graph showing the average development curve for the amplitude (Amplitude) of the second EEG according to the adaptive ability task, Figure 9 (b) is the latency of the second EEG according to the adaptive ability task It is a graph showing the average development curve for Here, the x-axis represents the age of reference children and adolescents, and the y-axis represents the standardized average value.

Referring to (a) of FIG. 9 , it can be seen that the average value of the size of the second EEG according to the adaptive ability task decreases slightly until the age of the reference children and adolescents is 9 to 12 years old, but increases as the age increases from the age of 13 years. In (a) of FIG. 9 , the graph SG 10 is a graph showing the magnitude of the second EEG according to the adaptive ability task. Here, the x-axis represents time (ms), and the y-axis represents potential (µV). The magnitude of the second brain wave according to the adaptive ability task may mean a maximum amplitude value in the graph SG 10 .

Referring to FIG. 9B , it can be seen that the average latency of the second EEG according to the adaptive ability task decreases somewhat as the age of the reference children and adolescents increases. In (b) of FIG. 9 , the graph SG 11 is a graph showing the latency of the second EEG according to the adaptive ability task. Here, the x-axis represents time (ms), and the y-axis represents potential (µV). The latency of the second EEG according to the adaptive ability task may refer to a period from the reaction time of the reference children and adolescents to the appearance of the maximum amplitude.

10 is a graph showing the average development curve of the second EEG according to the Ignore task in an exemplary embodiment. Figure 10 (a) is a graph showing the average development curve for the amplitude (Amplitude) of the second brain wave according to the neglect task, Figure 10 (b) is the second brain wave latency (Latency) according to the neglect task It is a graph showing the average development curve for Here, the x-axis represents the age of reference children and adolescents, and the y-axis represents the standardized average value.

Referring to (a) of FIG. 10 , it can be seen that the average value of the size of the second EEG according to the neglect task decreases as the age of the reference children and adolescents increases. In (a) of FIG. 10 , the graph SG 12 is a graph showing the magnitude of the second EEG according to the neglect task. Here, the x-axis represents time (ms), and the y-axis represents potential (µV). The magnitude of the second EEG according to the neglect task may mean a maximum amplitude value in the graph SG 12 .

Referring to (b) of FIG. 10 , it can be seen that the average value of the latency of the second EEG according to the neglect task increases somewhat as the age of the reference children and adolescents increases, and then decreases slightly based on the age of 12. In (b) of FIG. 10 , the graph SG 13 is a graph showing the latency of the second EEG according to the neglect task. Here, the x-axis represents time (ms), and the y-axis represents potential (µV). The latency of the second EEG according to the ignorance task may mean a period from the time of the reaction of the reference children and adolescents to the appearance of the maximum amplitude.

11 illustrates a computing environment including an example computing device suitable for use in example embodiments.

The example computing environment 200 shown in FIG. 11 includes a computing device 210 . Typically, each configuration may have different functions and capabilities, and may additionally include components suitable for the configuration, even if not described below. The computing device 210 may be a device or system for diagnosing a brain health state by measuring brain waves (eg, the brain health state diagnosis apparatus 100 ).

The computing device 210 includes at least one processor 212 , a computer readable storage medium 214 , and a bus 260 . The processor 212 is coupled to a bus 260 , which connects various other components of the computing device 210 to the processor 212 , including a computer-readable storage medium 214 .

The processor 212 may cause the computing device 210 to operate in accordance with the example embodiments discussed above. For example, the processor 212 may execute computer-executable instructions stored in the computer-readable storage medium 214 , and the computer-executable instructions stored in the computer-readable storage medium 214 are executed by the processor 212 . Computing device 210 may be configured to perform operations in accordance with certain example embodiments.

Computer-readable storage medium 214 may contain computer-executable instructions or program code (eg, instructions included in application 230 ), program data (eg, data used by application 230 ), and/or other suitable form. is configured to store the information of The application 230 stored in the computer readable storage medium 214 includes a predetermined set of instructions executable by the processor 212 .

The memory 216 and storage device 218 shown in FIG. 11 are examples of computer-readable storage media 214 . The memory 216 may be loaded with computer-executable instructions that may be executed by the processor 212 . Also, program data may be stored in the memory 216 . For example, such memory 216 may be volatile memory, such as random access memory, non-volatile memory, or a suitable combination thereof. As another example, storage device 218 may include one or more removable or non-removable components for storage of information. For example, storage device 218 can be a hard disk, flash memory, magnetic disk, optical disk, other form of storage medium that can be accessed by computing device 210 and can store desired information, or a suitable combination thereof.

Computing device 210 may also include one or more input/output interfaces 220 that provide interfaces for one or more input/output devices 270 . The input/output interface 220 is connected to the bus 260 . The input/output device 270 may be connected to (other components of) the computing device 210 via the input/output interface 220 . The input/output device 270 includes an input device such as a pointing device, a keyboard, a touch input device, a voice input device, a sensor device, and/or a photographing device and/or an output device such as a display device, a printer, a speaker and/or a network card. can do.

On the other hand, certain embodiments may include a computer-readable storage medium including a program for performing the process described in this specification on a computer. These computer-readable storage media may include program instructions, local data files, local data structures, and the like alone or in combination. The computer-readable storage medium may be those specially designed and constructed for the present invention. Examples of computer-readable storage media include hard disks, magnetic media such as floppy disks and magnetic tapes, optical recording media such as CD-ROMs and DVDs, magneto-optical media such as floppy disks, and ROMs, RAMs, flash memories, and the like. Hardware devices specially configured to store and execute the same program instructions are included. Examples of program instructions may include high-level language codes that can be executed by a computer using an interpreter or the like as well as machine language codes such as those generated by a compiler.

Although representative embodiments of the present invention have been described in detail above, those of ordinary skill in the art to which the present invention pertains will understand that various modifications are possible within the limits without departing from the scope of the present invention with respect to the above-described embodiments. . Therefore, the scope of the present invention should not be limited to the described embodiments, and should be defined by the claims described below as well as the claims and equivalents.

100: brain health condition diagnosis device
102: EEG measurement unit
104: data processing unit
106: database
108: diagnostic module

Claims (20)

one or more processors, and
A method performed in a computing device having a memory storing one or more programs to be executed by the one or more processors, the method comprising:
Acquiring the first EEG data in a state in which the task is not performed and the second EEG data in the state in which the task is performed of the reference children and adolescents, respectively;
Using the obtained first EEG data and second EEG data, the average related information of the first EEG data and the average related information of the second EEG data according to at least one of gender and age of the reference children and adolescents are calculated and stored, respectively. to do;
acquiring first EEG data in a state in which a task of the subject is not performed and second EEG data in a state in which a task is performed, respectively;
extracting the average-related information of the first EEG data and the average-related information of the second EEG data corresponding to the gender and age of the person to be measured, respectively;
comparing the first EEG data of the person to be measured and the average related information of the first EEG data, and comparing the second EEG data of the person to be measured and the average related information of the second EEG data; and
Comprising the step of checking the brain health state of the subject according to the comparison result,
The second EEG data is, the subject's suppression power (NoGo Suppression) task, reflective power (NoGo Monitoring) task, task performance (P3b) task, atmospheric condition task performance (Cue P3) task, preparation capability (CNV) task, adaptation It is data for brain waves measured while performing at least one of the ability (Novelty) task, and the Ignore task,
The step of confirming the brain health status of the person to be measured includes checking the frontal lobe development status of the person to be measured according to a comparison result of the second EEG data of the person to be measured and the average related information of the second EEG data , a method of providing information on brain health status in children and adolescents.
The method according to claim 1,
The task for obtaining the second EEG data is,
NoGo Suppression task, NoGo Monitoring task, P3b task, Cue P3 task, Preparatory capacity (CNV) task, Adaptive capacity (Novelty) task, and Ignore (Ignore) task. ) task, comprising at least one of the following tasks:
The method according to claim 1,
The average related information of the first EEG data includes at least one of an average value of the amplitude of the first EEG, a standard deviation of the size of the first EEG, and an average development curve for each age of the first EEG size do,
The average related information of the second EEG data includes an average value of the amplitude of the second EEG, an average value of the latency of the second EEG, a standard deviation of the size of the second EEG, and the second EEG. A method of providing information on brain health status of children and adolescents, comprising at least one of a standard deviation of latency, an average development curve for each age of the magnitude of the second brain wave, and an average development curve for each age of the latency of the second brain wave.
The method according to claim 1,
The first brain wave data includes at least one of delta wave, theta wave, alpha wave, SMR (Sensory Motor Rhythm), beta wave, and high beta wave,
The step of checking the brain health state of the person to be measured includes the step of determining whether the person is deficient in a neurotransmitter according to a result of comparing the first EEG data of the person to be measured and the average related information of the first EEG data A method of providing information on brain health status in children and adolescents, comprising.
5. The method according to claim 4,
When a deficiency occurs in the neurotransmitter of the subject, providing information on the brain health status of children and adolescents, further comprising the step of generating prescription information according to the type of the deficient neurotransmitter and the degree of the deficiency Way.
delete The method according to claim 1,
As a result of the confirmation, if there is an abnormality in the developmental state of the frontal lobe of the subject, information on the brain health state of children and adolescents further comprising the step of generating prescription information according to the abnormality and the degree of abnormality How to.
one or more processors, and
A method performed in a computing device having a memory storing one or more programs to be executed by the one or more processors, the method comprising:
Acquiring EEG data of a state in which the task of the reference children and adolescents is performed;
calculating and storing average related information of EEG data according to at least one of gender and age of the reference children and adolescents using the obtained EEG data;
acquiring EEG data of a state in which a task of the person to be measured is performed;
extracting average related information of EEG data corresponding to the gender and age of the subject;
comparing the EEG data of the subject and the average related information of the extracted EEG data; and
Comprising the step of checking the brain health state of the subject according to the comparison result,
The EEG data is, the target person's suppression power (NoGo Suppression) task, reflective power (NoGo Monitoring) task, task performance (P3b) task, atmospheric condition task performance (Cue P3) task, preparation capability (CNV) task, adaptive capability ( Novelty) task, and data for brain waves measured while performing at least one of the task, and ignorance (Ignore) task,
The step of confirming the brain health status of the person to be measured includes the step of checking the frontal lobe development state of the person to be measured according to the comparison result of the average related information of the EEG data of the person to be measured and the extracted EEG data, children and adolescents How to provide information about your brain health.
delete 9. The method of claim 8,
The average related information of the EEG data is,
The average value of the amplitude of the EEG, the average value of the latency of the EEG, the standard deviation of the size of the EEG, the standard deviation of the latency of the EEG, the average development curve for each age of the size of the EEG, and the EEG A method of providing information on brain health status in children and adolescents comprising at least one of the age-specific mean developmental curves of latency.
delete 9. The method of claim 8,
As a result of the confirmation, if there is an abnormality in the developmental state of the frontal lobe of the subject, information on the brain health state of children and adolescents further comprising the step of generating prescription information according to the abnormality and the degree of abnormality How to.
one or more processors;
Memory; and
A device comprising one or more programs, comprising:
wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors;
The program is
acquiring first EEG data in a state in which a task of the subject is not performed and second EEG data in a state in which a task is performed, respectively;
extracting the average-related information of the first EEG data and the average-related information of the second EEG data corresponding to the gender and age of the person to be measured, respectively;
comparing the first EEG data of the person to be measured and the average related information of the first EEG data, and comparing the second EEG data of the person to be measured and the average related information of the second EEG data; and
Includes instructions for executing the step of checking the brain health state of the subject according to the comparison result,
The task for obtaining the second EEG data is,
NoGo Suppression task, NoGo Monitoring task, P3b task, Cue P3 task, Preparatory capacity (CNV) task, Adaptive capacity (Novelty) task, and Ignore (Ignore) task. ) includes at least one of the tasks,
The program, in the step of checking the brain health state of the subject,
An apparatus comprising instructions for executing the step of confirming the frontal lobe development state of the measured subject according to a comparison result of the subject's second EEG data and the average related information of the second EEG data.
delete delete 14. The method of claim 13,
The program is
As a result of the check, if there is an abnormality in the frontal lobe development state of the person to be measured, the apparatus comprising instructions for further executing the step of generating prescription information according to the ability to have the abnormality and the degree of the abnormality.
one or more processors;
Memory; and
A device comprising one or more programs, comprising:
wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors;
The program is
acquiring EEG data of a state in which a task of the person to be measured is performed;
extracting average related information of EEG data corresponding to the gender and age of the subject;
comparing the EEG data of the subject and the average related information of the extracted EEG data; and
Includes instructions for executing the step of checking the brain health state of the subject according to the comparison result,
The task for obtaining the brain wave data is,
NoGo Suppression task, NoGo Monitoring task, P3b task, Cue P3 task, Preparatory capacity (CNV) task, Adaptive capacity (Novelty) task, and Ignore (Ignore) task. ) includes at least one of the tasks,
The program, in the step of checking the brain health state of the subject,
An apparatus comprising instructions for executing the step of confirming the frontal lobe development state of the measured subject according to a comparison result of the measured subject's EEG data and the average related information of the extracted EEG data.
delete delete 18. The method of claim 17,
The program is
As a result of the check, if there is an abnormality in the frontal lobe development state of the person to be measured, the apparatus comprising instructions for further executing the step of generating prescription information according to the ability to have the abnormality and the degree of the abnormality.

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