KR20190089678A - Method and electronic device for diagnosing and predicting a mental illness using a heart rate variability and a quantitative electroencephalography - Google Patents

Abstract

An apparatus for diagnosing and predicting a mental illness according to an embodiment of the present invention includes a measuring part having electrodes having a plurality of channels for measuring a quantitative electroencephalography signal; an amplifier for amplifying the quantitative electroencephalography signal measured by the measuring part; an electroencephalogram measuring device which measures heart rate variability; a signal extraction part for extracting the middle beta 2 of the quantitative electroencephalography signal and the low frequency of the heart rate variability based on the amplified quantitative electroencephalography signal and the measured heart rate variability; and a mental illness determination part configured to determine a mental illness using the middle beta 2 of the quantitative electroencephalography signal and the low frequency of the heart rate variability. Other embodiments are possible.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method and apparatus for diagnosing and predicting mental disorders using heart beat variability and quantitative EEG,

The present invention relates to an apparatus and a method for diagnosing and predicting a mental disease using quantitative electroencephalography (qEEG) and heart rate variability (HRV), and more particularly, LF) power and middle beta2 power of quantitative EEG. The present invention relates to a device and a method for diagnosing and predicting a mental disease of a patient.

People living in modern society are exposed to various situations and there is a lot of mental stress caused by them. Such stress causes mental diseases such as depression, and social problems caused by this are getting serious.

For example, mental illness can be induced in adulthood according to childhood trauma.

Childhood trauma is considered to be a risk factor for various affective disorders in adulthood as well as childhood.

Children experiencing trauma are at high risk for developing depression and anxiety disorders and may be more anxious than unexperienced children.

Therefore, if the mental illness that the patient is experiencing is judged to be due to psychosocial stress factors in childhood trauma and various other things, it can be treated more specifically for mental illness in relation to childhood trauma and other psychosocial factors Therefore, effective treatment of mental illness may be possible.

This is because there is accumulating evidence that the psychological and social stressors in childhood trauma and various other factors change our brain EEG and heart rate variability.

Therefore, the method of diagnosing and predicting mental illnesses related to childhood trauma and various other psychosocial factors is a very serious problem in the treatment of mental illness.

Therefore, a method for diagnosing and predicting a patient's mental illness associated with childhood trauma and various other psychosocial factors is currently in desperate need.

SUMMARY OF THE INVENTION The present invention has been made to overcome the above problems, and it is an object of the present invention to provide a method and apparatus for diagnosing and diagnosing mental disorders by measuring and evaluating low frequency (LF) power among heart rate variability and middle beta2 power of quantitative EEG And an object of the present invention is to provide a device and a method that can be predicted.

According to various embodiments of the present invention, a device for diagnosing and predicting a mental illness includes: a measurement unit having electrodes having a plurality of channels for measuring a quantitative EEG signal; An amplifier for amplifying the quantitative brain wave signal measured by the measuring unit; An electroencephalogram measuring instrument for measuring heart beat variability; A signal extractor for extracting the middle beta 2 of the quantitative EEG signal and the low frequency of the heart beat variability based on the amplified quantitative EEG signal and the measured heart beat variance; And a mental disease judgment unit for judging a mental disease using the middle beta 2 of the quantitative EEG signal and the low frequency of the heart beat variability.

According to various embodiments of the present invention, a method for diagnosing and predicting a mental illness includes: measuring a quantitative EEG signal using electrodes having a plurality of channels provided in a measurement unit; Amplifying the quantitative EEG signal measured by the measuring unit using an amplifier; Measuring heart rate variability using an electroencephalogram meter; Extracting the middle beta 2 of the quantitative EEG signal and the low frequency of the heart beat variability based on the amplified quantitative EEG signal and the measured heart beat variability using the signal extracting unit; And determining a mental illness using the middle beta 2 of the quantitative EEG signal and the low frequency of the heart beat variability through a mental disease judgment unit.

As described above, the apparatus and method for diagnosing a mental disorder according to the present invention can diagnose and predict a mental disease caused by childhood trauma in an early stage.

In addition, the accuracy of mental illness judgment can be improved by judging the mental illness based on concrete numerical values rather than psychological mentalities.

In addition, early childhood trauma and other treatments for mental illnesses due to psychosocial stress factors can be provided.

FIG. 1 is an exemplary view showing measurement electrodes disposed on a patient's head for measuring brain waves of a patient.
FIG. 2 is a block diagram showing two hypothetical models for the relationship between psychological and social stressors, heart rate variability, quantitative EEG, and emotional instability in adulthood in childhood trauma and others.
FIG. 3 is a block diagram illustrating a model suitable for the association between psychological and social stressors, heart rate variability, quantitative EEG, and emotional instability in adulthood in childhood trauma and the like.
FIG. 4 is a schematic view of a device for diagnosing and diagnosing a mental illness using quantitative EEG and heart beat variability according to an embodiment of the present invention. Referring to FIG.
5 is a flowchart illustrating a method for diagnosing and diagnosing a mental disease using quantitative EEG and heart beat variability according to an embodiment of the present invention.

Various embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the following description of the present invention, a detailed description of known functions and configurations incorporated herein will be omitted when it may make the subject matter of the present invention rather unclear. The following terms are defined in consideration of the functions of the present invention and may vary depending on the intention of the user, the intention of the operator, or the like. Therefore, the definition should be based on the contents throughout this specification. Other objects, features and advantages of the present invention will become apparent from the detailed description of the embodiments with reference to the accompanying drawings. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A preferred embodiment of a method for diagnosing and predicting a mental illness according to the present invention will be described with reference to the accompanying drawings. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. It is provided to let you know.

FIG. 1 is an exemplary view showing measurement electrodes disposed on a patient's head for measuring brain waves of a patient. FIG. 2 is a block diagram showing two hypothetical models for the relationship between psychological and social stressors, heart rate variability, quantitative EEG, and emotional instability in adulthood in childhood trauma and others. FIG. 3 is a block diagram illustrating a model suitable for the association between psychological and social stressors, heart rate variability, quantitative EEG, and emotional instability in adulthood in childhood trauma and the like.

Referring to FIGS. 1 to 3, the apparatus for diagnosing and predicting mental diseases according to the present invention can detect EEG (electroencephalography) signals of a patient using an amplifier having 62 Ag-AgCl electrodes.

For example, 62 Ag-AgCl electrodes (FP1, FPZ, FP2, AF3, AF4, F7, F5, F3, F1, FZ, F2, F4, F6, F8, FT7, FC5, , FC2, FC4, FC6, FT8, T7, C5, C3, C1, C2, C4, C6, T8, TP7, CP5, CP3, CP1, CPZ, CP2, CP4, CP6, TP8, , P3, P1, PZ, P2, P4, P6, P8, PO7, PO5, PO3, POZ, PO4, PO6, PO8, CB1, O1, OZ, O2, CB1, and CB2.

For example, fourteen electrodes (FP1, FPZ, FP2, AF3, AF4, F7, F5, F3, F1, FZ, F2, F4, F6, F8) Nine electrodes T7, C5, C3, C1, CZ, C2, C4, C6 and T8 can be arranged in the central region of the head of the patient and 21 electrodes P7, P5, P3, , PZ, P2, P4, P6, P8, PO7, PO5, PO3, POZ, PO4, PO6, PO8, CB1, O1, OZ, O2, TP7, TP8.

In one embodiment, the ground electrode of the amplifier can be placed in the patient's forehead, and the reference electrode can be placed in the patient's mastoids.

Vertical electrooculograms (EOGs) can be located above and below the left eye, and horizontal EOGs can be recorded at both ends of the patient's eye.

The impedance of the amplifier can be set below 5 kΩ and all data acquired by the EEG signal can be processed with a 0.1-100 Hz bandpass filter at a sampling rate of 1000 Hz and a notch filter filter can be used to remove noise of 60 Hz.

In one embodiment, EEG data may be obtained from patients resting their eyes closed.

EEG data can be divided into epochs less than 2 seconds in length (2048 points), and units (epochs) in which signals exceed ± 100 μV in all channels of the amplifier can be excluded. The EEG data are processed using a fast Fourier transformation using delta (1-4 Hz), theta (4-8 Hz), alpha 1 (8-10 Hz), alpha 2 (alpha 2) (10-12 Hz), beta 1 (beta 1) (12-18), beta 2 (beta 2) (18-22 Hz), beta 3 (22-30 Hz) and gamma (30-50 Hz) Branch frequency bands. On the other hand, the relative power of each electrode of the amplifier can be calculated by dividing the power of each band by the total power of the electrodes.

In one embodiment, the apparatus for diagnosing and diagnosing mental disorders according to the present invention uses an electroencephalogram (ECG) signal to determine heart rate variability (HRV) according to a 256 Hz sampling rate Can be measured.

The ECG electrode sensor included in the electroencephalogram measuring device may be attached to a part of a patient's body.

The device for diagnosing and diagnosing a mental disease can be applied to an electroencephalogram signal recording a high-pass filter having a cutoff frequency of 2 HZ for noise removal.

In addition, the device for diagnosing and predicting mental disorders can calculate the power spectrum of the heart rate variability signal using the Fourier transform and the heart rate variability signal can be obtained by using very low frequency power (VLF; <0.04 Hz) low frequency power (LF; 0.04-0.15 Hz), and high frequency power (HF; 0.15-0.4 Hz).

On the other hand, the correlation between psychiatric disorders, quantitative EEG and heart rate variability due to psychosocial stress factors in childhood trauma and various other factors can be confirmed by experimenting with multiple patients as follows.

For example, 103 patients were tested and the mean score of the Childhood Trauma Questionnaire (CTQ) was 42.29, which may indicate that an individual has experienced mild to moderate childhood trauma.

Of the patients, 47.5% experienced at least mild childhood trauma, and 9.9% experienced at least moderate to severe childhood trauma.

In addition, as a result of the correlation analysis of the patients, the total score of childhood trauma is highly related to the low frequencies of depression, anxiety, emotional instability, and heart rate variability.

In addition, the affective lability of the patients was found to be related to the middle beta2 power of the quantitative EEG, and emotional instability had a significant correlation with depression, state anxiety, and trait anxiety.

Two models are assumed for path analysis based on correlation analysis. The first hypothesis model consisted of emotional instability in the CTQ score, pathway from quantitative EEG middle beta 2 and middle beta 2 to emotional instability.

The second assumed model consisted of emotional instability in the CTQ score, emotional instability, middle beta 2 in the quantitative EEG, and low frequency in the middle beta 2 to the heart rate variability.

Figure 2 shows two assumed models.

The evaluation index for evaluating the fit of the two models was chi-square test (χ 2), comparative fit index (CFI), Tucker-Lewis index (TLI), root mean square error of approximation squared residuals (SRMR) were used.

The evaluation indices of hypothesis model A in Fig. 2 are χ 2 = 29.403, df = 11, p = .002; CFI = .927; TLI = .860; RMSEA = .128 (confidence interval = .073-.185); SRMR = .108; and AIC = 63.403. Also, the evaluation index of the hypothesis model B in Fig. 2 is?? 2 = 12, df = 11, p = .363; CFI = .996; TLI = .992; RMSEA = .030 (confidence interval = .000-.111); SRMR =. 059; and AIC = 46.003. It was determined that the fit index of B model in Fig. 2 satisfied the criterion and the AIC of the B model was much lower than that of the A model, so that it was more suitable to judge the patient than the A model.

According to the above determination, the final model is determined as shown in FIG.

The pathway from childhood trauma to depression, from depression to emotional instability, from emotional instability to the middle beta 2 of quantitative EEG, and from the middle beta 2 of the quantitative EEG to the low frequency of heart rate variability were identified .

Therefore, it can be confirmed that depression, emotional instability, heart beat variability and quantitative EEG changes may occur after childhood trauma.

In other words, childhood trauma can affect the emotional instability of the patient first, emotional instability can have a positive correlation with the middle beta 2 activity of the brain waves, middle beta 2 activity can affect the low frequency and negative a negative correlation can be obtained.

That is, it can be confirmed from the above experiment that the middle beta 2 of the quantitative EEG and the low frequency of the heart rate variability can be used to judge a mental disorder such as emotional instability according to childhood trauma.

In addition, childhood trauma may have a negative relationship with the low frequency of heart beat variability. In addition, middle beta 2 of quantitative EEG correlated negatively with the low frequency of heart rate variability.

In summary, emotional problems due to psychosocial stress factors in childhood trauma and others can be judged by detecting low-frequency of middle beta 2 and heart beat variability of quantitative EEG during adult period.

FIG. 4 is a schematic view of a device for diagnosing and diagnosing a mental illness using quantitative EEG and heart beat variability according to an embodiment of the present invention. Referring to FIG.

Referring to FIG. 4, an apparatus for diagnosing and predicting a mental disease according to an embodiment of the present invention includes a measurement unit 10 having electrodes having a plurality of channels for measuring a quantitative brain wave signal, (30) for measuring the heart beat variability, (30) a middle beta 2 of the quantitative EEG based on the amplified EEG signal and measured heart beat variability, and heart beat variability And a mental disease judgment unit 50 for judging a mental illness based on the signal extracted by the signal extracting unit 40. [

The apparatus for diagnosing and predicting a mental illness may further include a memory 60 for storing data related to quantitative EEG and heart beat variability extracted by the signal extracting unit.

5 is a flowchart illustrating a method for diagnosing and diagnosing a mental disease using quantitative EEG and heart beat variability according to an embodiment of the present invention. The operation of the apparatus for diagnosing and diagnosing a mental illness according to the present invention will now be described with reference to FIG.

Referring to FIG. 5, in step 501, a measurement unit 10 having electrodes having a plurality of channels for measuring a quantitative EEG signal may be disposed at a designated position of a head of a patient, The predictor can measure the electroencephalogram signal by performing measurement of potential based on neuronal activation in the brain using a fixed sampling interval at a predetermined sampling interval.

In step 502, the mental disease and prediction apparatus can amplify the quantitative EEG signal measured by the measuring unit 10 using the amplifier 20.

Since the quantitative brain wave measured by the measuring unit 10 is a weak signal, the measured quantitative brain wave signal is amplified by the amplifier 20.

In step 503, the mental disease and prediction apparatus can measure the heart rate variability using the electroencephalogram meter 30. [

In step 504, the mental illness and prediction device calculates a mean value of the mean beta 2 of the quantitative EEG signal and the low frequency of the heart beat variability of the quantitative EEG signal based on the amplified quantitative EEG signal and the measured heart beat variance using the signal extraction unit 40 Can be extracted.

In step 505, the mental illness and prediction device can determine the mental illness based on the middle beta 2 of the quantitative EEG signal and the low frequency of the heart beat variability using the mental disease judgment unit 50.

For example, the emotional instability of a patient according to childhood trauma has a positive correlation with the middle beta 2 activity of the EEG, and the middle beta 2 activity has a negative correlation with the low frequency of the heart rate variability.

In addition, the childhood trauma had a negative relationship with the low frequency of heart rate variability, and the middle beta 2 of the quantitative EEG correlated negatively with the low frequency of heart rate variability.

Therefore, the mental disease and prediction device can be judged as a mental disease caused by childhood trauma if the middle beta 2 of the quantitative EEG signal and the low frequency of heart beat variability satisfy the above-mentioned relationships.

For example, when the middle beta 2 of the quantitative EEG signal is higher than the normal value, the low frequency of the heart rate variability is lower than the normal value, and the middle beta 2 of the quantitative EEG and the low frequency of the heart rate variability are inversely proportional to each other, Childhood trauma, and various other psychological and social stressors.

On the other hand, the device for diagnosing and predicting mental diseases can store information relating to the patient's quantitative EEG and heart rate variability, and diagnosis and prediction information of the patient in the memory 60.

According to various embodiments of the present invention, a device for diagnosing and predicting a mental illness includes: a measurement unit having electrodes having a plurality of channels for measuring a quantitative EEG signal; An amplifier for amplifying the quantitative brain wave signal measured by the measuring unit; An electroencephalogram measuring instrument for measuring heart beat variability; A signal extractor for extracting the middle beta 2 of the quantitative EEG signal and the low frequency of the heart beat variability based on the amplified quantitative EEG signal and the measured heart beat variance; And a mental disease judgment unit for judging a mental disease using the middle beta 2 of the quantitative EEG signal and the low frequency of the heart beat variability.

According to various embodiments of the present invention, the mental disease determination unit may determine that the middleset brain wave signal has the middle beta 2 higher than the normal value, the low frequency of the heart beat variability lower than the normal value, If the low frequencies of heart beat variability are inversely proportional to each other, it can be judged as a mental disorder.

According to various embodiments of the present invention, a method for diagnosing and predicting a mental illness includes: measuring a quantitative EEG signal using electrodes having a plurality of channels provided in a measurement unit; Amplifying the quantitative EEG signal measured by the measuring unit using an amplifier; Measuring heart rate variability using an electroencephalogram meter; Extracting the middle beta 2 of the quantitative EEG signal and the low frequency of the heart beat variability based on the amplified quantitative EEG signal and the measured heart beat variability using the signal extracting unit; And determining a mental illness using the middle beta 2 of the quantitative EEG signal and the low frequency of the heart beat variability through a mental disease judgment unit.

According to various embodiments of the present invention, a method for diagnosing and predicting a mental illness is characterized in that the middle beta 2 of the quantitative EEG signal is higher than a normal value, the low frequency of the heart rate variability is lower than a normal value, And if the low frequency of the heart beat variability is inversely proportional to each other, judging the mental disease as a mental disorder.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments.

It will be apparent to those skilled in the art that various modifications may be made without departing from the scope of the present invention. Accordingly, the true scope of the present invention should be determined by the technical idea of the appended claims.

The present invention has been described with reference to the preferred embodiments. It will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

Therefore, the disclosed embodiments should be considered in an illustrative rather than a restrictive sense. The scope of the present invention is defined by the appended claims rather than by the foregoing description, and all differences within the scope of equivalents thereof should be construed as being included in the present invention.

10: Measuring section 20: Amplifier
40: psychiatric diagnosis part 50: psychiatric judgment part
60: Memory

Claims (4)

A measurement unit having electrodes having a plurality of channels for measuring a quantitative EEG signal;
An amplifier for amplifying the quantitative brain wave signal measured by the measuring unit;
An electroencephalogram measuring instrument for measuring heart beat variability;
A signal extractor for extracting the middle beta 2 of the quantitative EEG signal and the low frequency of the heart beat variability based on the amplified quantitative EEG signal and the measured heart beat variance; And a mental disease diagnosis unit for determining the mental illness using the middle beta 2 of the quantitative EEG signal and the low frequency of the heart beat variability. The method according to claim 1,
When the middle beta 2 of the quantitative EEG signal is higher than a normal value and the low frequency of the heart beat variability is lower than a normal value and the middle beta 2 of the quantitative EEG and the low frequency of the heart beat variability are inversely proportional to each other, Diagnostic and predictive devices for mental illness. Measuring a quantitative EEG signal using electrodes having a plurality of channels provided in a measurement unit;
Amplifying the quantitative EEG signal measured by the measuring unit using an amplifier;
Measuring heart rate variability using an electroencephalogram meter;
Extracting the middle beta 2 of the quantitative EEG signal and the low frequency of the heart beat variability based on the amplified quantitative EEG signal and the measured heart beat variability using the signal extracting unit; And
And determining a mental illness using the low-frequency of the middle beta 2 and the heart beat variability of the quantitative EEG signal through a mental disease judgment unit. The method of claim 3,
When the middle beta 2 of the quantitative EEG signal is higher than a normal value and the low frequency of the heart beat variability is lower than a normal value and the middle beta 2 of the quantitative EEG and the low frequency of the heart beat variability are inversely proportional to each other, The method comprising the steps of:

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