Method of determining dispersion of amplitude-frequency characteristics of brain alpha-rhythm in case of mental illnesses

FIELD: medicine.

SUBSTANCE: invention relates to field of medicine, namely to neurophysiological methods of examination. Registration of EEG is carried out, total power of modal fluctuation in alpha-rhythm range in one of leads is determined and FRα1 index is calculated as ration of said power to total power of all alpha range fluctuations in the same lead. Value of the sum of power of fluctuations, located ±0.5 Hz on the right and on the left from maximal power value, including maximal value, is determined, and FRα2 index is calculated as ratio of the obtained sum of power to total power of all fluctuations of alpha-range in the same lead. Intensity of brain affection is determined by comparison of obtained FRα1 and FRα2 values with standard values.

EFFECT: method makes it possible to determined quantitative ratio of alpha-rhythm, characteristic of separate nosologic units in psychiatry.

2 tbl, 1 dwg

 

The invention relates to medical applications, in particular neurophysiological research methods.

There is a method of determining the spectral radiation power of the alpha rhythm as its amplitude-frequency characteristics when conducting EEG studies of the brain. The mathematical basis of the amplitude-frequency analysis is the Fourier transform which takes various forms depending on the type of the analyzed signals. Common is the assumption that the studied processes (signals) are composed of a certain number (possibly infinite) of sine and/or cosine components (harmonics) successively increasing the number of frequencies. The Fourier transform decomposes the signal into a series of harmonic components without any loss of information (if arithmetically combine all harmonics, we get again the original signal). Each harmonic is determined by three parameters: amplitude, initial phase and frequency. The dependence of the amplitude and phase of the harmonics of the frequency is called the spectrum. The power spectrum P(i)=f(fi) represents the amplitude spectrum, squared P(i)=A(i)2. In practice, the spectral analysis of the EEG by using the built-in computer encephalograph programs. ISCO the initial power spectrum of a particular frequency of radiation can be displayed in graphical and tabular form (Gazdecki CENTURIES The inverse problem of EEG and clinical electroencephalography. Taganrog: Medic, 2000; Zhirmunskaya E.A. Clinical electroencephalography. M.: 1991; Max J. Methodology and technique of signal processing at the technical measurements. M.: Mir, 1983; Attributed R., L. Enochson Applied time series analysis. M.: Mir, 1982. Vol. 1, 2; Rusyns B.C., Grendel O.M., Boldyreva G.N., Wacker E.M. Biopotentials brain. The mathematical analysis. M.: Medicine, 1987).

The disadvantages of this method are:

1) when analyzing the power spectral amplitude harmonics are measured in millivolts recorded on the scalp voltage and translated in the mV squared, not understood by many researchers;

2) it is difficult to analyze nonlinear relationship (in this case, quadratic);

3) the power of the alpha rhythm does not demonstrate a direct correlation with pathological deviations and nosological forms of diseases of the brain;

4) encountered in pathology, visually defined on the graph, the "splitting" of the spectrum of the alpha rhythm, occurring at various mental illnesses, are described only qualitatively (modal, dimodolo, polymodal), which complicates the finding of correlation between the severity of a specified phenomenon and the clinical picture (Ivanov LB Applied take machine vision into what I electroencephalography. JSC "Antidoron", 2000).

The above method of studying changes in the alpha rhythm with mental illnesses not represent a complete picture of the disease the patient is qualitative and non-specific character not applicable for the purposes of nosological diagnosis of brain diseases, and do not accurately diagnose the severity of the pathological process.

The Method of determining the variance of the amplitude-frequency characteristics of the alpha rhythm of the brain in mental illness" has no analogues.

Object of the invention is the detection of quantitative changes of the spectrum of the alpha rhythm, pathognomonic organic lesions of the brain, allowing you to install their quantitative ratio, specific nosologic units in psychiatry.

The problem is solved by a method for determining the relative values that are a measure of the dispersion of the amplitude-frequency characteristics of the alpha rhythm, reflecting the structural content of the spectrum of its power in a particular patient, not showing individual features and changes specific to certain pathological conditions. Applying correlation analysis of the obtained quantities are produced normative parameters.

The essence of the proposed method for luchetta in the following.

Regular shooting of the background EEG on computer electroencephalograph 19 monopolar derivations according to the international system of electrodes "10-20", when the value of impedance of 10 ohms and less than the bandwidth of 0.3-50 Hz with a sampling rate of 256 Hz. As a reference used ear electrodes. The EEG registration is held at the position of the subject, seated in a comfortable chair, in a state of relaxed wakefulness. The EEG epoch length 20 s are subjected to a fast Fourier transformation using Windows Hannah in the band 3-30 Hz (step 0.25 Hz). Weekend review forms are formed by means of specialized WinEEG program, prepared in accordance with accepted standards of signal analysis, and represent graphs or tables of spectral power of the EEG at each lead in increments of 0.25 Hz.

Allocated a plot of duration of 20-25 seconds. On this plot is determined by the power spectrum in the whole range of radiation. On a standard chart (figure 1) is determined by the modal (maximum) power of the alpha rhythm (Mo). Calculates the power ratio of the modal (most pronounced) fluctuations of the alpha rhythm in any lead EEG to its total capacity in the same abstraction (α1). To clarify the existing violations is calculated ratio of the total is the second power of the alpha rhythm in the range of ±0.5 Hz from the modal (most pronounced) fluctuations to its total capacity (α 2). With this purpose to calculate (α1table capacity spectra rhythms exported from programs EEG, which is a rectangular matrix where the vertical are the names of standard EEG, and across - frequency oscillations from 0 to 30 Hz 0.25 Hz, is determined by the modal power (maximum power) fluctuations in any standard discharge (DoD) is in the range of the alpha rhythm (7-14 Hz). The same procedure can be carried out on graph spectra capacities rhythms provided by standard program EEG. Then define the total power of the alpha rhythm (M) by adding all the facilities in this abstraction in the alpha range (standard program EEG automatically provides this value in the summary table of power spectra). (α1) is calculated by the formula: Mo(1)/M×100%.

To calculate (α2must table capacity or capacities chart to select values capacities, which are located to the right and to the left of the modal values at 0.5 Hz (i.e. 2 to the right and to the left of the modal). All of these values, including modal, are summarized. The resulting value is divided Yes total power in this abstraction by the formula:

Where Mo is the modal power of the alpha rhythm (µv2),

M - Alova the power of the alpha rhythm.

The values obtained are compared with the target (table 1), obtained by statistical correlation analysis of clinical material, and a conclusion about the severity of the pathological process.

Table 2 - results of analysis of the clinical data produced by this method, which allows to clearly distinguish between the degree of brain damage.

The invention allows to introduce a quantitative parameter of the power spectrum of the alpha rhythm, reflecting the degree of brain lesions. Determination of the degree of change α1(%) and α2(%) allows to distinguish between normal and pathologically altered brain state, to the suggestion nosological facilities of these changes and to observe their dynamics.

This method was applied in GCOS OKB No. 1. BTW, Litvinova (Tver). In the process of learning 2235 electroencephalograms of patients and 115 healthy (control) were obtained from the data presented in table 2, confirming the proposed method of determining the variance of the amplitude-frequency characteristics of the alpha rhythm with mental illness.

Thus, there is a statistically significant correlation between the proposed indicators α1and α2and organic brain diseases.

64±0.5%
Table 1
Values α1(%)Values α2(%)The degree of organic brain damage
Over 24> 67Normal EEG
18-2161-66Light
15-1851-60Moderate
5-1415-50Significant
Table 2
The degree of dispersion of the alpha rhythmα1α2,
the left hemispherethe right hemispherethe left hemisphereright on usaria
Control (M±m, %) p<0.01Patients (M±m, %) p<0.01Control (M±m, %) p<0.01Patients (M±m, %) p<0.01Control (M±m, %) p<0.01Patients (M±m, %) p<0.01Control (M±m, %) p<0.01Patients (M±m, %) p<0.01
Minimal29±1%27±0.3%29±1.1%27±0.3%75±1.4%75±0.4%75±1.7%75±0.5%
n%60(52%)171(8%)63(55%)405(18%)69(60%)387(17%)76(75%)637(29%)
Light21±0.4%21±0.1%21±0.4%21±0.1%63±0.4%64±0.1%63±0.1%
n%49(43%)679(30%)42(37%)694(31%)29(25%)579(26%)32(28%)515(23%)
Moderate-Naya17±0.2%17±0.1%17±0.2%17±0.1%56±0.8%56±0.2%56±0.4%56±0.2%
n%6(5%)679(30%)9(8%)561(25%)13(11%)437(20%)5(4%)388(17%)
Considerable0±0%12±0.1%13±0%12±0.1%48±0.7%39±0.5%45±1.3% 38±0.6%
n%(0%)606(27%)1(1%)575(26%)4(3%)832(37%)2(2%)695(31%)
Only25±1.4%18±0.3%25±1.6%19±0.4%69±2.7%55±1%71±2.5%58±1.1%
n%115 (100%)2235 (100%)115 (100%)2235 (100%)115 (100%)2235 (100%)115 (100%)2235 (100%)

The method of determining the variance of the amplitude-frequency characteristics of the alpha rhythm of the brain in mental illness, including determination of the amplitude-frequency characteristics of the alpha rhythm on the basis of its power spectrum, wherein when recording standard EEG determine the total capacity of m is yuandong fluctuations in the range of the alpha rhythm in one of the leads and calculate the index α 1as the ratio of this power to the total power of all fluctuations in the alpha range and the same abstraction, then determine the value of the sum of power fluctuations, located on the right and left of the maximum power value ±0.5 Hz, including the maximum value, and calculate the indicator α2as the ratio of the determined amount of power to total power of all fluctuations in the alpha range in the same lead, and the severity of brain lesions detected by comparing the values α1and α2with normative values.



 

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1 tbl, 2 ex

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27 cl, 11 dwg

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5 dwg, 1 ex, 1 tbl

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2 ex, 1 tbl

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11 cl, 6 dwg

FIELD: medicine; medical engineering.

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15 cl, 10 dwg

FIELD: medicine, psychiatry.

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EFFECT: higher efficiency of diagnostics.

1 ex, 1 tbl

FIELD: medicine, neurophysiology.

SUBSTANCE: one should carry out EEG survey to detect spectrometrically the index of full range if alpha-rhythm both before and after therapy. Moreover, power index of full range of alpha-rhythm and the index of 9-10 Hz-strip's spectral power should be detected in occipital cerebral areas. One should calculate the value of the ratio of the index of 9-10 Hz-strip's spectral power to the index of full range of alpha-rhythm and at the increase of this value by 20% against the background it is possible to evaluate positive result of therapy. The method increases the number of diagnostic means applied in evaluating therapeutic efficiency in the field of neurophysiology.

EFFECT: higher efficiency of evaluation.

1 ex

FIELD: medicine, neurology.

SUBSTANCE: method involves carrying out the standard vascular and nootropic therapy. Diazepam is administrated under EEG control with the infusion rate that is calculated by the following formula: y = 0.0015x - 0.025 wherein y is the rate of diazepam administration, mg/h; x is an average EEG amplitude, mcV. Method provides enhancing the effectiveness of treatment of patients. Invention can be used for treatment of patients in critical severe period of ischemic insult.

EFFECT: enhanced effectiveness of treatment.

2 tbl, 1 dwg, 1 ex

FIELD: medicine.

SUBSTANCE: method involves selecting signals showing patient consciousness level and following evoked auditory potentials as responses to repeating acoustic stimuli, applying autoregression model with exogenous input signal and calculating AAI index showing anesthesia depth next to it.

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9 cl, 3 dwg

FIELD: medicine; experimental and medicinal physiology.

SUBSTANCE: device can be used for controlling changes in functional condition of central nervous system. Device has receiving electrodes, unit for reading electroencephalograms out, analog-to-digital converter and inductor. Low noise amplifier, narrow band filter linear array which can be program-tuned, sample and store unit, online memory, microcontroller provided with controlled permanent storage, liquid-crystal indicator provided with external control unit are introduced into device additionally. Receiving electrodes are fastened to top part of patient's head. Outputs of electrodes are connected with narrow band filters linear array through electroencephalograph. Output of linear array is connected with input of input unit which has output connected with input of analog-to-digital converter. First bus of analog-to-digital converter is connected with online storage. Recording/reading bus of microcontroller is connected with control input of input unit and its starting bus is connected with address input of online storage. Third control bus is connected with narrow band filters linear array. Second control bus is connected with liquid-crystal indicator. Output bus is connected with inductor. External control (keyboard) of first control bus is connected with microcontroller. Output of online storage is connected with data input of microcontroller through 12-digit second data bus. Efficiency of influence is improved due to getting specific directed influence being based onto general technological transparency of processing of human brain's signals and strictly specific influence based on the condition of better stimulation.

EFFECT: increased efficiency.

3 cl, 1 dwg, 1 tbl

FIELD: medicine, neurology, professional pathology.

SUBSTANCE: one should carry out either biochemical blood testing and electroencephalography or SMIL test, or ultrasound dopplerography of the main cranial arteries, rheoencephalography (REG) to detect the volume of cerebral circulation and hypercapnic loading and their digital values. Then it is necessary to calculate diagnostic coefficients F by the following formulas: Fb/e=6.3-0.16·a1+0.12·a2-1·a3+0.2·a4, or FSMIL=9.6+0.16·a5-0.11·a6-0.14·a7+0.07·a8, or Fhem=48.6-0.04·a9+0.15·a10+13.7·a11-0.02·a12+24.7·a13, where Fb/e -diagnostic coefficient for biochemical blood testings and EEG; FSMIL - diagnostic coefficient for SMIL test; Fhem - diagnostic coefficient for hemodynamic testing; 6.3; 9.6 and 48.6 - constants; a1 - the level of vitamin C in blood; a2 - δ-index by EEG; a3 - atherogenicity index; a4 - the level of α-proteides in blood; a5 - scale 3 value by SMIL; a6 - scale K value by SMIL; a7 - scale 5 value by SMIL; a8 - scale 7 value by SMIL; a9 - the level of volumetric cerebral circulation; a10 - the value of linear circulatory rate along total carotid artery, a11 - the value of resistive index along total carotid artery; a12 - the value for the tonicity of cerebral vessels at carrying out hypercapnic sampling by REG; a13 - the value for the intensity of cerebral circulation in frontal-mastoid deviation by REG. At F value being above the constant one should diagnose toxic encephalopathy, at F value being below the constant - discirculatory encephalopathy due to applying informative values.

EFFECT: higher accuracy of diagnostics.

6 ex, 1 tbl

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