RU2129301C1 - Method for diagnostics using static low- frequency signal - Google Patents

Abstract

FIELD: measuring instruments, medical devices. SUBSTANCE: method involves converting signal by means of measuring sequence of its amplitude samples and time, setting tolerant values for alternations of time intervals and amplitude which correspond to normal condition, detection of moment of alternation of sign of first derivative of input signal, storing signal value in each moment of alternation of its first derivative, detection of converted values of time interval t₁ in moments of alternation of sign of du/dt_I+1, first derivative of signal with respect to previous moment of sign of du/dt₁ and time interval t_I+1 between equal moments of alternation of sign of du/dt₂ as well amplitude in digital representation, analysis of phase difference of signal in each moment of alternation of sign of first signal derivative using comparison of values of phase differences and amplitude with given norms and identification of deviations of current values from given norms using comparison results. EFFECT: possibility of diagnostics using results of analysis of signal parameters. 2 dwg

Description

 The invention relates to measuring and medical equipment and can be used for conversion, transmission, automatic processing, storage of information about the respiratory system, the operation of turbines at stations and diagnosis.

 Known (application N 63 46611 from 09.16.88, Japan) is a data sampling method consisting of a set of operations: several discrete values of the input analog signal are extracted for each sampling period and selected from these discrete data as data characterizing the whole sampling period discrete values having a maximum deviation relative to the data cured in the previous sampling period.

 The disadvantage of this method is the need for additional and relatively complex operations to select extreme values, which is associated with time and delay in obtaining the final result when optimizing the results according to Kotelnikov’s criteria.

 The closest in technical essence to the present invention is a conversion method according to the Kotelnikov theorem for a stationary signal, which consists in the fact that a continuous signal u (t), the spectrum of which is bounded from above by the frequency Fb, is completely determined by its values, which are converted (counted) by sequential counting at discrete points through the interval dt = 1 / 2Fb (I.A. Lipkin, "Fundamentals of Statistical Radio Engineering, Information and Coding Theory", Moscow: Sov.radio, 1978, p. 22).

 The disadvantage of this method is the redundancy of the results with low information value, because analyze current data to detect irregularities in the operation of the object of the survey according to the parameters of the signal in the time domain.

 The technical result of the invention is to increase the information value of the results of the operation, analyze the work on the information-valuable parameters of the signal in the time domain, the results of which are the basis of diagnosis.

The technical result is achieved by the fact that in the diagnostic method for a static low-frequency signal, which consists in converting the signal by successively counting the values of its amplitude and time, set permissible values of the change in time intervals and amplitudes identifying the normal state, highlight the moment of change sgn dU / dt ₁ sign of the first derivative of the input signal, the signal values are stored at each moment of change sgn dU / dt _{1 of the} sign of the first derivative of the input signal, the converted the time interval ti at the moment of the sign change sgn du / dt _{i + 1} , the first derivative of the signal relative to the previous moment of the sign change sgn du / dt _i and the time interval t _{i + 1} between the equivalent moments of the sign change sgn du / dt _{2i of the} first derivative of the signal, and amplitude digitally analyzed time difference signal at each moment changes sign sgn dU / dt _i of the first derivative signal, which compares the value time difference and amplitude with predetermined rules, the current values identify deviations from predetermined norms on D ultatam comparison in case of exceeding a predetermined permissible level amplitude signal display identification results.

 The introduction of the operation sets the permissible values of the change in time intervals and amplitudes identifying the normal state, it is necessary to exclude redundant information about the normal state and is sufficient to read data on the signal parameters of a random process with signs of pathology and subsequent processing in case of going beyond.

Поставив это разложение в выражение момента

с учетом центральных моментов

получим

Если функция φ(x) изменяется в указанном интервале достаточно плавно, то в разложении можно ограничиться учетом лишь первых двух членов. При этом
M{φ(x)} = m_f(j) ~ φ(m_j)+0,5φ″(m_j)D_j.
Отсюда видно, что матожидание достаточно плавной функции от случайной величины приближенно определяется матожиданием и дисперсией, роль высших моментов убывает с увеличением их порядка.Introduction of the operation ALLOCATE the moment of changing the sign of the first derivative of the input signal is necessary and sufficient to determine when the signal value reaches the highest value, which increases the information value of the transmitted result while eliminating data redundancy. It can be shown that lower moments are more important than higher ones. In most practical cases, the probability density P (x) has the most significant value in the interval located near the mathematical expectation m _i , and the length of this interval is of the order of σ _j = V _Dj . If in this interval the function φ (x) is sufficiently smooth, then it can be represented with the necessary degree of accuracy by the Taylor series in a neighborhood of the point m _j

By putting this decomposition into an expression of the moment

taking into account the central points

we get

If the function φ (x) varies quite smoothly in the indicated interval, then in the expansion we can restrict ourselves to taking into account only the first two terms. Wherein
M {φ (x)} = m _{f (j)} ~ φ (m _j ) + 0.5φ ″ (m _j ) D _j .
This shows that the expectation of a sufficiently smooth function of a random variable is approximately determined by the expectation and dispersion, the role of higher moments decreases with an increase in their order.

 In addition, the introduced operation is necessary and sufficient for a new quality - adaptability. In the method algorithm, the dependence on the frequency properties of the input signal, i.e. it is operable in a wide range of frequencies and regardless of the shape / spectrum of the input signal (sinusoid, triangle, trapezoid...) provides the minimum necessary number of samples for its optimal recovery with the information value of each of them of the order of 0.95.

 Introduction of the operation REMEMBER the signal values at each moment dUi / dt; it is necessary and sufficient to save the signal data during the operation; they display the solution according to the results of comparison, because the signal has alternating sign du / dt.

The introduction of the operation distinguishes the values of the time interval ti at the moment of changing the sign sgn du / dt _{i + 1 of the} first derivative of the signal relative to the previous moment sgn du / dt _i (front) and the time interval t _{i + 1} between the equivalent sgn du / dt _2i , as well as the amplitudes in digital form, it is necessary and sufficient to present a description of the dynamics of work in digital form, for example, of the respiratory system or turbine, as the most common, to identify the presence of deviations in the work of identifying sound signals that contain information: noise (aggregate changed signal in a certain time domain and limited value) - normal state, low-frequency with a long interval duration - wheezing or knocking, high-frequency / with a short interval duration - whistling, amplitude level - degree of damage / disease, analysis of the current job description according to conditionally normal criteria that allows you to diagnose by objective criteria-deviations.

 Introduction of the operation, the signal is analyzed at different times at each moment the sign of the first derivative of the signal changes, it is necessary and sufficient to identify types / signs of pathology: wheezing, whistling, intensity.

 The analysis is carried out by comparing the current data with the data of the normal state to predict the onset of the disease on a single and low signal level.

 The introduction of the operation compares the values of the differences in time and amplitude with the given norms is necessary and sufficient to obtain information about the state of the studied object (respiratory organs, turbine, ...), continuous analysis of the signal parameters of the diagnosed object, which eliminates the possibility of losing their one-time deviations from the given criteria / norms .

 The introduction of the operation identifies the deviations of the current values from the set values according to the results of the comparison if the signal amplitude exceeds the specified minimum level is necessary and sufficient to eliminate data redundancy determined by the "noise" of breathing, cardiac muscle function, change of turbine mode, surgical intervention by hardware in case of critical deviation , for example, the sound of a turbine due to bearing wear.

 The introduction of the operation displays the identification results necessary and sufficient for prompt reporting of the state of the controlled object (respiratory organs, turbines, ...). The operation allows you to imagine the rhythm of the heart muscle during the diagnosis of a person.

 Thus, the set of operations and the sequence of their implementation provide an increase in the information value of the results of the operations, analyze the work by informationally valuable signal parameters in the time domain, the results of which are the basis for the diagnosis and analysis of the operation of the object (respiratory organs, turbines, ...) according to the parameters (amplitude, duration) in the time domain. The amount of data is sufficient to detect deviations / disease and graphical representation of the signal on the PC monitor screen by software. An additional positive effect is: - when examining a person - obtaining information about the work of the heart - prompt decision-making by technical means prior to human intervention for critical deviations of the object at no additional cost.

 Operations - comparison, the account can be performed in microelectronic performance. The latter will make it possible to implement the method in a small-sized version of the device, the dimensions of which will be commensurate with a stethoscope known in medicine and technology (ship engines, station turbines, ...).

 In FIG. 1 is a timing chart explaining a method algorithm; FIG. 2 - a variant of the structure of the system that implements the method.

 The system comprises a sensor / microphone 1, a generator 2 of a grid of reference frequencies, an ADC block 3, a control unit 4, a time-to-digit converter (PCC) 5, a block of 6 standards, a display unit 7, an analysis unit 8.

 The sensor 1 is connected to the display unit 7 through a serial connection of the unit 3, the control unit 4, the converter 5 time is a digit, the analysis unit 8, the first output of the unit 3 is connected to the second input of the converter 5, the output of the generator 2 is connected to the converter 5, and the other output with the third input of block 8 through the series connection of block 8, block 4 and block 6, the third output of control block 4 is connected to the fourth input of block 8, and the second output of block 3 is connected to the output of converter 5.

 The method works as follows.

 In the initial state, the parameter values corresponding to the normal operation of the controlled object for examination and diagnostics (from block 6 to block 8 of Fig. 2) are set to the values of the time intervals corresponding to the "whistle" (small values, points 1, 3 of Fig. 1, Uc) and wheezing (large values, points 9, 11 of Fig. 1, Uc) and absent in the normal (points 8, 9 of Fig. 1, Uc) state of the object / patient, i.e. other than "noise", as well as the lower value of the signal level. This is expressed in determining the minimum range boundaries at the maximum allowable amplitude of the "noise" signal.

Upon receipt from the sensor 1 of an electric signal (ESD) of FIG. 1, Uc transform it by successively counting the current values of its amplitude and time, identify the moments of sign change sgn du / dt of the first derivative (FIG. 1, dt _i , block 3 of FIG. 2) the sign of the first derivative in the form of messages of FIG. 1dt _i , dT _j for reading current data with maximum information value. The samples contain information about the signal in the form of coordinates: amplitude and time used: for analysis and restoration of the signal sequentially for each of these points. The dU / dt sign diagrams of FIG. 1, t _i correspond to the electrical signal of the respiratory organs and are the basis for the formation of identifier signals of its changes in FIG. 1, dT _i . The set of operations and the sequence of their execution allows you to read at characteristic times determined by the signal at characteristic times determined by the signal to read the values of the ESD. If necessary, detailed information for diagnosis can be obtained at time points 1, 2, 3,. . . in FIG. 1, Uc. At the moment of arrival of the i-th tooth (blocks 3, 4 of Fig. 2), the value of the time interval (block 5 of Fig. 2) is read relative to the previous one. This method provides a fairly detailed description of the signal, i.e. information on fronts and duration. This requires setting the start and end of the signal, for which moments with the same sign sgn du / dt are selected. It is at these points after reading the data on time intervals that the initial state is established (block 5 of Fig. 2). Thus, information on the ESD in digital code is obtained.

 The current data on the time interval (block 5 of Fig. 2) of the signal and amplitude (block 3 of Fig. 2) are constantly analyzed: compares (block 8 of Fig. 2) with the corresponding given values / norms (from block 6 of Fig. 2), make a decision (blocks 7, 8 of Fig. 2) on the results of comparison at the moments sgn du / dt: "-" - edge duration (points 1,3, ..), "+" - signal amplitude and duration.

 Identification of decisions made: R-wave in amplitude and duration (in the case of respiratory organs), the fact and type of pathology on the fact of deviation from the set norms in case the amplitude exceeds a predetermined threshold (block 8 of Fig. 2).

 To present the identification results in an understandable form, they are displayed (block 7 of Fig. 2), for example, by the duration of the light presentation "wheeze", "whistle" or sound. The intensity of pathological factors between the R-waves is identified by the intensity of the presentation (frequency of light radiation, ..).

 The R-wave is represented (blocks 4, 5, 7 of Fig. 2) by one-time / pulse signals, according to which it is possible to calculate the heart rate (heart rate), which can be colored (block 4 of Fig. 2) with time marks (10, 15 sec) .

 In the process of counting, FORM (block 7 of Fig. 2) the data with a serial code and AGREE data input with the processing speed of a PC for visualization and storage of data. These operations can have two modifications: direct input to a PC or via a telephone line to a diagnostic center. The high informational value of the readout results allows the use of simple software tools for representing the signal by linear approximation on the monitor screen.

 The action of the method is tested on mock-ups performed mainly on the ICs of series 561 and 140, where the ADC is used (RF patent N 2024194, containing a comparator, RAM, DAC, a unit for evaluating the sign of the first derivative, a reversible counter, a voltage reference source with a set of connections, a time converter -digit (PCV) based on the decision on which a positive decision was made to grant a patent according to application N 94011424, consisting of a counter, triggers, NAND elements, a majority element, and a set of connections. microelectronic performance on Xilinx XC3000 based on programmable logic integrated circuits (FPGAs) .Achieved technical result allows to obtain information about the work of the respiratory system during the examination, to differentially evaluate the form of the wheezing - whistle disease, at the same time evaluate the state of the heart, identify disease onset at single or small levels of pathologies, increase the value of the conversion results to 90 - 95% without additional treatment systems by eliminating data redundancy, which both sintering the graphical representation of the signal using a PC, a small amount of data allows you to transfer information over the telephone network in the accepted standards, to accumulate information about people with chronic diseases, which will allow you to monitor changes during the illness according to objective indicators - in digital and graphic form.

 Testing shows: the results confirm the efficiency and effectiveness for use in the fields of: cardiology, neurology, ... A model of the device with an electrocardiogram (EX) program according to the formula of R.M.Baevsky is being tested in the children's department of neurology of the region. hospital them. Semashko, N. Novgorod, under the guidance of prof., MD Troshina V.M. and showed: instead of 1-1.5 hours / child - 5-7 minutes, supplementing the program with information - gender, age - increases the efficiency of diagnosis, the small size and affordable price of a stethoscope that implements this method will make it a family tool, increasing the effectiveness of therapists and pediatricians in diagnosing respiratory diseases in humans and reducing the need for fluorography.

 Testing for diagnostics of operation of the turbine / engine type was carried out on a 50 Hz network transformer with a short-term excess of the operating mode, which was assessed by increasing the level of "background" by ear. The diagnostic system identified excess signal level and duration.

Claims (1)

A diagnostic method for a static low-frequency signal, which consists in converting the signal by successively counting the values of its amplitude and time, characterized in that the permissible values of the change in time intervals and amplitudes identifying the normal state are set, and the moment sgn dU _i / dt of the first sign is changed derivative of the input signal, the signal values are stored at each moment of changing the sign sgn dU _i / dt of the first derivative of the input signal, the converted values of the time interval t _i are extracted at the moment of changing the sign sgn du / dt _{i + l of the} first derivative of the signal relative to the previous moment of changing the sign sgn du / dt _i and the time interval t _{i + l} between the equivalent moments of changing the sign sgn du / dt _{2i of the} first derivative of the signal, as well as the amplitude in the digital form, analyze the signal differences at each moment of the sign change sgn dU _i / dt of the first derivative of the signal, for which they compare the values of the differences and amplitudes with the given norms, identify the deviations of the current values from the given norms according to the results of comparison in the case exceeding the signal amplitude of a given acceptable level, display the results of identification.

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