RU2766751C1 - Method for diagnosing asthmatic bronchitis in process of lung auscultation in adults - Google Patents

Abstract

FIELD: medicine.

SUBSTANCE: invention refers to medicine, particularly to pulmonology and functional diagnostics, and aims at diagnosing asthmatic bronchitis in pulmonary auscultation during examination of a patient using an electronic stethoscope. Method for diagnosing asthmatic bronchitis in the process of auscultation of the lungs of adults involves recording a respiratory noise in a point above the larynx region using an electronic stethoscope for 30 seconds, followed by sampling the signal in a computer with a sampling rate of 4 kHz. Further, calculating the value of the indicator variable Id as the average value of the squares of the elements of the main diagonal of the RR matrix, which is the product of the reference matrix Re corresponding to the signal of a person having no respiratory disease by the bispectrum matrix

,

where

is the third-order sample moment (bispectrum matrix element), x(i) is the i^th sample of the recorded respiratory noise signal x(t), I is the number of samples of the discrete signal x(t), k and l are the indices readings of time shifts from a plurality of {0, 50, 80, 100, 140, 190}. Then the patient’s state is correlated with the following groups: “patient is healthy”, if Id ⸦ [0; 4], “presence of asthmatic bronchitis is highly probable”, if Id ⸦ [32; 50], “additional examination is required”, if the value of Id is not included in the specified intervals.

EFFECT: increased noise immunity of respiratory sound recording during lung auscultation using an electronic stethoscope and the efficiency of automated diagnosis of asthmatic bronchitis by calculating a certain indicator variable for the examined patient and comparing its value with the threshold value previously determined on a representative sample of healthy people.

1 cl, 2 ex

Description

The invention relates to medicine, in particular to pulmonology and functional diagnostics, and is intended for diagnosing asthmatic bronchitis by auscultation of the lungs during examination of a patient using an electronic stethoscope.

Asthmatic bronchitis has an infectious-allergic nature and is provoked both infectiously (viruses, bacteria, fungi) and allergens. Timely diagnosis of the disease allows you to stop and treat it in a shorter time and with greater efficiency. During preventive and primary examinations, auscultation of the lungs is used. On auscultation, the physician identifies, as a rule, hard breathing, accompanied by wheezing or moist rales. The primary diagnosis in this case has little sensitivity (of the order of 0.7-0.75 or less for a doctor who is not specialized in the field of pulmonology) and, as a rule, requires further examination of the patient with instrumental methods in a clinical setting. In this regard, the diagnosis of asthmatic bronchitis using a non-electronic stethoscope is not the most effective method.

The use of electronic stethoscopes makes it possible to automate the diagnostic process using computer programs that implement various signal transformations, significantly increasing diagnostic sensitivity, specificity and efficiency. A significant increase in diagnostic capabilities occurs when using electronic stethoscopes with subsequent processing of the recorded information (Zaitseva E.G., Chernetsky M.V., Shevel N.A. On the possibility of remote diagnosis of the human respiratory system by auscultation. Instruments and measurement methods . 2020;11 (2):148-154 https://doi.org/10.21122/2220-9506-2020-11-2-148-154).

A known method for diagnosing broncho-obstructive syndrome (RU 2 731 389, Malinina S.V. and Furmanova E.G., 2019) consists in registering a respiratory noise signal at certain points for 25 seconds, with the use of a fast Fourier transform to obtain pseudospectrum, calculation of further defined, characterizing the pseudospectrum, "wheezing coefficients" and comparing the obtained values with threshold values for diagnosis. The disadvantage of using the method of the invention for diagnosing asthmatic bronchitis is the need for auscultation at several points with the identification of the values of the wheezing coefficients on the training set and the presence of systematic shifts in the values of these coefficients when applying the fast Fourier transform. To eliminate this and other shortcomings, it is proposed to use a bispectrum. Its use as an indicator variable was first described in the work of Aleksenko V.V. (Alesenko V.V. Vibrations in technology: a reference book: in 6 volumes - M .: Mashinostroenie, 1981, V. 5: Measurements and tests. - 496 s).

Recognition of asthmatic bronchitis is proposed to be carried out by the minimum of the Euclidean distance from the reference bispectrum. The following advantages of the bispectrum are used: the function allows restoring information about the phase shifts of the analyzed signal, the Gaussian noise bispectrum is equal to zero (noise immunity improves), the bispectrum is invariant to the original signal shift, the calculation of the discrete spectral function requires less computational resources (than the calculation of integral indicators).

The use of the bispectrum for diagnostic purposes for solving medical problems is described, for example, in the works of Khabarov M.Yu. (Khabarova M. Yu., Indyukhin A. F. Possibilities of polyspectral analysis of electroencephalograms in the study of cognitive processes // Proceedings of the Southern Federal University. Technical sciences. - 2008. - V. 83. - No. 6.), Zhang Ji-Wu, Zheng Chong and Xie Au. Bispectrum analysis of focal is chemic cerebral EEG signal using third-order recursion method //IEE Trans.Biomedical Engtnttring.-March 2000.-Vol 47, no.3. -P.118-127 (the possibilities of using the bispectrum as a classifier in the analysis of the biological signal of the EEG in order to identify various ischemic disorders of the brain are analyzed) and Porevoy A.S. (Poreva A. S. et al. The use of polyspectral analysis to determine diagnostic signs in the breathing sounds of patients with COPD // Bulletin of the National Technical University KhPI. Series: New developments in modern technologies. - 2014. - No. 36. - P. 49- 55.) In particular, the latter paper proposes a method for analyzing breath sounds in healthy people and patients with chronic obstructive pulmonary disease (COPD) based on the calculation of the bicoherence function by analyzing breath sounds for classification identification of the state of health of the respiratory system (for COPD).

The main disadvantage of the proposed approaches is the calculation of bispectral matrices of large dimensions, which leads to the need to store large amounts of data that do not have indicator characteristics for a particular disease (in particular, asthmatic bronchitis). In addition, this approach is not applicable to the automatic diagnosis of asthmatic bronchitis using an electronic stethoscope. The use of auscultation, without subsequent computer processing of respiratory noise, is currently used in propaedeutics, predicative, preventive diagnostics with a mandatory subsequent examination of the patient by instrumental methods.

The technical objective of the method is to increase the diagnostic efficiency of diagnosing asthmatic bronchitis using an electronic stethoscope, including by improving noise immunity when registering respiratory noise.

The technical result of increasing the noise immunity of recording respiratory sounds during auscultation of the lungs using an electronic stethoscope and the effectiveness of automated diagnosis of asthmatic bronchitis is achieved by calculating a certain indicator variable for the examined patient and comparing its value with a threshold value previously determined on a representative sample of healthy people.

, где RR - произведение эталонной матрицы This result is achieved by the fact that the method for diagnosing asthmatic bronchitis in the process of auscultation of the lungs of adults consists in registering respiratory noise at a point above the larynx area using an electronic stethoscope for 30 seconds, followed by sampling the signal in a computer with a sampling rate of 4 kHz and calculating the value indicator variable Id (mean value of the squares of the elements of the main diagonal of the matrix RR according to the formula

, where RR is the product of the reference matrix

,

,

, где

- выборочный момент третьего порядка (элемент матрицы биспектра), x(i) - i-я дискрета зарегистрированного сигнала дыхательного шума x(t), I - количество отсчетов дискретного сигнала x(t), k и l - значения индексов отсчетов временных сдвигов из множества {0, 50, 80, 100, 140, 190}) для соотнесения состояния пациента к группам: «пациент здоров» - Id ⸦ [0; 4], «высоковероятно наличие астматического бронхита» - Id ⸦ [32; 50], «требуется дополнительное обследование» - если значение Id не входит в указанные интервалы.corresponding to the signal of a person who does not have a respiratory disease, on the bispectrum matrix calculated by the formula

, where

is the sampling moment of the third order (element of the bispectrum matrix), x(i) is the i-th sample of the recorded breath signal x(t), I is the number of samples of the discrete signal x(t), k and l are the index values of the samples of time shifts from sets {0, 50, 80, 100, 140, 190}) to correlate the patient's condition to the groups: "patient is healthy" - Id ⸦[0; 4], "highly likely to have asthmatic bronchitis" - Id ⸦[32; 50], “an additional examination is required” - if the value of Id is not included in the specified intervals.

That is, with the help of an electronic stethoscope, a breath noise signal is recorded in a patient at a point above the larynx area for 30 seconds, for which an indicator coefficient is calculated (subsequently compared with a threshold), which is the average of the squared deviation of the values of the main diagonal of the product of the obtained matrix of the respiratory sound signal bispectrum of the examined patient to the reference inverse matrix of the signal bispectrum of a person who does not have respiratory diseases.

The method is carried out as follows. Using an electronic stethoscope (for example, 3M™ Littmann with Bluetooth 3200BK27 - manufacturer: 3M Littmann, USA), the patient registers a respiratory sound at a point above the larynx for 30 seconds. This signal is transmitted to the computing device, which performs the following actions to correlate the patient's condition to one of the groups - "the patient is healthy" or "the presence of asthmatic bronchitis is highly likely" - according to the algorithm:

1. The signal is sampled at a frequency of 4 kHz, - to form a discrete signal (x(t)).

2. The bispectrum matrix is determined by the formula:

, (1)

, (one)

- выборочный момент третьего порядка (элемент матрицы биспектра), x(i) - i-я дискрета сигнала x(t), k и l - индексы отсчетов временных сдвигов, I - количество отсчетов дискретного сигнала x(t).where

- sampling moment of the third order (element of the bispectrum matrix), x(i) - i-th sample of the signal x(t), k and l - indices of time shift samples, I - number of samples of the discrete signal x(t).

The shift parameters k and l are elements of the set {0,50,80,100,140,190}.

умножается на эталонную матрицу Re (представляющую собой биспектральную матрицу сигнала дыхательного шума для здорового человека) RR=

·Re:3. The resulting matrix

multiplied by the reference matrix Re (which is the bispectral matrix of the respiratory sound signal for a healthy person) RR=

Re:

4. The indicator Id is calculated as the average value of the squares of the main diagonal of the RR matrix:

.

.

5. The value of Id is compared with the intervals I1=[0; 4] and I2=[32; fifty]. If the value of Id falls within the interval I1, then it is concluded that the patient has a high probability of not having asthmatic bronchitis. If the Id value falls within the I2 interval, then it is concluded that the patient has a high probability of having asthmatic bronchitis. If the Id value does not fall within the specified intervals I1 and I2, then a conclusion is made about the need for further examination for the presence of another lung disease.

Examples of specific implementation.

Example 1 Patient A. Age: 54 years. Teacher. Complaints of shortness of breath, palpitations, cough with sputum, slight pain in the heart. She underwent a course of treatment at the regional clinical hospital, where she was first diagnosed with asthmatic bronchitis and prescribed basic therapy with prednisolone. Objectively: a satisfactory condition, the color of the skin is clean, of a physiological norm, the physique is correct, height is 168 cm, weight is 76.5 kg. On auscultation over all parts of the lungs, vesicular, uniform, without pronounced wheezing, slight edema in the lower extremities, lymph nodes are not palpable, the thyroid gland is slightly enlarged, the shape of the chest is correct, breathing is deep (breathing rate is 26 per minute), with percussion of the lungs, slight dullness of sound over the entire surface.

An electronic stethoscope recorded a patient's respiratory noise at a point above the larynx for 30 seconds. The signal from the electronic stethoscope was transmitted to a computer, where it was sampled at a frequency of 4 kHz. The bispectrum matrix is obtained by formula (1):

After multiplying by the reference matrix

the RR matrix is calculated:

The coefficient Id=36.17 is calculated . Since its value falls within the range [32; 50], then we conclude that the patient has a high probability of having asthmatic bronchitis (which is clinically confirmed).

Example 2. Patient L. Annual preventive examination. 5th year student of a technical university. Age 23 full years. Height - 174 cm, weight - 62 kg, asthenic physique. There are no complaints. Close relatives of respiratory diseases are not observed. There are no bad habits (alcoholism, drugs, smoking). Previously transferred diseases of the respiratory system and Botkin's disease denies. The respiratory rate is 18 per minute. Pressure 110/80. Pulse - 75. Body temperature - 36.7. Saturation - 0.99. The general condition is satisfactory, consciousness is clear, facial expression is calm. Breathing through the nose is free. Auscultation of the lungs revealed no pathological changes. There are no wheezing. Integuments of physiological coloring. Turgor is not changed. There is no pigmentation. Subcutaneous tissue is moderate, edema is not observed. Lymph nodes are not enlarged. Muscle development is moderate, tone is normal. The joints are symmetrical and painless.

Recorded breath sounds at a point above the larynx for 30 seconds. The signal from an electronic stethoscope was sampled in a computer at a frequency of 4 kHz. The bispectrum matrix is obtained by formula (1):

After multiplying by the reference matrix

the RR matrix is calculated:

The coefficient Id=1.36 is calculated. Since it falls within the range [0; 4], then a conclusion is made about the high probability that the patient does not have lung diseases - (which is confirmed clinically).

Claims (7)

A method for diagnosing asthmatic bronchitis during auscultation of the lungs of adults, characterized by the registration of respiratory noise at a point above the region of the larynx using an electronic stethoscope for 30 seconds, followed by sampling the signal in a computer with a sampling rate of 4 kHz and calculating the value of the indicator variable Id (the average value of the squares of the elements the main diagonal of the matrix RR by the formula

, where RR is the product of the reference matrix

, corresponding to the signal of a person who does not have a respiratory disease, on the bispectrum matrix calculated by the formula

, where

is the sampling moment of the third order (element of the bispectrum matrix), x(i) is the i-th sample of the recorded breath signal x(t), I is the number of samples of the discrete signal x(t), k and l are the index values of the samples of time shifts from sets {0, 50, 80, 100, 140, 190}) to correlate the patient's condition to the groups: "patient is healthy" - Id ⸦[0; 4], "highly likely to have asthmatic bronchitis" - Id ⸦[32; 50], “an additional examination is required” - if the value of Id is not included in the specified intervals.