Category Archives: Biotechnical and medical systems

EXPERT EVALUATION AND OPTIMIZATION MODELING OF CONTROL AND OVERSIGHT ACTIVITY ON ENSURING THE QUALITY OF DRUGS

UDC 05.13.10
doi: 10.26102/2310-6018/2019.24.1.044

I.V. Safonov, Y.E. Lvovich


Ensuring the quality of medicines is currently one of the most important provisions of the state health policy. To reduce the risk of receipt of substandard and counterfeit medicines to the population, it is necessary to optimize the functioning of the current system of control and supervision activities aimed at the optimal use of available resources under specified conditions and restrictions. The main form of control and supervisory activities are inspections of objects of circulation of medicines or objects of control. To ensure an optimal plan for the audit, an optimization model is proposed that minimizes the number of objects included in the inspection plan, taking into account the limitation on planned costs and the necessary frequency of inspection of producers at risk. At the same time, the maximum number of tested drugs should be provided during the inspection of each object. A model refers to the problems of the multialternative optimization. A two-step procedure is proposed to solve this problem. A typical problem of discrete programming is solved – the problem of minimal coverage. When searching for the number of dominant solutions to the problem, basic variational procedures are used to obtain several solutions. To select the best option, it is proposed to use expert evaluation procedures. The developed optimization model is aimed at wide application in the work of the regional Department of Roszdravnadzor of the Voronezh region.

Keywords: expert evaluation,optimization modeling, the problem of minimum coverage, control and supervisory activities, drugs.

Full text:
SafonovLvovich_1_19_1.pdf

CODE IMAGES OF ELECTRIC CELL INFORMATION SIGNAL SIGNALS FOR CONTROLLING ROBOT-TECHNICAL DEVICES BY MEANS OF BRAIN-COMPUTER INTERFACE

UDC 004.5
doi: 10.26102/2310-6018/2019.24.1.025

S.A. Philist, E.V. Petrunina, A.A. Trifonov, A.V. Serebrovsky

A method based on the use of code images obtained by generating a set of code messages on a certain EEG segment is proposed for decoding EEG in brain-computer interfaces. A code message is generated by encoding EEG signals at the outputs of a block of band-pass filters. In the frequency range of the EEG, four frequency bands are allocated, which corresponds to four channels for each EEG lead. The code messages of the four channels form the image of the EEG, which, when decoded, receives control signals to the servos of the robotic device. The image of the code messages is formed on the basis of the theory of multisets. For training the EEG image classifier, a software and hardware complex is used, including an electromyograph, an electroencephalograph, a band-pass filter unit and a computing device that discrete the signals from the electromyograph output and the band pass filter unit. The label of the image class was determined by the electromyograph lead signal corresponding to the motor unit being classified. Records with the fields of the code image and the corresponding class label of the control command are placed in the database. The proposed method is an alternative to the method of EEG decoding based on biofeedback.

Keywords: :brain-computer interface, electroencephalogram, electromyogram, image of code messages, multiset, learner classifier, algorithm, training sample.

Full text:
PhilistSoavtori_1_19_1.pdf

FORECESSION ELECTROMYOGRAPHY RECOGNITION AND GESTURES SELECTION FOR PROTESIS CONTROL

UDC 612.743, 612.817.2
doi: 10.26102/2310-6018/2019.24.1.017

R.Y. Budko, N.N. Chernov, N.A. Budko, A.Y. Budko

The relevance of this study is due to one of the main problems existing today in the field of building man-machine interfaces – is the creation of an effective management system that interacts directly with the user and external devices replacing functions (prostheses, wheelchairs, etc.). In this regard, this work is devoted to the study of the possibility of using physiological gestures from the daily life of a person to control the prosthesis with the safety of the forearm for at least one third. The leading approach to the study of this problem is the use of methods of statistical processing of experimental data, digital signal processing, machine learning algorithms and pattern recognition. This approach allows a comprehensive study of the electromyogram (EMG) of the forearm when making voluntary movements at different levels of the implementation of the myo-control system. The article presents the results of the EMG study recorded for 11 arbitrary movements from a group of subjects, describes the procedure for pre-processing the EMG and identifying characteristic features for signal recognition, discloses a method for classifying movements using an artificial neural network based on radial basic functions (RBF). Eight of the most suitable for classification movements were identified and ranked according to the classification accuracy: relaxation (like zero movement), hand opening, fist, hand flexion, hand supination, hand extension, hand pronation, pinch. The materials of the article are of practical value for building systems based on the human-machine interface, as well as for classification tasks in electrophysiology applications.

Keywords: :electromyogram, prosthesis, biocontrol, human-machine interface, machine learning, artificial neural networks.

Full text:
BudkoSoavtori_1_19_1.pdf

FUZZY MODELS OF THE ESTIMATION OF THE LEVEL OF ERGONOMICS OF TECHNICAL SYSTEMS AND ITS EFFECTS ON THE STATE OF HEALTH OF A HUMAN OPERATOR TAKING INTO ACCOUNT THE FUNCTIONAL RESERVE OF THE BODY

UDC 614.2
doi: 10.26102/2310-6018/2019.24.1.015

N.A.Korenevskiy, S.N.Rodionova, T.N.Govorukhina, M.A.Myasoedova

The paper studies the impact of the ergonomics of technical systems on the emergence and development of occupational diseases of a human operator, taking into account the functional reserve of his body. In view of the complexity of the analytical description of the interaction mechanisms of the human-technical system, a methodology for the synthesis of hybrid fuzzy decision rules, focused on solving poorly formalizable problems, was chosen as the mathematical apparatus of research. In the framework of the chosen methodology, the individual estimates of the ergonomic level by basic indicators are averaged by the functions of the ergonomic level, which are aggregated into final decision rules. Evaluation of the impact of ergonomic level and other significant risk factors is carried out using the appropriate membership functions, which are aggregated into fuzzy models of forecasting and early diagnosis of occupational diseases. Using the example of diseases of the nervous system in drivers of Russian-made tractors, it has been shown that the simultaneous consideration of ergonomic risk factors and the size of the functional reserve with other significant endogenous and exogenous factors helps to improve the quality of decisions made about the health status of the human body. At the same time, confidence in the correctness of the prognosis and early diagnosis exceeds 0.86, which allows us to recommend the resulting decision-making models in the practice of occupational physicians.

Keywords: : ergonomics, functional reserve, health status, membership functions, fuzzy logic, prediction, early diagnosis.

Full text:
KorenevskiySoavtori_1_19_1.pdf

A MATHEMATICAL MODEL OF THE ASSESSMENT OF THE SEVERITY OF GENITAL HERPES ON THE BASIS OF FUZZY LOGIC

UDC 615.47
doi: 10.26102/2310-6018/2019.24.1.009

M.I. Lukashov, E.V Pismennaya, O.Y. Olisova, L.V. Starodubtseva, L.V. Shulga


The work is devoted to the urgent problem of improving the quality of medical care for the population suffering from genital herpes due to the timely and qualitative assessment of the severity of the disease under study. In the course of the research, a fuzzy mathematical model was obtained, which allows to distinguish four classes of patient’s conditions: patients with clinically undetectable genital herpes; patients with detected traces of herpes; patients with detected herpes; patients with clinically observed herpes. The methodology used in the synthesis of hybrid fuzzy decision rules allows to reliably separate the selected classes of States in the conditions of incomplete and fuzzy representation of the original data with a strongly overlapping structure of classes. The chosen classification system allows to rationalize the choice of treatment regimens depending on the individual condition of patients. As a result of the research it was found that the use of fuzzy logic of decision-making, can improve the quality of decision-making, according to the stages of disease by 10,…, 15% and reduce the duration of treatment by 5,…10%, which allows us to recommend the results for use in medical practice.

Keywords: : mathematical model, genital herpes, fuzzy logic of decision – making, laboratory indicators.

Full text:
LukashovSoavtori_1_19_1.pdf

ANALYSIS OF THE IMPORTANCE OF SURVIVAL PREDICTORS AFTER MYOCARDIAL INFARCTION USING THE CAPLAN-MEIER METHOD

UDC 314.48
doi: 10.26102/2310-6018/2019.24.1.007

I.L. Kashirina, M.A. Firyulina, E.Y. Gafanovich


This article analyzes the nature of the influence of some factors on the survival rate of patients after myocardial infarction (MI). This study is necessary for the subsequent development of algorithms for predicting the risk of mortality from myocardial infarction, as well as planning treatment and preventive measures. Cardiovascular diseases make the largest contribution to the mortality rate of the population, they account for about 33% of the total number of deaths. After analyzing the nature of the influence of some factors, it is possible to draw conclusions that contribute to the reduction of these mortality indicators. The analysis was carried out by the Kaplan-Meier method using the STATISTICA 12 software package, module “Survival Analysis”. For the analysis, a non-personalized sample of patients admitted to hospitals in the Voronezh Region diagnosed with MI in 2015–2017, was supplemented with information on registered deaths after discharge of patients. The study showed that the greatest risk of death in the first five days after the onset of myocardial infarction. At the same time, 20-day survival is observed in 86% of patients undergoing MI. The analysis showed that the history of the disease arterial hypertension does not affect mortality in myocardial infarction. Gender of the patient is also not important. The effect of thrombolytic therapy is controversial (does not affect or worsens the prognosis of survival).

Keywords: : dispersion, concentration, pollutants, numerical solution of equations, one-and two-dimensional problems.

Full text:
KashirinaSoavtori_1_19_1.pdf

OPTIMIZATION OF SCHEMES OF MEDICAL AND RECREATIONAL ACTIVITIES FOR CHRONIC OBLITERATING DISEASES OF ARTERIES OF THE LOWER EXTREMITIES USING THE THEORY OF MEASUREMENT OF LATENT VARIABLES

UDC 616.5-002.4

A.V.Bykov , N.A.Korenevsky , A.I.Kolesnik, T.N.Govorukhina


The aim of the proposed study is to increase the effectiveness of medical treatment activities of patients with chronic obliterating diseases of the arteries of the lower limbs, including their malignant development – critical ischemia of the lower limbs, due to the use of adequate mathematical methods. As an adequate mathematical apparatus, the theory of measuring latent variables with the G.Rush model is chosen, with the help of which hidden connections are established between known variables (indicator variables) and a variable that does not have an explicit analytic connection with indicator variables, but in relation to which, at a conceptual level, it is known , that such a connection can exist. This variable is called hidden or latent. From the point of view of the choice of the optimal schemes of medical and recreational activities, specific drugs, their dosage, rates and methods of administration, etc. serve as indicator variables, and the effectiveness of treatment as a latent variable. The evaluation of the effectiveness of medical and recreational activities selected at the expert level is provided by the interactive package RUMM 2020, which implements the model of G. Rush, which processes the initial statistical information that was formed during five years when observed by 400 patients of the Kursk Regional Clinical Hospital suffering from different stages of the HOZANK and receiving various treatment regimens. The effectiveness of the treatment measures was controlled by the change in the intensity of the pain syndrome in the lower limbs according to the author’s questionnaire.Using the RUMM 2020 package, it was found that, as effective drugs in the treatment of chronic obliterating diseases, it is advisable to use a combination of such drugs as alprostan, vesel-duf, fractiparin, actovegin, 6% reforming, pradax and ethoxidol. In the online mode of experts with the RUMM 2020 package for these drugs, the treatment regimens were refined and it was shown that the intensity of the pain syndrome, the effectiveness of treatment for newly received treatment regimens is increased by an average of 75%, which allows them to be recommended to the medical practice of vascular surgeons and angiologists.

Keywords: : chronic obliterating diseases of lower limbs, theory of latent variables measurement, optimal treatment regimens.

Full text:
BykovSoavtors_4_18_2.pdf

NEURAL NETWORK MODELING OF THE PROCESS OF SELECTING A PATTERN FOR THE TREATMENT OF PATIENTS WITH CHRONIC PYELONEPHRITIS AND UROLITHIASIS

UDC 681.3

K.O. Levenkov, E.N. Korovin, E.I. Novikova


The article deals with the basic aspects of designing a neural network model for choosing a treatment regimen for chronic pyelonephritis and urolithiasis. One of the most common non-specific chronic kidney diseases is a chronic pyelonephritis. Currently, mathematical modeling of biological systems is one of the main directions of mathematical methods in medical practice. The paper demonstrates network operation. The construction of a multilayer perceptron was carried out on the basis of the Neural Networks module in the Statistica program. The resulting neural network model has 5 outputs, each of which is identical to the types of treatment present in the training set. The developed model provides an opportunity to choose one of 5 types of treatment: Y1 – conservative therapy with antibacterial, antispasmodic and anti-inflammatory drugs in combination with physiotherapeutic procedures; Y2 – conservative therapy in combination with surgical treatment in the amount of contact lithotripsy (KLT); Y3 – conservative therapy in combination with surgical treatment in the volume of distant lithotripsy (DLT); Y4 – conservative therapy in combination with surgical treatment in the amount of percutaneous nephrolitholapaxy (PNLT); Y5 is an open surgery and conservative treatment. The developed model makes it possible to choose one of 5 types of treatment. The reliability of this model was 94%.

Keywords: : neural network modeling, chronic pyelonephritis, urolithiasis, multilayer perceptron, neuron, test set, pattern recognition system.

Full text:
LevenkovSoavtors_4_18_1.pdf

STUDY OF THE SPREAD OF TRANSVERSE ELASTIC WAVES IN BIOLOGICAL TISSUES

UDC 534.222

А.I. Mikhraliyeva, V. A. Karstin, N.P. Zagray, N.N. Chernov


The method of excitation of transverse acoustic waves in biological tissues for the purpose of visualization of the subcutaneous structures of the peripheral vascular system is considered. The separation of longitudinal and transverse acoustic waves is carried out by measuring the speed of sound over the time of its propagation in the measuring and reference lines. A laboratory setup for the excitation of a transverse acoustic wave in biological tissues and a technique for measuring the characteristics of the propagation of transverse waves are described. The installation had two acoustic measuring and reference lines. A high-frequency pulse was simultaneously applied to the piezoelectric transducers of the measuring line and the reference line. The measurements were carried out first with no sample in the measuring line, then with a tissue sample. The readings of the micrometer screw, which determine the thickness of the reference liquid layer, were recorded. The velocity of the transverse wave in biological tissue was calculated according to the equality of the time gaps of the passage of acoustic waves through the sample of biological tissue and the layer of reference fluid. The results of measuring the speed of propagation of transverse waves in various biological tissues are given. Measuring the speed of propagation of transverse elastic waves in various samples of healthy and pathological tissues allows you to create a database of velocities of propagation of ultrasonic waves, which makes it possible to conduct an early and reliable diagnosis of pathologies.

Keywords: : transverse and longitudinal acoustic waves in biological tissue, the peripheral vascular system, visualization.

Full text:
MikhraliyevaSoavtors_4_18_1.pdf

MATHEMATICAL MODELS FOR PREDICTION AND EARLY DIAGNOSIS OF DISEASES OF THE NERVOUS SYSTEM PROVOKED BY CONTACTS WITH TOXIC CHEMICALS

UDC 615.47

L.V. Starodubtseva, R.V. Stepashov, L.P. Lazurina, R.A. Krupchatnikov,
L.V. Shulga


The work is devoted to the urgent problem of improving the quality of medical care to workers in contact with toxic chemicals in the process of their production or during the production process. In the course of studies, it was shown that contact with toxic chemicals causes a range of diseases among which occupy a significant place disease of the nervous system. One of the ways to combat this class of diseases is timely and qualitative prognosis and early diagnosis allows to prescribe adequate schemes of prevention and treatment. Taking into account the multiplicative and prolonged effect of toxтв ic chemicals on the human body, as well as the heterogeneity and fuzziness of the description of the studied classes of States for the synthesis of the relevant decision rules, the methodology of synthesis of hybrid fuzzy decision rules developed at the Department of biomedical engineering of Southwestern state University was used. In the course of application of this methodology mathematical models of forecasting of emergence of diseases of nervous system with the reliable three-year forecast and diagnostics of early stages of this class of diseases were received. In the course of statistical tests on representative control samples, it was shown that the confidence in the decisions made exceeds 0.85. Practical applications of the proposed method and models will improve the quality of medical services to employees of the agro-industrial complex by increasing the working age and reducing disability.

Keywords: : models, forecasting, early diagnostics, diseases, nervous system, toxic chemicals.

Full text:
StarodubzevaSoavtors_4_18_1.pdf