Метод и алгоритмы локализации кластеров адаптационного потенциала в биотехнических системах реабилитации лиц с ограниченными возможностями здоровья
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Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

Method and algorithms for localizing clusters of adaptive potential in biotechnical systems of rehabilitation type for people with disabilities

Butusov A.V.,  idKiselev A.V., Hyder Alavsi H.A.,  Petrunina E.V.,  Safronov R.I.,  idShulga L.V.

UDC 004.891.3:004.932.2
DOI: 10.26102/2310-6018/2023.41.2.012

  • Abstract
  • List of references
  • About authors

To improve the rehabilitation effectiveness for people with disabilities, an individual approach is required while taking into account the constitutional peculiarities of each patient with a view to optimizing the choice of means for rehabilitation measures or treatment. For the rehabilitation of people with disabilities, a method for classifying the adaptive potential is proposed to control and manage their functional state during therapy or a session of a rehabilitation procedure. A method for localizing clusters in the space of surrogate markers has been developed, which includes four stages differing in that the first stage reveals relevant markers that characterize the change in the adaptive potential of a living system under the influence of an exogenous factor; at the second stage, the proof of the reliability of adaptive potential level clustering is carried out; at the third stage, the classification results are analyzed on dynamic training samples, and at the fourth stage, the statistical heterogeneity and / or heterogeneity of the identified clusters is analyzed. A hybrid adaptive potential classifier has been developed, which includes five "weak" classifiers built on the basis of fuzzy decision-making logic, and a fully connected neural network of direct signal propagation as an aggregator. Testing of the hybrid classifier was carried out on the experimental group of postinfarction patients. Efficiency was evaluated using ROC analysis. The quality indicators of the synthesized hybrid classifier classification make it possible to recommend it for biotechnical systems of a rehabilitation type which carry out medical and restorative procedures for post-infarction patients.

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Butusov Andrey Vladimirovich

Southwest State University

Kursk, The Russian Federation

Kiselev Aleksey Viktorovich
Candidate of Technical Sciences

ORCID |

Southwest State University

Kursk, The Russian Federation

Hyder Alavsi Hussein Ali

Southwest State University

Kursk, The Russian Federation

Petrunina Elena Valerievna
Candidate of Technical Sciences, Associate Professor

Moscow Polytechnic University

Moscow, The Russian Federation

Safronov Ruslan Igorevich
Candidate of Technical Sciences, Associate Professor

Kursk State Agricultural Academy named after I.I. Ivanov

Kursk, The Russian Federation

Shulga Leonid Vasilievich
Doctor of Medical Sciences, Professor

ORCID |

Southwest State University

Kursk, The Russian Federation

Keywords: adaptive potential, hybrid classifier, virtual model, algorithm, recurrent myocardial infarction, cumulative survival

For citation: Butusov A.V., Kiselev A.V., Hyder Alavsi H.A., Petrunina E.V., Safronov R.I., Shulga L.V. Method and algorithms for localizing clusters of adaptive potential in biotechnical systems of rehabilitation type for people with disabilities. Modeling, Optimization and Information Technology. 2023;11(2). URL: https://moitvivt.ru/ru/journal/pdf?id=1333 DOI: 10.26102/2310-6018/2023.41.2.012 (In Russ).

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Full text in PDF

Received 29.03.2023

Revised 21.04.2023

Accepted 26.05.2023

Published 30.06.2023