Адаптивная биотехническая система с роботизированным устройством для восстановления двигательных функций нижних конечностей постинсультных больных
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Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
Online media
issn 2310-6018

Adaptive biotechnical system with a robotic device for the restoration of motor functions of the lower extremities in post-stroke patients

idFilist S.A. Trifonov A.A.   idKuzmin A.A. Petrunina E.V.   Mohamad T.S.  

UDC 004.89
DOI: 10.26102/2310-6018/2021.34.3.022

  • Abstract
  • List of references
  • About authors

To restore the motor functions of the lower extremities in post-stroke patients, it is proposed to use a biotechnical system with a robotic device. The control is based on the analysis and classification of electromyosignals. The robotic device is controlled by a fuzzy control module, which allows maintaining three modes of rehabilitation, selecting and switching them depending on the functional state of the patient, thereby deciding on the optimal rehabilitation program for the current functional state of the patient. The control model includes three fuzzy control modules with the corresponding bases of fuzzy decision rules and it allows you to adapt the rehabilitation procedure to the functional state of the patient. To assess the effectiveness of the proposed method of rehabilitation, the experimental group included 23 patients who underwent exacerbations from 25 days to 5 years, including patients with subacute (<180 days after exacerbation) and chronic (> 180 days after exacerbation) conditions. After a course of rehabilitation by means of a biotechnical system with a fuzzy control module, there is a significant increase in the maxima of the support reaction force Rz on the affected leg in the experimental group in relation to the control group. Accordingly, the amplitude of the front push in the experimental group increased by 62% (120%), the rear push by 58% (115%), while in the control group the amplitude increase was 40% (101%) and 41% (105 %). In this case, distinct maxima of the support reaction component Rz appear on the paretic leg.

1. Al'-Bareda A.Ya.S., Brezhneva A.N., Tomakova R.A. Algorithms for the synthesis of optimal control in biotechnical systems of rehabilitation type based on neural network technologies. Sistemnyi analiz i upravlenie v biomeditsinskikh sistemakh. 2018;17(3):750-754. (In Russ)

2. Trifonov A.A, Petrunina E.V., Filist S.A., Kuz'min A.A., Zhilin V.V. Biotechnical system with virtual reality in rehabilitation complexes with artificial feedbacks. Izvestiya Yugo-Zapadnogo gosudarstvennogo universiteta. Seriya: Upravlenie, vychislitel'naya tekhnika, informatika. Meditsinskoe priborostroenie. 2019;9(4):46-66. (In Russ)

3. Trifonov A., Filist S., Degtyarev S., Serebrovsky V., and Shatalova O. Human–Machine Interface of Rehabilitation Exoskeletons with Redundant Electromyographic Channels. Proceedings of 15th International Conference on Electromechanics and Robotics “Zavalishin’s Readings”. Springer, Singapore, 2021;237-247. DOI: https://doi.org/10.1007/978-981-15-5580-0_19.

4. Filist S.A., Shatalova O.V., Efremov M.A. Hybrid neural network with macro layers for medical applications. Neurocomputers. 2014;6:35-39. (In Russ)

5. Efremov M.A., Shatalova O.V., Fedyanin V.V., Shutkin A.N. Hybrid multi-agent classifiers in biotechnical systems for the diagnosis of diseases and monitoring of medicinal prescriptions. Neurocomputers. 2015;6:42-47. (In Russ)

6. Petrova T.V., Filist S.A., Degtyarev S.V., Kiselev A.V., Shatalova O.V. Predictors of synchronicity of system rhythms of living systems for classifiers of their functional states. Sistemnyi analiz i upravlenie v biomeditsinskikh sistemakh. 2018;17(3):693-700. (In Russ)

7. Filist S.A., Petrunina E.V., Trifonov A.A., Serebrovskii A.V. Electroencephalogram signal codes for controlling robotic devices through a brain-computer interface. Modeling, Optimization and Information Technology. 2019;7(1). Available at: https://moitvivt.ru/ru/journal/pdf?id=555. DOI: 10.26102/2310-6018/2019.24.1.025 (accessed 10.08.2021). (In Russ)

8. Trifonov A.A., Kuzmin A.A., Filist S. A. and Petrunina E.V. Neural network model in the exoscelete verticalization control system. Journal of Phisics: Conference Series. 2020;1679(3). Available at: https://iopscience.iop.org/article/10.1088/1742-6596/1679/3/032036/pdf. DOI:10.1088/1742-6596/1679/3/032036 (accessed 15.08.2021).

9. Trifonov A.A., Filist S.A., Kuz'min A.A., Zhilin V.V., Petrunina E.V. A two-level neural network model of an electromyosignal decoder in an exoskeleton verticalization control system. Prikaspiiskii zhurnal: upravlenie i vysokie tekhnologii, 2020;(4):99-111. (In Russ)

10. Trifonov A.A., Kuz'min A.A., Petrunina E.V., Kadyrova S. Means of assessing muscle load and muscle fatigue for controlling the exoskeleton in a combined mode. Lazery. Izmereniya. Informatsiya. 2021;1(1):55-66.

Filist Sergey Aleksevich
Doctor of Technical Sciences, Professor Professor
Email: SFilist@gmail.com

Scopus | ORCID | eLibrary |

South-West State University

Kursk, Russian Federation

Trifonov Andrey Andreevich

Email: voldraf@mail.ru

Southwestern State University

Kursk, Russian Federation

Kuzmin Alexander Andreevich
Candidate of Technical Sciences Associate Professor
Email: ku3bmin@gmail.com

Scopus | ORCID | eLibrary |

South-West State University

Kursk, Russian Federation

Petrunina Elena Valerevna
Candidate of Technical Sciences Associate Professor

Moscow State University for the Humanities and Economics

Moscow, Russian Federation

Mohamad Tufik Shekhine
Candidate of Technical Sciences

Kursk State Medical University

Kursk, Russian Federation

Keywords: fuzzy control module, post-stroke patients, robotic device, algorithm, base of fuzzy decision rules

For citation: Filist S.A. Trifonov A.A. Kuzmin A.A. Petrunina E.V. Mohamad T.S. Adaptive biotechnical system with a robotic device for the restoration of motor functions of the lower extremities in post-stroke patients. Modeling, Optimization and Information Technology. 2021;9(3). Available from: https://moitvivt.ru/ru/journal/pdf?id=1037 DOI: 10.26102/2310-6018/2021.34.3.022 (In Russ).

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Full text in PDF

Received 15.08.2021

Revised 12.09.2021

Accepted 15.09.2021

Published 17.10.2021