EFFICACY OF COMPLEX NEUROREHABILITATION OF PATIENTS WITH A POST-STROKE ARM PARESIS WITH THE USE OF A BRAIN-COMPUTER INTERFACE+EXOSKELETON SYSTEM

Cover Page


Cite item

Full Text

Abstract

Background: Rehabilitation of patients with poststroke motor disorders with the use of a brain-computer interface (BCI)+exoskeleton may raise the rehabilitation to a  new high-tech level and allow for an effective correction of the post-stroke dysfunction. Aim: To assess the efficacy of BCI+exoskeleton procedures for neurorehabilitation of patients with post-stroke motor dysfunction. Materials and methods: The study included 40 patients with a history of cerebral stroke (mean age 59±10.4 years, 26 male and 14 female). Thirty six of them had had an ischemic stroke and 4, a hemorrhagic stroke from 2 months to 4 years before the study entry. All patients had a various degree post-stroke hemiparesis predominantly of the arm. The main group patients (n=20), in addition to conventional therapy, had 10  sessions (3  times daily) of BCI+exoskeleton. The BCI recognized the hand ungripping imagined by the patient and, by a  feedback signal, the exoskeleton exerted the passive movement in the paretic arm. The control group patients (n=10) had 10  BCI+exoskeleton sessions without imaginary movements, and the exoskeleton functioned in a  random mode. The comparison group included 10  patients who received only standard treatment. Results: At the end of rehabilitation treatment (day 14), all study groups demonstrated an improvement in the function of the paretic extremity. There was an improvement of functioning and daily activities in the main group, compared to the control and the comparison groups: the change in the modified Rankin scale score was 0.4±0.1, 0.1±0.1  and 0±0.2 (p<0.05), in the Bartel scale score, 5.6±0.8, 2.3±0.3 and 1±0.2 (p<0.001), respectively. In the BCI+exoskeleton group the motor function of the paretic arm assessed by the ARAT scale, improved by 5.5±1.3  points (2.4±0.6  points in the control group and 1.9±0.7  in the comparison group, р<0.05), and as assessed by the Fugl-Meyer scale, by 10.8±1.5 points (3.8±1.05 points in the comparison group, p<0.001). Conclusion: Rehabilitation of patients with post-stroke paresis with the use of BCI+exoskeleton led not also to a decrease in neurological deficit and an improvement of the paretic arm motor function, but also improved parameters of daily activities. Further studies of the effects of BCI+exoskeleton rehabilitation procedures on the course of motor function restoration are planned.

About the authors

A. A. Frolov

Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Sciences

Email: fake@neicon.ru

PhD in Biology, Professor; Head of Mathematical Neurobiology of Learning Laboratory

5А Butlerova ul., Moscow, 117485

Russian Federation

E. V. Biryukova

Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Sciences;
Pirogov Russian National Research Medical University

Email: fake@neicon.ru

PhD in Biology, Senior Research Fellow, Mathematical Neurobiology of Learning Laboratory

5А Butlerova ul., Moscow, 117485

1 Ostrovityanova ul., Moscow, 117997

Russian Federation

P. D. Bobrov

Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Sciences

Email: fake@neicon.ru

Research Fellow, Mathematical Neurobiology of Learning Laboratory

5А Butlerova ul., Moscow, 117485

Russian Federation

M. E. Kurganskaya

Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Sciences

Email: fake@neicon.ru

PhD, Research Fellow, Mathematical Neurobiology of Learning Laboratory

5А Butlerova ul., Moscow, 117485

Russian Federation

O. G. Pavlova

Institute of Higher Nervous Activity and Neurophysiology of Russian Academy of Sciences

Email: fake@neicon.ru

PhD in Biology, Senior Research Fellow, Mathematical Neurobiology of Learning Laboratory

5А Butlerova ul., Moscow, 117485

Russian Federation

A. A. Kondur

Moscow Regional Research and Clinical Institute (MONIKI)

Email: fake@neicon.ru

Postgraduate Student, Chair of Neurology, Postgraduate Training Faculty

61/2 Shchepkina ul., Moscow, 129110

Russian Federation

L. G. Turbina

Moscow Regional Research and Clinical Institute (MONIKI)

Email: fake@neicon.ru

MD, PhD, Professor; Chair of Neurology, Postgraduate Training Faculty

61/2 Shchepkina ul., Moscow, 129110

Russian Federation

S. V. Kotov

Moscow Regional Research and Clinical Institute (MONIKI)

Author for correspondence.
Email: kotovsv@yandex.ru

MD, PhD, Professor; Head of Department of Neurology; Head of Chair of Neurology, Postgraduate Training Faculty

61/2 Shchepkina ul., Moscow, 129110

Tel.: +7 (495) 631 73 62

Russian Federation

References

  1. Faralli A, Bigoni M, Mauro A, Rossi F, Carul￾li D. Noninvasive strategies to promote functional recovery after stroke. Neural Plast. 2013;2013:854597. doi: 10.1155/2013/854597.
  2. Yoon JA, Koo BI, Shin MJ, Shin YB, Ko HY, Shin YI. Effect of constraint-induced movement therapy and mirror therapy for patients with subacute stroke. Ann Rehabil Med. 2014;38(4):458–66. doi: 10.5535/ arm.2014.38.4.458.
  3. Котов СВ. Новые технологии в диагностике и лечении больных в остром периоде инсульта. Русский медицинский журнал. 2014;22(10):712–6.
  4. Lin BS, Pan JS, Chu TY, Lin BS. Development of a Wearable Motor-Imagery-Based Brain-Computer Interface. J Med Syst. 2016;40(3):71. doi: 10.1007/s10916-015-0429-6.
  5. Hwang HJ, Kwon K, Im CH. Neurofeedback-based motor imagery training for brain-computer interface (BCI). J Neurosci Methods. 2009;179(1):150–6. doi: 10.1016/j. jneumeth.2009.01.015.
  6. Mrachacz-Kersting N, Jiang N, Stevenson AJ, Niazi IK, Kostic V, Pavlovic A, Radovanovic S, Djuric-Jovicic M, Agosta F, Dremstrup K, Farina D. Efficient neuroplasticity induction in chronic stroke patients by an associative brain-computer interface. J Neurophysiol. 2016;115(3):1410–21. doi: 10.1152/ jn.00918.2015.
  7. Neuper C, Scherer R, Reiner M, Pfurtscheller G. Imagery of motor actions: differential effects of kinesthetic and visual-motor mode of imagery in single-trial EEG. Brain Res Cogn Brain Res. 2005;25(3):668–77. doi: 10.1016/j.cogbrainres.2005.08.014.
  8. Dimyan MA, Cohen LG. Neuroplasticity in the context of motor rehabilitation after stroke. Nat Rev Neurol. 2011;7(2):76–85. doi: 10.1038/ nrneurol.2010.200.
  9. Prasad G, Herman P, Coyle D, McDonough S, Crosbie J. Applying a brain-computer interface to support motor imagery practice in people with stroke for upper limb recovery: a feasibility study. J Neuroeng Rehabil. 2010;7:60. doi: 10.1186/1743-0003-7-60.
  10. Ang KK, Guan C, Chua KS, Ang BT, Kuah C, Wang C, Phua KS, Chin ZY, Zhang H. Clinical study of neurorehabilitation in stroke using EEG-based motor imagery brain-computer interface with robotic feedback. Conf Proc IEEE Eng Med Biol Soc. 2010;2010:5549–52. doi: 10.1109/IEMBS.2010.5626782.
  11. Pichiorri F, Morone G, Petti M, Toppi J, Pisotta I, Molinari M, Paolucci S, Inghilleri M, Astolfi L, Cincotti F, Mattia D. Brain-computer interface boosts motor imagery practice during stroke recovery. Ann Neurol. 2015;77(5):851–65. doi: 10.1002/ana.24390.
  12. Ang KK, Chua KS, Phua KS, Wang C, Chin ZY, Kuah CW, Low W, Guan C. A Randomized Controlled Trial of EEG-Based Motor Imagery Brain-Computer Interface Robotic Rehabilitation for Stroke. Clin EEG Neurosci. 2015;46(4):310–20. doi: 10.1177/1550059414522229.
  13. Котов СВ, Турбина ЛГ, Бобров ПД, Фролов АА, Павлова ОГ, Курганская МЕ, Бирюкова ЕВ. Реабилитация больных, перенесших инсульт, с помощью биоинженерного комплекса «интерфейс мозг-компьютер + экзоскелет». Журнал неврологии и психиатрии им. С.С. Корсакова. 2014;14(12–2):66–72.
  14. Фролов АА, Мокиенко ОА, Люкманов РХ, Черникова ЛА, Котов СВ, Турбина ЛГ, Бобров ПД, Бирюкова ЕВ, Кондур АА, Иванова ГЕ, Старицын АН, Бушкова ЮВ, Джалагония ИЗ, Курганская МЕ, Павлова ОГ, Будилин СЮ, Азиатская ГА, Хижникова АЕ, Червяков АВ, Лукьянов АЛ, Надарейшвили ГГ. Предварительные результаты контролируемого исследования эффективности технологии ИМК – экзоскелет при постинсультном парезе руки. Вестник РГМУ. 2016;(2):17–25.
  15. Bohannon RW, Smith MB. Interrater reliability of a modified Ashworth scale of muscle spasticity. Phys Ther. 1987;67(2): 206–7.
  16. Fugl-Meyer AR, Jääskö L, Leyman I, Olsson S, Steglind S. The post-stroke hemiplegic patient. 1. A method for evaluation of physical performance. Scand J Rehabil Med. 1975;7(1):13–31.
  17. Lyle RC. A performance test for assessment of upper limb function in physical rehabilitation treatment and research. Int J Rehabil Res. 1981;4(4):483–92.
  18. Белова АН, ред. Шкалы, тесты и опросники в медицинской реабилитации. М.: Антидор; 2002. 440 с.
  19. Котов СВ, Турбина ЛГ, Бобров ПД, Фролов АА, Павлова ОГ, Курганская МЕ, Бирюкова ЕВ. Применение комплекса «интерфейс “мозг – компьютер” и экзоскелет» и техники воображения движения для реабилитации после инсульта. Альманах клинической медицины. 2015;39:15–21. doi: 10.18786/2072- 0505-2015-39-15-21.
  20. Бирюкова ЕВ, Павлова ОГ, Курганская МЕ, Бобров ПД, Турбина ЛГ, Фролов АА, Давыдов ВИ, Сильченко АВ, Мокиенко ОА. Восстановление двигательной функции руки с помощью экзоскелета кисти, управляемого интерфейсом мозг – компьютер. Cлучай пациента с обширным поражением мозговых структур. Физиология человека. 2016;42(1):19–30. doi: 10.7868/S0131164616010033

Supplementary files

Supplementary Files
Action
1. JATS XML

Copyright (c) 2016 Frolov A.A., Biryukova E.V., Bobrov P.D., Kurganskaya M.E., Pavlova O.G., Kondur A.A., Turbina L.G., Kotov S.V.

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies