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Use of a Brain–Computer Interface + Exoskeleton Technology in Complex Multimodal Stimulation in the Rehabilitation of Stroke Patients

Neuroscience and Behavioral Physiology volume 50, pages 987–991 (2020)Cite this article

Introduction. Studies of the potentials of brain–computer neural interface technology with an arm exoskeleton (BCNI) in training to motor imagery in the recovery of higher mental functions in patients constitute an interesting task. The effectiveness of multimodal stimulation including diverse information channels needs to be assessed, as this approach should promote stimulation of neuroplasticity and improvement to interhemisphere interactions. Objectives. To study the influences of multimodal stimulation using BCNI technologies on the restoration of cognitive functions in stroke patients. Materials and methods. A total of 44 stroke patients were studied and treated at periods of two months to two years after onset. Patients were divided into two groups with comparable main parameters: a study group (22 patients) and a reference group (22 patients). Patients of the study group underwent a program of complex multimodal stimulation including procedures using BCNI technologies, cognitive training, use of a stabilometric platform with biological feedback for the support reaction, and vibrotherapy. Patients of the reference group received only BCNI. Results. After treatment, statistically significant improvements in therapeutic results were obtained in the form of improvements in memory, attention, and visuospatial skills in patients of the study group as compared with those of the reference group. Conclusions. Questions of cognitive training using BCNI technologies are currently a relatively new direction in neurorehabilitation; the promising results obtained here provide evidence of the potential of this direction.

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References

  1. A. S. Kadykov and N. V. Shakhparonova, “Rehabilitation of poststroke patients. The role of medication therapy,” Meditsinsk. Sov., 4, No. 1, 92–98 (2013), https://www.med-sovet.pro.

    Google Scholar 

  2. I. V. Saenko, E. I. Kremneva, O. V. Glebova, et al., “New approaches tot rehabilitation of patients with CNS lesions based on gravitational mechanisms,” Fiziol. Cheloveka, 43, No. 5, 118–128 (2017), https://www.maik.ru/journals/humphys.htm.

    Google Scholar 

  3. K. K. Ang, K. S. Chua, K. S. Phua, et al., “Randomized controlled trial of EEG-based motor imagery brain-computer interface robotic rehabilitation for stroke,” Clin. EEG Neurosci., 46, No. 4, 310–320 (2015).

    Article  Google Scholar 

  4. T. Kim, S. Kim, and B. Lee, “Effects of action observational training plus brain-computer interface-based functional electrical stimulation on paretic arm motor recovery in patient with stroke: A randomized controlled trial,” Occup. Ther. Int., 23, No. 1, 39–47 (2016), https://doi.org/10.1002/oti.1403.

    Article  PubMed  Google Scholar 

  5. A. A. Frolov, O. A. Mokienko, R. Kh. Lyukmanov, et al., “Preliminary results of a controlled study of the effi cacy of BCI-exoskeleton technology in poststroke paresis of the arms,” Vestn. RGMU, 2, 17–25 (2016), http://www.vestnikrgmu.ru/?lang=en.

    Google Scholar 

  6. G. Y. Kim, M. R. Han, and H. G. Lee, “Effect of dual-task rehabilitative training on cognitive and motor function of stroke patients,” J. Phys. Ther. Sci., 26, No. 1, 1–6 (2014), https://doi.org/10.1589/jpts.26.1

    Article  PubMed  PubMed Central  Google Scholar 

  7. S. V. Kotov, L. G. Turbina, P. D. Bobrov, et al., “Use of a brain–computer interface and exoskeleton and movement imagery techniques for poststroke rehabilitation,” Alman. Klin. Med., 39, 15–21 (2015), http://almclinmed.ru.

    Google Scholar 

  8. S. V. Kotov, L. G. Turbina, P. D. Bobrov, et al., “Rehabilitation of stroke patients using a brain–computer interface + exoskeleton bioengineering system,” Zh. Nevrol. Psikhiatr., 114, No. 12–2, 66–72 (2014).

    CAS  Article  Google Scholar 

  9. S. Borson, J. Scanlan, M. Brush, et al., “The mini-cog: a cognitive ‘vital signs’ measure for dementia screening in multi-lingual elderly,” Int. J. Geriatr. Psychiatry, 15, No. 11, 1021–1027 (2000).

    CAS  Article  Google Scholar 

  10. O. V. Kubryak, E. V. Isakova, S. V. Kotov, et al., “Increases in patients’ vertical stability in the acute period of stroke,” Zh. Nevrol. Psikhiatr., 114, No. 12–2, 61–65 (2014), https://doi.org/10.17116/jnevro201411412261-65.

    Article  Google Scholar 

  11. Yu. V. Egorova, V. I. Sheregeshev, E. V. Isakova, et al., “Rehabilitation of elderly patients with cognitive impairments in the early recovery period of ischemic stroke sing biological feedback and multichannel muscle electrostimulation,” Klinich. Gerontol., 23, No. 11–12, 97–104 (2017).

    Google Scholar 

  12. M. Semprini, M. Laffranchi, V. Sanguineti, et al., “Technological approaches for neurorehabilitation: from robotic devices to brain stimulation and beyond,” Front. Neurol., 9, 212 (2018), https://doi.org/10.3389/fneur.2018.00212.

  13. L. Carelli, F. Solca, A. Faini, et al., “Brain–computer interface for clinical purposes: cognitive assessment and rehabilitation,” Biomed. Res. Int., 1695290 (2017), https://doi.org/10.1155/2017/1695290.

  14. A. Riccio, F. Pichiorri, F. Schettini, et al., “Interfacing brain with computer to improve communication and rehabilitation after brain damage,” Prog. Brain Res., 228, 357–387 (2016), https://doi.org/10.1016/bs.pbr.2016.04.018.

    CAS  Article  PubMed  Google Scholar 

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  1. Vladimirskii Moscow Regional Research Clinical Institute, Moscow, Russia

    S. V. Kotov, E. V. Isakova & E. V. Slyun’kova

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  1. S. V. Kotov
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  2. E. V. Isakova
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  3. E. V. Slyun’kova
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Correspondence to S. V. Kotov.

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Translated from Zhurnal Nevrologii i Psikhiatrii imeni S. S. Korsakova, Vol. 119, No. 12, Iss. 2, Stroke, pp. 37–42, December, 2019.

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Kotov, S.V., Isakova, E.V. & Slyun’kova, E.V. Use of a Brain–Computer Interface + Exoskeleton Technology in Complex Multimodal Stimulation in the Rehabilitation of Stroke Patients. Neurosci Behav Physi 50, 987–991 (2020). https://doi.org/10.1007/s11055-020-00996-x

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  • DOI: https://doi.org/10.1007/s11055-020-00996-x

Keywords

  • stroke
  • rehabilitation
  • cognitive impairments
  • cognitive stimulation
  • vibrotherapy
  • brain–computer neural interface + exoskeleton