Objective. To study the potential for use of a bioengineered system consisting of an electroencephalograph, a personal computer running a program for the synchronous data transmission, recognition, and classification of electroencephalogram (EEG) signals, and formation of control commands in real time, combined with a hand exoskeleton (a bioengineered “brain–computer interface (BCI) with exoskeleton” system) for the motor rehabilitation of patients with poststroke upper limb paresis. Materials and methods. Brain–computer interfaces have potential for use in neurorehabilitation. A total of five patients with poststroke upper limb paresis received neurorehabilitation courses consisting of 8–10 sessions. All the patients had large foci of poststroke changes of cortical-subcortical locations as demonstrated by MRI scans. Results. Improvements in neurological status on the NIHSS were seen after courses of sessions, with significant increases in the volume and strength of movements in the paralyzed hand, improvements in the coordination of its movements, and minor decreases in the level of spasticity. There was an increase in daily activity on the Barthel index, mainly due to improvement in fi ne motor function. Levels of disability showed clear changes on the modified Rankin scale. Conclusions. Use of the “brain–computer interface (BCI) with exoskeleton” system in the rehabilitation of patients with poststroke paresis of the hand gave positive results, pointing to the need to continue these studies.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
S. V. Kotov, L. V. Stakhovskaya (eds.), E. V. Isakova, et al., Stroke, MIA. Moscow (2004).
D. Lloyd-Jones, R. J. Adams, T. M. Brown, et al., “Heart disease and stroke statistics – 2010 update: a report from the American Heart Association,” Circulation, 121, 46–215 (2010).
S. Paolucci, M. Bragoni, P. Coiro, et al., “Quantification of the probability of reaching mobility independence at discharge from a rehabilitation hospital in nonwalking early ischemic stroke patients: a multivariate study,” Cerebrovasc. Diseases, 26, No. 1, 16–22 (2008).
M. C. Cirstea and M. F. Levin, “Improvement of arm movement patterns and endpoint control depends on type of feedback during practice in stroke survivors,” Neurorehab. Neural Repair, 21, No. 5, 398–411 (2007).
C. E. Lang, J. R. Macdonald, D. S. Reisman, et al., “Observation of amounts of movement practice provided during stroke rehabilitation,” Arch. Phys. Med. Rehabil., 90, No. 10, 1692–1698 (2009).
J. W. Krakauer, “Motor learning: its relevance to stroke recovery and neurorehabilitation,” Curr. Opin. Neurol., 19, No. 1, 84–90 (2006).
J. M. Belda-Lois, S. Mena-Del Horno, I. Bermejo-Bosch, et al., “Rehabilitation of gait after stroke: a review towards a top-down approach,” J. Neuroeng. Rehabil., 13, 8–66 (2011).
M. Iosa, G. Morone, A. Fusco, et al., Seven Capital Devices for the Future of Stroke Rehabilitation, Hindawi Publishing Corporation Stroke Research and Treatment (2012), doi: 10.1155/2012/187965.
P. Bobrov, A. Frolov, C. Cantor, et al., “Brain–computer interface based on generation of visual images,” PLoS One, 6, No. 6, 20674 (2011), doi: 10.1371/journal.pone.0020674.
C. Enzinger, S. Ropele, F. Fazekas, et al., “Brain motor system function in a patient with complete spinal cord injury following extensive brain–computer interface training,” Exp. Brain Res., 190, No. 2, 215–223 (2008).
G. Pfurtscheller, G. R. Muller-Putz, R. Scherer, and C. Neuper, “Rehabilitation with brain–computer interface systems,” Computer, 41, No. 10, 58–65 (2008).
H. P. Adams, G. del Zoppo, M. J. Alberts, et al., “Guidelines for the early management of adults with ischemic stroke,” Stroke, 38, 1655–1711 (2007).
D. S. Nichols-Larsen, P. C. Clark, A. Zeringue, et al., “Factors influencing stroke survivors’ quality of life during subacute recovery,” Stroke, 36, No. 7, 1480–1484 (2005).
S. J. Albert and J. Kesselring, “Neurorehabilitation,” in: Textbook of Stroke Medicine, M. Brainin and W.-D. Heiss (eds.), Cambridge University Press (2010), pp. 283–306.
R. Dickstein and J. E. Deutsch, “Motor imagery in physical therapist practice,” Phys. Ther., 87, 942–953 (2007), doi: 10.2522/ptj.20060331.
N. Sharma, V. M. Pomeroy, and J. C. Baron, “Motor imagery: a back door to the motor system after stroke?” Stroke, 37, 1941–1952 (2006), doi: 10.1161/01.STR.0000226902.43357.fc.
C. Neuper, R. Scherer, S. Wriessnegger, and G. Pfurtscheller, “Motor imagery and action observation: modulation of sensorimotor brain rhythms during mental control of a brain–computer interface,” Clin. Neurophysiol., 120, 239–247 (2009).
G. Pfurtscheller and F. H. Lopes da Silva, “Event-related EEG/MEG synchronization and desynchronization: basic principles,” Clin. Neurophysiol., 110, 1842–1857 (1999).
D. J. McFarland and J. R. Wolpaw, “Sensorimotor rhythm-based brain computer interface (BCI): model order selection for autoregressive spectral analysis,” J. Neural. Eng., 5, 155–162 (2008).
A. A. Frolov, E. V. Biryukova, P. D. Bobrov, et al., “Principles of rehabilitation based on the use of a brain–computer interface and biologically appropriate control of an exoskeleton,” Fiziol. Cheloveka, 39, No. 2, 99–113 (2013).
A. C. Lo, P. D. Guarino, L. G. Richards, et al., “Robot-assisted therapy for longterm upper-limb impairment after stroke,” N. Eng. J. Med., 362, 1772– 1783 (2010).
C. D. Takahashi, L. Der-Yeghiaian, V. Le, et al., “Robot-based hand motor therapy after stroke,” Brain, 131, 425–437 (2008).
M.-H. Milot, S. J. Spencer, V. Chan, et al., “A crossover pilot study evaluating the functional outcomes of two different types of robotic movement training in chronic stroke survivors using the arm exoskeleton BONES,” J. Neuroeng. Rehabil., 10, 112 (2013).
Author information
Authors and Affiliations
Corresponding author
Additional information
Translated from Zhurnal Nevrologii i Psikhiatrii imeni S. S. Korsakova, Vol. 114, No. 12, Iss II, Stroke, pp. 66–71, December, 2014.
Rights and permissions
About this article
Cite this article
Kotov, S.V., Turbina, L.G., Bobrov, P.D. et al. Rehabilitation of Stroke Patients with a Bioengineered “Brain–Computer Interface with Exoskeleton” System. Neurosci Behav Physi 46, 518–522 (2016). https://doi.org/10.1007/s11055-016-0270-5
Published:
Issue date:
DOI: https://doi.org/10.1007/s11055-016-0270-5