2019 / 06

Next Paper
DOI: 10.24075/brsmu.2019.078

ORIGINAL RESEARCH

Brain-computer-interface technology with multisensory feedback for controlled ideomotor training in the rehabilitation of stroke patients

Bushkova YuV1, Ivanova GE1, Stakhovskaya LV2, Frolov AA3
About authors

1 Research Center of Cerebrovascular Pathology and Stroke, Ministry of Health of the Russian Federation, Moscow, Russia

2 Pirogov Russian National Research Medical University, Moscow, Russia

3 Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Moscow, Russia

Correspondence should be addressed: Yuliya V. Bushkova
Ostrovityanova, 1, str. 10, Moscow, 117342; moc.liamg@777hsubajiluJ

About paper

Funding: the study was supported by the Russian Foundation for Basic Research (Grant ID 16-29-08247 ofi_m).

Author contribution: Bushkova YuV — study planning; literature analysis; data acquisition, analysis and interpretation; manuscript preparation; Ivanova GE — study planning; literature analysis; data interpretation; manuscript preparation; Stakhovskaya LV — study planning; data interpretation; manuscript preparation; Frolov AA — manuscript preparation.

Received: 2019-11-12 Accepted: 2019-11-24 Published online: 2019-12-08
|
  1. Kutashov VA, Budnevskiy AV, Priputnevich DN, Surzhko GV. Psychological features of patients with consequences of acute disorders of cerebral circulation, hamper their social adaptation. Vestnik nevrologii, psihiatrii i nejrohirurgii. 2014; (8): 8–13.
  2. Roman GC. Facts, myths, and controversies in vascular dementia. J Neurol Sci. 2004; 226: 49–52.
  3. Ang KK, Phua KS, Wang C, Chin ZY, Kuah CW, Low W, et al. Randomized Controlled Trial of EEG-Based Motor Imagery Brain- Computer Interface Robotic Rehabilitation for Stroke. Clinical EEG and neuroscience. 2015; 46 (4): 310–20. https://doi. org/10.1177/1550059414522229.
  4. Frolov AA, Mokienko OA, Lyukmanov RKh, Chernikova LA, Kotov SV, et al. Preliminary results of a controlled study of the effectiveness of IMC-exoskeleton technology for post-stroke paresis of the arm. Vestnik RSMU. 2016; (2): 175.
  5. Novak DA, Grefkes C, Arneli M, Fink GR. Interhemispheric competition after stroke: brain stimulation to enhance recovery of function of the affected hand. Neururehabil Neural Repair. 2009; (23): 641–57.
  6. Sharma N, Simmons LH, Jones PS, Day DJ, Carpenter TA, Pomeroy VM, et al. Motor imagery after subcortical stroke: a functional magnetic resonance imaging study. Stroke. 2009; 40 (4): 315–24.
  7. Johnson SH, Sprehn G, Saykin AJ. Intact motorimagery in chronic upper limb hemiplegics: evidence foractivity-independent action representations. Journal of Cognitive Neuroscience. 2002; 14 (6): 841–52.
  8. Barclay-Goddard RE, Stevenson TJ, Poluha W, Thalman L. Mental practice for treating upper extremity deficits in individuals with hemiparesis after stroke. Cochrane Database Syst Rev. 2011; 11 (5): CD005950. DOI: 10.1002/14651858.CD005950.pub4.
  9. Chholak P, Niso G, Maksimenko VA, Kurkin SA, Frolov NS, Pitsik EN et al. Visual and kinesthetic modes affect motor imagery classification in untrained subjects. 2019 Jul 8; 9 (1): 9838. DOI:10.1038/s41598-019-46310-9.
  10. Schmidt R, Lee T. Motor Control and Learning: A Behavioral Emphasis. Champaign, IL: Human Kinetics, 1999; 592 р.
  11. Bajaj S, Butler AJ, Drake D, Dhamala M. Brain effective connectivity during motor-imagery and execution following stroke and rehabilitation. Neuroimage Clin. 2015 (8): 572–82. https://doi. org/10.1016/j.nicl.2015.06.006.
  12. Page SJ, Levine P, Leonard A. Mental practice in chronic stroke: results of a randomized, placebo-controlled trial. Stroke. 2007 Apr; 38 (4): 1293–7.
  13. Braun SM, Beurskens AJ, Borm PJ, Schack T, Wade DT. The effects of mental practice in stroke rehabilitation: a systematic review. Arch Phys Med Rehabil. 2006 Jun; 87 (6): 842–52.
  14. Román GC. Facts, myths, and controversies in vascular dementia. J Neurol Sci. 2004 Nov 15; 226 (1–2): 49–52.
  15. Sauvage C, De Greef N, Manto M, Jissendi P, Nioche C, Habas C. Reorganization of large-scale cognitive networks during automation of imagination of a complex sequential movement // Journal of neuroradiology. 2015; 42 (2): 115–25.
  16. Kaplan AYa. Neurophysiological foundations and practical implementation of the technology of the brain of machine interfaces in neurological rehabilitation. Human Physiology. 2016; 42 (1): 118–27.
  17. Hall CR, Martin KA. Measuring movement imagery abilities: A revision of the Movement Imagery Questionnaire. Journal of mental imagery. 1997.
  18. Bocti C, Legault V, Leblanc N, Berger L, Nasreddine Z, BeaulieuBoire I, et al. Vascular cognitive impairment: most useful subtests of the Montreal Cognitive Assessment in minor stroke and transient ischemic attack. Dement Geriatr Cogn Disord. 2013; 36 (3–4): 154–62.
  19. Compston A. Aids to the investigation of peripheral nerve injuries. Medical Research Council: Nerve Injuries Research Committee. His Majesty’s Stationery Office: 1942; pp. 48 (iii) and 74 figures and 7 diagrams; with aids to the examination of the peripheral nervous system. By Michael O’Brien for the Guarantors of Brain. Saunders Elsevier, 2010; pp. 64.
  20. Oldfield RC. The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia. 1971 Mar; 9 (1): 97–113.
  21. Bohannon RW, Smith MB. Interrater reliability of a modified Ashworth scale of muscle spasticity. Phys Ther. 1987 Feb; 67 (2): 206–7.
  22. Bobrov PD, Korshakov AV, Roshchin VYu, Frolov AA. Bayesian approach to the implementation of the brain-computer interface based on the representation of movements. Journal of Higher Nervous Activities. 2012; 62 (1): 89–99.
  23. Jorgensen HS, Nakayama H, Raaschou HO, Olsen TS. Recovery of walking function in stroke patients: the Copenhagen Stroke Study. Archives of Physical Medicine and Rehabilitation. 1995. 76 (1): 27–32.
  24. Stroke in adults: central paresis of the upper limb. Clinical recommendations ICD10: I60/I61/I62/I63/I64/I69.
  25. Sanford J, Moreland J, Swanson LR, Stratford PW, Gowland C. Reliability of the Fugl–Meyer assessment for testing motor performance in patients following stroke. Phys Ther. 1993 Jul; 73 (7): 447–54.
  26. Doussoulin SA, Rivas SR, Campos SV. Validation of «Action Research Arm Test» (ARAT) in Chilean patients with a paretic upper limb after a stroke. Rev Med Chil. 2012 Jan; 140 (1): 59– 65. Spanish.
  27. Bogolyubov VM. Medicinskaja reabilitacija. M.: BINOM, 2010; s. 21.
  28. Wolpaw JR, McFarland DJ. Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. Proc Natl Acad Sci USA. 2004 (101): 17849–54.
  29. Vidaurre C, Blankertz B. Towards a cure for BCI illiteracy. Brain Topogr. 2010; (23): 194–8.
  30. Ahn M, Chan S. Performance variation in motor imagery brain – computer interface: A brief review. J Neurosci Methods. 2015; (243): 103–10.