ORIGINAL RESEARCH

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

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
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Motor recovery of the upper limb is a priority in the neurorehabilitation of stroke patients. Advances in the brain-computer interface (BCI) technology have significantly improved the quality of rehabilitation. The aim of this study was to explore the factors affecting the recovery of the upper limb in stroke patients undergoing BCI-based rehabilitation with the robotic hand. The study recruited 24 patients (14 men and 10 women) aged 51 to 62 years with a solitary supratentorial stroke lesion. The lesion was left-hemispheric in 11 (45.6%) patients and right-hemispheric in 13 (54.4%) patients. Time elapsed from stroke was 4.0 months (3.0; 12.0). The median MoCa score was 25.0 (23.0; 27.0). The rehabilitation course consisted of 9.5 sessions (8.0; 10.0). We established a significant moderate correlation between motor imagery performance (the MIQ-RS score) and the efficacy of patient-BCI interaction. Patients with high MIQ-RS scores (47.5 (32.0; 54.0) achieved a better control of the BCI-driven hand exoskeleton (63.0 (54.0; 67.0), R = 0.67; p < 0.05). Recovery dynamics were more pronounced in patients with high MIQ-RS scores: the median score on the Fugl-Meyer Assessment scale was 14 (8.0; 16.0) points vs 10 (6.0; 13.0) points in patients with low MIQ-RS scores. However, the difference was not significant. Thus, we established a correlation between a patient’s ability for motor imagery (MIQ-RS) and the efficacy of patient-BCI interaction. A larger patient sample might be necessary to assess the effect of these factors on motor recovery dynamics.

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