Rehabilitation of patients with post-stroke cognitive impairment using the P300-based brain—computer interface: results of a randomized controlled trial
Bibliographic record
Abstract
Objective. To study the effects of a 10-day cognitive training using the brain—computer interface (BCI) technology at the P300 wavelength on the recovery of cognitive functions in poststroke patients. Material and methods. The study included 30 patients, aged 22-82 years, with ischemic stroke less than 3 months old and moderate cognitive impairment (<26 points on the Montreal Cognitive Assessment Scale (MoCA)). All patients underwent neuropsychological testing, assessment of the presence of depression, assessment of activity in daily life. Patients were randomized into two groups: patients of group 1 (main) underwent a 10-day course of cognitive rehabilitation in the form of daily exercises in the BCI environment at the P300 wave equipped with a headset for recording an electroencephalogram (EEG). Patients of group 2 (control) received a standard set of rehabilitation measures. Results. There was an increase in the mean score of the MoCA «Attention» domain in the main group of patients (2.3±1.24 to 5.2±1.16 points) compared with the control group (5.9±1.00 to 4.2±0.94 points, p<0.05). The results of covariance analysis with repeated measures, taking into account the factors «Visit» and «Group», the covariate «Depression» and «Number of training sessions» revealed significant effects for the MoCA domains «Naming» (p<0.05), «Attention» (p<0.05), «Abstraction» (p<0.05). By the end of the 10-day cognitive training using BCI, patients of the main group showed a significant increase in the number of entered letters (20.8±2.01 to 25.9±1.7 characters (p=0.02) compared with the control group (21.9±1.9 to 23.1±1.8, p=0.06). When comparing the number of words entered by patients after 10 days, a significant difference was found between the main and control groups (p<0.05). Conclusion. Rehabilitation of patients with post-stroke cognitive impairment using P300 BCI has a significant positive effect on the restoration of cognitive functions, primarily attention.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".