Multimodal Stimulation in Impaired Gait and Balance Correction in Post-Stroke Patients
Bibliographic record
Abstract
Aim: To assess the effect of multimodal virtual reality stimulation on gait and balance restoration in patients in acute and early recovery ischemic stroke. Design: Comparative randomised clinical study. Materials and methods. This study enrolled 67 patients with primary ischemic stroke which occurred during past 6 months, complicated with hemiparesis or lower limb monoparesis. Patients included 47 men and 20 women aged 44 to 75 years old. Patients were divided into two groups: in the study group (n = 36), the primary rehabilitation was supplemented with multimodal stimulation exercises on a training virtual reality set; controls (n = 31) had only primary therapy. Rehabilitation efficiency was assessed using the Montreal Cognitive Assessment, Hospital Anxiety and Depression Scale, National Institutes of Health Stroke Scale (NIHSS), Medical Research Council Scale (MRCS), Tinetti Test, Rivermead Mobility Index. Results. In the study group, a course of rehabilitation resulted in marked improvement in motor functions and functional independence. NIHSS symptoms intensity decreased from 5.5 [4.0; 7.0] to 4.0 [3.0; 5.0] points in the study group and from 6.0 [5.0; 7.0] to 5.0 [4.5; 6.0] points in the control group (p = 0.019). Rivermead Mobility Index increased from 7.0 [6.0; 10.0] to 10.0 [8.0; 12.0] points in the study group and from 7.0 [5.0; 7.5] to 8.0 [6.5; 10.5] points in the control group (p = 0.049). When multimodal stimulation was added, also a more prominent increase in the MRCS muscle strength of the lower limb was observed: an increase was 0.7 [0.3; 0.9] points in the study group and 0.4 [0.2; 0.7] points in controls (p = 0.046). Conclusion. Multimodal stimulation is an efficient adjuvant approach to rehabilitation of patients shortly after an ischemic stroke. Keywords: virtual reality, medical rehabilitation, neurorehabilitation, ischemic stroke, pneumatic stimulation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".