Transcutaneous spinal cord stimulation improves postural stability in individuals with multiple sclerosis
Bibliographic record
Abstract
BACKGROUND: Widespread demyelination in the central nervous system can lead to progressive sensorimotor impairments following multiple sclerosis, with compromised postural stability during standing being a common consequence. As such, clinical strategies are needed to improve postural stability following multiple sclerosis. The objective of this study was therefore to investigate the effect of non-invasive transcutaneous spinal stimulation on postural stability during upright standing in individuals with multiple sclerosis. METHODS: Center of pressure displacement and electromyograms from the soleus and tibialis anterior were recorded in seven individuals with multiple sclerosis during standing without and with transcutaneous spinal stimulation. Center of pressure and muscle activity measures were calculated and compared between no stimulation and transcutaneous spinal stimulation conditions. The relationship between the center of pressure displacement and electromyograms was quantified using cross-correlation analysis. RESULTS: For transcutaneous spinal stimulation, postural stability was significantly improved during standing with eyes closed: the time- and frequency-domain measures obtained from the anterior-posterior center of pressure fluctuation decreased and increased, respectively, and the tibialis anterior activity was lower compared to no stimulation. Conversely, no differences were found between no stimulation and transcutaneous spinal stimulation when standing with eyes open. CONCLUSION: Following multiple sclerosis, transcutaneous spinal stimulation improved postural stability during standing with eyes closed, presumably by catalyzing proprioceptive function. Future work should confirm underlying mechanisms and explore the clinical value of transcutaneous spinal stimulation for individuals with multiple sclerosis.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".