Corticospinal and Clinical Effects of Muscle Tendon Vibration in Neurologically Impaired Individuals. A Scoping Review
Bibliographic record
Abstract
This review verified the extent, variety, quality and main findings of studies that have tested the neurophysiological and clinical effects of muscle tendon vibration (VIB) in individuals with sensorimotor impairments. The search was conducted on PubMed, CINAHL, and SportDiscuss up to April 2024. Studies were selected if they included humans with neurological impairments, applied VIB and used at least one measure of corticospinal excitability using transcranial magnetic stimulation (TMS). Two investigators assessed the studies' quality using critical appraisal checklists and extracted relevant data. The 10 articles included were diverse in populations and methods, generally rated as 'average' to 'good' quality. All studies reported an increased corticospinal excitability in the vibrated muscle, but the effects of VIB on non-vibrated muscles remain unclear. Positive clinical changes in response to VIB were reported in a few studies, such as a decreased spasticity and improved sensorimotor function. These changes were sometimes correlated with corticospinal effects, suggesting a link between VIB-induced plasticity and clinical improvements. Despite the limited and heterogeneous literature, this review supports the facilitatory influence of VIB on motor outputs controlling vibrated muscles, even with altered sensorimotor functions. It highlights knowledge gaps and suggests future research directions on VIB mechanisms and clinical implications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".