Electrical cutaneous stimulation of the foot sole does not enhance rate of torque development during maximal effort isometric plantarflexion in females
Bibliographic record
Abstract
Rate of torque development (RTD) measures how rapidly one can generate torque and is crucial for balance and athletic performance. Fast RTD depends on the rapid recruitment of high threshold motor units (MUs). Cutaneous electrical stimulation has been shown to alter MU excitability, favoring high threshold MUs via reduced recruitment thresholds. A strong coupling exists between foot sole cutaneous mechanoreceptors and motor neurons of lower-limb muscles, yet it remains unknown if cutaneous input can impact RTD via modulation of MU excitability. This study aimed to investigate whether electrical stimulation across the heel could alter plantarflexion RTD. 11 young and healthy females underwent eight sets of five explosive isometric plantarflexion contractions on a dynamometer while sitting with hip, knee and ankle angles of 80°, 110°, and 90°, respectively. All participants achieved > 95 % voluntary activation of their plantar flexors. Four sets of contractions were performed with heel cutaneous electrical stimulation (1.0 ms pulses delivered at 300 Hz, at 2 × perceptual threshold) and four sets with no stimulation. Instantaneous RTD values were analyzed in 25 ms epochs from onset to 250 ms. No significant differences were observed between stimulation conditions within each epoch, thus our results suggest that electrical cutaneous stimulation does not alter RTD in this population.
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 | 0.000 | 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) | 0.003 | 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".