Neuromuscular Fatigue Is Not Different between Constant and Variable Frequency Stimulation
Bibliographic record
Abstract
This study compared fatigue development of the triceps surae induced by two electrical stimulation protocols composed of constant and variable frequency trains (CFTs, VFTs, 450 trains, 30 Hz, 167 ms ON, 500 ms OFF and 146 ms ON, 500 ms OFF respectively). For the VFTs protocol a doublet (100 Hz) was used at the beginning of each train. The intensity used evoked 30% of a maximal voluntary contraction (MVC) and was defined using CFTs. Neuromuscular tests were performed before and after each protocol. Changes in excitation-contraction coupling were assessed by analysing the M-wave [at rest (Mmax) and during MVC (Msup)] and associated peak twitch (Pt). H-reflex [at rest (Hmax) and during MVC (Hsup)] and the motor evoked potential (MEP) during MVC were studied to assess spinal and corticospinal excitability of the soleus muscle. MVC decrease was similar between the protocols (-8%, P<0.05). Mmax, Msup and Pt decreased after both protocols (P<0.01). Hmax/Mmax was decreased (P<0.05), whereas Hsup/Msup and MEP/Msup remained unchanged after both protocols. The results indicate that CFTs and VFTs gave rise to equivalent neuromuscular fatigue. This fatigue resulted from alterations taking place at the muscular level. The finding that cortical and spinal excitability remained unchanged during MVC indicates that spinal and/or supraspinal mechanisms were activated to compensate for the loss of spinal excitability at rest.
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 | 0.001 |
| 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".