Contraction fatigue, strength adaptations, and discomfort during conventional versus wide-pulse, high-frequency, neuromuscular electrical stimulation: a systematic review
Bibliographic record
Abstract
Neuromuscular electrical stimulation (NMES) can be delivered in a conventional form (CONVNMES) and using relatively wide-pulses and high-frequencies (WPHFNMES). WPHFNMES is proposed to reduce contraction fatigability and generate larger contractions with less discomfort than CONVNMES; however, there are no systematic reviews to guide the selection of NMES types. This systematic review compared the effects of CONVNMES versus WPHFNMES on contraction fatigability, strength adaptations, and perceived discomfort in clinical and non-clinical populations. Eight studies were included. When averaged across all non-clinical participants in individual short- and long-term studies, there was either no difference between CONVNMES and WPHFNMES for all outcomes or WPHFNMES produced more fatigability. In a subset of non-clinical participants (“responders”), however, WPHFNMES reduced contraction fatigability during a single session. Long-term studies found no differences between protocols for strength adaptations in non-clinical participants and those with multiple sclerosis. We concluded that WPHFNMES reduces contraction fatigability only in the short-term studies and in non-clinical responder participants and may exacerbate fatigability in non-responders. This review was registered in the prospective international registry of systematic reviews/PROSPERO (Registration Number: CRD42020153907). Novelty: WPHF NMES may reduce fatigue in some participants and exacerbate fatigue in others. There were no differences in long-term studies between WPHF and CONV NMES on strength adaptations. Future high-quality research is needed to optimize outcomes of NMES-based programs.
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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 | 0.006 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.009 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".