Eccentric Cycling Is an Alternative to Nordic Hamstring Exercise to Increase the Neuromuscular Function of Knee Flexors in Untrained Men
Bibliographic record
Abstract
ABSTRACT: Valdes, O, Inzulza, S, Collao, N, Garcia-Vicencio, S, Tufano, JJ, Earp, J, Venegas, M, and Peñailillo, L. Eccentric cycling is an alternative to Nordic hamstring exercise to increase the neuromuscular function of knee flexors in untrained men. J Strength Cond Res 37(11): 2158-2166, 2023-Nordic hamstring exercise (NHE) has been proposed to reduce knee flexor (KF) injuries. However, submaximal alternatives to NHE are necessary for the clinical or weaker population. The aim of this study was to compare the effects of Nordic hamstring training (NHT) and eccentric cycling (ECC) training on the neuromuscular function of the KF. Twenty healthy men (27.7 ± 3.5 years) were randomly assigned into 2 groups that performed 10 training sessions (2-3 sessions·week-1) of either NHT (n = 10) or ECC (n = 10). Maximal voluntary isometric contraction of the KF and knee extensor (KE) muscles (MVICKF and MVICKE) was measured, and the hamstring/quadriceps strength (H/Q) ratio was calculated. Furthermore, changes in NHE maximum reaction force (NHE-MRFKF), NHE break-point angle (NHE-BPA), and muscle activity of the semitendinosus (STEMG) and biceps femoris (BFEMG) during the NHE after the interventions were compared. Although no group × time effects were observed (p = 0.09-0.70), but time effects were found for all variables. Pairwise comparisons revealed that MVICKF (+16.9%; p = 0.02), H/Q ratio (+11.8%; p = 0.01), NHE-MRFKF (+19.8%; p = 0.005), and NHE-BPA (+30.8%; p = 0.001) increased after ECC, whereas NHE-MRFKF (+9.7%; p = 0.003), NHE-BPA (+35.5%; p = 0.0002), and STEMG (+33.7%; p = 0.02) increased after NHT. A group × time effect was observed (p = 0.003) in BFEMG, revealing an increase only after ECC (+41.1%; p < 0.0001). Similar neuromuscular adaptations were found after both training modalities. Therefore, ECC provides similar adaptations as NHT and may serve as an alternative form of KF training for those unable to perform NHE.
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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 | 0.000 |
| 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) | 0.001 | 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".