Investigating the role of task intensity on motor unit fatigue recovery
Notice bibliographique
Résumé
Background: It is unclear how the intensity as well as the underlying contributions of larger versus smaller motor units of a performed task impacts fatigue recovery. Therefore, I tested two hypotheses: that the normalized force response (NFR) at each time point would be greater following the high intensity versus low intensity task, indicating that recovery is greater following fatigue at a higher intensity of effort; and, that the NFR at each time point would be greater following the 100Hz stimulation compared to the 20Hz stimulation, indicating that longer term, low-frequency frequency fatigue had occurred. \n \nMethods: Fourteen males and fourteen females performed a high (70% of their Maximum Voluntary Force (MVF)) and low (20%MVF) intensity isometric elbow extension task, one week apart, until task failure. Recovery was then measured as the force from muscle electrical stimulation at high (100Hz) and low (20Hz) frequencies over one hour. \n \nResults: A three-factor repeated measures Analysis of Variance (ANOVA) found that significant interaction effects existed between intensity and time (F (6.0,162.8) = 12.94, p < 0.001, ηp2 = 0.32), and between frequency and time (F (8.64,233.29) = 6.92, p < 0.001, ηp2 = 0.20). Post-hoc pair wise comparisons to decompose the intensity by time interaction revealed that the NFR was initially higher (0-4 minutes) following the high intensity protocol relative to the low intensity protocol, but then declined and was lower (from 10-40 minutes) before returning to similar levels as the recovery time approached 60 minutes, with the NFR significantly different at minutes 35 and 60. In contrast, decomposing the frequency by time interaction revealed that the NFR remained higher from minutes 0-60 following high frequency stimulation compared to low frequency stimulation. \n \nConclusion: From these results, I observed that that the higher intensity task caused a greater initial recovery of NFR when compared to recovery from the same task performed at a lower intensity. However, the NFR underwent a force depression following the initial recovery, such that the NFR remained significantly lower following fatigue caused by a high intensity relative to low intensity isometric contraction for up to thirty minutes following task failure. I also observed that the recruited motor units required a higher stimulation frequency to generate forces that were closer to baseline levels at the same input voltage, independent of the intensity of task performed. This indicated that long-term low frequency mechanisms characteristic of smaller motor unit fatigue accumulation may have similarly contributed to both high and low intensity fatigue recovery profiles. Overall, these findings suggest that muscle fatigue from a sustained isometric contraction may continue to accumulate even after the fatiguing stimulus has been removed. These findings also suggest that overall recovery may be driven by the amount of fatigue accumulated in smaller motor units. Both findings should be considered when informing models that measure muscle fatigue accumulation and recovery.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».