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The Impact of Mental Fatigue on Force and Motor Unit Firing Variability in Young Adults

2019· article· en· W2955171329 on OpenAlexaff
Katie Kowalski, Anita Christie

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2019
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsWestern University
Fundersnot available
KeywordsMental fatigueIsometric exercisePsychomotor vigilance taskPhysical medicine and rehabilitationPsychomotor learningPsychologyAudiologyVigilance (psychology)Physical therapyMedicineCognitionPsychiatryClinical psychologySleep deprivationCognitive psychology

Abstract

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Mental fatigue leads to declines in performance of tasks such as cycling time trial performance and skill-based outcomes such as soccer shot accuracy. The neuromuscular mechanisms leading to these declines are not well understood. Although force variability has been shown to increase under dual-task conditions, it is not known if these results extend to conditions of mental fatigue. PURPOSE: The purpose of this study was to assess the impact of mental fatigue on variability in motor output in healthy, young individuals. Specifically, we sought to determine if a task that induces mental fatigue has effects on force and motor unit firing variability. METHODS: Nineteen participants (10 female, 9 male) performed 10-s isometric contractions at 20 and 50% maximum voluntary contraction (MVC) before, during, and after completing 20 min of the psychomotor vigilance task (PVT). The PVT is a sustained attention task that induces mental fatigue, as indicated by increases in reaction time (RT) to visual stimuli. Force and indwelling motor unit (MU) firings were measured prior to and immediately following performance of the PVT (single task), and within the first and final minutes of PVT performance (dual task). Subjective ratings of fatigue were also obtained using a 10-point Likert scale before and after the PVT. RESULTS: Reaction time increased by 14% from the beginning of the PVT (276.14 ± 31.54 ms) to the end (314.15 ± 37.74 ms, p<0.001). Subjects also subjectively reported greater levels of fatigue following the PVT (4.95 ± 1.84) compared to before (3.00 ± 1.20, p<0.001), indicating successful induction of mental fatigue. For the coefficient of variation (CV) of force there was no significant main effect of time (p=0.14) or contraction intensity (p=0.33), and no significant interaction (p=0.51). For the CV of the MU interspike interval there was a main effect of contraction intensity with a greater CV of the interspike interval during the 50% MVC (19.51 ± 3.84%) than the 20% MVC (14.87 ± 3.59%, p<0.001) contractions. However, there was no significant main effect of time (p=0.83) and no significant interaction (p=0.23). CONCLUSION: Inducing mental fatigue did not lead to changes in the variability of force production or motor unit firing during isometric contractions at 20 and 50% MVC as a single-task or during a concurrent cognitive task.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.010
GPT teacher head0.259
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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