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The Effect of Fatigue on the Biomechanics of Recreational Runners with Patellofemoral Pain

2015· article· en· W2472935293 on OpenAlexaff
Christopher Napier, Gillian L. Hatfield, Jack Taunton, Michael A. Hunt

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2015
Typearticle
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicinePhysical medicine and rehabilitationBiomechanicsFascia lataMediusPhysical therapyPatellofemoral pain syndromeBicepsTreadmillMuscle fatigueRepeated measures designStress fracturesKinematicsElectromyographySurgeryMathematicsAnatomy

Abstract

fetched live from OpenAlex

Patellofemoral pain syndrome (PFPS) is one of the most common injuries experienced by recreational runners. Pain is often absent at the beginning of activity, but tends to worsen with fatigue during a run. This may be due to the effect of fatigue on the magnitude of activation of muscles responsible for controlling hip and knee biomechanics, thus altering the loading environment of the patellofemoral joint and predisposing to PFPS pathology. PURPOSE: To compare the effects of fatigue on strength and muscle activation during an exhaustive run in female runners with and without PFPS. Kinematic and spatiotemporal variables were also examined as a means to understand the strength and muscle activation differences between groups. METHODS: Five females (33.5 +/-8.8 years of age) with a history of PFPS for > 2 months and five age-matched, healthy control females (32.8 +/-7.4 years of age) ran on a treadmill at a self-selected speed to a pre-determined level of fatigue (Rating of Perceived Exertion=17). Strength of the major hip muscles was measured pre- and post-run using handheld dynamometry. Surface EMG was recorded wirelessly from the following muscles: gluteus medius, tensor fascia lata, rectus femoris, and biceps femoris. EMG as well as kinematic and spatiotemporal data were collected at 3-minute intervals until termination. Comparisons were made between the 0%, 50%, and 100% intervals of the run using separate 2-way ANOVAs, with fatigue as the repeated measure for each variable of interest and post hoc Tukey HSD tests for significant main effects. RESULTS: Hip external rotation (ER) strength was significantly decreased in the PFPS group from pre- to post-run (mean difference = 0.09 Nm/kg, p = 0.045). Females with PFPS also demonstrated increased peak activation of gluteus medius. Peak hip internal rotation (IR) (mean difference = 3.44°, p = 0.291) and adduction (mean difference = 0.84°, p = 0.294) both trended toward an increase in the PFPS group from the beginning to the end of the exhaustive run. CONCLUSIONS: Females with PFPS exhibited decreased strength of hip external rotators following an exhaustive run compared to healthy, age-matched controls, which may be a factor in the increased hip IR angle in this group. EMG analysis revealed increased activation of gluteus medius. Greater activation levels may result in earlier fatigue to hip external rotators, leading to altered hip kinematics and a predisposition to PFPS.

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)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.025
GPT teacher head0.253
Teacher spread0.227 · 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
Published2015
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