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Record W4413388561 · doi:10.37190/abb/209529

Alterations of landing biomechanics from an inclined treadmill running-induced fatigue protocol

2025· article· en· W4413388561 on OpenAlexaff
Hanhui Jiang, Qichang Mei, Zixiang Gao, Justin Fernandez, Yaodong Gu

Bibliographic record

VenueActa of Bioengineering and Biomechanics · 2025
Typearticle
Languageen
FieldMedicine
TopicAutomotive and Human Injury Biomechanics
Canadian institutionsCalgary Laboratory ServicesUniversity of Calgary
FundersNatural Science Foundation of NingboNingbo UniversityNational Natural Science Foundation of China
KeywordsBiomechanicsTreadmillPhysical medicine and rehabilitationMedicineAeronauticsPhysical therapyEngineeringAnatomy

Abstract

fetched live from OpenAlex

Purpose This study examines the biomechanical effects of running-induced fatigue on the kinematic and kinetic changes of the lower limb during a countermovement jump (CMJ) via analyzing variations in joint biomechanics during landing. Methods A running-induced fatigue protocol was employed to explore changes in joint angle, moments, stiffness, and loading rate during the CMJ landing pre and post -fatigue. Paired-sample t-tests assessed changes in discrete parameters of joint stiffness, loading rates, and time-varying parameters were compared with one-dimensional statistical parametric mapping. Results Fatigue significantly reduced the range of motion (ROM) during landing, with significant differences in angles, specifically the dorsi-plantar flexion of right ankle, flexion-extension of left hip, rotation of left knee, and adduction-abduction of right knee (P<0.001). The first loading rate at touchdown decreased by 10%, and the time intervals between the first and second peak and the second and third peak reduced by 40% and 80%, respectively. Joint loading increased and the sagittal joint stiffness of left hip, right knee, and right ankle exhibited significant differences post-fatigue (P<0.001). Knee joint reduced the flexion angle (P<0.001) and the load of knee joint (P<0.001) during post-fatigue, with the role compensated by hip and ankle joints to achieve balance in the lower limb kinetic chain. Conclusions These findings provide pilot evidence that running fatigue may lead to changes in lower limb joint loadings and provide a scientific foundation for fatigue prediction and injury assessment.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.338
Teacher spread0.304 · 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 teacher head, not a consensus.

Study designBench or experimental
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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

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