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Record W7037300461

Downhill Dilemma: Analyzing Joint Force on Variable Speed and Gradient

2024· article· en· W7037300461 on OpenAlexaboutno aff

Bibliographic record

VenueTopSCHOLAR (Western Kentucky University) · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBryophyte Studies and Records
Canadian institutionsnot available
Fundersnot available
KeywordsAnkleKinematicsJoint (building)Repeated measures designTreadmillKnee Joint
DOInot available

Abstract

fetched live from OpenAlex

Movement on declined slopes poses unique mechanical stresses when compared to level surfaces. Both downhill (DH) running and walking have seen large amounts of load force absorption on the knee (French 2018; Abe et.al., 2011) with some forces possibly being distributed to the hip and ankle joints. Though research is limited about lower extremity joint kinematics across all three joints. PURPOSE: To better understand the joint forces placed on the hip, knee, and ankle with variable speed and decline gradient METHODS: Nine participants (5 male and 4 female; Age = 24.09 ± 2.81 yrs; Weight = 75.12 ± 13.67 kg; Height = 1724.89 ± 68.58 mm) were asked to walk and run, in five-minute intervals on an instrumented treadmill (Bertec, Inc. Columbus, OH) at self-selected velocities. Conditions were determined in randomized order (C1 = walk flat, C2 = run flat, C3 = DH Walk, C4 = DH Run) and intervals were performed at a flat plane as well as a decline of -9°. Data collection used 8 video cameras recording at 50 hZ. (Theia, Inc., Kingston, Ontario, Canada) and analyzed using Visual 3D (C-Motion, Inc.,Germantown, MD). Data was further analyzed (using C2 vs C4 and C1 vs C3) using a repeated measure ANOVA with Tukey-b post-hoc test (family-wise α = 0.05). RESULTS: Analysis saw significant (p < 0.05) joint forces across all conditions. Highest hip and ankle forces reported in C2 (hip = -20.99±2.06 N/kg; ankle = -20.20±1.86 N/kg). Highest knee forces reported in C4 (knee = -22.07±3.0 N/kg). Highest velocity reported in C2 (2.56±0.44 m/s). CONCLUSION: The current study found C2 imposed higher forces on the ankle and hip compared to other conditions. C4 presented higher forces in the knee. Participants could self-select speeds for each condition, resulting in C2 having the fastest running speed. Evidence has suggested that higher speeds tend to increase joint forces (Schache et al., 2011) which may contribute to the findings of the current study, however, may have significance in a real-world setting. Higher speeds and joint force loading can be an indicator of lower extremity injury (French, 2018). Therefore, future research should look into DH/Flat Running and its implications on injury in an applied setting.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.875
Threshold uncertainty score0.281

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.187
Teacher spread0.171 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

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