MétaCan
Menu
Back to cohort

Energy Storage And Return From Footwear And Biological Structures While Running

2022· article· en· W4294841909 on OpenAlexaff
Emily Matijevich, Gilbert N. Lam, Fan Yang, Eric C. Honert, Benno M. Nigg

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2022
Typearticle
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsAnkleWork (physics)Ground reaction forceMathematicsKinematicsFoot (prosody)BiomechanicsInverse dynamicsOrthodonticsPhysical medicine and rehabilitationEngineeringMedicineSurgeryMechanical engineeringPhysicsAnatomy

Abstract

fetched live from OpenAlex

Energy Storage and Return from Footwear and Biological Structures While Running Extraordinary performances have been achieved by runners using advanced footwear. Previous research has found energetically favorable changes in biological joint kinetics while running in such footwear. However, there is limited research that also quantifies footwear kinetics during running. PURPOSE: To compare energy storage and return from footwear and biological structures while running in shoes of varying constructions. METHODS: Fifteen male runners ran in a motion analysis lab while kinematics and ground reaction forces were collected. Three footwear conditions of varying construction were evaluated (Shoe A, B, C). Shoe A had the greatest midsole compliance and longitudinal bending stiffness. Hip, knee, and ankle joint powers were computed using inverse dynamics to evaluate the mechanical work at biological joints. Distal rearfoot power was computed to evaluate the net mechanical work from the biological foot and footwear structures (Foot + Footwear). Kruskal-Wallis and Wilcoxon signed-rank tests were used for between footwear comparisons. RESULTS: Negative Foot + Footwear work (energy storage) was significantly greater in Shoe A (0.29 ± 0.07 J/kg) than Shoe B (0.21 ± 0.06 J/kg, p < 0.001), but not Shoe C (0.26 ± 0.08 J/kg, p = 0.055). Positive Foot + Footwear work (energy return) was significantly greater in Shoe A (0.30 ± 0.09 J/kg) than both other shoes (Shoe B: 0.19 ± 0.08 J/kg, p = 0.001; Shoe C: 0.15 ± 0.07 J/kg, p < 0.001). Positive ankle work was significantly lower in Shoe A (0.61 ± 0.08 J/kg) than both other shoes (Shoe B: 0.68 ± 0.09 J/kg, p < 0.001; Shoe C: 0.67 ± 0.06 J/kg, p = 0.003). Hip and knee work were not significantly different between shoe conditions (p > 0.05). CONCLUSION: Understanding how advanced footwear stores and returns energy during running may explain the reduction in work required by biological structures and resulting increased performance. Supported by Li-Ning.

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)0.000
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.018
GPT teacher head0.226
Teacher spread0.209 · 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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueMedicine & Science in Sports & ExerciseSame topicLower Extremity Biomechanics and PathologiesFrench-language works237,207