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Metatarsophalangeal Joint Movement in Olympic Sprinters

2002· article· en· W2073171594 on OpenAlexaff
Darren J. Stefanyshyn, Jason R. Krell, Dann L. Chow

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2002
Typearticle
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsForefootJoint (building)KinematicsTrack and field athleticsPhysical medicine and rehabilitationAthletesMathematicsEnergy (signal processing)Movement (music)SimulationPhysical therapyComputer scienceMedicineStatisticsAcousticsEngineeringPhysicsStructural engineering

Abstract

fetched live from OpenAlex

Introduction: In sprinting, the metatarsophalangeal (MP) joint flexes as an athlete rolls onto the forefoot but does not extend until after take-off (Stefanyshyn and Nigg, 1997). As a result, energy absorbed at the MP joints is substantial, however, the energy produced in the second half of the stance-phase at this joint is minimal. Since the absorbed energy is dissipated and not stored for later re-use, one could speculate that a reduction of such energy absorption may lead to an increase in performance. That is, if all the energy can be directed toward the movement task and not wasted on auxiliary tasks, performance may be improved. The amount of energy absorbed at the MP joint is a function of both the moment generated about the joint as well as the maximal joint movement. Thus, if either of these variables is decreased, the amount of energy absorbed at the MP joint should be decreased, potentially resulting in an increase in performance. Therefore, the purpose of this investigation was to determine the relationship between metatarsophalangeal joint movement and sprinting performance during an elite competition. Methods: Kinematic data were recorded during the heats, semi-final and final races of the mens and womens 100m sprints at the 2000 Sydney Olympic Games. In total, measurements were performed on 70 athletes (50 males and 20 females). The data were collected at approximately the 60m mark of the race using two high-speed digital cameras (JVC 9800) sampling at 120 Hz. Both cameras were set with the fields of view focussed on a 1.5m section of track. The first camera was focused between lanes 3 and 4 while the second camera was focused on lanes 6 and 7. The video data were hand digitised and the MP joint angle was defined as the angle between the plantar surface of the forefoot and rearfoot of the shoe. A correlational analysis was performed to quantify the relationship between MP joint bending and sprint performance. Results: The average peak extension at the MP joint was similar between males and females, 36.5° and 37.7° respectively. Very low and non-significant correlations were found between peak extension at the MP joint and 100m sprint time for both male (r = 0.351, p = 0.994) and female (r = 0.180, p = 0.777) athletes. Discussion: On average, during competition the MP joint underwent a large range of movement, which corresponded well with values previously reported from in lab testing (Stefanyshyn and Nigg, 1997). Similar to the in lab testing, the athletes only flexed their MP joint minimally at take-off. It has been shown that increasing the bending stiffness of a shoe and decreasing the extension of the MP joint leads to improvements in vertical jump performance (Stefanyshyn and Nigg, 2000). However, there was no relation between the maximal extension of the MP joint and sprinting performance in this study. Thus, it may be that the concept of reducing the energy lost does not apply to sprinting performance. However, recent pilot studies with increased bending stiffness in sprint shoes have shown positive improvements in sprinting performance. Alternatively, it is possible that kinematics alone may not be sufficient to predict performance measures in sprinting. Further investigation into the kinetics and energy absorption at the MP joint is necessary to fully understand the role of the MP joint in sprinting performance. Acknowledgements: Funding for this study was provided from a grant by the International Olympic Committee, Medical Commission.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.000

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 head0.025
GPT teacher head0.235
Teacher spread0.210 · 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 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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Citations2
Published2002
Admission routes1
Has abstractyes

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