How athletes’ biomechanical running characteristics effect running economy during the use of running shoes with and without carbon inserts
Bibliographic record
Abstract
To maximise running economy (RE), shoe manufacturers placed carbon plates within the midsole of shoes. Shoe technology research is limited on understanding the variability of individual responses to carbon-plated shoes and how these responses vary across running velocities. Little research on same shoe characteristics with and without a stiff element has been completed. This study aimed to investigate how running shoes with carbon versus without a carbon composite stiff element alter individual running biomechanics and the metabolic cost of running. Ethical approval was gained from Cardiff Metropolitan University Ethics Committee. Ten male athletes (69 ± 9 kg; 174 ± 4 cm; 28 ± 9 years) completed two submaximal incremental treadmill runs. One test was completed in a shoe without carbon (C1), the other test was completed in carbon shoes (C2), the order of testing for each shoe were randomised. Running velocity started at 9 km/h and increased by 1 km/h every four mins, blood lactate samples were taken after every stage. Once 4 mmol·L−1 (OBLA; the second lactate turn point) had been reached one more stage was completed. Gas exchange was analysed throughout the whole test. The first 15 s of the final 2 minutes of each stage was recorded using Theia3D markerless motion capture software (Theia3Dv2022.1.0.2309, Theia Markerless, Inc., Kingston, ON, Canada). Data were analysed in 4 stages, the initial stage, pre-OBLA, OBLA and post-OBLA. Physiology data were averaged over the final two mins of each stage. Discrete joint angles were taken from each stage, and an average of the 15 s recording was taken for spatiotemporal measure. Data were analysed using a four-way repeat measures ANOVA, to show individual differences. Non-parametric data were analysed using Wilcoxon signed-rank test. Hedges g calculations were completed to calculate effect size (ES). Results showed significant increase in flight time (FT; P = 0.04, ES = 0.20) in the pre-OBLA stage when using C2. Metatarsophalangeal joint (MTP) dorsiflexion showed significant increase during the initial stage in C2 (P = 0.05, ES = 0.8), and ankle dorsiflexion had significant increase in the post-OBLA stage in C2 (P = 0.03, ES = 0.2). The were no significant differences present in the physiology data. Across the physiological, spatiotemporal and kinematics, high dispersions around the mean were exhibited. Findings suggest that to improve RE, mechanical and spatiotemporal changes need to be present when using C2. Further findings show carbon shoes elicit highly individual responses to both RE and mechanics of running.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".