Effects of a Curved Heel Shape in a Running Shoe on Biomechanical Variables and Comfort
Bibliographic record
Abstract
(1) Background: The purpose of this study was to investigate the effects of a rounded heel shoe (RHS) and rounded lateral heel shoe (RLHS) on impact and lower extremity stability as well as their relationships with comfort during running. (2) Methods: Twenty healthy male adults participated in the study. The data were collected using eight infrared cameras while participants were running at a speed of 2.7 m/s in three shoe conditions on an instrumented treadmill. (3) Results: The peak vertical ground reaction force (PVGRF) was statistically smaller for the RHS and RLHS compared with the normal shoes (NS) (p < 0.05). The range of motion of inversion–eversion at the ankle joint was statistically smaller for the RLHS compared with the NS and RHS (p < 0.05). Increased dorsiflexion of the ankle joint at heel contact was negatively related to the comfort of a running shoe, and increased dorsi-plantarflexion ROM was positively related to comfort. (4) Conclusions: Based on these results, a curved heel shape of a running shoe may provide a positive influence on the biomechanical function and the comfort of running shoes. Future study, including measurements of lower extremity muscle activations and long-term comfort, would be beneficial to help validate current findings and develop further applications.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".