Shoe Midsole Longitudinal Bending Stiffness and Running Economy, Joint Energy, and EMG
Bibliographic record
Abstract
PURPOSE: It has been shown that mechanical energy is dissipated at the metatarsophalangeal (MTP) joint during running and jumping. Furthermore, increasing the longitudinal bending stiffness of the midsole significantly reduced the energy dissipated at the MTP joint and increased jump performance. It was hypothesized that increasing midsole longitudinal bending stiffness would also lead to improvements in running economy. This study investigated the influence of midsole longitudinal bending stiffness on running economy (performance variable) and evaluated the local effects on joint energetics and muscular activity. METHODS: Carbon fiber plates were inserted into running shoe midsoles and running economy, joint energy, and electromyographic (EMG) data were collected on 13 subjects. RESULTS: Approximately a 1% metabolic energy savings was observed when subjects ran in a stiff midsole relative to the control midsole. Subjects with a greater body mass had a greater decrease in oxygen consumption rates in the stiff midsole relative to the control midsole condition. The stiffer midsoles showed no significant differences in energy absorption at the MTP joint compared with the control shoe. Finally, no significant changes were observed in muscular activation. CONCLUSION: Increasing midsole longitudinal bending stiffness led to improvements in running economy, yet the underlying mechanisms that can be attributed to this improvement are still not fully understood.
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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) | 0.002 | 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".