Impact Attenuation And Kinetic Characteristics Of Cross Training Shoes In Landing And Jumping Activities
Bibliographic record
Abstract
Very few footwear studies have examined athletic shoes designed for sports other than running. Cross-training footwear is designed to meet needs of a variety of sports and sport training environments with key features that include generating power for performance and attenuating impacts for injury prevention. PURPOSE To examine kinetic characteristics of impact attenuation in landing and power generation in jumping of four different cross training shoes. METHODS Ten healthy male recreational athletes (age:21.5±2.5 yrs) performed five step-off landing trials and five maximum vertical jumping trials in each of four cross-training shoes (from three leading footwear manufacturers). Right sagittal kinematic data (120 Hz), ground reaction forces (GRF,1200 Hz), and forehead and distal tibia accelerations (ACC, landing only) were measured simultaneously. The landing height was determined individually based upon potential energy of a “mid-size” person (80 kg) landing from a 0.6 m height. Material tests were performed on selected sizes of each shoe model.A one-way repeated measures ANOVA and post-hoc comparisons (p < 0.05) were performed on selected variables. RESULTS The results from the landing trials showed that Shoes A (23 N/kg) and B (26 N/kg) had significantly smaller forefoot peak GRF than Shoes C (29 N/kg) and D 28 N/kg). Shoes A (2274 N/kg/s) and B (2630 N/kg/s) also showed lower loading rate associated with the forefoot contact than Shoes C (3316 N/kg/s) and D (3336 N/kg/s). No significant changes were seen in ACC data. The jumping GRF results normalized to the individual jump height indicated significantly greater peak power for Shoes C (50 Wm/kg) and D (51 Wm/kg) compared to A (48 Wm/kg). Maximum peak GRF for Shoe D (16 Nm/kg) was greater than Shoe A (15 Nm/kg). In addition, kinematic data showed not clear trends in landing or jumping trials. The material testing indicated that Shoes A and B had the smallest forefoot stiffness values (9.2 and 9.6 N/mm) compared to Shoe C and D (18.0 and 12.7 N/mm) obtained in a fixibility test. Energy loss for Shoes A and B (41%and 43%) were greater than Shoes C and D (33 and 35%). CONCLUSIONS The results suggested that the Shoes A and B showed slightly better forefoot impact attenuation properties. Shoe D and C demonstrated better jumping performance than Shoe A. But better performance may come at a price of decreased cushioning.
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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 | 0.001 | 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) | 0.001 | 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".