The Biomechanical Demands on the Hip During Progressive Stepping Tasks
Bibliographic record
Abstract
Hatfield, GL, Charlton, JM, Cochrane, CK, Hammond, CA, Napier, C, Takacs, J, Krowchuk, NM, and Hunt, MA. The biomechanical demands on the hip during progressive stepping tasks. J Strength Cond Res 31(12): 3444-3453, 2017-Functional hip strengthening exercises are important components of lower extremity (LE) rehabilitation and include single-leg squats (SLS), step-downs (SD), and step-ups (SU). The biomechanical demand of these tasks is unclear. This repeated-measures study determined hip biomechanical demands in a healthy population. Twenty individuals (10 men, 26.6 ± 5.1 years, 22.1 ± 2.3 kg·m) participated. Three-dimensional motion, ground reaction force data, and surface electromyograms (EMG) were recorded during 4 randomly ordered tasks. Outcomes included frontal and sagittal plane hip moment impulses and muscle activity for each task. Repeated measures analysis of variance models (alpha = 0.05) determined between-task differences. Step-down and SLS were most biomechanically demanding, with significantly higher hip flexion and adduction moment impulses, and gluteus medius (GM) and quadriceps activity compared with half step-down (HSD) and SU. No significant difference was found between SD and SLS, indicating minimal difference in demand between the 2 tasks, likely due to kinematic similarities in performance; there were no significant differences in knee or hip sagittal plane angle excursion, or peak pelvic obliquity angle between the 2 tasks. Step-up was least demanding, with the lowest hip flexion and adduction moment impulses and GM, quadriceps, and hamstrings activity. Step-up was least demanding on the hip and would be a good starting task for hip strengthening protocols. Step-down and SLS were most demanding, requiring higher hip moments and muscle activity. These results provide evidence, which may be used in planning of progressive rehabilitation programs for patients with LE pathologies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".