Contributions of Lower-Limb Muscle Power in Gait of People Without Impairments
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Although gait asymmetry in rehabilitation has been documented, little is known about propulsion and control tasks performed by each limb and how these tasks are managed between the lower limbs. The purpose of this study was to test the hypothesis that the leading limb contributes mainly to forward progression, whereas the trailing limb provides control and propels the lower limb to a lesser extent. SUBJECTS: Nineteen men with an average age of 26.2 years (SD=3.2, range=21-34) and no history of orthopedic ailments participated in the study. METHODS: Muscle power was determined using an 8-camera high-speed video system synchronized with 2 force plates. The principal-component analysis method was applied to reduce and classify 52 gait variables for each limb, and Pearson correlations were used to determine the interactions within the data sets for each limb. RESULTS: Gait propulsion was initiated by the hip of the leading limb shortly after heel-strike and was maintained throughout the stance phase. Control was the main task of the trailing limb, as evidenced by the power absorption bursts at the hip and knee. CONCLUSION AND DISCUSSION: Within-limb interaction further emphasized the functional relationship between forward progression and control tasks and highlighted the importance of frontal- and transverse-plane actions during gait.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 | 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) | 0.000 | 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".