Muscular Activity of Lower Extremity Muscles Running on Treadmill Compared with Different Overground Surfaces
Bibliographic record
Abstract
The objective of this study is to compare the muscular activity of lower extremity muscles while running on treadmill and on overground surfaces. A total of 13 experienced heel-to-toe runners participated in the study. Electromyographic (EMG) data of four lower extremity muscles, including rectus femoris, tibialis anterior, biceps femoris, and gastrocnemius, were collected using the Noraxon EMG system while running on a treadmill and on overground surfaces at a running speed of 3.8 m/s. The obtained data were then analyzed. In this study, throughout the stance phase, the EMG values in the rectus femoris (P<0.01) and the biceps femoris (P<0.05) were higher while running on overground surfaces than those on a treadmill. The EMG values in the rectus femoris (P<0.05) and the biceps femoris (P<0.05) were also higher on concrete than those on grass in the stance phase. Results showed that the muscle activity was significantly different in treadmill running than in overground running. The difference in muscle activity while running on different overground surfaces was also found in this study. Kinematic adjustment of the lower extremity may explain the EMG difference while running on different surfaces.
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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 | 0.000 |
| 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) | 0.001 | 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".