Effects of drop height and surface instability on neuromuscular activation during drop jumps
Bibliographic record
Abstract
The purpose of this study was to examine whether drop height-induced changes in leg muscle activity during drop jumps (DJ) are additionally modulated by surface condition. Twenty-four healthy participants (23.7 ± 1.8 years) performed DJs on a force plate on stable, unstable, and highly unstable surfaces using different drop heights (i.e., 20 cm, 40 cm, 60 cm). Electromyographic (EMG) activity of soleus (SOL), gastrocnemius (GM), tibialis anterior (TA) muscles and coactivation of TA/SOL and TA/GM were analyzed for time intervals 100 ms prior to ground contact (preactivation) and 30-60 ms after ground contact [short latency response (SLR)]. Increasing drop heights resulted in progressively increased SOL and GM activity during preactivation and SLR (P < 0.01; 1.01 ≤ d ≤ 5.34) while TA/SOL coactivation decreased (P < 0.05; 0.51 ≤ d ≤ 3.01). Increasing surface instability produced decreased activities during preactivation (GM) and SLR (GM, SOL) (P < 0.05; 1.36 ≤ d ≤ 4.30). Coactivation increased during SLR (P < 0.05; 1.50 ≤ d ≤ 2.58). A significant drop height × surface interaction was observed for SOL during SLR. Lower SOL activity was found on unstable compared to stable surfaces for drop heights ≥40 cm (P < 0.05; 1.25 ≤ d ≤ 2.12). Findings revealed that instability-related changes in activity of selected leg muscles are minimally affected by drop height.
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 | 0.001 | 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 | 0.001 |
| 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".