Effects of rear-foot instability devices on lower-limb muscle activation during the Bulgarian split squat in male football players
Bibliographic record
Abstract
Unilateral resistance exercises such as the Bulgarian Split Squat (BSS) are commonly used to develop lower-limb strength, postural control, and neuromuscular coordination, depending on training variables (e.g., load and intensity). Although instability training increases muscle activation, few studies have examined the effect of rearfoot instability on neuromuscular responses during BSS. This randomized crossover study investigated the acute effects of three rear-foot instability devices on muscle activation during the ascent and descent phases of the BSS in 23 trained male football players. Participants performed body-weight BSS under four conditions: stable platform, BOSU ball, Swiss ball (Swiss), and TRX suspension. Surface electromyography (sEMG) recorded activation of the rectus femoris (RF), vastus lateralis (VL), vastus medialis (VM), biceps femoris (BF), semitendinosus (ST), and gluteus maximus (GM). Two‑way repeated‑measures ANOVA showed significantly greater activation during ascent for BF (p < 0.001), ST (p = 0.006), VL (p < 0.001), VM (p < 0.001), and GM (p < 0.001). Quadriceps activation during descent was highest on the Swiss: RF (Swiss vs. stable: p = 0.002; Swiss vs. BOSU: p < 0.001; Swiss vs. TRX: p = 0.006), VL (Swiss vs. stable: p = 0.017; Swiss vs. BOSU: p = 0.001), and VM (Swiss vs. stable: p = 0.024; Swiss vs. BOSU: p = 0.046). TRX increased ST activation during the ascent compared to the Swiss (p = 0.034), and the BOSU showed higher ST activation than the Swiss during the descent (p = 0.004). Surface significantly affected activation (ST: p = 0.018; RF: p < 0.001; VL: p < 0.001; VM: p = 0.013; GM: p = 0.042), and there was a significant surface × phase interaction for GM (p = 0.041). The findings highlight rearfoot instability as an effective programming variable to selectively enhance muscle activation without external loading, supporting its application in strength and rehabilitation programs.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".