Effect of Using a Suspension Training System on Muscle Activation During the Performance of a Front Plank Exercise
Bibliographic record
Abstract
The objective of the study was to examine the effect of suspension training on muscle activation during performance of variations of the plank exercise. Twenty-one participants took part. All individuals completed 2 repetitions each of 4 different plank exercises that consisted of a floor based plank, or planks with arms suspended, feet suspended, or feet and arms suspended using a TRX Suspension System. During plank performance, muscle activation was recorded from rectus abdominis, external oblique, rectus femoris, and serratus anterior (SA) muscles using electromyography. All planks were performed for a total of 3 seconds. Resulting muscle activation data were amplitude normalized, and root mean square activation was then determined over the full 3 second duration of the exercise. A significant main effect of plank type was found for all muscles. Post hoc analysis and effect size examination indicated that abdominal muscle activation was higher in all suspended conditions compared to the floor based plank. The highest level of abdominal muscle activation occurred in the arms suspended and arms/feet suspended conditions, which did not differ from one another. Rectus femoris activation was greatest during the arms suspended condition, whereas SA activity peaked during normal and feet suspended planks. These results indicate that suspension training as performed in this study seems to be an effective means of increasing muscle activation during the plank exercise. Contrary to expectations, the additional instability created by suspending both the arms and feet did not result in any additional abdominal muscle activation. These findings have implications in prescription and progression of core muscle training programs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.002 | 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".