Exercises to Activate the Deeper Abdominal Wall Muscles
Bibliographic record
Abstract
The abdominal wall is a prime target for therapeutic exercises aimed to prevent and rehabilitate low back pain and to enhance performance training. This study examined the "Lewit," a corrective exercise prescribed for several purposes, which is performed lying supine in a crook-lying position and involves forceful breathing. Muscle activation and lumbar posture were compared with bracing the abdominal wall (stiffening) with robust effort and "hollowing" (attempting to draw in the wall toward the naval) with robust effort. Eight healthy male volunteers with 6 channels of electromyography were collected by means of surface electrode pairs of the rectus abdominis, external oblique, and internal oblique (IO) together with lumbar motion. The Lewit exercise caused higher muscle activity in the deeper abdominal wall muscles, in particular the IO and by default the transverse abdominis were activated at 54% maximum voluntary contractions (MVCs) on average and 84% MVC peak with no change in spine posture to maintain the elastic equilibrium of the lumbar spine. The Lewit is a deep oblique muscle activation exercise, and the activation levels are of a sufficient magnitude for training muscle engrams. This information will assist strength and conditioning coaches with program design decisions where this corrective abdominal exercise may be considered for clients who elevate the ribcage during strength exertions, or for clients targeting the deep obliques.
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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) | 0.002 | 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".