Temporal Coactivation of Abdominal Muscles During Dynamic Stability Exercises
Bibliographic record
Abstract
The purpose of this study was to determine abdominal muscle temporal responses to a leg-loading exercise protocol and if differences exist between those able and unable to minimize lumbar-pelvic motion during this protocol. The focus was a supine bilateral leg-loading task that incorporated a slide (level 4) or no slide (level 5). Thirty-three healthy subjects (mean age 24 years) completed the task while surface electromyograms (EMG) from 5 abdominal muscle sites were recorded. Subjects were assigned to stable or unstable groups based on their ability to minimize lumbar-pelvic motion. After time and amplitude normalization, electromyography waveforms were entered into a pattern recognition procedure and scores for each principal pattern were calculated. Four principal patterns explained 90% of variance in the waveform data, with these principal patterns capturing the mean pattern, the relative amplitude change during the leg-extension phase, and subtle changes in shape throughout the exercise. Significant interactions (p < 0.05) were found for principal patterns; 1, 2, and 4 scores; and significant main (p < 0.05) effects for principal pattern 3 scores. These results illustrate temporal synchrony among the abdominal wall muscle activation during the bilateral leg-loading tasks; however, there was less variability in the activation patterns during the leg-lift and leg extension-phases for those who were able to minimize lumbar-pelvic motion compared to those who were unable to perform the task correctly. These results illustrate the need to focus on coordinated recruiting of the abdominal wall muscles in an organized manner and not simply increasing the intensity of activation for stabilization training.
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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) | 0.000 | 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".