Influence of different control strategies on muscle activation patterns in trunk muscles
Bibliographic record
Abstract
Adequate training of the trunk muscles is essential to prevent low back pain. Although sit-ups are simple to perform, the perceived high effort is the reason why training the abdominal muscles is seldom continued over a longer period of time. It is well known that the abdominal muscles are inferior to the back muscles in terms of force, but this cannot explain the extreme difference in perceived effort between trunk flexion and extension tasks. Therefore, this study was aimed at the identification of control strategy influences on the muscular stress level. Thirty-nine subjects were investigated. The performed tasks were restricted to the sagittal plane and were implemented with simulated and realized tilt angles. Subjects were investigated in an upright position with their lower bodies fixed and their upper bodies free. Posture-controlled tasks involved graded forward and backward tilting, while force-controlled tasks involved the application of force based on a virtual tilt angle. The Surface EMG (SEMG) was taken from five trunk muscles on both sides. Control strategies seemed to have no systematic influence on the SEMG amplitudes of the back muscles. In contrast, the abdominal muscles exhibited significantly higher stress levels under posture-controlled conditions without relevantly increasing antagonistic co-activation of back muscles. The abdominal muscles' relative differences ranged from an average of 20% for the external oblique abdominal muscle to approximately 40% for the rectus abdominal muscle. The perceived high effort expended during sit-ups can now be explained by the posture-controlled contractions that are required.
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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 | 0.000 | 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) | 0.000 | 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".