Abdominal Muscle Response During Curl-ups on Both Stable and Labile Surfaces
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: With the current interest in stability training for the injured low back, the use of labile (movable) surfaces, underneath the subject, to challenge the motor control system is becoming more popular. Little is known about the modulating effects of these surfaces on muscle activity. The purpose of this study was to establish the degree of modulating influence of the type of surface (whether stable or labile) on the mechanics of the abdominal wall. In this study, the amplitude of muscle activity together with the way that the muscles coactivated due to the type of surface under the subject were of interest. SUBJECTS: Eight men (mean age=23.3 years [SD=4.3], mean height=177.6 cm [SD=3.4], mean weight=72.6 kg [SD=8.7]) volunteered to participate in the study. All subjects were in good health and reported no incidence of acute or chronic low back injury or prolonged back pain prior to this experiment. METHODS: All subjects were requested to perform 4 different curl-up exercises-1 on a stable surface and the other 3 on varying labile surfaces. Electromyographic signals were recorded from 4 different abdominal sites on the right and left sides of the body and normalized to maximal voluntary contraction (MVC) amplitudes. RESULTS: Performing curl-up exercises on labile surfaces increased abdominal muscle activity (eg, for curl-up on a stable surface, rectus abdominis muscle activity was 21% of MVC and external oblique muscle activity was 5% of MVC; for curl-up with the upper torso on a labile ball, rectus abdominis muscle activity was 35% of MVC and external oblique muscle activity was 10% of MVC). Furthermore, it appears that increases in external oblique muscle activity were larger than those of other abdominal muscles. CONCLUSION AND DISCUSSION: Performing curl-ups on labile surfaces changes both the level of muscle activity and the way that the muscles coactivate to stabilize the spine and the whole body. This finding suggests a much higher demand on the motor control system, which may be desirable for specific stages in a rehabilitation program.
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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) | 0.002 | 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".