Trunk Muscle Activation Patterns, Lumbar Compressive Forces, and Spine Stability When Using the Bodyblade
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The objective of this study was to analyze the trunk muscle activation patterns, spine kinematics, and lumbar compressive forces that occur when using the Bodyblade, a popular tool in physical medicine clinics. SUBJECTS: The participants were 14 male subjects who were healthy and who were recruited from a university population. METHODS: With data collected from surface electromyography of selected trunk and shoulder muscles, video analysis, and a 3-dimensional lumbar spine position sensor, modeling methods were used to quantify L4-5 compressive forces and spine stability. RESULTS: Large-amplitude oscillation of a vertically oriented Bodyblade resulted in the greatest activation levels of the internal oblique and external oblique muscles (average amplitude=48% and 26% of maximal voluntary isometric contraction, respectively), which were associated with L4-5 compressive forces as high as 4,328 N. Instantaneous stability increased with well-coordinated effort, muscle activation, and compression, but decreased when subjects had poor technique. DISCUSSION AND CONCLUSION: The way the Bodyblade is used may either enhance or compromise spine stability. Associated lumbar compressive forces may be inappropriate for some people with compression-intolerant lumbar spine pathology.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".