An Electromyographic Study of Low-Velocity Rear-End Impacts
Bibliographic record
Abstract
STUDY DESIGN: Experimental analysis was performed to determine the effects of low-velocity rear-end impacts on phasic and magnitudinal activity of the cervical muscles in expected and unexpected conditions. OBJECTIVES: To determine the phasic response of the cervical muscles to increasing low-velocity rear-end impacts, and to compare the quantitative effects of awareness and unawareness of impending impact. SUMMARY OF BACKGROUND DATA: The literature contains little information on the etiology of whiplash injuries. Animal and cadaver studies have yielded some insight into the phenomenon. However, in vivo studies of the cervical muscular response and head-neck kinematics to low-velocity impacts are rare. METHODS: Seven healthy volunteers were subjected to rear-end impacts of 4.9, 8.8, 10.8, and 13.7 m/s2 acceleration at two levels of expectation: expected and unexpected. Bilateral electromyograms of the sternocleidomastoids, trapezii, and splenii capitis were recorded. Triaxial accelerometers recorded the acceleration of the chair, torso at the shoulder level, and head of the participant. RESULTS: At an acceleration of 13.7 m/s2, the sternocleidomastoids generated up to 179% of their maximal voluntary contraction electromyogram, whereas the splenii and trapezii did not exceed 35% of their maximal voluntary contraction in most of the experimental conditions. Electromyographic variables were significantly affected by the levels of acceleration and expectation (P < 0.001). The onset time and peak electromyogram time for the sternocleidomastoid progressively decreased with increasing levels of acceleration. The kinetic variables and the electromyographic variables regressed significantly on the acceleration (P < 0.01), explaining from 96% to 100% of the variability. CONCLUSIONS: Muscle responses were greater with higher levels of acceleration. Because the muscular component of the head-neck complex plays a central role in the abatement of higher acceleration levels, it may be a primary site of injury in the whiplash phenomenon.
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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) | 0.003 | 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".