Accident reconstructions of falls, collisions, and punches in sports
Bibliographic record
Abstract
Objective Impacts to the head are the primary cause of concussive injuries in sport and can occur in a multitude of different environments. Each event is composed of combinations of impact characteristics (striking velocity, impact mass, and surface compliance) that present unique loading conditions on the head and brain. The purpose of this study was to compare falls, collisions, and punches from accident reconstructions of sports-related head impacts using linear, rotational accelerations and maximal principal strain of brain tissue from finite element simulation. Methods This study compared four types of head impact events through reconstruction. Seventy-two head impacts were taken from medical reports of accidental falls and game video of ice hockey, American football, and mixed-martial arts. These were reconstructed using physical impact systems to represent helmeted and unhelmeted falls, player-to-player collisions, and punches to the head. Head accelerations were collected using a Hybrid III headform and were input into a finite element brain model used to approximate strain in the cerebrum associated with the external loading conditions. Results Significant differences ( p < 0.01) were found for peak linear and rotational accelerations magnitudes (30–300 g and 3.2–7.8 krad/s 2 ) and pulse durations between all impact event types characterized by unique impact parameters. The only exception was found where punch impacts and helmeted falls had similar rotational durations. Regression analysis demonstrated that increases to strain from unhelmeted falls were significantly influenced by both linear and rotational accelerations, meanwhile helmeted falls, punches, and collisions were influenced by rotational accelerations alone. Conclusion This report illustrates that the four distinct impact events created unique peak head kinematics and brain tissue strain values. These distinct patterns of head acceleration characteristics suggest that it is important to keep in mind that head injury can occur from a range of low to high acceleration magnitudes and that impact parameters (surface compliance, striking velocity, and impact mass) play an important role on the duration-dependent tolerance to impact loading.
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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 | 0.000 |
| 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".