In vivo anterior cruciate ligament strain behaviour during a rapid deceleration movement: case report
Bibliographic record
Abstract
The mechanism of anterior cruciate ligament (ACL) injury is still unclear. To gain this insight, knowledge of the mechanical behaviour of the healthy ACL during activities that may stress the ligament must be investigated in vivo. The goal of this research was to measure ACL strain in vivo during rapid deceleration, a sport type movement that has been previously shown to precede injuries to the ACL in healthy subjects. A young male subject with no previous knee joint injuries volunteered after informed consent. The strain gauge device (DVRT) was calibrated and surgically implanted in the antero-medial band of the intact ACL. The subject was then transported to the lab for data collection. The zero strain position of the ACL was determined using the slack-taut technique. The subject hopped as quickly as possible from a distance of 1.5 m to the target, an X taped at the centre of a force plate, landing with the instrumented left leg and stopping in the landed position. The entire collection window was five seconds at 1000 Hz. A total of three rapid deceleration trials were collected and averaged over the hop cycle. The slack-taut test was then repeated to ensure proper operation of the DVRT and the reliability of the results. The results showed an average peak strain of the ACL during the instrumented Lachman test of 2.00+/-0.17%. The average peak strain of the ACL during the rapid deceleration task was 5.47+/-0.28%. The data indicate that the RD task caused an increase in peak ACL strain that is much higher than during the instrumented Lachman test, and that the strain begins to increase during the flight phase, prior to landing, and reaches a peak that corresponds to the peak ground reaction force. This technique may be used in further sport-specific movements to gain insight into movement patterns associated with ACL injury mechanisms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".