Exploring inertial sensing technology to quantify gait patterns in Thoroughbred foals before and after corrective trimming for angular limb deformities
Bibliographic record
Abstract
Angular limb deformities are a common orthopaedic problem in Thoroughbred foals. In some cases, these deformities resolve naturally but in other cases treatment, such as farriery intervention consisting of remedial trimming and/or shoeing, or surgery, is required to correct associated movement abnormalities. With advances in inertial measurement unit (IMU) technology, foal movement patterns can now be objectively measured. This study used IMU technology to determine whether Thoroughbred foals presenting with angular forelimb deformities had differences in their gait asymmetry, upper body range of motion (XSens MTw sensors, n = 10 foals) or the duration of stride cycle phases and stride length (Werkman Black forelimb hoof sensors, n = 5 foals) at walk before and after corrective trimming. Paired sample t-tests indicated that there was no significant difference in gait asymmetry parameters or range of motion at the poll, withers, tubera coxae and sacrum before and after trimming (p>0.05). Linear mixed models were used to compare before/after trimming data for the stride cycle phase durations and stride length and included speed as a covariate and foal as a random factor. After trimming, forelimb landing duration significantly decreased by 5.5 ms (25%), while mid-stance and breakover durations increased by 26.8 ms (7.0%) and 7.6 ms (4.8%), respectively; total stride duration post-trim was 24.0 ms (2.6%) longer than pre-trim. Stride length was also 3.3 cm (2.4%) longer after trimming. Further investigation in a larger cohort of foals is needed as part of a longitudinal assessment to evaluate gait changes during development, and to relate this to their locomotor performance as adult horses.
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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 | 0.001 | 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) | 0.000 | 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 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".