Overground Gait Kinematics and Muscle Activation Patterns in the Yucatan Mini Pig
Bibliographic record
Abstract
Abstract A growing number of spinal cord injury, neuromodulation, and cell therapy studies on porcine models, especially the Yucatan minipigs (YMPs), have been recently reported. This is due to the large similarities between human and porcine neuroanatomy and biomechanics. To assess treatment modalities and locomotor recovery in this model, there is an obvious need for detailed characterization of normative overground gait in neurologically intact YMPs. The objective of this study was to assess gait biomechanics and the effect of overground walking speed on gait parameters, kinematics, and electromyographic (EMG) activity in the hindlimb muscles of YMPs. Nine neurologically-intact adult YMPs were trained to walk overground in a straight line. Whole-body kinematics and EMG activity of hindlimb muscles were recorded and analyzed at 6 different speed ranges (0.4-0.59, 0.6-0.79, 0.8-0.99, 1.0-1.19, 1.2-1.39, and 1.4-1.6 m/s). A MATLAB program was developed to detect strides and gait events automatically from motion-captured data. Significant decreases in stride duration, stance and swing times and an increase in stride length were observed with increasing speed. A transition in gait pattern occurred at the 1.0m/s walking speed. Significant increases in the range of motion of the knee and ankle joints were observed at higher speeds. Also, the points of minimum and maximum knee and ankle joint angles occurred earlier in the gait cycle at higher speeds. The onset of EMG activity in the biceps femoris muscle occurred significantly earlier in the gait cycle with increasing speed. A comprehensive characterization of overground walking in neurologically-intact YMPs is provided. These normative measures set the basis against which the effects of future interventions on locomotor capacity in YMPs can be compared.
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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 | 0.000 |
| 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) | 0.001 | 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".