Ultrasound-tensiometry: A new method for measuring differential loading within a tendon during movement
Bibliographic record
Abstract
BACKGROUND: Tendons transmit tensile load from muscles to the skeleton. Differential loading across a tendon can occur, especially when it contains subtendons originating from distinct muscles. Tendon shear wave speed has previously been shown to reflect local tensile stress. Hence, a tool that measures spatial variations in wave speed may reflect differential loading within a tendon during human movement. RESEARCH QUESTION: Do wave speeds measured via high-framerate ultrasound-based tensiometry correspond with differential loading across a tendon? METHODS: Ultrasound-tensiometry uses an external mechanical actuator to induce waves and high-framerate plane wave ultrasound imaging (20 kHz) to track tissue displacements arising from wave propagation within a tendon. Local tissue displacements are temporally and spatially filtered to remove high-frequency noise and reflected waves. A Radon transform of the spatio-temporal displacement data is used to compute the shear wave speed across the tendon. We evaluated ultrasound-tensiometry's ability to measure differential loading across a tendon using in silico, ex vivo and in vivo approaches. The in silico approach used a finite element model to simulate wave propagation along two adjacent subtendons undergoing differential loading. The ex vivo experiment measured wave speed in adjacent porcine flexor subtendons subjected to differential loading. In vivo, we tracked wave speed across the Achilles tendon while a participant performed calf stretches to differentially load the subtendons, and while walking on a treadmill at 1.5 m/s. RESULTS: Wave speeds modulated with local tendon stress under both in silico and ex vivo conditions, with higher wave speeds observed in subtendons subjected to higher loads (6-16 m/s higher at 1.5× load differential). Spatial variations in in vivo Achilles tendon wave speeds were consistent with differential subtendon loading arising from distinct muscle loads (maximum range: 0-137 m/s, resolution: 0.1 mm×0.2 mm, precision: ±0.2 m/s). SIGNIFICANCE: High-framerate ultrasound-tensiometry tracks spatial variations in tendon wave speed, which may be useful to investigate local tissue loading and to delineate individual muscle contributions to movement.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".