Shear-wave multi-frequency pulse for single-shot viscoelastic sensing
Bibliographic record
Abstract
Time-resolved estimation of viscoelastic properties is essential for capturing dynamic mechanical changes in soft materials and biological tissues. Viscoelastic parameters can be estimated from shear-wave velocity (SWV) dispersion, but repeated excitations at different frequencies limit temporal resolution. We introduce a method of SWV dispersion measurement using a shear-wave multi-frequency pulse (SW-MFP) that encodes several chosen frequencies into a single excitation. Shear elasticity and viscosity estimates are obtained by fitting the measured SWV dispersion to the Kelvin–Voigt model. Experiments were performed using a compact setup with dual plane wave ultrasound transducers and a miniaturized SW actuator. Tissue-mimicking phantoms with varied viscoelastic properties were distinguished by their SWV dispersion curves and corresponding viscoelastic parameter estimates. These results demonstrate SW-MFP for single-shot viscoelastic sensing, providing a pathway toward real-time viscoelastic characterization of dynamic soft materials in biomedical and industrial applications.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".