Non-invasive <i>in vivo</i> measurement of the mechanical properties of human vocal fold tissue
Bibliographic record
Abstract
The mechanical properties of the vocal fold mucosa have a great effect on the vocal folds oscillations, and voice quality. A non-invasive method was developed and examined to obtain the mechanical properties of human vocal fold tissue in vivo via measurements of the mucosal wave propagation speed during phonation. High speed and MRI images of three subject’s vocal folds were captured while phonating at different pitches. The images obtained from these two techniques were matched and the dimensions of the vocal folds were obtained. The mucosal wave propagation speed was determined for the three subjects at different pitches through an automatic image processing procedure. The shear modulus of the subjects’ vocal fold mucosa was then calculated using a surface (Rayleigh) wave propagation model and the measured wave speeds. This is revealed that the mucosal wave propagation speed and the shear modulus of the vocal fold tissue increased with the pitch. The results were in good agreement with those from other studies obtained via in vitro measurements, thereby supporting the validity of the proposed measurement method. This method offers the potential for in vivo clinical assessments.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".