Evaluation of contact pressure in human vocal folds during phonation using high-speed videoendoscopy, electroglottography, and magnetic resonance imaging
Bibliographic record
Abstract
Mechanical stresses on the vocal folds surface during high pitch or amplitude phonation have been postulated to cause vocal fold damage. Models for the quantitative estimate of the contact pressure may be valuable for prevention and treatment. The objective of this study was to non-invasively estimate the contact pressure for different phonation types, frequencies and amplitudes in human subjects using concurrent high-speed videoendoscopy and eletroglottography. The edge velocities before and after contact were estimated from the analysis of consecutive digital images. Instantaneous contact areas were determined from electroglottography along with Magnetic resonance image (MRI). The contact pressure was assessed using the impulse momentum form of Newton's second law. Investigations were carried out in quantitative human subjects to compare contact pressures for three different voice types, frequencies and amplitude levels. Contact pressures for breathy, normal and pressed voice were obtained for five subjects. The results were verified through comparisons with values measured directly using a probe microphone. The proposed method appears to be robust and accurate for contact pressure estimation.
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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 | 0.002 |
| 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 | 0.001 | 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".