Sensitivity of Phonation Onset Pressure to Vocal Fold Stiffness Distribution.

Phonation onset is characterized by the unstable growth of vocal fold (VF) vibrations that ultimately results in self-sustained oscillation and the production of modal voice. Motivated by histological studies, much research has focused on the role of the layered structure of the vocal folds in influencing phonation onset, wherein the outer "cover" layer is relatively soft and the inner "body" layer is relatively stiff. Recent research, however, suggests that the body-cover (BC) structure over-simplifies actual stiffness distributions by neglecting important spatial variations, such as inferior-superior (IS) and anterior-posterior gradients and smooth transitions in stiffness from one histological layer to another. Herein, we explore sensitivity of phonation onset to stiffness gradients and smoothness. By assuming no a priori stiffness distribution and considering a second-order Taylor series sensitivity analysis of phonation onset pressure with respect to stiffness, we find two general smooth stiffness distributions most strongly influence onset pressure: a smooth stiffness containing aspects of BC differences and IS gradients in the cover, which plays a role in minimizing onset pressure, and uniform increases in stiffness, which raise onset pressure and frequency. While the smooth stiffness change contains aspects qualitatively similar to layered BC distributions used in computational studies, smooth transitions in stiffness result in higher sensitivity of onset pressure than discrete layering. These two general stiffness distributions also provide a simple, low-dimensional, interpretation of how complex variations in VF stiffness affect onset pressure, enabling refined exploration of the effects of stiffness distributions on phonation onset.

The effect of swelling on vocal fold kinematics and dynamics.

Swelling in the vocal folds is caused by the local accumulation of fluid, and has been implicated as a phase in the development of phonotraumatic vocal hyperfunction and related structural pathologies, such as vocal fold nodules. It has been posited that small degrees of swelling may be protective, but large amounts may lead to a vicious cycle wherein the engorged folds lead to conditions that promote further swelling, leading to pathologies. As a first effort to explore the mechanics of vocal fold swelling and its potential role in the etiology of voice disorders, this study employs a finite-element model with swelling confined to the superficial lamina propria, which changes the volume, mass, and stiffness of the cover layer. The impacts of swelling on a number of vocal fold kinematic and damage measures, including von Mises stress, internal viscous dissipation, and collision pressure, are presented. Swelling has small but consistent effects on voice outputs, including a reduction in fundamental frequency with increasing swelling (10 Hz at 30 % swelling). Average von Mises stress decreases slightly for small degrees of swelling but increases at large magnitudes, consistent with expectations for a vicious cycle. Both viscous dissipation and collision pressure consistently increase with the magnitude of swelling. This first effort at modeling the impact of swelling on vocal fold kinematics, kinetics, and damage measures highlights the complexity with which phonotrauma can influence performance metrics. Further identification and exploration of salient candidate measures of damage and refined studies coupling swelling with local phonotrauma are expected to shed further light on the etiological pathways of phonotraumatic vocal hyperfunction.

Examining the influence of epithelium layer modeling approaches on vocal fold kinematics and kinetics.

Grouping the thin epithelium and thicker superficial lamina propria layers into a single cover layer has been widely adopted in finite element vocal fold models. Recent silicone vocal fold studies have suggested, however, that inclusion of a distinct epithelial layer leads to more physiologically representative motion. This study systematically explores the ramifications of incorporating an epithelial layer into a cover grouping for finite element vocal fold modeling. A membrane model for the epithelium is introduced to facilitate parametric investigation by reducing the mesh density requirement of the epithelium into a single infinitesimally thin layer. Excluding the epithelium entirely leads to increased energy in higher order modes and larger inferior-superior excursion of the folds. Integrating the epithelium into a cover layer with volume-weighted average stiffness results in similar kinematics to that of a model treating the epithelium as a distinct layer. However, the internal stress/strain and contact pressure during collision are higher, and viscous dissipation is lower, when the epithelium is integrated into the cover. Thus, careful treatment of the epithelium is recommended for finite element studies, particularly when employing the models for estimating measures dependent upon internal stress/strain and/or collision pressure, such as vocal dose.

Modeling the influence of COVID-19 protective measures on the mechanics of phonation.

In an effort to mitigate the 2019 novel coronavirus disease pandemic, mask wearing and social distancing have become standard practices. While effective in fighting the spread of the virus, these protective measures have been shown to deteriorate speech perception and sound intensity, which necessitates speaking louder to compensate. The goal of this paper is to investigate via numerical simulations how compensating for mask wearing and social distancing affects measures associated with vocal health. A three-mass body-cover model of the vocal folds (VFs) coupled with the sub- and supraglottal acoustic tracts is modified to incorporate mask and distance dependent acoustic pressure models. The results indicate that sustaining target levels of intelligibility and/or sound intensity while using these protective measures may necessitate increased subglottal pressure, leading to higher VF collision and, thus, potentially inducing a state of vocal hyperfunction, a progenitor to voice pathologies.

Bayesian estimation of vocal function measures using laryngeal high-speed videoendoscopy and glottal airflow estimates: An in vivo case study.

This study introduces the in vivo application of a Bayesian framework to estimate subglottal pressure, laryngeal muscle activation, and vocal fold contact pressure from calibrated transnasal high-speed videoendoscopy and oral airflow data. A subject-specific, lumped-element vocal fold model is estimated using an extended Kalman filter and two observation models involving glottal area and glottal airflow. Model-based inferences using data from a vocally healthy male individual are compared with empirical estimates of subglottal pressure and reference values for muscle activation and contact pressure in the literature, thus providing baseline error metrics for future clinical investigations.

The effect of high-speed videoendoscopy configuration on reduced-order model parameter estimates by Bayesian inference.

Bayesian inference has been previously demonstrated as a viable inverse analysis tool for estimating subject-specific reduced-order model parameters and uncertainties. However, previous studies have relied upon simulated glottal area waveforms with superimposed random noise as the measurement. In practice, high-speed videoendoscopy is used to measure glottal area, which introduces practical imaging effects not captured in simulated data, such as viewing angle, frame rate, and camera resolution. Herein, high-speed videos of the vocal folds were approximated by recording the trajectories of physical vocal fold models controlled by a symmetric body-cover model. Twenty videos were recorded, varying subglottal pressure, cricothyroid activation, and viewing angle, with frame rate and video resolution varied by digital video manipulation. Bayesian inference was used to estimate subglottal pressure and cricothyroid activation from glottal area waveforms extracted from the videos. The resulting estimates show off-axis viewing of 10° can lead to a 10% bias in the estimated subglottal pressure. A viewing model is introduced such that viewing angle can be included as an estimated parameter, which alleviates estimate bias. Frame rate and pixel resolution were found to primarily affect uncertainty of parameter estimates up to a limit where spatial and temporal resolutions were too poor to resolve the glottal area. Since many high-speed cameras have the ability to sacrifice spatial for temporal resolution, the findings herein suggest that Bayesian inference studies employing high-speed video should increase temporal resolutions at the expense of spatial resolution for reduced estimate uncertainties.