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.