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.
Previous work using ambulatory voice recordings has shown no differences in average vocal behavior between patients with phonotraumatic vocal hyperfunction and matched controls. This study used larger groups to replicate these results and expanded the analysis to include distributional characteristics of ambulatory voice use and measures indicative of glottal closure.
Subjects included 180 adult women: 90 diagnosed with vocal fold nodules or polyps and 90 age-, sex-, and occupation-matched controls with no history of voice disorders. Weeklong summary statistics (average, variability, skewness, kurtosis) of voice use were computed from neck-surface acceleration recorded using an ambulatory voice monitor. Voice measures included estimates of sound pressure level (SPL), fundamental frequency (fo), cepstral peak prominence, and the difference between the first and second harmonic magnitudes (H1–H2).
Statistical comparisons resulted in medium–large differences (Cohen's d ≥ 0.5) between groups for SPL skewness, fo variability, and H1–H2 variability. Two logistic regressions (theory-based and stepwise) found SPL skewness and H1–H2 variability to classify patients and controls based on their weekly voice data, with an area under the receiver operating characteristic curve of 0.85 and 0.82 on training and test sets, respectively.
Compared to controls, the weekly voice use of patients with phonotraumatic vocal hyperfunction reflected higher SPL tendencies (negatively skewed SPL) with more abrupt glottal closure (reduced H1–H2 variability, especially toward higher values). Further work could examine posttreatment data (e.g., after surgery and/or therapy) to determine the extent to which these differences are associated with the etiology and pathophysiology of phonotraumatic vocal fold lesions.
Subglottal air pressure plays a major role in voice production and is a primary factor in controlling voice onset, offset, sound pressure level, glottal airflow, vocal fold collision pressures, and variations in fundamental frequency. Previous work has shown promise for the estimation of subglottal pressure from an unobtrusive miniature accelerometer sensor attached to the anterior base of the neck during typical modal voice production across multiple pitch and vowel contexts. This study expands on that work to incorporate additional accelerometer-based measures of vocal function to compensate for non-modal phonation characteristics and achieve an improved estimation of subglottal pressure. Subjects with normal voices repeated /p/-vowel syllable strings from loud-to-soft levels in multiple vowel contexts (/a/, /i/, and /u/), pitch conditions (comfortable, lower than comfortable, higher than comfortable), and voice quality types (modal, breathy, strained, and rough). Subject-specific, stepwise regression models were constructed using root-mean-square (RMS) values of the accelerometer signal alone (baseline condition) and in combination with cepstral peak prominence, fundamental frequency, and glottal airflow measures derived using subglottal impedance-based inverse filtering. Five-fold cross-validation assessed the robustness of model performance using the root-mean-square error metric for each regression model. Each cross-validation fold exhibited up to a 25% decrease in prediction error when the model incorporated multi-dimensional aspects of the accelerometer signal compared with RMS-only models. Improved estimation of subglottal pressure for non-modal phonation was thus achievable, lending to future studies of subglottal pressure estimation in patients with voice disorders and in ambulatory voice recordings.