Impact of Nonmodal Phonation on Estimates of Subglottal Pressure From Neck-Surface Acceleration in Healthy Speakers

Marks, Katherine L.; Lin, Jonathan Z.; Fox, Annie B.; Toles, Laura E.; Mehta, Daryush D.

doi:10.1044/2019_jslhr-s-19-0067

Cited by 18 publications

(11 citation statements)

References 60 publications

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“…Applying this formula to the laboratory data (237 tokens) in the current study to estimate subglottal pressure resulted in a root-mean-square error of 2.86 cm H 2 O and mean absolute error of 2.11 cm H 2 O. The relatively good performance for such a simple formula supports the idea that simple regression architectures are adequate for predicting subglottal pressure in vocally typical conditions; estimation accuracy of linear regression models reduces when non-modal voice qualities are included (Marks et al, 2019(Marks et al, , 2020Lin et al, 2020). The model-based approach of the current work allows for the estimation of additional measures of vocal function (e.g., vocal fold collision pressure, laryngeal muscle activation).…”

Section: Discussionsupporting

confidence: 63%

Estimation of Subglottal Pressure, Vocal Fold Collision Pressure, and Intrinsic Laryngeal Muscle Activation From Neck-Surface Vibration Using a Neural Network Framework and a Voice Production Model

et al. 2021

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The ambulatory assessment of vocal function can be significantly enhanced by having access to physiologically based features that describe underlying pathophysiological mechanisms in individuals with voice disorders. This type of enhancement can improve methods for the prevention, diagnosis, and treatment of behaviorally based voice disorders. Unfortunately, the direct measurement of important vocal features such as subglottal pressure, vocal fold collision pressure, and laryngeal muscle activation is impractical in laboratory and ambulatory settings. In this study, we introduce a method to estimate these features during phonation from a neck-surface vibration signal through a framework that integrates a physiologically relevant model of voice production and machine learning tools. The signal from a neck-surface accelerometer is first processed using subglottal impedance-based inverse filtering to yield an estimate of the unsteady glottal airflow. Seven aerodynamic and acoustic features are extracted from the neck surface accelerometer and an optional microphone signal. A neural network architecture is selected to provide a mapping between the seven input features and subglottal pressure, vocal fold collision pressure, and cricothyroid and thyroarytenoid muscle activation. This non-linear mapping is trained solely with 13,000 Monte Carlo simulations of a voice production model that utilizes a symmetric triangular body-cover model of the vocal folds. The performance of the method was compared against laboratory data from synchronous recordings of oral airflow, intraoral pressure, microphone, and neck-surface vibration in 79 vocally healthy female participants uttering consecutive /pæ/ syllable strings at comfortable, loud, and soft levels. The mean absolute error and root-mean-square error for estimating the mean subglottal pressure were 191 Pa (1.95 cm H2O) and 243 Pa (2.48 cm H2O), respectively, which are comparable with previous studies but with the key advantage of not requiring subject-specific training and yielding more output measures. The validation of vocal fold collision pressure and laryngeal muscle activation was performed with synthetic values as reference. These initial results provide valuable insight for further vocal fold model refinement and constitute a proof of concept that the proposed machine learning method is a feasible option for providing physiologically relevant measures for laboratory and ambulatory assessment of vocal function.

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Section: Discussionsupporting

confidence: 63%

Estimation of Subglottal Pressure, Vocal Fold Collision Pressure, and Intrinsic Laryngeal Muscle Activation From Neck-Surface Vibration Using a Neural Network Framework and a Voice Production Model

et al. 2021

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“…However, these authors also demonstrated that the SPL skewness correlated well with the skewness of the non-SPL calibrated neck skin acceleration magnitude (physical vibration units of cm/s 2 , in units of dB) which serves to corroborate the significant differences in skewness between patients and controls. It has also been shown that the amplitude of the ACC signal actually correlates better with subglottal pressure than with SPL ( Fryd et al, 2016 ; Marks et al, 2019 ). Thus, irrespective of the extent to which greater SPL skewness reflects the use of “louder” speech, this finding supports the view that patients with phonotrauma are employing higher laryngeal forces (including subglottal pressure) to phonate than healthy controls ( Van Stan et al, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Differences Between Female Singers With Phonotrauma and Vocally Healthy Matched Controls in Singing and Speaking Voice Use During 1 Week of Ambulatory Monitoring

Toles

Ortiz

Marks

et al. 2021

Am J Speech Lang Pathol

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Purpose Previous ambulatory voice monitoring studies have included many singers and have combined speech and singing in the analyses. This study applied a singing classifier to the ambulatory recordings of singers with phonotrauma and healthy controls to determine if analyzing speech and singing separately would reveal voice use differences that could provide new insights into the etiology and pathophysiology of phonotrauma in this at-risk population. Method Forty-two female singers with phonotrauma (vocal fold nodules or polyps) and 42 healthy matched controls were monitored using an ambulatory voice monitor. Weeklong statistics (average, standard deviation, skewness, kurtosis) for sound pressure level (SPL), fundamental frequency, cepstral peak prominence, the magnitude ratio of the first two harmonics ( H 1 –H 2 ), and three vocal dose measures were computed from the neck surface acceleration signal and separated into singing and speech using a singing classifier. Results Mixed analysis of variance models found expected differences between singing and speech in each voice parameter, except SPL kurtosis. SPL skewness, SPL kurtosis, and all H 1 –H 2 distributional parameters differentiated patients and controls when singing and speech were combined. Interaction effects were found in H 1 –H 2 kurtosis and all vocal dose measures. Patients had significantly higher vocal doses in speech compared to controls. Conclusions Consistent with prior work, the pathophysiology of phonotrauma in singers is characterized by more abrupt/complete glottal closure (decreased mean and variation for H 1 –H 2 ) and increased laryngeal forces (negatively skewed SPL distribution) during phonation. Application of a singing classifier to weeklong data revealed that singers with phonotrauma spent more time speaking on a weekly basis, but not more time singing, compared to controls. Results are used as a basis for hypothesizing about the role of speaking voice in the etiology of phonotraumatic vocal hyperfunction in singers.

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“…Later formulations of vocal dose measures have attempted to incorporate the effects of vocal fold collision [50], which is important since phonotrauma is hypothesized to be caused by repetitive stress on the mid-membranous portion of the vocal folds [5][6][7]. Since the data in this study point toward a potential 1:1 correspondence between vocal fold collision pressure and subglottal pressure in certain scenarios, we can take advantage of work aimed at estimating subglottal pressure from neck-surface vibration and apply this analysis to ambulatory voice signals [61][62][63][64].…”

Section: Discussionmentioning

confidence: 99%

Direct Measurement and Modeling of Intraglottal, Subglottal, and Vocal Fold Collision Pressures during Phonation in an Individual with a Hemilaryngectomy

et al. 2021

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The purpose of this paper is to report on the first in vivo application of a recently developed transoral, dual-sensor pressure probe that directly measures intraglottal, subglottal, and vocal fold collision pressures during phonation. Synchronous measurement of intraglottal and subglottal pressures was accomplished using two miniature pressure sensors mounted on the end of the probe and inserted transorally in a 78-year-old male who had previously undergone surgical removal of his right vocal fold for treatment of laryngeal cancer. The endoscopist used one hand to position the custom probe against the surgically medialized scar band that replaced the right vocal fold and used the other hand to position a transoral endoscope to record laryngeal high-speed videoendoscopy of the vibrating left vocal fold contacting the pressure probe. Visualization of the larynx during sustained phonation allowed the endoscopist to place the dual-sensor pressure probe such that the proximal sensor was positioned intraglottally and the distal sensor subglottally. The proximal pressure sensor was verified to be in the strike zone of vocal fold collision during phonation when the intraglottal pressure signal exhibited three characteristics: an impulsive peak at the start of the closed phase, a rounded peak during the open phase, and a minimum value around zero immediately preceding the impulsive peak of the subsequent phonatory cycle. Numerical voice production modeling was applied to validate model-based predictions of vocal fold collision pressure using kinematic vocal fold measures. The results successfully demonstrated feasibility of in vivo measurement of vocal fold collision pressure in an individual with a hemilaryngectomy, motivating ongoing data collection that is designed to aid in the development of vocal dose measures that incorporate vocal fold impact collision and stresses.

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Impact of Nonmodal Phonation on Estimates of Subglottal Pressure From Neck-Surface Acceleration in Healthy Speakers

Cited by 18 publications

References 60 publications

Estimation of Subglottal Pressure, Vocal Fold Collision Pressure, and Intrinsic Laryngeal Muscle Activation From Neck-Surface Vibration Using a Neural Network Framework and a Voice Production Model

Estimation of Subglottal Pressure, Vocal Fold Collision Pressure, and Intrinsic Laryngeal Muscle Activation From Neck-Surface Vibration Using a Neural Network Framework and a Voice Production Model

Differences Between Female Singers With Phonotrauma and Vocally Healthy Matched Controls in Singing and Speaking Voice Use During 1 Week of Ambulatory Monitoring

Direct Measurement and Modeling of Intraglottal, Subglottal, and Vocal Fold Collision Pressures during Phonation in an Individual with a Hemilaryngectomy

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