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1.
Appl Sci (Basel) ; 12(1)2022 Jan.
Article in English | MEDLINE | ID: mdl-36313121

ABSTRACT

Subglottal Impedance-Based Inverse Filtering (IBIF) allows for the continuous, non-invasive estimation of glottal airflow from a surface accelerometer placed over the anterior neck skin below the larynx. It has been shown to be advantageous for the ambulatory monitoring of vocal function, specifically in the use of high-order statistics to understand long-term vocal behavior. However, during long-term ambulatory recordings over several days, conditions may drift from the laboratory environment where the IBIF parameters were initially estimated due to sensor positioning, skin attachment, or temperature, among other factors. Observation uncertainties and model mismatch may result in significant deviations in the glottal airflow estimates; unfortunately, they are very difficult to quantify in ambulatory conditions due to a lack of a reference signal. To address this issue, we propose a Kalman filter implementation of the IBIF filter, which allows for both estimating the model uncertainty and adapting the airflow estimates to correct for signal deviations. One-way analysis of variance (ANOVA) results from laboratory experiments using the Rainbow Passage indicate an improvement using the modified Kalman filter on amplitude-based measures for phonotraumatic vocal hyperfunction (PVH) subjects compared to the standard IBIF; the latter showing a statistically difference (p-value = 0.02, F = 4.1) with respect to a reference glottal volume velocity signal estimated from a single notch filter used here as ground-truth in this work. In contrast, maximum flow declination rates from subjects with vocal phonotrauma exhibit a small but statistically difference between the ground-truth signal and the modified Kalman filter when using one-way ANOVA (p-value = 0.04, F = 3.3). Other measures did not have significant differences with either the modified Kalman filter or IBIF compared to ground-truth, with the exception of H1-H2, whose performance deteriorates for both methods. Overall, both methods (modified Kalman filter and IBIF) show similar glottal airflow measures, with the advantage of the modified Kalman filter to improve amplitude estimation. Moreover, Kalman filter deviations from the IBIF output airflow might suggest a better representation of some fine details in the ground-truth glottal airflow signal. Other applications may take more advantage from the adaptation offered by the modified Kalman filter implementation.

2.
J Speech Lang Hear Res ; 65(8): 2881-2895, 2022 08 17.
Article in English | MEDLINE | ID: mdl-35930680

ABSTRACT

PURPOSE: This exploratory study aims to investigate variations in voice production in the presence of background noise (Lombard effect) in individuals with nonphonotraumatic vocal hyperfunction (NPVH) and individuals with typical voices using acoustic, aerodynamic, and vocal fold vibratory measures of phonatory function. METHOD: Nineteen participants with NPVH and 19 participants with typical voices produced simple vocal tasks in three sequential background conditions: baseline (in quiet), Lombard (in noise), and recovery (5 min after removing the noise). The Lombard condition consisted of speech-shaped noise at 80 dB SPL through audiometric headphones. Acoustic measures from a microphone, glottal aerodynamic parameters estimated from the oral airflow measured with a circumferentially vented pneumotachograph mask, and vocal fold vibratory parameters from high-speed videoendoscopy were analyzed. RESULTS: During the Lombard condition, both groups exhibited a decrease in open quotient and increases in sound pressure level, peak-to-peak glottal airflow, maximum flow declination rate, and subglottal pressure. During the recovery condition, the acoustic and aerodynamic measures of individuals with typical voices returned to those of the baseline condition; however, recovery measures for individuals with NPVH did not return to baseline values. CONCLUSIONS: As expected, individuals with NPVH and participants with typical voices exhibited a Lombard effect in the presence of elevated background noise levels. During the recovery condition, individuals with NPVH did not return to their baseline state, pointing to a persistence of the Lombard effect after noise removal. This behavior could be related to disruptions in laryngeal motor control and may play a role in the etiology of NPVH. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.20415600.


Subject(s)
Vocal Cords , Voice , Acoustics , Glottis , Humans , Phonation
3.
Front Physiol ; 12: 732244, 2021.
Article in English | MEDLINE | ID: mdl-34539451

ABSTRACT

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.

4.
J Acoust Soc Am ; 147(5): EL434, 2020 05.
Article in English | MEDLINE | ID: mdl-32486812

ABSTRACT

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.


Subject(s)
Phonation , Voice , Bayes Theorem , Glottis , Humans , Male , Vibration , Vocal Cords
5.
PLoS One ; 13(12): e0209017, 2018.
Article in English | MEDLINE | ID: mdl-30571719

ABSTRACT

Phonotraumatic vocal hyperfunction (PVH) is associated with chronic misuse and/or abuse of voice that can result in lesions such as vocal fold nodules. The clinical aerodynamic assessment of vocal function has been recently shown to differentiate between patients with PVH and healthy controls to provide meaningful insight into pathophysiological mechanisms associated with these disorders. However, all current clinical assessment of PVH is incomplete because of its inability to objectively identify the type and extent of detrimental phonatory function that is associated with PVH during daily voice use. The current study sought to address this issue by incorporating, for the first time in a comprehensive ambulatory assessment, glottal airflow parameters estimated from a neck-mounted accelerometer and recorded to a smartphone-based voice monitor. We tested this approach on 48 patients with vocal fold nodules and 48 matched healthy-control subjects who each wore the voice monitor for a week. Seven glottal airflow features were estimated every 50 ms using an impedance-based inverse filtering scheme, and seven high-order summary statistics of each feature were computed every 5 minutes over voiced segments. Based on a univariate hypothesis testing, eight glottal airflow summary statistics were found to be statistically different between patient and healthy-control groups. L1-regularized logistic regression for a supervised classification task yielded a mean (standard deviation) area under the ROC curve of 0.82 (0.25) and an accuracy of 0.83 (0.14). These results outperform the state-of-the-art classification for the same classification task and provide a new avenue to improve the assessment and treatment of hyperfunctional voice disorders.


Subject(s)
Glottis/physiopathology , Point-of-Care Testing , Voice Disorders/diagnosis , Voice Disorders/physiopathology , Accelerometry , Adult , Air Movements , Diagnosis, Computer-Assisted , Female , Humans , Middle Aged , Smartphone , Vocal Cords/physiopathology , Voice , Voice Disorders/etiology , Young Adult
6.
J Speech Lang Hear Res ; 60(8): 2159-2169, 2017 08 16.
Article in English | MEDLINE | ID: mdl-28785762

ABSTRACT

Purpose: The purpose of this study was to determine the validity of preliminary reports showing that glottal aerodynamic measures can identify pathophysiological phonatory mechanisms for phonotraumatic and nonphonotraumatic vocal hyperfunction, which are each distinctly different from normal vocal function. Method: Glottal aerodynamic measures (estimates of subglottal air pressure, peak-to-peak airflow, maximum flow declination rate, and open quotient) were obtained noninvasively using a pneumotachograph mask with an intraoral pressure catheter in 16 women with organic vocal fold lesions, 16 women with muscle tension dysphonia, and 2 associated matched control groups with normal voices. Subjects produced /pae/ syllable strings from which glottal airflow was estimated using inverse filtering during /ae/ vowels, and subglottal pressure was estimated during /p/ closures. All measures were normalized for sound pressure level (SPL) and statistically tested for differences between patient and control groups. Results: All SPL-normalized measures were significantly lower in the phonotraumatic group as compared with measures in its control group. For the nonphonotraumatic group, only SPL-normalized subglottal pressure and open quotient were significantly lower than measures in its control group. Conclusions: Results of this study confirm previous hypotheses and preliminary results indicating that SPL-normalized estimates of glottal aerodynamic measures can be used to describe the different pathophysiological phonatory mechanisms associated with phonotraumatic and nonphonotraumatic vocal hyperfunction.


Subject(s)
Air Pressure , Dysphonia/physiopathology , Glottis/physiopathology , Laryngeal Diseases/physiopathology , Phonation/physiology , Adult , Algorithms , Female , Humans , Signal Processing, Computer-Assisted , User-Computer Interface
7.
IEEE Trans Audio Speech Lang Process ; 21(9): 1929-1939, 2013 Sep.
Article in English | MEDLINE | ID: mdl-25400531

ABSTRACT

A model-based inverse filtering scheme is proposed for an accurate, non-invasive estimation of the aerodynamic source of voiced sounds at the glottis. The approach, referred to as subglottal impedance-based inverse filtering (IBIF), takes as input the signal from a lightweight accelerometer placed on the skin over the extrathoracic trachea and yields estimates of glottal airflow and its time derivative, offering important advantages over traditional methods that deal with the supraglottal vocal tract. The proposed scheme is based on mechano-acoustic impedance representations from a physiologically-based transmission line model and a lumped skin surface representation. A subject-specific calibration protocol is used to account for individual adjustments of subglottal impedance parameters and mechanical properties of the skin. Preliminary results for sustained vowels with various voice qualities show that the subglottal IBIF scheme yields comparable estimates with respect to current aerodynamics-based methods of clinical vocal assessment. A mean absolute error of less than 10% was observed for two glottal airflow measures -maximum flow declination rate and amplitude of the modulation component- that have been associated with the pathophysiology of some common voice disorders caused by faulty and/or abusive patterns of vocal behavior (i.e., vocal hyperfunction). The proposed method further advances the ambulatory assessment of vocal function based on the neck acceleration signal, that previously have been limited to the estimation of phonation duration, loudness, and pitch. Subglottal IBIF is also suitable for other ambulatory applications in speech communication, in which further evaluation is underway.

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