Literature DB >> 30908260

Neurophysiological Muscle Activation Scheme for Controlling Vocal Fold Models.

Rodrigo Manriquez, Sean D Peterson, Pavel Prado, Patricio Orio, Gabriel E Galindo, Matias Zanartu.   

Abstract

A physiologically-based scheme that incorporates inherent neurological fluctuations in the activation of intrinsic laryngeal muscles into a lumped-element vocal fold model is proposed. Herein, muscles are activated through a combination of neural firing rate and recruitment of additional motor units, both of which have stochastic components. The mathematical framework and underlying physiological assumptions are described, and the effects of the fluctuations are tested via a parametric analysis using a body-cover model of the vocal folds for steady-state sustained vowels. The inherent muscle activation fluctuations have a bandwidth that varies with the firing rate, yielding both low and high-frequency components. When applying the proposed fluctuation scheme to the voice production model, changes in the dynamics of the system can be observed, ranging from fluctuations in the fundamental frequency to unstable behavior near bifurcation regions. The resulting coefficient of variation of the model parameters is not uniform with muscle activation. The stochastic components of muscle activation influence both the fine structure variability and the ability to achieve a target value for pitch control. These components can have a significant impact on the vocal fold parameters, as well as the outputs of the voice production model. Good agreement was found when contrasting the proposed scheme with prior experimental studies accounting for variability in vocal fold posturing and spectral characteristics of the muscle activation signal. The proposed scheme constitutes a novel and physiologically-based approach for controlling lumped-element models for normal voice production and can be extended to explore neuropathological conditions.

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Year:  2019        PMID: 30908260      PMCID: PMC6557719          DOI: 10.1109/TNSRE.2019.2906030

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  43 in total

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Authors:  Michael Döllinger; Ulrich Hoppe; Frank Hettlich; Jörg Lohscheller; Stefan Schuberth; Ulrich Eysholdt
Journal:  IEEE Trans Biomed Eng       Date:  2002-08       Impact factor: 4.538

2.  A model for neurologic sources of aperiodicity in vocal fold vibration.

Authors:  I R Titze
Journal:  J Speech Hear Res       Date:  1991-06

3.  Discharge rate variability influences the variation in force fluctuations across the working range of a hand muscle.

Authors:  Chet T Moritz; Benjamin K Barry; Michael A Pascoe; Roger M Enoka
Journal:  J Neurophysiol       Date:  2004-12-22       Impact factor: 2.714

4.  Rules for controlling low-dimensional vocal fold models with muscle activation.

Authors:  Ingo R Titze; Brad H Story
Journal:  J Acoust Soc Am       Date:  2002-09       Impact factor: 1.840

5.  Dependence of neuronal correlations on filter characteristics and marginal spike train statistics.

Authors:  Tom Tetzlaff; Stefan Rotter; Eran Stark; Moshe Abeles; Ad Aertsen; Markus Diesmann
Journal:  Neural Comput       Date:  2008-09       Impact factor: 2.026

6.  Analysis, synthesis, and perception of voice quality variations among female and male talkers.

Authors:  D H Klatt; L C Klatt
Journal:  J Acoust Soc Am       Date:  1990-02       Impact factor: 1.840

7.  Non-stationary Bayesian estimation of parameters from a body cover model of the vocal folds.

Authors:  Paul J Hadwin; Gabriel E Galindo; Kyle J Daun; Matías Zañartu; Byron D Erath; Edson Cataldo; Sean D Peterson
Journal:  J Acoust Soc Am       Date:  2016-05       Impact factor: 1.840

8.  The study of laryngeal muscle activity in normal human subjects and in patients with laryngeal dystonia using multiple fine-wire electromyography.

Authors:  A D Hillel
Journal:  Laryngoscope       Date:  2001-04       Impact factor: 3.325

9.  Differential roles for the thyroarytenoid and lateral cricoarytenoid muscles in phonation.

Authors:  Dinesh K Chhetri; Juergen Neubauer
Journal:  Laryngoscope       Date:  2015-07-21       Impact factor: 3.325

10.  Correspondence between laryngeal vocal fold movement and muscle activity during speech and nonspeech gestures.

Authors:  Christopher J Poletto; Laura P Verdun; Robert Strominger; Christy L Ludlow
Journal:  J Appl Physiol (1985)       Date:  2004-05-07
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  2 in total

1.  LaDIVA: A neurocomputational model providing laryngeal motor control for speech acquisition and production.

Authors:  Hasini R Weerathunge; Gabriel A Alzamendi; Gabriel J Cler; Frank H Guenther; Cara E Stepp; Matías Zañartu
Journal:  PLoS Comput Biol       Date:  2022-06-23       Impact factor: 4.779

2.  Triangular body-cover model of the vocal folds with coordinated activation of the five intrinsic laryngeal muscles.

Authors:  Gabriel A Alzamendi; Sean D Peterson; Byron D Erath; Robert E Hillman; Matías Zañartu
Journal:  J Acoust Soc Am       Date:  2022-01       Impact factor: 1.840

  2 in total

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