Neurophysiological Muscle Activation Scheme for Controlling Vocal Fold Models

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

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

9 Citas (Scopus)


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.

Idioma originalInglés
Número de artículo8668847
Páginas (desde-hasta)1043-1052
Número de páginas10
PublicaciónIEEE Transactions on Neural Systems and Rehabilitation Engineering
EstadoPublicada - may. 2019


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