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Pathological Voice Source Analysis System Using a Flow Waveform-Matched Biomechanical Model.

Xiaojun Zhang1,2, Lingling Gu2, Wei Wei2

  • 1School of Electronic and Information Engineering, Soochow University, Suzhou 215000, China.

Applied Bionics and Biomechanics
|July 31, 2018
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Summary
This summary is machine-generated.

This study developed a novel system for analyzing pathological voice production using nonlinear dynamics and an optimized two-mass model. The findings reveal how vocal cord paralysis impacts voice acoustics and biomechanics.

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Area of Science:

  • Biomechanics of voice production
  • Nonlinear dynamics in biological systems
  • Pathological voice analysis

Background:

  • Voice disorders stem from vocal cord lesions affecting vibration and airflow.
  • Accurate modeling of vocal cord dynamics is crucial for understanding voice pathologies.
  • Existing models may not fully capture the nonlinear complexities of pathological voice.

Purpose of the Study:

  • To design and validate a pathological voice source analysis system.
  • To investigate nonlinear characteristics of vocal cord vibration in pathological voices.
  • To analyze acoustic parameter changes due to subglottal pressure and vocal cord paralysis.

Main Methods:

  • Integration of nonlinear dynamics with an optimized asymmetric two-mass model.
  • Utilizing a fitting procedure combining genetic particle swarm optimization and a quasi-Newton method.
  • Analysis of sustained vowel /a/ samples from the MEEI database for normal and pathological voices.

Main Results:

  • The proposed biomechanical model accurately reproduces vocal cord vibration.
  • Paralyzed vocal cords were shown to increase model coupling stiffness.
  • Distinct subglottal pressures and varying degrees of paralysis alter acoustic parameters like fundamental frequency.

Conclusions:

  • The developed system effectively models pathological voice production.
  • The study provides insights into the biomechanical effects of vocal cord paralysis.
  • The optimized asymmetric two-mass model offers high accuracy in simulating vocal cord vibration.