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Glottal Flow Patterns Analyses for Parkinson’s Disease Detection: Acoustic and Nonlinear Approaches

  • Elkyn Alexander Belalcázar-BolañosEmail author
  • Juan Rafael Orozco-Arroyave
  • Jesús Francisco Vargas-Bonilla
  • Tino Haderlein
  • Elmar Nöth
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9924)

Abstract

In this paper we propose a methodology for the automatic detection of Parkinson’s Disease (PD) by using several glottal flow measures including different time-frequency (TF) parameters and nonlinear behavior of the vocal folds. Additionally, the nonlinear behavior of the vocal tract is characterized using the residual wave. The proposed approach allows modeling phonation (glottal flow) and articulation (residual wave) properties of speech separately, which opens the possibility to address symptoms related to dysphonia and dysarthria in PD, independently. Speech recordings of the five Spanish vowels uttered by a total of 100 speakers (50 with PD and 50 Healthy Controls) are considered. The results indicate that the proposed approach allows the automatic discrimination of PD patients and healthy controls with accuracies of up to \(78\,\%\) when using the TF-based measures.

Keywords

Dysarthria Nonlinear behavior Glottal flow Parkinson’s Disease Dysphonia Time-frequency 

Notes

Acknowledgments

This work was financed by COLCIENCIAS, project N o 111556933858.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Elkyn Alexander Belalcázar-Bolaños
    • 1
    Email author
  • Juan Rafael Orozco-Arroyave
    • 1
    • 2
  • Jesús Francisco Vargas-Bonilla
    • 1
  • Tino Haderlein
    • 2
  • Elmar Nöth
    • 2
  1. 1.Faculty of EngineeringUniversidad de Antioquia UdeAMedellínColombia
  2. 2.Pattern Recognition LabFriedrich-Alexander-Universität Erlangen-Nürnberg (FAU)ErlangenGermany

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