Monitoring ALS from speech articulation kinematics

  • Pedro Gómez
  • Ana R. M. Londral
  • Andrés Gómez
  • Daniel Palacios
  • Victoria Rodellar
S.I. : Advances in Bio-Inspired Intelligent Systems
  • 6 Downloads

Abstract

Patients affected by amyotrophic lateral sclerosis (ALS) show specific dysarthria in their speech resulting in specific marks which could be used to detect early symptoms and monitor the evolution of the disease in time. Classically articulation marks have been mainly based on static premises. Articulation kinematics from acoustic correlates may help in producing measurements depending on the dynamic behaviour of speech. Specifically, distribution functions from the absolute kinematic velocity estimated on a simplified articulation model can be used in establishing distances based on information theory concepts between running speech segments from patients and controls. As an example, several cases of ALS were studied longitudinally using this methodology. The study shows that the performance of dynamic articulation quality correlates may be sensitive and robust in tracking illness progress. Conclusions foresee the use of speech as a valuable monitoring methodology for ALS timely neurodegenerative progression.

Keywords

Amyotrophic lateral sclerosis Neuromotor diseases Kullback–Leibler divergence Speech articulation 

Notes

Acknowledgments

This work was supported by Calouste Gulbenkian Foundation and the Portuguese Association of ALS (APELA), as well as by Grant TEC2016-77791-C4-4-R (Plan Nacional de I + D+i, Ministry of Economic Affairs and Competitiveness of Spain).

Compliance with ethical standards

Conflict of interest

The authors declare that this research has been conducted according to the Helsinki Declaration on ethical standards, it has been carried on public or non-profit funding, and they do not have any conflict of interest regarding the research objectives, procedures and results.

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Copyright information

© The Natural Computing Applications Forum 2018

Authors and Affiliations

  1. 1.Center for Biomedical TechnologyUniversidad Politécnica de MadridPozuelo De Alarcón, MadridSpain
  2. 2.Translational Clinical Physiology Lab, Instituto de Medicina MolecularUniversity of LisbonLisbonPortugal
  3. 3.Escola Superior de Tecnologia de SetúbalInstituto Politécnico de SetúbalSetúbalPortugal

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