Observatorio de I+D+i UPM

Memorias de investigación
Artículos en revistas:
A forced gaussians based methodology for the differential evaluation of Parkinson's Disease by means of speech processing
Año:2019
Áreas de investigación
  • Tecnología electrónica y de las comunicaciones,
  • Ciencias de la computación y tecnología informática
Datos
Descripción
Literature evidences the existence of hypokinetic dysarthria in parkinsonian patients and, consequently, the objective characterization of the dysarthric signs associated to the articulatory aspect of speech can be used to detect Parkinson?s Disease (PD) providing clinicians with new tools to support the clinical diagnosis. However, no work has analyzed in detail the importance of the different phonemes in the automatic detection of PD from the speech. This work proposes new approaches for this detection by using new classification schemes that allow to compare independently the different phonetic units of patients and controls employed during several speechtasks. Three different parkinsoniancorpora were used allowing cross-validationand cross-corpora trials. The results of cross-validation trials (k-folds) provided accuracies between 81% and 94%, with AUC between 0.87 and 0.97 depending on the corpus, while cross-corpora trials yielded accuracies between 66% and 76% with AUC between 0.76 and 0.87. These results suggest that PD affects to the articulatory sequence as a whole, influencing more clearly phonetic units requiring a higher narrowing of the vocal tract. Additionally, text-dependent utterances are considered as the recommended speech task for the detection of PD in this type of schemes as these allow to compare more precisely the phonetic units of patients and controls. Lastly, this work discusses the existence of a glass ceiling in the accuracy of the systems for the automatic detection of PD using speech, concluding that this is below 95% for most of the cases.
Internacional
Si
JCR del ISI
Si
Título de la revista
Biomedical Signal Processing And Control
ISSN
1746-8094
Factor de impacto JCR
3,137
Información de impacto
Volumen
48
DOI
10.1016/j.bspc.2018.10.020
Número de revista
Desde la página
205
Hasta la página
220
Mes
SIN MES
Ranking
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Participantes
  • Autor: L. Moro-Velázquez (Johns Hopkins University)
  • Autor: Jorge Andres Gomez Garcia (UPM)
  • Autor: Juan Ignacio Godino Llorente (UPM)
  • Autor: J Villalba (Johns Hopkins University)
  • Autor: J. Rusz (University of Prague)
  • Autor: S. Shattuck-Hufnagel (Massachusetts institute of Technology)
  • Autor: N. Dehak (Johns Hopkins University)
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Investigación en Bioingeniería y Optoelectrónica
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