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Erschienen in: Cognitive Computation 4/2013

01.12.2013

Characterizing Neurological Disease from Voice Quality Biomechanical Analysis

verfasst von: Pedro Gómez-Vilda, Victoria Rodellar-Biarge, Víctor Nieto-Lluis, Cristina Muñoz-Mulas, Luis Miguel Mazaira-Fernández, Rafael Martínez-Olalla, Agustín Álvarez-Marquina, Carlos Ramírez-Calvo, Mario Fernández-Fernández

Erschienen in: Cognitive Computation | Ausgabe 4/2013

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Abstract

The dramatic impact of neurological degenerative pathologies in life quality is a growing concern nowadays. Many techniques have been designed for the detection, diagnosis, and monitoring of the neurological disease. Most of them are too expensive or complex for being used by primary attention medical services. On the other hand, it is well known that many neurological diseases leave a signature in voice and speech. Through the present paper, a new method to trace some neurological diseases at the level of phonation will be shown. In this way, the detection and grading of the neurological disease could be based on a simple voice test. This methodology is benefiting from the advances achieved during the last years in detecting and grading organic pathologies in phonation. The paper hypothesizes that some of the underlying neurological mechanisms affecting phonation produce observable correlates in vocal fold biomechanics and that these correlates behave differentially in neurological diseases than in organic pathologies. A general description about the main hypotheses involved and their validation by acoustic voice analysis based on biomechanical correlates of the neurological disease is given. The validation is carried out on a balanced database of normal and organic dysphonic patients of both genders. Selected study cases will be presented to illustrate the possibilities offered by this methodology.

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Metadaten
Titel
Characterizing Neurological Disease from Voice Quality Biomechanical Analysis
verfasst von
Pedro Gómez-Vilda
Victoria Rodellar-Biarge
Víctor Nieto-Lluis
Cristina Muñoz-Mulas
Luis Miguel Mazaira-Fernández
Rafael Martínez-Olalla
Agustín Álvarez-Marquina
Carlos Ramírez-Calvo
Mario Fernández-Fernández
Publikationsdatum
01.12.2013
Verlag
Springer US
Erschienen in
Cognitive Computation / Ausgabe 4/2013
Print ISSN: 1866-9956
Elektronische ISSN: 1866-9964
DOI
https://doi.org/10.1007/s12559-013-9207-2

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