Publication detail

Evaluating Instability on Phonation in Parkinson's Disease and Aging Speech

GOMEZ-RODELLAR, A. PALACIOS-ALONSO, D. FERRÁNDEZ VICENTE, J.M. MEKYSKA, J. ALVAREZ MARQUINA, A. GOMEZ-VILDA, P.

Original Title

Evaluating Instability on Phonation in Parkinson's Disease and Aging Speech

English Title

Evaluating Instability on Phonation in Parkinson's Disease and Aging Speech

Type

book chapter

Language

en

Original Abstract

Speech is controlled by axial neuromotor systems, highly sensible to certain neurodegenerative illnesses as Parkinson’s Disease (PD). Patients suffering PD present important alterations in speech, which manifest in phonation, articulation, prosody and fluency. Usually phonation and articulation alterations are estimated using different statistical frameworks and methods. The present study introduces a new paradigm based on Information Theory fundamentals to use common statistical tools to differentiate and score PD speech on phonation and articulation estimates. A study describing the performance of a methodology based on this common framework on a database including 16 PD patients, 16 age-paired healthy controls (HC) and 16 mid-age normative subjects (NS) is presented. The results point out to the clear separation between PD patients and HC subjects with respect to NS, but an unclear differentiation between PD and HC. The most important conclusion is that special effort is needed to establish differentiating features between PD, and organic laryngeal, from aging speech.

English abstract

Speech is controlled by axial neuromotor systems, highly sensible to certain neurodegenerative illnesses as Parkinson’s Disease (PD). Patients suffering PD present important alterations in speech, which manifest in phonation, articulation, prosody and fluency. Usually phonation and articulation alterations are estimated using different statistical frameworks and methods. The present study introduces a new paradigm based on Information Theory fundamentals to use common statistical tools to differentiate and score PD speech on phonation and articulation estimates. A study describing the performance of a methodology based on this common framework on a database including 16 PD patients, 16 age-paired healthy controls (HC) and 16 mid-age normative subjects (NS) is presented. The results point out to the clear separation between PD patients and HC subjects with respect to NS, but an unclear differentiation between PD and HC. The most important conclusion is that special effort is needed to establish differentiating features between PD, and organic laryngeal, from aging speech.

Keywords

Parkinson’s disease; phonation distortion; aging speech; speech neuromechanics

Released

10.05.2019

ISBN

978-3-030-19650-9

Book

From Bioinspired Systems and Biomedical Applications to Machine Learning

Pages from

340

Pages to

351

Pages count

12

URL

BibTex


@inbook{BUT156879,
  author="Jiří {Mekyska}",
  title="Evaluating Instability on Phonation in Parkinson's Disease and Aging Speech",
  annote="Speech is controlled by axial neuromotor systems, highly sensible to certain neurodegenerative illnesses as Parkinson’s Disease (PD). Patients suffering PD present important alterations in speech, which manifest in phonation, articulation, prosody and fluency. Usually phonation and articulation alterations are estimated using different statistical frameworks and methods. The present study introduces a new paradigm based on Information Theory fundamentals to use common statistical tools to differentiate and score PD speech on phonation and articulation estimates. A study describing the performance of a methodology based on this common framework on a database including 16 PD patients, 16 age-paired healthy controls (HC) and 16 mid-age normative subjects (NS) is presented. The results point out to the clear separation between PD patients and HC subjects with respect to NS, but an unclear differentiation between PD and HC. The most important conclusion is that special effort is needed to establish differentiating features between PD, and organic laryngeal, from aging speech.",
  booktitle="From Bioinspired Systems and Biomedical Applications to Machine Learning",
  chapter="156879",
  doi="10.1007/978-3-030-19651-6_33",
  howpublished="print",
  year="2019",
  month="may",
  pages="340--351",
  type="book chapter"
}