Publication detail

Advances in a Multimodal Approach for Dysphagia Analysis Based on Automatic Voice Analysis

LOPEZ-DE-IPINA, K. SATUE-VILLAR, A. FAÚNDEZ ZANUY, M. ARREOLA, V. ORTEGA, O. CLAVÉ, P. SANZ-CARTAGENA, M. MEKYSKA, J. CALVO, P.

Original Title

Advances in a Multimodal Approach for Dysphagia Analysis Based on Automatic Voice Analysis

English Title

Advances in a Multimodal Approach for Dysphagia Analysis Based on Automatic Voice Analysis

Type

book chapter

Language

en

Original Abstract

Parkinson’s disease (PD) is the second most frequent neurodegenerative disease with prevalence among general population reaching 0.1–1 %, and an annual incidence between 1.3–2.0/10,000 inhabitants. The most obvious symptoms are movement-related such as tremor, rigidity, slowness of movement and walking difficulties and frequently these are the symptoms that lead to the PD diagnoses but also they could have dysphagia. In this sense voice analysis is a safe, non-invasive, and reliable screening procedure for PD patients with dysphagia, which could detect patients at high risk of clinically significant aspiration. In this paper we will present a part of an ongoing project that will evaluate automatic speech analysis based on linear and non-linear features. These can be reliable predictors/indicators of swallowing and balance impairments in PD. An important advantage of voice analysis is its low intrusiveness and easy implementation in clinical practice. Thus, if a significant correlation between these simple analyses and the gold standard video-fluoroscopic analysis will imply simpler and less stressing diagnostic test for the patients as well as the use of cheaper analysis systems.

English abstract

Parkinson’s disease (PD) is the second most frequent neurodegenerative disease with prevalence among general population reaching 0.1–1 %, and an annual incidence between 1.3–2.0/10,000 inhabitants. The most obvious symptoms are movement-related such as tremor, rigidity, slowness of movement and walking difficulties and frequently these are the symptoms that lead to the PD diagnoses but also they could have dysphagia. In this sense voice analysis is a safe, non-invasive, and reliable screening procedure for PD patients with dysphagia, which could detect patients at high risk of clinically significant aspiration. In this paper we will present a part of an ongoing project that will evaluate automatic speech analysis based on linear and non-linear features. These can be reliable predictors/indicators of swallowing and balance impairments in PD. An important advantage of voice analysis is its low intrusiveness and easy implementation in clinical practice. Thus, if a significant correlation between these simple analyses and the gold standard video-fluoroscopic analysis will imply simpler and less stressing diagnostic test for the patients as well as the use of cheaper analysis systems.

Keywords

Speech analysis, dysphagia, Parkinson’s disease, database

Released

19.06.2016

Publisher

Springer International Publishing

Location

Switzerland

ISBN

978-3-319-33746-3

Book

Advances in Neural Networks

Pages from

201

Pages to

211

Pages count

11

BibTex


@inbook{BUT126225,
  author="Karmele {Lopez-de-Ipina} and Antonio {Satue-Villar} and Marcos {Faúndez Zanuy} and Viridiana {Arreola} and Omar {Ortega} and Pere {Clavé} and M. Pilar {Sanz-Cartagena} and Jiří {Mekyska} and Pilar {Calvo}",
  title="Advances in a Multimodal Approach for Dysphagia Analysis Based on Automatic Voice Analysis",
  annote="Parkinson’s disease (PD) is the second most frequent neurodegenerative disease with prevalence among general population reaching 0.1–1 %, and an annual incidence between 1.3–2.0/10,000 inhabitants. The most obvious symptoms are movement-related such as tremor, rigidity, slowness of movement and walking difficulties and frequently these are the symptoms that lead to the PD diagnoses but also they could have dysphagia. In this sense voice analysis is a safe, non-invasive, and reliable screening procedure for PD patients with dysphagia, which could detect patients at high risk of clinically significant aspiration. In this paper we will present a part of an ongoing project that will evaluate automatic speech analysis based on linear and non-linear features. These can be reliable predictors/indicators of swallowing and balance impairments in PD. An important advantage of voice analysis is its low intrusiveness and easy implementation in clinical practice. Thus, if a significant correlation between these simple analyses and the gold standard video-fluoroscopic analysis will imply simpler and less stressing diagnostic test for the patients as well as the use of cheaper analysis systems.",
  address="Springer International Publishing",
  booktitle="Advances in Neural Networks",
  chapter="126225",
  doi="10.1007/978-3-319-33747-0_20",
  howpublished="print",
  institution="Springer International Publishing",
  year="2016",
  month="june",
  pages="201--211",
  publisher="Springer International Publishing",
  type="book chapter"
}