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LOPEZ-DE-IPINA, K. CALVO, P. FAÚNDEZ ZANUY, M. CLAVÉ, P. NASCIMENTO, W. MARTINEZ DE LIZARDUY, U. DANIEL, A. VIRIDIANA, A. ORTEGA, O. MEKYSKA, J. SANZ-CARTAGENA, M.
Original Title
Automatic voice analysis for dysphagia detection
Type
journal article in Scopus
Language
English
Original Abstract
Purpose: A videofluoroscopic analysis is the gold standard approach to determine whether a dysphagia problem exists. This procedure is invasive as it involves radiation but also provides the most direct physical evidence of swallowing problems. The main goal of this study was to evaluate an automatic tool based on voice analysis to support medical detection of dysphagia. Methods: An automatic voice analysis system has been developed. Prior to (basal) and immediately following (viscosity) swallowing liquids of varying viscosity and volume, individuals with Parkinson Disease were required to produce the same test word. The acoustic features (linear and non-linear) of this word were then analyzed with regard to specific situations by standard and Machine Learning methods. Results: The results indicated a high degree of accuracy in detecting voice associated with basal and viscosity states. Conclusion: Thus, while the gold standard of dysphagia diagnosis continues to involve video-fluoroscopy analysis, the consideration of voice analysis may prove to be a far simpler and less invasive approach to diagnosis by advanced voice features.
Keywords
voice analysis; dysphagia; Parkinson disease; detection
Authors
LOPEZ-DE-IPINA, K.; CALVO, P.; FAÚNDEZ ZANUY, M.; CLAVÉ, P.; NASCIMENTO, W.; MARTINEZ DE LIZARDUY, U.; DANIEL, A.; VIRIDIANA, A.; ORTEGA, O.; MEKYSKA, J.; SANZ-CARTAGENA, M.
Released
3. 4. 2018
Publisher
Taylor and Francis Ltd.
ISBN
2050-5728
Periodical
Speech, Language and Hearing
Year of study
21
Number
2
State
United Kingdom of Great Britain and Northern Ireland
Pages from
86
Pages to
89
Pages count
4
URL
http://www.tandfonline.com/doi/full/10.1080/2050571X.2017.1369017
BibTex
@article{BUT140606, author="Karmele {Lopez-de-Ipina} and Pilar {Calvo} and Marcos {Faúndez Zanuy} and Pere {Clavé} and Weslania Viviane {Nascimento} and Unai {Martinez de Lizarduy} and Alvarez-Berdugo {Daniel} and Arreola García {Viridiana} and Omar {Ortega} and Jiří {Mekyska} and M. Pilar {Sanz-Cartagena}", title="Automatic voice analysis for dysphagia detection", journal="Speech, Language and Hearing", year="2018", volume="21", number="2", pages="86--89", doi="10.1080/2050571X.2017.1369017", issn="2050-5728", url="http://www.tandfonline.com/doi/full/10.1080/2050571X.2017.1369017" }