Automatic voice analysis for dysphagia detection

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F18%3APU125121" target="_blank" >RIV/00216305:26220/18:PU125121 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.tandfonline.com/doi/full/10.1080/2050571X.2017.1369017" target="_blank" >http://www.tandfonline.com/doi/full/10.1080/2050571X.2017.1369017</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/2050571X.2017.1369017" target="_blank" >10.1080/2050571X.2017.1369017</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Automatic voice analysis for dysphagia detection

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Automatic voice analysis for dysphagia detection

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30210 - Clinical neurology

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Speech, Language and Hearing

ISSN

2050-5728

e-ISSN

—

Svazek periodika

21

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

4

Strana od-do

86-89

Kód UT WoS článku

000434869900007

EID výsledku v databázi Scopus

2-s2.0-85031404349