Automatic voice analysis for dysphagia detection
The result's identifiers
Result code in 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>
Result on the web
<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>
Alternative languages
Result language
angličtina
Original language name
Automatic voice analysis for dysphagia detection
Original language description
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.
Czech name
—
Czech description
—
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
30210 - Clinical neurology
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Speech, Language and Hearing
ISSN
2050-5728
e-ISSN
—
Volume of the periodical
21
Issue of the periodical within the volume
2
Country of publishing house
GB - UNITED KINGDOM
Number of pages
4
Pages from-to
86-89
UT code for WoS article
000434869900007
EID of the result in the Scopus database
2-s2.0-85031404349