A Methodology to Differentiate Parkinson's Disease and Aging Speech Based on Glottal Flow Acoustic Analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F20%3APU137165" target="_blank" >RIV/00216305:26220/20:PU137165 - isvavai.cz</a>
Result on the web
<a href="https://www.worldscientific.com/doi/pdf/10.1142/S0129065720500586" target="_blank" >https://www.worldscientific.com/doi/pdf/10.1142/S0129065720500586</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1142/S0129065720500586" target="_blank" >10.1142/S0129065720500586</a>
Alternative languages
Result language
angličtina
Original language name
A Methodology to Differentiate Parkinson's Disease and Aging Speech Based on Glottal Flow Acoustic Analysis
Original language description
Speech is controlled by axial neuromotor systems, therefore, it is highly sensitive to the effects of neurodegenerative illnesses such as Parkinson’s Disease (PD). Patients suffering from PD present important alterations in speech, which are manifested in phonation, articulation, prosody, and fluency. These alterations may be evaluated using statistical methods on features obtained from glottal, spectral, cepstral, or fractal descriptions of speech. This work introduces an evaluation paradigm based on Information Theory (IT) to differentiate the effects of PD and aging on glottal amplitude distributions. The study is conducted on a database including 48 PD patients (24 males, 24 females), 48 age-matched healthy controls (HC, 24 males, 24 females), and 48 mid-age normative subjects (NS, 24 males, 24 females). It may be concluded from the study that Hierarchical Clustering (HiCl) methods produce a clear separation between the phonation of PD patients from NS subjects (accuracy of 89.6% for both male and female subsets), but the separation between PD patients and HC subjects is less efficient (accuracy of 75.0% for the male subset and 70.8% for the female subset). Conversely, using feature selection and Support Vector Machine (SVM) classification, the differentiation between PD and HC is substantially improved (accuracy of 94.8% for the male subset and 92.8% for the female subset). This improvement was mainly boosted by feature selection, at a cost of information and generalization losses. The results point to the possibility that speech deterioration may affect HC phonation with aging, reducing its difference to PD phonation.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20601 - Medical engineering
Result continuities
Project
<a href="/en/project/NU20-04-00294" target="_blank" >NU20-04-00294: Diagnostics of Lewy body diseases in prodromal stage based on multimodal data analysis</a><br>
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS
ISSN
0129-0657
e-ISSN
1793-6462
Volume of the periodical
2050058
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
20
Pages from-to
1-20
UT code for WoS article
000575545000005
EID of the result in the Scopus database
2-s2.0-85091556886