J
Jan Rusz
Researcher at Czech Technical University in Prague
Publications - 98
Citations - 3208
Jan Rusz is an academic researcher from Czech Technical University in Prague. The author has contributed to research in topics: Dysarthria & Speech disorder. The author has an hindex of 26, co-authored 98 publications receiving 2260 citations. Previous affiliations of Jan Rusz include First Faculty of Medicine, Charles University in Prague & Charles University in Prague.
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Quantitative acoustic measurements for characterization of speech and voice disorders in early untreated Parkinson’s disease
TL;DR: It was found that measurement of the fundamental frequency variations applied to two selected tasks was the best method for separating healthy from PD subjects and it has been demonstrated that 78% of early untreated PD subjects indicate some form of vocal impairment.
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Automated analysis of connected speech reveals early biomarkers of Parkinson’s disease in patients with rapid eye movement sleep behaviour disorder
TL;DR: It is shown that subliminal parkinsonian speech deficits can be reliably captured even in RBD patients, which are at high risk of developing PD or other synucleinopathies, and automated vocal analysis should soon be able to contribute to screening and diagnostic procedures for prodromal parkinsonia in natural environments.
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Imprecise vowel articulation as a potential early marker of Parkinson's disease: effect of speaking task.
Jan Rusz,Roman Cmejla,Tereza Tykalová,Hana Ruzickova,Jiri Klempir,Veronika Majerová,Jana Picmausová,Jan Roth,Evzen Ruzicka +8 more
TL;DR: Impaired vowel articulation may be considered as a possible early marker of PD because complex tasks such as monologue are more likely to elicit articulatory deficits in parkinsonian speech, compared to other speaking tasks.
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Automatic detection of Parkinson's disease in running speech spoken in three different languages.
Juan Rafael Orozco-Arroyave,Florian Hönig,Julián D. Arias-Londoño,Jesús Francisco Vargas-Bonilla,Khaled Daqrouq,Sabine Skodda,Jan Rusz,Elmar Nöth +7 more
TL;DR: A method for the characterization of the speech signals, based on the automatic segmentation of utterances into voiced and unvoiced frames, is addressed here and proves to be more accurate than classical approaches in the automatic classification of speech of people with PD and healthy controls.
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Automatic evaluation of articulatory disorders in Parkinson's disease
TL;DR: Imprecise consonant articulation was found to be the most powerful indicator of PD-related dysarthria and is envisaged as the first step towards development of acoustic methods allowing the automated assessment of articulatory features in dysarthrias.