Automated analysis of connected speech reveals early biomarkers of Parkinson’s disease in patients with rapid eye movement sleep behaviour disorder

Abstract For generations, the evaluation of speech abnormalities in neurodegenerative disorders such as Parkinson’s disease (PD) has been limited to perceptual tests or user-controlled laboratory analysis based upon rather small samples of human vocalizations. Our study introduces a fully automated...

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Autores principales:	Jan Hlavnička, Roman Čmejla, Tereza Tykalová, Karel Šonka, Evžen Růžička, Jan Rusz
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/b75bee7e9b214b98a624b63b64969a44
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spelling	oai:doaj.org-article:b75bee7e9b214b98a624b63b64969a442021-12-02T16:07:58ZAutomated analysis of connected speech reveals early biomarkers of Parkinson’s disease in patients with rapid eye movement sleep behaviour disorder10.1038/s41598-017-00047-52045-2322https://doaj.org/article/b75bee7e9b214b98a624b63b64969a442017-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-00047-5https://doaj.org/toc/2045-2322Abstract For generations, the evaluation of speech abnormalities in neurodegenerative disorders such as Parkinson’s disease (PD) has been limited to perceptual tests or user-controlled laboratory analysis based upon rather small samples of human vocalizations. Our study introduces a fully automated method that yields significant features related to respiratory deficits, dysphonia, imprecise articulation and dysrhythmia from acoustic microphone data of natural connected speech for predicting early and distinctive patterns of neurodegeneration. We compared speech recordings of 50 subjects with rapid eye movement sleep behaviour disorder (RBD), 30 newly diagnosed, untreated PD patients and 50 healthy controls, and showed that subliminal parkinsonian speech deficits can be reliably captured even in RBD patients, which are at high risk of developing PD or other synucleinopathies. Thus, automated vocal analysis should soon be able to contribute to screening and diagnostic procedures for prodromal parkinsonian neurodegeneration in natural environments.Jan HlavničkaRoman ČmejlaTereza TykalováKarel ŠonkaEvžen RůžičkaJan RuszNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-13 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jan Hlavnička Roman Čmejla Tereza Tykalová Karel Šonka Evžen Růžička Jan Rusz Automated analysis of connected speech reveals early biomarkers of Parkinson’s disease in patients with rapid eye movement sleep behaviour disorder
description	Abstract For generations, the evaluation of speech abnormalities in neurodegenerative disorders such as Parkinson’s disease (PD) has been limited to perceptual tests or user-controlled laboratory analysis based upon rather small samples of human vocalizations. Our study introduces a fully automated method that yields significant features related to respiratory deficits, dysphonia, imprecise articulation and dysrhythmia from acoustic microphone data of natural connected speech for predicting early and distinctive patterns of neurodegeneration. We compared speech recordings of 50 subjects with rapid eye movement sleep behaviour disorder (RBD), 30 newly diagnosed, untreated PD patients and 50 healthy controls, and showed that subliminal parkinsonian speech deficits can be reliably captured even in RBD patients, which are at high risk of developing PD or other synucleinopathies. Thus, automated vocal analysis should soon be able to contribute to screening and diagnostic procedures for prodromal parkinsonian neurodegeneration in natural environments.
format	article
author	Jan Hlavnička Roman Čmejla Tereza Tykalová Karel Šonka Evžen Růžička Jan Rusz
author_facet	Jan Hlavnička Roman Čmejla Tereza Tykalová Karel Šonka Evžen Růžička Jan Rusz
author_sort	Jan Hlavnička
title	Automated analysis of connected speech reveals early biomarkers of Parkinson’s disease in patients with rapid eye movement sleep behaviour disorder
title_short	Automated analysis of connected speech reveals early biomarkers of Parkinson’s disease in patients with rapid eye movement sleep behaviour disorder
title_full	Automated analysis of connected speech reveals early biomarkers of Parkinson’s disease in patients with rapid eye movement sleep behaviour disorder
title_fullStr	Automated analysis of connected speech reveals early biomarkers of Parkinson’s disease in patients with rapid eye movement sleep behaviour disorder
title_full_unstemmed	Automated analysis of connected speech reveals early biomarkers of Parkinson’s disease in patients with rapid eye movement sleep behaviour disorder
title_sort	automated analysis of connected speech reveals early biomarkers of parkinson’s disease in patients with rapid eye movement sleep behaviour disorder
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/b75bee7e9b214b98a624b63b64969a44
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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

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