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Smartphone Allows Capture of Speech Abnormalities Associated With High Risk of Developing Parkinson's Disease

J Rusz, J Hlavnicka, T Tykalova, M Novotny, P Dusek, K Sonka, E Ruzicka

Jazyk angličtina Země Spojené státy americké

Perzistentní odkaz   https://www.medvik.cz/link/bmc20016377

Grantová podpora
NV15-28038A MZ0 CEP - Centrální evidence projektů
NV16-28914A MZ0 CEP - Centrální evidence projektů

Although smartphone technology provides new opportunities for the recording of speech samples in everyday life, its ability to capture prodromal speech impairment in persons with a high risk of developing Parkinson's disease (PD) has never been investigated. Speech data were acquired through a smartphone as well as a professional microphone with a linear frequency response from 50 participants with a rapid eye movement sleep behavior disorder that are at a high risk of developing PD and related neurodegenerative disorders. Additionally, recordings of 30 newly diagnosed, untreated PD patients and 30 healthy participants were evaluated. Acoustic assessment of 11 speech dimensions representing the key aspects of hypokinetic dysarthria in the early stages of PD was performed. Smartphone allowed the detection of speech abnormalities in participants with a high risk of developing PD. Acoustic measurements related to fundamental frequency variability, duration of pause intervals, and rate of speech timing extracted from spontaneous speech were sufficiently sensitive to significantly separate groups (area under curve of 0.85 between PD and controls) and showed very strong correlation and reliability between the professional microphone and the smartphone. Speech-based biomarkers collected through smartphones may have the potential to revolutionize the diagnostic process in neurodegenerative diseases and improve stratification for future neuroprotective therapy in PD.

Citace poskytuje Crossref.org

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$a Although smartphone technology provides new opportunities for the recording of speech samples in everyday life, its ability to capture prodromal speech impairment in persons with a high risk of developing Parkinson's disease (PD) has never been investigated. Speech data were acquired through a smartphone as well as a professional microphone with a linear frequency response from 50 participants with a rapid eye movement sleep behavior disorder that are at a high risk of developing PD and related neurodegenerative disorders. Additionally, recordings of 30 newly diagnosed, untreated PD patients and 30 healthy participants were evaluated. Acoustic assessment of 11 speech dimensions representing the key aspects of hypokinetic dysarthria in the early stages of PD was performed. Smartphone allowed the detection of speech abnormalities in participants with a high risk of developing PD. Acoustic measurements related to fundamental frequency variability, duration of pause intervals, and rate of speech timing extracted from spontaneous speech were sufficiently sensitive to significantly separate groups (area under curve of 0.85 between PD and controls) and showed very strong correlation and reliability between the professional microphone and the smartphone. Speech-based biomarkers collected through smartphones may have the potential to revolutionize the diagnostic process in neurodegenerative diseases and improve stratification for future neuroprotective therapy in PD.
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