BACKGROUND: Speech dysfunction represents one of the initial motor manifestations to develop in Parkinson's disease (PD) and is measurable through smartphone. OBJECTIVE: The aim was to develop a fully automated and noise-resistant smartphone-based system that can unobtrusively screen for prodromal parkinsonian speech disorder in subjects with isolated rapid eye movement sleep behavior disorder (iRBD) in a real-world scenario. METHODS: This cross-sectional study assessed regular, everyday voice call data from individuals with iRBD compared to early PD patients and healthy controls via a developed smartphone application. The participants also performed an active, regular reading of a short passage on their smartphone. Smartphone data were continuously collected for up to 3 months after the standard in-person assessments at the clinic. RESULTS: A total of 3525 calls that led to 5990 minutes of preprocessed speech were extracted from 72 participants, comprising 21 iRBD patients, 26 PD patients, and 25 controls. With a high area under the curve of 0.85 between iRBD patients and controls, the combination of passive and active smartphone data provided a comparable or even more sensitive evaluation than laboratory examination using a high-quality microphone. The most sensitive features to induce prodromal neurodegeneration in iRBD included imprecise vowel articulation during phone calls (P = 0.03) and monopitch in reading (P = 0.05). Eighteen minutes of speech corresponding to approximately nine calls was sufficient to obtain the best sensitivity for the screening. CONCLUSION: We consider the developed tool widely applicable to deep longitudinal digital phenotyping data with future applications in neuroprotective trials, deep brain stimulation optimization, neuropsychiatry, speech therapy, population screening, and beyond. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Department of Circuit Theory Faculty of Electrical Engineering Czech Technical University Prague Prague Czech Republic

Department of Mathematics Informatics and Cybernetics Faculty of Chemical Engineering University of Chemistry and Technology Prague Czech Republic

Department of Neurology and ARTORG Center Inselspital Bern University Hospital University of Bern Bern Switzerland

Department of Neurology and Centre of Clinical Neuroscience 1st Faculty of Medicine Charles University and General University Hospital Prague Czech Republic

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Nat Rev Neurol. 2024 Sep;20(9):505. doi: 10.1038/s41582-024-01007-0. PubMed

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