Evidence map›Paper›PMID 41467327›Full record

ArticleAnnals of neurology2026

Speech Biomarkers From Smartphone Calls Track Progression in REM Sleep Behavior Disorder and Parkinson's Disease.

Michal Šimek, Tereza Tykalová, Michal Novotný, Vojtěch Illner, Tomáš Kouba, Martin Šubert, Pavel Sovka, Jan Švihlík, Evžen Růžička, Karel Šonka and 2 more

Abstract read
In one paragraph

Article in Annals of neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Michal ŠimekDepartment of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
Tereza TykalováDepartment of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
Michal NovotnýDepartment of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
Vojtěch IllnerDepartment of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
Tomáš KoubaDepartment of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
Martin ŠubertDepartment of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
Pavel SovkaDepartment of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
Jan ŠvihlíkDepartment of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.
Evžen RůžičkaDepartment of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic.ORCID 0000-0002-4893-9661
Karel ŠonkaDepartment of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic.
Petr DušekDepartment of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic.
Jan RuszDepartment of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic.ORCID 0000-0002-1036-3054

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis 24-month longitudinal study involving isolated rapid eye movement sleep behavior disorder (iRBD), early-stage Parkinson's disease (PD), and matched healthy control subjects aimed to assess whether acoustic speech features from real-world smartphone calls provide passive progressive biomarkers in synucleinopathies.

methodsParticipants underwent clinical assessments at baseline, 1, and 2 years. Speech was continuously captured during phone calls via a standardized smartphone application, segmented, and analyzed for speech impairment severity end points and key acoustic features of monopitch, vowel articulation, voice quality, and articulation rate. We used linear mixed-effect modeling to estimate speech progression and calculated sample size requirements to demonstrate slowing of progression under anticipated treatment effects.

resultsOver 31,000 phone calls (>1,000 hours) were collected from 71 participants including those with iRBD, PD, and healthy controls. Compared with controls, both individuals with iRBD and PD showed significant declines in speech impairment severity end points based on spectral changes and artificial intelligence-based neural embeddings. The subjects with iRBD also exhibited declines in vowel articulation and articulation rate. For a 2-year neuroprotective trial aiming for 50% drug efficacy, the most efficient sample size estimate based on time-to-event analysis was 74 iRBD and 84 PD participants per arm using the neural embedding end point.

interpretationThe phone call analysis requiring no patient effort or clinical supervision can detect speech decline in prodromal and early synucleinopathies, providing a potential paradigm shift for clinical trial design and neuroprotective intervention end points. ANN NEUROL 2026;99:935-948.

Indexed as

Parkinson DiseaseREM Sleep Behavior DisorderSmartphoneSpeechAgedBiomarkersDisease ProgressionFemaleHumansLongitudinal StudiesMaleMiddle AgedBiomarkers

Identifiers

PMID41467327
PMCPMC13011784

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.