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Smartwatch AI could spot Parkinson's years before symptoms

NCT ID NCT07706829

Not yet recruiting Knowledge-focused Sponsor: Queen Mary University of London Source: ClinicalTrials.gov ↗

First seen Jul 16, 2026 · Last updated Jul 21, 2026 · Updated 3 times

Summary

This study tests whether an artificial intelligence model can estimate a person's risk of developing Parkinson's disease. Participants aged 50 and older who have certain early warning signs—like REM sleep behavior disorder, drops in blood pressure upon standing, or reduced sense of smell—wear a smartwatch and use a phone app for six months. The AI combines this digital data with clinical and genetic information to see how well it predicts brain changes linked to Parkinson's.

What this could mean

Our plain-language read of the trial. This is informational only — not medical advice or a prediction.

Active substance
smartwatch and phone app
What this could lead to
If successful, this could lead to a simple, non-invasive way to identify people at high risk for Parkinson's disease before major symptoms appear.
What could go wrong
This is an early, small proof-of-concept study. The AI model may not be accurate enough, and results may not apply to the general population.

This is an AI summary of the original study and may miss details. Read our disclaimer.

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Conditions

The condition(s) this trial relates to.

anosmia Parkinson disease primary orthostatic hypotension REM sleep behavior disorder

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

HYPOSMIA NEUROGENIC ORTHOSTATIC HYPOTENSION PARKINSON DISEASE (PD) REM SLEEP BEHAVIOR DISORDER (IRBD)

Contacts and locations

Study contacts

  • Contact

    Phone: •••-•••-•••• Email: •••••@•••••

Locations

  • Centre Hospitalier Universitaire de Toulouse

    Toulouse, France

    Contact Phone: •••-•••-•••• Email: •••••@•••••

  • Fundación Iniciativa para las Neurociencias. Hospital Ruber Internacional.

    Madrid, Spain

    Contact Phone: •••-•••-•••• Email: •••••@•••••

  • Queen Mary University of London

    London, United Kingdom

    Contact Phone: •••-•••-•••• Email: •••••@•••••

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