AI wearable could spot Parkinson's freezing episodes at home

NCT ID NCT07580612

Recruiting now Knowledge-focused Sponsor: KU Leuven Source: ClinicalTrials.gov ↗

First seen Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This study tests an artificial intelligence algorithm that uses wearable sensors to detect freezing of gait—a sudden inability to walk—in people with Parkinson's disease. Researchers want to see if the AI works accurately in home environments, not just in the lab. About 126 participants will wear sensors and perform walking tasks while being video-recorded for comparison. The goal is to improve fall risk monitoring and eventually enable real-time detection.

What this could mean

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

Active substance: artificial intelligence algorithm for gait analysis
What this could lead to: If successful, this could lead to a reliable home-based tool to automatically detect freezing of gait, helping doctors assess fall risk without requiring clinic visits.
What could go wrong: This is an early-stage validation study in a home setting, so the algorithm may not perform as well outside the lab. It is not a treatment and does not directly improve symptoms.

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Conditions

The condition(s) this trial relates to.

Parkinson disease

As listed by the trial registrant

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

ARTIFICAL INTELLIGENCE FREEZING OF GAIT PARKINSON DISEASE, IDIOPATHIC VALIDATION WEARABLE SENSORS

Contacts and locations

Locations

Center for the study of movement, cognition and mobility
NOT_YET_RECRUITING

Tel Aviv, 64, Israel
Department of Rehabilitation Sciences
RECRUITING

Leuven, 3001, Belgium
Sports Science and Neurorehabilitation
NOT_YET_RECRUITING

Hamburg, 20457, Germany

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