Development of Digital Services for Parkinson's Disease
Recruiting now · Not applicable
Conditions studied: Healthy Controls, Parkinson's Disease
In brief
In this project, ocular motor, pupil and gait data in people with Parkinson's disease (PD) will be collected in order to develop machine learning models for the diagnosis and monitoring of PD. With this, the investigators aim to advance the state of the art in PD diagnosis and monitoring. By integrating the principles of machine learning with high-quality sensor data, more accurate and earlier diagnosis could potentially be achieved. Ocular motor and pupil data will be collected with the standard clinical examination and with neos, a medical device approved for objective ocular motor and pupil measurement. Gait will be collected using an IMU sensor and GaitQ senti, a consumer device that allows for an objective and continuous remote gait monitoring.
Key facts
- Study ID
- NCT06733077
- Run by
- University of Exeter
- People needed
- 80
- Starts
- 2024-12-20
- Expected to finish
- 2026-04-01
- Last updated by the study team
- 2025-02-03
Who can join
Age: 18 and older. Sex: any. Healthy volunteers: accepted.
Where it is running
- University of Exeter — Exeter, United Kingdom (enrolling)
Full record on ClinicalTrials.gov
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