Development of Digital Services for Parkinson's Disease

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.

NCT Number	NCT06733077
Lead Sponsor	University of Exeter Collaborators: University of Zurich, University Hospital, Zürich, machineMD AG, GaitQ company
Conditions	Healthy Controls, Parkinson's Disease
Enrollment	80 participants
Start Date	2024-12-20
Primary Completion	2026-04-01 (estimated)
Study Completion	2026-04-01 (estimated)
Updated on ClinicalTrials.gov	2025-02-03