Condition: Healthy Controls · Parkinson's Disease · Sponsor: University of Exeter
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.
This description comes directly from the study's public registry record.
Pavlos Evangelidis, PhD · 00447866138722 · p.evangelidis@exeter.ac.uk
Helen Dawes, PhD · 01392 40 2969 · H.Dawes@exeter.ac.uk
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| University of Exeter | Exeter, United Kingdom | Recruiting |
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Source record: clinicaltrials.gov/study/NCT06733077