Developing digital tools for diagnosing and monitoring Parkinson's disease
Official title: Development of Digital Diagnostics and Intervention Services for Parkinson's Disease
Run by University of Exeter · NCT06733077 · Data updated 2026-11-12
This study is testing new digital tools that use eye and walking data to see if they can help doctors diagnose and monitor Parkinson's disease more accurately.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 80 (estimated) |
| Sponsor | University of Exeter Academic / other |
| Locations | 1 site (Exeter) |
| Status | Recruiting |
| Started | December 20, 2024 |
| Main results expected | April 1, 2026 |
| Study ends | April 1, 2026 |
| Registry record updated | February 3, 2025 |
| Trial ID | NCT06733077 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates include adults diagnosed with idiopathic Parkinson's disease or related conditions who can self-report their symptoms and walk independently.
✕Probably not a fit
Patients with severe cognitive impairments or those unable to walk, even with assistance, may not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This project aims to collect ocular motor, pupil, and gait data from individuals with Parkinson's disease to create machine learning models for improved diagnosis and monitoring. By utilizing high-quality sensor data and integrating machine learning techniques, the study seeks to enhance the accuracy and timeliness of Parkinson's disease diagnoses. Participants will undergo standard clinical examinations alongside advanced measurements using approved medical devices and consumer technology for continuous gait monitoring. The goal is to move away from subjective assessments and provide objective, quantitative data for better patient care.
Why it matters
Potential benefit: If successful, this approach could lead to earlier and more accurate diagnoses of Parkinson's disease, improving patient outcomes.
How similar studies have gone: Other studies have shown promise in using digital health technologies and machine learning for monitoring Parkinson's disease, indicating a growing field of research.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion criteria Participants with Parkinson's \[Phase 1,2,3,4\] * Diagnosis of idiopathic Parkinson's disease (UK Brain Bank Criteria) or other appropriate condition specific scale \[stroke, multiple sclerosis, arthritis or osteoporosis\] * Able to self-report history of daily gait freezing and/or festination for people with PD or gait and/or transfers affected by condition * Able to walk unsupported or using an aid for at least 5 minutes and satisfactory completion of the Canadian PARQ and if over 69 used to carrying out this level of exercise * Adult (+18 years old) * Normal or corrected-to-normal vision (Snellen Visual Acuity \> 12/18) or safe to mobilise with support * Montreal Cognitive assessment score \>21 or ability to follow 2 stage commands Healthy participants \[Phase 1,2,3\] * With no long-term conditions affecting movement * Able to walk unsupported or using an aid for at least 3 minutes and satisfactory completion of the Canadian PARQ and if over 69 used to carrying out this level of exercise * Adult (+18 years old) * Normal or corrected-to-normal vision (Snellen Visual Acuity \> 12/18) or safe to mobilise with support * Montreal Cognitive assessment score \>21 or ability to follow 2 stage commands Exclusion criteria Participants with Parkinson's * Any physical or mental condition affecting ability to safely participate in this level of activity and capacity to understand testing as demonstrated by ability to safely follow commands and pass the PARQ by the research team. * Cognitive impairment affecting ability to safely participate and follow instructions * Any injury or disorder that may affect balance (other than Parkinson's or referring primary condition) * Any skin conditions or broken skin in the calf and behind knee area * Deep brain stimulation or pacemaker implants or other implant that may interfere with the measurement system * Medications likely to affect eye sight or use of virtual reality sytstem Healthy participants * Any physical or mental condition affecting ability to safely participate in this level of activity and capacity to understand testing as demonstrated by ability to safely follow commands and pass the PARQ by the research team. * Cognitive impairment affecting ability to safely participate and follow instructions * Any injury or disorder that may affect balance (other than Parkinson's or referring primary condition) * Any skin conditions or broken skin in the calf and behind knee area * Deep brain stimulation or pacemaker implants or other implants that may interfere with the measurement system
Where it's running
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University of Exeter
Exeter, United Kingdom Recruiting
Study contacts
- Principal investigator: Helen Dawes, PhD — University of Exeter
- Study coordinator: Pavlos Evangelidis, PhD
- Email: p.evangelidis@exeter.ac.uk
- Phone: 00447866138722
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.