RecruitingNAINTERVENTIONAL

Development of Digital Services for Parkinson's Disease

This study is working to create new digital tools to help diagnose and keep track of Parkinson's disease more accurately. Currently, diagnosing Parkinson's relies a lot on doctors' observations and patient reports, which can sometimes be unclear or change from day to day. Researchers will collect detailed information about how people's eyes move, how their pupils react, and how they walk, using special devices. They'll gather this data from people with Parkinson's and healthy volunteers. The goal is to use this information to build smart computer models that can spot Parkinson's earlier and monitor its progress more effectively, hopefully leading to more personalised care.

At a glance

Status

Recruiting

Phase

Sponsor

University of Exeter

Enrolment target

Start

20 Dec 2024

Estimated completion

01 Apr 2026

Healthy Controls Parkinson's Disease

What is this study about?

Parkinson's disease is a condition that affects the brain and can cause problems with movement. Currently, doctors usually diagnose Parkinson's by talking to patients about their health history, doing physical check-ups, and watching how they move. However, this can be tricky because symptoms can change day by day, and what patients remember or explain might not always be perfectly clear.

This study is looking for better ways to diagnose Parkinson's disease earlier and keep a closer eye on how it progresses. The researchers believe that by using new technology, they can get more exact information. They are collecting very detailed information about how people's eyes move, how their pupils react to light, and how they walk. They'll use special eye-tracking equipment and small sensors worn on the body for walking.

The aim is to use all this precise data to train computer programs (often called 'machine learning'). These programs will learn to recognise patterns that could help doctors diagnose Parkinson's disease more accurately and potentially at an earlier stage. This could mean people get the right care sooner, which is a really important step forward.

Key takeaways

Aims to create better digital tools for Parkinson's diagnosis and monitoring.
Collects detailed eye movement, pupil, and walking data.
Includes both people with Parkinson's and healthy volunteers.
Could lead to earlier and more accurate diagnosis in the future.
Uses advanced technology to gather precise information.
Participation helps advance understanding of Parkinson's disease.

Who may be eligible?

The study is looking for two main groups of people: adults (aged 18 or older) who have Parkinson's disease and healthy adults who do not have any long-term conditions affecting their movement.

For those with Parkinson's, you'd need to have received a formal diagnosis and be able to walk by yourself or with a walking aid for at least 5 minutes. You also need to have good enough vision (even with glasses or contacts) to see clearly and be able to understand and follow simple instructions.

For healthy volunteers, you'd also need to be able to walk on your own or with an aid for at least 3 minutes, have good vision, and be able to understand instructions easily. If you have any serious conditions that affect your balance, have certain implants like a pacemaker, or skin conditions on your calves/knees, you wouldn't be able to take part.

Could this study suit you?

Answer these quick questions to see if you may be eligible. This is a guide only — the research team makes the final call.

Are you 18 years old or older?
If you have Parkinson's, have you been formally diagnosed?
Can you walk on your own or with an aid for at least 5 minutes (if you have Parkinson's) or 3 minutes (if healthy)?
Do you have good vision (even with glasses/contacts)?
Can you understand and follow simple instructions?
Do you have any conditions that seriously affect your balance, or certain implants like a pacemaker?

Answer every question to see your result.

What does participation involve?

The study involves collecting data on your eye movements, pupil reactions, and how you walk. You'll use a special medical device for objective eye and pupil measurements. For walking, you'll wear a sensor (IMU sensor and GaitQ senti device). The study aims to gather this information to help develop digital services for diagnosis and monitoring. The total duration of your involvement isn't specified in detail but would likely involve a few appointments to collect this data.

Potential risks and benefits

Taking part in this study may not directly benefit you, but the information you provide could help improve how Parkinson's disease is diagnosed and monitored for future patients. There are no direct medical risks mentioned, but you might experience some mild discomfort from wearing the sensors or from the eye tests. You are free to withdraw from the study at any time, for any reason, without it affecting your medical care.

Locations (1)

Some site locations are approximate. We're improving this — please verify with the trial team before travelling.

University of Exeter
Verified postcode
Exeter, United Kingdom· Recruiting

Common questions

What is the main goal of this study?

The main goal is to create better digital tools to diagnose and monitor Parkinson's disease more accurately and earlier than current methods.

What kind of information will you collect from me?

Researchers will collect data on how your eyes move, how your pupils react, and how you walk, using special devices.

Is this study only for people with Parkinson's?

No, the study is for both adults with Parkinson's disease and healthy adults without conditions that affect movement.

Will taking part in this study improve my Parkinson's?

While this study might not directly improve your personal condition, your involvement is very important for improving future diagnosis and care for others with Parkinson's.

What does 'machine learning models' mean?

It means computer programs that can 'learn' from the collected data to find patterns and help doctors understand Parkinson's more effectively.

How to find out more

Pavlos Evangelidis, PhD

p.evangelidis@exeter.ac.uk 00447866138722 Official trial record

Always speak to your GP or specialist before deciding to take part in a study.