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This study will investigate new, non-invasive methods to help diagnose Parkinson's disease. Researchers will use advanced eye imaging (hyperspectral retinal photography and OCT), computerized memory and thinking tests, and voice analysis to identify patterns linked to Parkinson's. The goal is to improve early and accurate diagnosis of Parkinson's disease without the need for spinal taps or invasive tests.
Full description
This study aims to improve how Parkinson's disease is diagnosed by testing new, non-invasive techniques that do not require spinal taps or other invasive procedures. Researchers are investigating whether changes in the eye's retina, detected with hyperspectral imaging and optical coherence tomography (OCT), can help pinpoint Parkinson's disease. These methods use special photographs and scans, similar to those performed at an eye clinic or optometrist, to analyze patterns linked to nerve cells and blood vessels in the retina.
Additionally, participants will take computerized tests to measure memory, attention, and thinking skills. Since Parkinson's disease can also affect speech, the study will analyze voice recordings for specific changes that are common in the disease, such as reduced volume and strength. By combining information from eye images, cognitive tests, and voice analysis, the project hopes to develop a faster and more accurate way to diagnose Parkinson's disease at an earlier stage.
The study is open to both people with Parkinson's disease and healthy volunteers, and the new diagnostic tools being tested could make future diagnosis simpler, more comfortable, and accessible to a wider population
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Inclusion and exclusion criteria
Inclusion criteria for Parkinson's group:
Inclusion criteria for control group:
Exclusion criteria:
Definition of healthy:
60 participants in 2 patient groups
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Central trial contact
Anders Behrens, MD. PhD.
Data sourced from clinicaltrials.gov
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