Diego Guarin, PhD, an assistant professor of applied physiology and kinesiology in the University of Florida’s College of Health and Human Performance has developed an open-source computer program that uses artificial intelligence (AI) to analyze videos of patients with Parkinson’s disease and other movement disorders, thereby addressing the potential risk of inconsistency and subjectivity in traditional clinical assessments. The tool, called VisionMD, helps doctors more accurately monitor subtle motor changes, improving patient care and advancing clinical research. VisionMD analyzes standard videos—whether recorded on a smartphone, laptop, or over Zoom—and automatically extracts precise motion metrics. The software runs entirely on local computers, ensuring data privacy.
Florian Lange, a neurologist at University Hospital Würzburg, Germany, and Martin Reich, a neuroimaging professor at University of Würzburg, Germany, adapted VisionMD to help them optimize treatment for patients with tremor, particularly those using deep brain stimulation (DBS) implants.
“A big challenge with many aspects of medicine today is how difficult it is to get objective data, especially with movement disorders like Parkinson’s disease or tremor,” Lange said. “If…[we] watched the same video of a patient, we might rate the severity at…different levels. But the software gives us precise, unbiased data.” By recording videos of patients at a variety of stimulator settings, the software identifies which DBS configuration offers the best symptom relief.
As open-source software, the program is freely available to improve and customize. The team is also working to expand the tool’s capabilities by adding more motor assessment tasks frequently used in clinical settings. Early adopters say VisionMD’s accessibility and ease of use have the potential to transform movement disorder research and care.
To access VisionMD, go to https://mea-lab.github.io/VisionMD-Tutorial/.
