Video processing and AI track progression of Parkinson’s disease

Developed by Diego Guarin, PhD, an assistant professor of applied physiology and kinesiology at the University of Florida (UF), the system applies machine learning to analyse video recordings of patients performing the finger-tapping test, a standard test for Parkinson’s disease that involves quickly tapping the thumb and index finger 10 times. 

“By studying these videos, we could detect even the smallest alterations in hand movements that are characteristic of Parkinson’s disease but might be difficult for clinicians to visually identify,” Guarin said in a statement. “The beauty of this technology is that a patient can record themselves performing the test, and the software analyses it and informs the clinician how the patient is moving so the clinician can make decisions.” 

Parkinson’s disease is a brain disorder that affects movement and can result in slowness of movement, tremors, stiffness, plus difficulty with balance and coordination. Symptoms usually begin gradually and worsen over time. According to UF, there is no specific lab or imaging test that can diagnose Parkinson’s disease, but a series of exercises and manoeuvres performed by the patient helps clinicians identify and evaluate the severity of the disorder.