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When clinicians evaluate someone with Parkinson's disease, they typically ask patients to perform a series of movements, like making a fist, rotating their forearms or walking across a room. They'll then assign a score from 0, indicating normal movement, to 4, indicating severe impairment.

This scoring system, called the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS), is simple, allowing clinicians around the world to assess a patient's motor symptoms. But because it places a broad range of movement characteristics into a small number of categories, it can be difficult to capture subtle changes in movement or precisely monitor how Parkinson's disease progresses over time.

"One clinician's definition of score 1 (written as 'minor impairment' in the score guidelines) can vary a lot from others, so while the guidelines standardize scoring, in the end there is still some degree of subjectivity," said Kyungdo Kim, a Ph.D. student in Duke University's Department of Biomedical Engineering. "If we want to more precisely track how this disease progresses, we need an explainable, objective system for quantifying movement."

A new approach, developed by Kim, Dr. Kyle Mitchell, an associate professor of neurology, Timothy Dunn, an assistant professor of biomedical engineering, and others in the Dunn lab could provide just that. The research, published in npj Parkinson's Disease , introduces a system called TULIP that captures and quantifies human movement in three dimensions.

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