This paper describes an automatic, explainable video-based human motion analysis approach for assessing Parkinson's disease motor signs, aimed at objective diagnosis and monitoring.

Provides a scalable, noninvasive method to quantify motor symptoms and generate clinical biomarkers useful for patient stratification and trial endpoints, but offers little insight into disease mechanisms or therapeutic targets.