Automatic and explainable assessment for Parkinson's disease by video-based human motion understanding.
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.
What the AI sees
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.
Research significance
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.
Source abstract
No abstract available.