Automated video-based movement assessment using machine learning to support personalized treatment of movement disorders
We developed a a machine learning pipeline to train models to automatically assess dystonia and choreoathetosis of children with dyskinetic cerebral palsy using 2D coordinates of body points extracted from videos.
A smartwatch software for measuring play with a data-driven, interdisciplinary approach
Advancing technology for multimodal analysis of emotion expression in everyday life
Advancing therapy change process research