Deep neural networks enable quantitative movement analysis using single-camera videos

We developed machine learning methods for estimating gait metrics from ordinary single-camera videos of children with cerebral palsy. The work explores how computer vision could make quantitative movement analysis more accessible.

Lukas Kidzinski and Bryan Yang contributed equally to this work.

Read the published paper for the methods, validation, and study limitations.