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

In the context of diseases impairing movement, quantitative assessment of motion is critical to medical decision-making but is currently possible only with expensive motion capture systems and trained personnel. Here, the authors present a method for predicting clinically relevant motion parameters...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Łukasz Kidziński, Bryan Yang, Jennifer L. Hicks, Apoorva Rajagopal, Scott L. Delp, Michael H. Schwartz
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
Materias:
Q
Acceso en línea:https://doaj.org/article/16ae278becf743e49bd54eccf9afc9a2
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Descripción
Sumario:In the context of diseases impairing movement, quantitative assessment of motion is critical to medical decision-making but is currently possible only with expensive motion capture systems and trained personnel. Here, the authors present a method for predicting clinically relevant motion parameters from an ordinary video of a patient.