Quantifying normal and parkinsonian gait features from home movies: Practical application of a deep learning–based 2D pose estimator

OBJECTIVE: Gait movies recorded in daily clinical practice are usually not filmed with specific devices, which prevents neurologists benefitting from leveraging gait analysis technologies. Here we propose a novel unsupervised approach to quantifying gait features and to extract cadence from normal a...

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Detalles Bibliográficos
Autores principales: Sato, Kenichiro, Nagashima, Yu, Mano, Tatsuo, Iwata, Atsushi, Toda, Tatsushi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6855634/
https://www.ncbi.nlm.nih.gov/pubmed/31725754
http://dx.doi.org/10.1371/journal.pone.0223549

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6855634/
https://www.ncbi.nlm.nih.gov/pubmed/31725754
http://dx.doi.org/10.1371/journal.pone.0223549

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