Quantitative Gait Feature Assessment on Two-Dimensional Body Axis Projection Planes Converted from Three-Dimensional Coordinates Estimated with a Deep Learning Smartphone App

To assess pathological gaits quantitatively, three-dimensional coordinates estimated with a deep learning model were converted into body axis plane projections. First, 15 healthy volunteers performed four gait patterns; that is, normal, shuffling, short-stepped, and wide-based gaits, with the Three-...

Descripción completa

Detalles Bibliográficos
Autores principales: Yamada, Shigeki, Aoyagi, Yukihiko, Iseki, Chifumi, Kondo, Toshiyuki, Kobayashi, Yoshiyuki, Ueda, Shigeo, Mori, Keisuke, Fukami, Tadanori, Tanikawa, Motoki, Mase, Mitsuhito, Hoshimaru, Minoru, Ishikawa, Masatsune, Ohta, Yasuyuki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9865115/
https://www.ncbi.nlm.nih.gov/pubmed/36679412
http://dx.doi.org/10.3390/s23020617

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9865115/
https://www.ncbi.nlm.nih.gov/pubmed/36679412
http://dx.doi.org/10.3390/s23020617

Ejemplares similares