Cargando…
Environment Classification for Robotic Leg Prostheses and Exoskeletons Using Deep Convolutional Neural Networks
Robotic leg prostheses and exoskeletons can provide powered locomotor assistance to older adults and/or persons with physical disabilities. However, the current locomotion mode recognition systems being developed for automated high-level control and decision-making rely on mechanical, inertial, and/...
Autores principales: | Laschowski, Brokoslaw, McNally, William, Wong, Alexander, McPhee, John |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8855111/ https://www.ncbi.nlm.nih.gov/pubmed/35185507 http://dx.doi.org/10.3389/fnbot.2021.730965 |
Ejemplares similares
-
ExoNet Database: Wearable Camera Images of Human Locomotion Environments
por: Laschowski, Brock, et al.
Publicado: (2020) -
Editorial: Lighter and more efficient robotic joints in prostheses and exoskeletons: Design, actuation and control
por: Sun, Yuanxi, et al.
Publicado: (2023) -
Classification of Lifting Techniques for Application of A Robotic Hip Exoskeleton
por: Chen, Baojun, et al.
Publicado: (2019) -
Model-Based Mid-Level Regulation for Assist-As-Needed Hierarchical Control of Wearable Robots: A Computational Study of Human-Robot Adaptation
por: Nasr, Ali, et al.
Publicado: (2022) -
Design and Feasibility Study of a Leg-exoskeleton Assistive Wheelchair Robot with Tests on Gluteus Medius Muscles
por: Huang, Gao, et al.
Publicado: (2019)