Determining grasp selection from arm trajectories via deep learning to enable functional hand movement in tetraplegia

BACKGROUND: Cervical spinal cord injury severely affects grasping ability of its survivors. Fortunately, many individuals with tetraplegia retain residual arm movements that allow them to reach for objects. We propose a wearable technology that utilizes arm movement trajectory information and deep l...

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Detalles Bibliográficos
Autores principales: Bhagat, Nikunj, King, Kevin, Ramdeo, Richard, Stein, Adam, Bouton, Chad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Short Report
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7449026/
https://www.ncbi.nlm.nih.gov/pubmed/32864392
http://dx.doi.org/10.1186/s42234-020-00053-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7449026/
https://www.ncbi.nlm.nih.gov/pubmed/32864392
http://dx.doi.org/10.1186/s42234-020-00053-5

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