COMBAHO: A deep learning system for integrating brain injury patients in society
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http://hdl.handle.net/10045/108800
Título: | COMBAHO: A deep learning system for integrating brain injury patients in society |
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Autor/es: | Garcia-Rodriguez, Jose | Gomez-Donoso, Francisco | Oprea, Sergiu | Garcia-Garcia, Alberto | Cazorla, Miguel | Orts-Escolano, Sergio | Bauer, Zuria | Castro-Vargas, John Alejandro | Escalona, Félix | Ivorra-Piqueres, David | Martínez González, Pablo | Aguirre Molina, Eugenio | García Silvente, Miguel | Garcia-Perez, Marcelo | Cañas, Jose Maria | Martín Rico, Francisco | Gines, Jonathan | Rivas, Francisco Miguel |
Grupo/s de investigación o GITE: | Arquitecturas Inteligentes Aplicadas (AIA) | Robótica y Visión Tridimensional (RoViT) |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Tecnología Informática y Computación | Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial |
Palabras clave: | Robot assistants | Ambient assisted living | Rehabilitation aids |
Área/s de conocimiento: | Arquitectura y Tecnología de Computadores | Ciencia de la Computación e Inteligencia Artificial |
Fecha de publicación: | sep-2020 |
Editor: | Elsevier |
Cita bibliográfica: | Pattern Recognition Letters. 2020, 137: 80-90. https://doi.org/10.1016/j.patrec.2019.02.013 |
Resumen: | In the last years, the care of dependent people, either by disease, accident, disability, or age, is one of the current priority research topics in developed countries. Moreover, such care is intended to be at patients home, in order to minimize the cost of therapies. Patients rehabilitation will be fulfilled when their integration in society is achieved, either in the family or in a work environment. To address this challenge, we propose the development and evaluation of an assistant for people with acquired brain injury or dependents. This assistant is twofold: in the patient’s home is based on the design and use of an intelligent environment with abilities to monitor and active learning, combined with an autonomous social robot for interactive assistance and stimulation. On the other hand, it is complemented with an outdoor assistant, to help patients under disorientation or complex situations. This involves the integration of several existing technologies and provides solutions to a variety of technological challenges. Deep leaning-based techniques are proposed as core technology to solve these problems. |
Patrocinador/es: | This work has been funded by the Spanish Government TIN2016-76515-R grant for the COMBAHO project, supported with Feder funds. It has also been supported by the University of Alicante project GRE16-19 and the Valencian Government GV/2018/022. This work has also been supported by Spanish grants for PhD studies FPU15/04516 and ACIF/2017/243. Experiments were made possible by a generous hardware donation from NVIDIA. |
URI: | http://hdl.handle.net/10045/108800 |
ISSN: | 0167-8655 (Print) | 1872-7344 (Online) |
DOI: | 10.1016/j.patrec.2019.02.013 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © 2019 Elsevier B.V. |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.1016/j.patrec.2019.02.013 |
Aparece en las colecciones: | INV - AIA - Artículos de Revistas INV - RoViT - Artículos de Revistas |
Archivos en este ítem:
Archivo | Descripción | Tamaño | Formato | |
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Garcia-Rodriguez_etal_2020_PatternRecognLett_final.pdf | Versión final (acceso restringido) | 2,7 MB | Adobe PDF | Abrir Solicitar una copia |
Garcia-Rodriguez_etal_2020_PatternRecognLett_accepted.pdf | Accepted Manuscript (acceso abierto) | 479,81 kB | Adobe PDF | Abrir Vista previa |
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