A Socially Assistive Robot for Elderly Exercise Promotion
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http://hdl.handle.net/10045/93448
Título: | A Socially Assistive Robot for Elderly Exercise Promotion |
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Autor/es: | Martinez-Martin, Ester | Cazorla, Miguel |
Grupo/s de investigación o GITE: | Robótica y Visión Tridimensional (RoViT) |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial |
Palabras clave: | Assistive robotics | Elderly healthcare | Human action recognition |
Área/s de conocimiento: | Ciencia de la Computación e Inteligencia Artificial |
Fecha de publicación: | 5-jun-2019 |
Editor: | IEEE |
Cita bibliográfica: | IEEE Access. 2019, 7: 75515-75529. doi:10.1109/ACCESS.2019.2921257 |
Resumen: | The population ageing phenomenon leads to an unceasing need for home-based healthcare systems to continuously monitor the elderly’s cognitive and physical health. In this sense, physical activity may be beneficial in preserving cognition in elder life as well as in providing clinicians and therapists with the indicative of elderly’s health condition. Nevertheless, current systems fail to promote and monitor the elderly’s physical activity in their living environments. This paper is aimed at providing a socially assistive robot solution for this task. Since robot acceptance depends to a great extent on its robustness in performing tasks, we have focused on exercise recognition due to its great importance for both clinicians and elderly. For that, two different tasks were carried out. First, an image dataset for physical exercise recognition has been generated. Then, a comparative analysis of several deep learning techniques is presented. This paper reveals a great performance in the exercise recognition of CNN-LSTM with an exercise recognition accuracy of 99.87%. |
Patrocinador/es: | This work was supported in part by the Spanish Government under Grant TIN2016-76515-R, and in part by Feder Funds. |
URI: | http://hdl.handle.net/10045/93448 |
ISSN: | 2169-3536 |
DOI: | 10.1109/ACCESS.2019.2921257 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © 2019 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.1109/ACCESS.2019.2921257 |
Aparece en las colecciones: | INV - RoViT - Artículos de Revistas |
Archivos en este ítem:
Archivo | Descripción | Tamaño | Formato | |
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2019_Martinez_Cazorla_IEEEAccess.pdf | 8,69 MB | Adobe PDF | Abrir Vista previa | |
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