A Socially Assistive Robot for Elderly Exercise Promotion

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Title: A Socially Assistive Robot for Elderly Exercise Promotion
Authors: Martinez-Martin, Ester | Cazorla, Miguel
Research Group/s: Robótica y Visión Tridimensional (RoViT)
Center, Department or Service: Universidad de Alicante. Departamento de Ciencia de la Computación e Inteligencia Artificial
Keywords: Assistive robotics | Elderly healthcare | Human action recognition
Knowledge Area: Ciencia de la Computación e Inteligencia Artificial
Issue Date: 5-Jun-2019
Publisher: IEEE
Citation: IEEE Access. 2019, 7: 75515-75529. doi:10.1109/ACCESS.2019.2921257
Abstract: 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%.
Sponsor: 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
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2019 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission.
Peer Review: si
Publisher version: https://doi.org/10.1109/ACCESS.2019.2921257
Appears in Collections:INV - RoViT - Artículos de Revistas

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