Assistive Technology for Elderly Care: An Overview
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http://hdl.handle.net/10045/116321
| Title: | Assistive Technology for Elderly Care: An Overview |
|---|---|
| Authors: | Martinez-Martin, Ester | Costa, Angelo |
| 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 technology | Cognitive assistants | Robotics | Healthcare |
| Knowledge Area: | Ciencia de la Computación e Inteligencia Artificial |
| Issue Date: | 25-Jun-2021 |
| Publisher: | IEEE |
| Citation: | IEEE Access. 2021, 9: 92420-92430. https://doi.org/10.1109/ACCESS.2021.3092407 |
| Abstract: | Global demographic changes have resulted in a growing technological demand to meet the arisen social needs. In particular, the increasingly ageing population requires assistive technologies to stay at home for longer independently while receiving continuous healthcare. In this sense, a wide academic and industrial research is taking place, introducing these technologies in hospitals and rehabilitation centres. This paper aims at providing an overview of research projects for elderly care and assistance, focusing on cognitive and robot assistants due to their popularity in the area. More precisely, physical and/or cognitive rehabilitation are presented. This paper also discusses their limitations and the open challenges to be tackled in order to be successfully integrated in our society. |
| URI: | http://hdl.handle.net/10045/116321 |
| ISSN: | 2169-3536 |
| DOI: | 10.1109/ACCESS.2021.3092407 |
| Language: | eng |
| Type: | info:eu-repo/semantics/article |
| Rights: | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. |
| Peer Review: | si |
| Publisher version: | https://doi.org/10.1109/ACCESS.2021.3092407 |
| Appears in Collections: | INV - RoViT - Artículos de Revistas |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
 Martinez-Martin_Costa_2021_IEEEAccess.pdf | 3,4 MB | Adobe PDF | Open Preview | |
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