FallDeF5: A Fall Detection Framework Using 5G-Based Deep Gated Recurrent Unit Networks

FallDeF5: A Fall Detection Framework Using 5G-Based Deep Gated Recurrent Unit Networks

Fall prevalence is high among elderly people, which is challenging due to the severe consequences of falling. This is why rapid assistance is a critical task. Ambient assisted living (AAL) uses recent technologies such as 5G networks and the internet of medical things (IoMT) to address this research...

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Bibliographic Details
Main Authors: Mabrook S. Al-Rakhami, Abdu Gumaei, Meteb Altaf, Mohammad Mehedi Hassan, Bader Fahad Alkhamees, Khan Muhammad, Giancarlo Fortino
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
5G
deep learning
edge computing
fall detection
healthcare system
Internet of Medical Things
Online Access:https://ieeexplore.ieee.org/document/9462896/

Internet

https://ieeexplore.ieee.org/document/9462896/

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