Discrete Human Activity Recognition and Fall Detection by Combining FMCW RADAR Data of Heterogeneous Environments for Independent Assistive Living

Discrete Human Activity Recognition and Fall Detection by Combining FMCW RADAR Data of Heterogeneous Environments for Independent Assistive Living

Human activity monitoring is essential for a variety of applications in many fields, particularly healthcare. The goal of this research work is to develop a system that can effectively detect fall/collapse and classify other discrete daily living activities such as sitting, standing, walking, drinki...

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Bibliographic Details
Main Authors: Umer Saeed, Syed Yaseen Shah, Syed Aziz Shah, Jawad Ahmad, Abdullah Alhumaidi Alotaibi, Turke Althobaiti, Naeem Ramzan, Akram Alomainy, Qammer H. Abbasi
Format: Article
Language:English
Published: MDPI AG 2021-09-01
Series:Electronics
Subjects:
radio-frequency
FMCW RADAR
next generation healthcare
contactless monitoring
fall detection
deep learning
Online Access:https://www.mdpi.com/2079-9292/10/18/2237

Internet

https://www.mdpi.com/2079-9292/10/18/2237

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