Characterization of Physical Movement Signatures from WiFi-based Passive Forward Scattering Radar

Assistive living technologies has been continuously developed and improved. The use of related devices promotes independence, safety, and improved quality of life. These are relevant for elderly and individuals with special needs who live in private, nursing, and elderly homes. Various type of senso...

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Published in:International Journal of Emerging Technology and Advanced Engineering
Main Author: Nasarudin M.N.F.; Razali H.; Ismail N.N.; Zakaria N.A.Z.; Alnaeb A.; Ali M.S.A.M.; Rashid N.E.A.
Format: Article
Language:English
Published: IJETAE Publication House 2022
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143287016&doi=10.46338%2fijetae1122_03&partnerID=40&md5=86a0af68c0f108e831562343771ef08f
id 2-s2.0-85143287016
spelling 2-s2.0-85143287016
Nasarudin M.N.F.; Razali H.; Ismail N.N.; Zakaria N.A.Z.; Alnaeb A.; Ali M.S.A.M.; Rashid N.E.A.
Characterization of Physical Movement Signatures from WiFi-based Passive Forward Scattering Radar
2022
International Journal of Emerging Technology and Advanced Engineering
12
11
10.46338/ijetae1122_03
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143287016&doi=10.46338%2fijetae1122_03&partnerID=40&md5=86a0af68c0f108e831562343771ef08f
Assistive living technologies has been continuously developed and improved. The use of related devices promotes independence, safety, and improved quality of life. These are relevant for elderly and individuals with special needs who live in private, nursing, and elderly homes. Various type of sensors has since been developed and tested. This study aims to assess the capability of passive forward scattering radar to characterize physical movement signatures. To reduce the cost of bistatic topology, the source of signal for transmitter uses wireless fidelity technology. A total of 144 samples of radar signatures are acquired for walking, bending, sitting, and kneeling. Initially, the pulse-based signal is filtered and undergoes enveloping procedure. Subsequently, the signature of different movements is characterized. The time-series signal is then transformed to Fourier spectrum and power spectral density. The characteristics in frequency domain are analysed, and spectral centroid features are extracted. The distribution of features is visualized through box plot, which indicates good separability between the four movements. © 2022 by the Author(s).
IJETAE Publication House
22502459
English
Article
All Open Access; Bronze Open Access
author Nasarudin M.N.F.; Razali H.; Ismail N.N.; Zakaria N.A.Z.; Alnaeb A.; Ali M.S.A.M.; Rashid N.E.A.
spellingShingle Nasarudin M.N.F.; Razali H.; Ismail N.N.; Zakaria N.A.Z.; Alnaeb A.; Ali M.S.A.M.; Rashid N.E.A.
Characterization of Physical Movement Signatures from WiFi-based Passive Forward Scattering Radar
author_facet Nasarudin M.N.F.; Razali H.; Ismail N.N.; Zakaria N.A.Z.; Alnaeb A.; Ali M.S.A.M.; Rashid N.E.A.
author_sort Nasarudin M.N.F.; Razali H.; Ismail N.N.; Zakaria N.A.Z.; Alnaeb A.; Ali M.S.A.M.; Rashid N.E.A.
title Characterization of Physical Movement Signatures from WiFi-based Passive Forward Scattering Radar
title_short Characterization of Physical Movement Signatures from WiFi-based Passive Forward Scattering Radar
title_full Characterization of Physical Movement Signatures from WiFi-based Passive Forward Scattering Radar
title_fullStr Characterization of Physical Movement Signatures from WiFi-based Passive Forward Scattering Radar
title_full_unstemmed Characterization of Physical Movement Signatures from WiFi-based Passive Forward Scattering Radar
title_sort Characterization of Physical Movement Signatures from WiFi-based Passive Forward Scattering Radar
publishDate 2022
container_title International Journal of Emerging Technology and Advanced Engineering
container_volume 12
container_issue 11
doi_str_mv 10.46338/ijetae1122_03
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143287016&doi=10.46338%2fijetae1122_03&partnerID=40&md5=86a0af68c0f108e831562343771ef08f
description Assistive living technologies has been continuously developed and improved. The use of related devices promotes independence, safety, and improved quality of life. These are relevant for elderly and individuals with special needs who live in private, nursing, and elderly homes. Various type of sensors has since been developed and tested. This study aims to assess the capability of passive forward scattering radar to characterize physical movement signatures. To reduce the cost of bistatic topology, the source of signal for transmitter uses wireless fidelity technology. A total of 144 samples of radar signatures are acquired for walking, bending, sitting, and kneeling. Initially, the pulse-based signal is filtered and undergoes enveloping procedure. Subsequently, the signature of different movements is characterized. The time-series signal is then transformed to Fourier spectrum and power spectral density. The characteristics in frequency domain are analysed, and spectral centroid features are extracted. The distribution of features is visualized through box plot, which indicates good separability between the four movements. © 2022 by the Author(s).
publisher IJETAE Publication House
issn 22502459
language English
format Article
accesstype All Open Access; Bronze Open Access
record_format scopus
collection Scopus
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