A portable continuous wave radar system to detect elderly fall

Muhammad Arslan Ali, Malikeh Pour Ebrahim, Mehmet Rasit Yuce

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Abstract

Fall is the leading cause of death among elderly people worldwide. In this work a low power portable continuous wave radar (CWR) system is proposed to detect elderly fall. This paper presents experimental evaluation of the system to detect human fall motion among various sitting, standing and walking activities. Signals from three subjects with different heights and weights engaged with the different movement activities including walking, sitting, standing and fall in front of the proposed radar system are analyzed. Overall, 60 fall and 180 non-fall activities were recorded. The Short-time Fourier Transform (STFT) is employed to obtain time-frequency Doppler signatures of different human activities. Radar data is analysed by using MATLAB and an algorithm is employed to classify the fall on the basis of analysed data. The results show that the proposed portable CWR can be used to detect fall from non-fall activities with almost 100% accuracy.

Original languageEnglish
Title of host publicationBody Area Networks - Smart IoT and Big Data for Intelligent Health Management
Subtitle of host publication14th EAI International Conference, BODYNETS 2019, Proceedings
EditorsLorenzo Mucchi, Matti Hämäläinen, Sara Jayousi, Simone Morosi
Place of PublicationCham Switzerland
PublisherSpringer
Pages3-11
Number of pages9
Edition14th
ISBN (Electronic)9783030348335
ISBN (Print)9783030348328
DOIs
Publication statusPublished - 2019
EventInternational Conference on Body Area Networks 2019 - Florence, Italy
Duration: 2 Oct 20193 Oct 2019
Conference number: 14th
http://bodynets2019.eai-conferences.org/
https://link.springer.com/book/10.1007/978-3-030-34833-5 (Proceedings)

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
PublisherSpringer
Volume297
ISSN (Print)1867-8211
ISSN (Electronic)1867-822X

Conference

ConferenceInternational Conference on Body Area Networks 2019
Abbreviated titleBodyNets 2019
CountryItaly
CityFlorence
Period2/10/193/10/19
Internet address

Keywords

  • CWR
  • Fall detection
  • STFT

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