Software Defined Radio Based Testbed for Large Scale Body Movements

Ashleibta, A., Shah, S. , Zahid, A., Imran, M. A. and Abbasi, Q. H. (2021) Software Defined Radio Based Testbed for Large Scale Body Movements. In: 2020 IEEE International Symposium on Antennas and Propagation and North American Radio Science Meeting, Montréal, QC, Canada, 05-10 Jul 2020, pp. 2079-2080. ISBN 9781728166704 (doi: 10.1109/IEEECONF35879.2020.9330027)

Abstract

Monitoring Activities of Daily Livings (ADLs) has opened doors for numerous applications including patient monitoring, search & rescue, intrusion detection and so on. However, the parameterssuch as operating frequency, transmitting power, and antenna design are static where each application requires particular hardware applications. This paper lays the foundation for ADLs and presents the design of the testbed based on Universal Software Radio Peripheral (USRP) in conjunction with omni directional antenna, that can be used for detecting large scale body movements such as walking, sitting, standing, and critical events such as falls and small-scale movements. The core idea is to extract the channel state information (CSI) from the received signal since each body motion produces a unique CSI signature. In this context, we have performed various human activities such as walking, sitting on a chair etc. in indoor environment using two USRPs. The experimental results indicate that each body motion can be visually identified by examining the CSI data.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Abbasi, Professor Qammer and Imran, Professor Muhammad and Zahid, Mr Adnan and Shah, Mr Syed and Ashleibta, Aboajeila Milad Abdulhadi
• Authors: Ashleibta, A., Shah, S., Zahid, A., Imran, M. A., and Abbasi, Q. H.
• College/School: College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering; College of Science and Engineering > School of Engineering > Systems Power and Energy
• ISSN: 1947-1491
• ISBN: 9781728166704
• Copyright Holders: Copyright © 2020 IEEE
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher

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