AI-based Real-time Classification of Human Activity using Software Defined Radios

Taylor, W., Taha, A. , Dashtipour, K., Shah, S. A. , Abbasi, Q. H. and Imran, M. A. (2022) AI-based Real-time Classification of Human Activity using Software Defined Radios. In: 1st International Conference on Microwave, Antennas & Circuits (ICMAC 2021), Islamabad, Pakistan, 21-22 Dec 2021, pp. 1-4. ISBN 9781665400862 (doi: 10.1109/ICMAC54080.2021.9678242)

Abstract

Real-time monitoring is an essential part in the development of healthcare monitoring systems. Research has shown that human movement affects the propagation of radio frequencies, as signals will reflect off the human body. Machine Learning techniques have been used in research to classify patterns observed in the signal propagation. This paper makes use of universal software radio peripheral devices to create a wireless communication link where the signal propagation data, known as channel state information, is collected while a user moves or remains still. A machine learning model which achieved an accuracy result of 93.25 % is used to classify between movement and no activity. Inference is then used to decide if the human position is sitting or standing and detected movements are used to differentiate between the two positions. The testbed implements cloud storage and a web-interface to present a visualisation of the human position.

• Item Type: Conference Proceedings
• Additional Information: William Taylor's studentship is funded by CENSIS UK through Scottish funding council in collaboration with British Telecom. This work is supported in parts by EPSRC EP/T021020/1 and EP/T021063/1.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Taha, Dr Ahmad and Imran, Professor Muhammad and Taylor, Mr William and Abbasi, Dr Qammer and Shah, Mr Syed and Dashtipour, Dr Kia
• Authors: Taylor, W., Taha, A., Dashtipour, K., Shah, S. A., Abbasi, Q. H., and Imran, M. A.
• 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
• ISBN: 9781665400862
• Copyright Holders: Copyright © 2021 The Authors
• First Published: First published in 2021 1st International Conference on Microwave, Antennas & Circuits (ICMAC), 2021, pp. 1-4
• Publisher Policy: Reproduced in accordance with the publisher copyright policy

Related URLs

• Organisation

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
307829		Quantum-Inspired Imaging for Remote Monitoring of Health & Disease in Community Healthcare	Jonathan Cooper	Engineering and Physical Sciences Research Council (EPSRC)	EP/T021020/1	ENG - Biomedical Engineering