Respiration symptoms monitoring in body area networks

Liu, L., Shah, S. , Zhao, G. and Yang, X. (2018) Respiration symptoms monitoring in body area networks. Applied Sciences, 8(4), 568. (doi: 10.3390/app8040568)

Abstract

This work presents a framework that monitors particular symptoms such as respiratory conditions (abnormal breathing pattern) experienced by hyperthyreosis, sleep apnea, and sudden infant death syndrome (SIDS) patients. The proposed framework detects and monitors respiratory condition using S-Band sensing technique that leverages the wireless devices such as antenna, card, omni-directional antenna operating in 2 GHz to 4 GHz frequency range, and wireless channel information extraction tool. The rhythmic patterns extracted using S-Band sensing present the periodic and non-periodic waveforms that correspond to normal and abnormal respiratory conditions, respectively. The fine-grained amplitude information obtained using aforementioned devices is used to examine the breathing pattern over a period of time and accurately identifies the particular condition.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Shah, Mr Syed
• Authors: Liu, L., Shah, S., Zhao, G., and Yang, X.
• College/School: College of Science and Engineering > School of Engineering > Systems Power and Energy
• Journal Name: Applied Sciences
• Publisher: MDPI
• ISSN: 2076-3417
• ISSN (Online): 2076-3417
• Published Online: 06 April 2018
• Copyright Holders: Copyright © 2018 The Authors
• First Published: First published in Applied Sciences 8(4): 568
• Publisher Policy: Reproduced under a Creative Commons License