Respiration Symptoms Monitoring in Body Area Networks

Liu, Lu, Shah, Syed ORCID: https://orcid.org/0000-0003-2052-1121, Zhao, Guoqing and Yang, Xiaodong (2018) Respiration Symptoms Monitoring in Body Area Networks. Applied Sciences, 8 (4). p. 568.

Preview

Published Version Available under License Creative Commons Attribution. Download (21MB) | Preview

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.