Breathing rhythm analysis in body centric networks

Fan, D., Ren, A. , Zhao, N., Yang, X., Zhang, Z., Shah, S. A. , Hu, F. and Abbasi, Q. H. (2018) Breathing rhythm analysis in body centric networks. IEEE Access, 6, pp. 32507-32513. (doi: 10.1109/ACCESS.2018.2846605)

Abstract

Respiratory rhythm is the marker of respiratory diseases. A compromised respiratory system can be life threatening and potentially cause damage to other organs and tissues. However, most people do not realize the importance of respiratory rhythm detection because of expensive and limited medical conditions. In this paper, we present a noncontact and economically viable respiratory rhythm-detection system using S-band sensing technique. The system leverages microwave sensing platform to capture the minute variations caused by breathing. Subsequently, we implement data preprocessing and respiratory rate estimation for acquired wireless data to achieve respiratory rhythm detection. The experimental results not only validate the feasibility of respiratory rhythm detection using S-band sensing technique but also demonstrate that the S-Breath system provides a good performance.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Abbasi, Professor Qammer and Shah, Mr Syed and Ren, Dr Aifeng
• Authors: Fan, D., Ren, A., Zhao, N., Yang, X., Zhang, Z., Shah, S. A., Hu, F., and Abbasi, Q. H.
• College/School: College of Science and Engineering > School of Engineering; College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering; College of Science and Engineering > School of Engineering > Systems Power and Energy
• Journal Name: IEEE Access
• Publisher: IEEE
• ISSN: 2169-3536
• ISSN (Online): 2169-3536
• Copyright Holders: Copyright © 2018 IEEE
• First Published: First published in IEEE Access 6:32507-32513
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher