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.
%0 Journal Article
%1 8382152
%A Fan, D.
%A Ren, A.
%A Zhao, N.
%A Yang, X.
%A Zhang, Z.
%A Shah, S. A.
%A Hu, F.
%A Abbasi, Q. H.
%D 2018
%J IEEE Access
%K Analysis Body Breathing Centric Networks Rhythm in
%P 32507-32513
%R 10.1109/ACCESS.2018.2846605
%T Breathing Rhythm Analysis in Body Centric Networks
%U https://ieeexplore.ieee.org/document/8382152/
%V 6
%X 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.
@article{8382152,
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.},
added-at = {2021-04-07T00:39:54.000+0200},
author = {{Fan}, D. and {Ren}, A. and {Zhao}, N. and {Yang}, X. and {Zhang}, Z. and {Shah}, S. A. and {Hu}, F. and {Abbasi}, Q. H.},
biburl = {https://www.bibsonomy.org/bibtex/23431a620f27923e68922363d72d4c8d9/azizshahics},
doi = {10.1109/ACCESS.2018.2846605},
interhash = {19ca6ea05d31ed8820de01c53e784752},
intrahash = {3431a620f27923e68922363d72d4c8d9},
issn = {2169-3536},
journal = {IEEE Access},
keywords = {Analysis Body Breathing Centric Networks Rhythm in},
pages = {32507-32513},
timestamp = {2021-04-07T00:39:54.000+0200},
title = {Breathing Rhythm Analysis in Body Centric Networks},
url = {https://ieeexplore.ieee.org/document/8382152/},
volume = 6,
year = 2018
}