Small-Scale Perception in Medical Body Area Networks

Objective: Non-invasive respiration detection methods are of great value to healthcare applications and disease diagnosis with their advantages of minimizing the patient's physical burden and lessen the requirement of active cooperation of the subject. This method avoids extra preparations, red...

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Main Authors: Dou Fan, Aifeng Ren, Nan Zhao, Daniyal Haider, Xiaodong Yang, Jie Tian
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Journal of Translational Engineering in Health and Medicine
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8892401/
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spelling doaj-0800d35333414389b820bfc0e6739a952021-03-29T18:41:20ZengIEEEIEEE Journal of Translational Engineering in Health and Medicine2168-23722019-01-01711110.1109/JTEHM.2019.29516708892401Small-Scale Perception in Medical Body Area NetworksDou Fan0https://orcid.org/0000-0002-5869-8152Aifeng Ren1https://orcid.org/0000-0003-1129-5601Nan Zhao2https://orcid.org/0000-0002-5353-0158Daniyal Haider3https://orcid.org/0000-0002-9302-871XXiaodong Yang4https://orcid.org/0000-0002-4701-1204Jie Tian5https://orcid.org/0000-0003-0498-0432School of Electronic Engineering, Xidian University, Xi’an, ChinaSchool of Electronic Engineering, Xidian University, Xi’an, ChinaSchool of Electronic Engineering, Xidian University, Xi’an, ChinaSchool of Electronic Engineering, Xidian University, Xi’an, ChinaSchool of Electronic Engineering, Xidian University, Xi’an, ChinaSchool of Life Science and Technology, Xidian University, Xi’an, ChinaObjective: Non-invasive respiration detection methods are of great value to healthcare applications and disease diagnosis with their advantages of minimizing the patient's physical burden and lessen the requirement of active cooperation of the subject. This method avoids extra preparations, reduces environmental constraints, and strengthens the possibility of real-time respiratory detection. Furthermore, identifying abnormal breathing patterns in real-time is necessary for the diagnosis and monitoring of possible respiratory disorders. Method: A non-invasive method for detecting multiple breathing patterns using C-band sensing technique is presented, which is used for identifying different breathing patterns in addition to extract respiratory rate. We first evaluate the feasibility of this non-contact method in measuring different breathing patterns. Then, we detect several abnormal breathing patterns associated with certain respiratory disorders at real time using C-band sensing technique in indoor environment. Results: Mean square error (MSE) and correlation coefficient (CC) are used to evaluate the correlation between C-band sensing technique and contact respiratory sensor. The results show that all the MSE are less than 0.6 and all CC are more than 0.8, yielding a significant correlation between the two used for detecting each breathing pattern. Clinical Impact: C-band sensing technique is not only used to determine respiratory rates but also to identify breathing patterns, regarding as a preferred noncontact alternative approach to the traditional contact sensing methods. C-band sensing technique also provides a basis for the non-invasive detection of certain respiratory disorders.https://ieeexplore.ieee.org/document/8892401/Breathing patternsC-band sensing techniquenon-invasive detectionrespiratory rate
collection DOAJ
language English
format Article
sources DOAJ
author Dou Fan
Aifeng Ren
Nan Zhao
Daniyal Haider
Xiaodong Yang
Jie Tian
spellingShingle Dou Fan
Aifeng Ren
Nan Zhao
Daniyal Haider
Xiaodong Yang
Jie Tian
Small-Scale Perception in Medical Body Area Networks
IEEE Journal of Translational Engineering in Health and Medicine
Breathing patterns
C-band sensing technique
non-invasive detection
respiratory rate
author_facet Dou Fan
Aifeng Ren
Nan Zhao
Daniyal Haider
Xiaodong Yang
Jie Tian
author_sort Dou Fan
title Small-Scale Perception in Medical Body Area Networks
title_short Small-Scale Perception in Medical Body Area Networks
title_full Small-Scale Perception in Medical Body Area Networks
title_fullStr Small-Scale Perception in Medical Body Area Networks
title_full_unstemmed Small-Scale Perception in Medical Body Area Networks
title_sort small-scale perception in medical body area networks
publisher IEEE
series IEEE Journal of Translational Engineering in Health and Medicine
issn 2168-2372
publishDate 2019-01-01
description Objective: Non-invasive respiration detection methods are of great value to healthcare applications and disease diagnosis with their advantages of minimizing the patient's physical burden and lessen the requirement of active cooperation of the subject. This method avoids extra preparations, reduces environmental constraints, and strengthens the possibility of real-time respiratory detection. Furthermore, identifying abnormal breathing patterns in real-time is necessary for the diagnosis and monitoring of possible respiratory disorders. Method: A non-invasive method for detecting multiple breathing patterns using C-band sensing technique is presented, which is used for identifying different breathing patterns in addition to extract respiratory rate. We first evaluate the feasibility of this non-contact method in measuring different breathing patterns. Then, we detect several abnormal breathing patterns associated with certain respiratory disorders at real time using C-band sensing technique in indoor environment. Results: Mean square error (MSE) and correlation coefficient (CC) are used to evaluate the correlation between C-band sensing technique and contact respiratory sensor. The results show that all the MSE are less than 0.6 and all CC are more than 0.8, yielding a significant correlation between the two used for detecting each breathing pattern. Clinical Impact: C-band sensing technique is not only used to determine respiratory rates but also to identify breathing patterns, regarding as a preferred noncontact alternative approach to the traditional contact sensing methods. C-band sensing technique also provides a basis for the non-invasive detection of certain respiratory disorders.
topic Breathing patterns
C-band sensing technique
non-invasive detection
respiratory rate
url https://ieeexplore.ieee.org/document/8892401/
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AT daniyalhaider smallscaleperceptioninmedicalbodyareanetworks
AT xiaodongyang smallscaleperceptioninmedicalbodyareanetworks
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