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Small-Scale Perception in Medical Body Area Networks

文献类型：期刊论文

作者Fan, Dou2; Ren, Aifeng2; Zhao, Nan2; Haider, Daniyal2; Yang, Xiaodong2; Tian, Jie1,3
刊名IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE-JTEHM
出版日期2019
卷号7页码:11
关键词Sensors Monitoring Wireless sensor networks Wireless communication Channel state information OFDM Real-time systems Breathing patterns C-band sensing technique non-invasive detection respiratory rate
ISSN号2168-2372
DOI10.1109/JTEHM.2019.2951670
通讯作者Yang, Xiaodong(xdyang@xidian.edu.cn) ; Tian, Jie(jaytian99@gmail.com)
英文摘要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.
WOS关键词SYSTEM
资助项目National Natural Science Foundation of China[61671349] ; National Natural Science Foundation of China[61301175] ; Fundamental Research Funds for the Central Universities[JB180205]
WOS研究方向Engineering
语种英语
WOS记录号WOS:000501202500001
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities
源URL[http://ir.ia.ac.cn/handle/173211/29347]  
专题自动化研究所_中国科学院分子影像重点实验室
通讯作者Yang, Xiaodong; Tian, Jie
作者单位1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
2.Xidian Univ, Sch Elect Engn, Xian 710071, Shaanxi, Peoples R China
3.Xidian Univ, Sch Life Sci & Technol, Xian 710126, Shaanxi, Peoples R China
推荐引用方式
GB/T 7714		 Fan, Dou,Ren, Aifeng,Zhao, Nan,et al. Small-Scale Perception in Medical Body Area Networks[J]. IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE-JTEHM,2019,7:11.
APA Fan, Dou,Ren, Aifeng,Zhao, Nan,Haider, Daniyal,Yang, Xiaodong,&Tian, Jie.(2019).Small-Scale Perception in Medical Body Area Networks.IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE-JTEHM,7,11.
MLA Fan, Dou,et al."Small-Scale Perception in Medical Body Area Networks".IEEE JOURNAL OF TRANSLATIONAL ENGINEERING IN HEALTH AND MEDICINE-JTEHM 7(2019):11.

入库方式： OAI收割

来源：自动化研究所

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