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Sensors 2015, 15(7), 14830-14844; doi:10.3390/s150714830

A Method for Remotely Sensing Vital Signs of Human Subjects Outdoors

1
Department of Biomedical Engineering, Fourth Military Medical University, Xi'an 710032, China
2
Shaanxi University of Technology, Hanzhong 723001, China
*
Authors to whom correspondence should be addressed.
Academic Editor: Leonhard M. Reindl
Received: 16 April 2015 / Revised: 15 May 2015 / Accepted: 11 June 2015 / Published: 24 June 2015
(This article belongs to the Section Remote Sensors)
View Full-Text   |   Download PDF [2535 KB, uploaded 24 June 2015]   |  

Abstract

After chemical or nuclear leakage or explosions, finding survivors is a huge challenge. Although human bodies can be found by smart vehicles and drones equipped with cameras, it is difficult to verify if the person is alive or dead this way. This paper describes a continuous wave radar sensor for remotely sensing the vital signs of human subjects. Firstly, a compact and portable 24 GHz Doppler radar system is designed to conduct non-contact detection of respiration signal. Secondly, in order to improve the quality of the respiration signals, the self-correlation and adaptive line enhancer (ALE) methods are proposed to minimize the interferences of any moving objects around the human subject. Finally, the detection capabilities of the radar system and the signal processing method are verified through experiments which show that human respiration signals can be extracted when the subject is 7 m away outdoors. The method provided in this paper will be a promising way to search for human subjects outdoors. View Full-Text
Keywords: 24 GHz Doppler radar; searching for survivors; respiration; moving object interference 24 GHz Doppler radar; searching for survivors; respiration; moving object interference
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Li, C.; Chen, F.; Jin, J.; Lv, H.; Li, S.; Lu, G.; Wang, J. A Method for Remotely Sensing Vital Signs of Human Subjects Outdoors. Sensors 2015, 15, 14830-14844.

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