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Sensors 2015, 15(3), 6383-6398;

Assessment of Human Respiration Patterns via Noncontact Sensing Using Doppler Multi-Radar System

Marvell Technology Group Ltd., 5488 Marvell Lane, Santa Clara, CA 95054, USA
Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409, USA
Author to whom correspondence should be addressed.
Academic Editor: Vittorio M.N. Passaro
Received: 20 January 2015 / Revised: 7 March 2015 / Accepted: 9 March 2015 / Published: 16 March 2015
(This article belongs to the Section Physical Sensors)
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Human respiratory patterns at chest and abdomen are associated with both physical and emotional states. Accurate measurement of the respiratory patterns provides an approach to assess and analyze the physical and emotional states of the subject persons. Not many research efforts have been made to wirelessly assess different respiration patterns, largely due to the inaccuracy of the conventional continuous-wave radar sensor to track the original signal pattern of slow respiratory movements. This paper presents the accurate assessment of different respiratory patterns based on noncontact Doppler radar sensing. This paper evaluates the feasibility of accurately monitoring different human respiration patterns via noncontact radar sensing. A 2.4 GHz DC coupled multi-radar system was used for accurate measurement of the complete respiration patterns without any signal distortion. Experiments were carried out in the lab environment to measure the different respiration patterns when the subject person performed natural breathing, chest breathing and diaphragmatic breathing. The experimental results showed that accurate assessment of different respiration patterns is feasible using the proposed noncontact radar sensing technique. View Full-Text
Keywords: radar; respiration; noncontact; vital sign radar; respiration; noncontact; vital sign

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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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Gu, C.; Li, C. Assessment of Human Respiration Patterns via Noncontact Sensing Using Doppler Multi-Radar System. Sensors 2015, 15, 6383-6398.

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