title: Assessment of human respiration patterns via noncontact sensing using Doppler multi-radar system.
abstract: 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.
authors.affiliation: Marvell Technology Group Ltd., 5488 Marvell Lane, Santa Clara, CA 95054, USA. cgu@marvell.com.|Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409, USA. cgu@marvell.com.
authors.forename: Changzhan
authors.initials: C
authors.lastname: Gu
authors.affiliation: Department of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79409, USA. changzhi.li@ttu.edu.
authors.forename: Changzhi
authors.initials: C
authors.lastname: Li
mesh_terms: D006339:Heart Rate / Q000502:physiology; D006801:Humans; D008991:Monitoring, Physiologic; D011825:Radar; D058998:Remote Sensing Technology / Q000295:instrumentation*; D012119:Respiration; D012815:Signal Processing, Computer-Assisted