A Contactless On-Bed Radar System for Human Respiration Monitoring

Qian Zhai, Xiangyu Han, Yi Han, Jingang Yi, Shuoyu Wang, Tao Liu

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

Healthcare automation technologies have led to develop 'smart' home with intelligent sensing systems to fully monitor vital signs. One important healthcare application of the millimeter-wave radar sensor is the respiratory rate (RR) estimation. Accurate and robust measurements of respiration motion and RR estimation in nonhospital facilities is a challenging task. We present a novel contactless on-bed radar system for respiration monitoring for 'smart' home. A simplified trunk model and a mode-decomposition-based respiration reconstruction are designed for analysis of 2-D radar profile to extract nonstationary breathing motion information. Resting breathing experiments with different respiratory patterns and human poses are performed to evaluate the performance of the proposed system. The results show that the system measures respiration-induced body movement with a root-mean-squared error of 0.31 mm and a mean accuracy of 89.6%. For RR estimation, the overall accuracy is 97.1% under normal respiratory patterns and 93.4% under abnormal respiratory patterns.

Original languageEnglish (US)
Article number4004210
JournalIEEE Transactions on Instrumentation and Measurement
Volume71
DOIs
StatePublished - 2022

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Electrical and Electronic Engineering

Keywords

  • Healthcare automation
  • millimeter-wave (MMW) radar
  • noncontact
  • respiration

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