A Real-time Respiration Monitoring System Using WiFi-Based Radar Model

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

This paper proposes and experimentally validates a novel WiFi-based radar model for indoor WiFi sensing, which enables accurate measurement of the radial velocity of objects. A human respiratory monitoring system based on the proposed WiFi radar model is developed. The respiratory monitoring system also leverages principal component analysis (PCA) on the MIMO WiFi channel state information ratio (CSIR) information to extract the components related to human activities. Doppler frequency of respiratory motion is obtained from time-frequency analysis of the CSIR through short-time Fourier transform (STFT). Experimental results show that the WiFi-based radar model achieves high accuracy in velocity measurement with an average error of less than 1.5% and can be used to real-time monitor the respiration rate.

Original languageEnglish
Title of host publicationIEEE International Symposium on Circuits and Systems, ISCAS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2082-2086
Number of pages5
ISBN (Electronic)9781665484855
DOIs
StatePublished - 2022
Event2022 IEEE International Symposium on Circuits and Systems, ISCAS 2022 - Austin, United States
Duration: 27 May 20221 Jun 2022

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2022-May
ISSN (Print)0271-4310

Conference

Conference2022 IEEE International Symposium on Circuits and Systems, ISCAS 2022
Country/TerritoryUnited States
CityAustin
Period27/05/221/06/22

Keywords

  • CSI ratio
  • Doppler radar
  • Respiration monitoring
  • WiFi
  • Wireless sensing

Fingerprint

Dive into the research topics of 'A Real-time Respiration Monitoring System Using WiFi-Based Radar Model'. Together they form a unique fingerprint.

Cite this