WiFi CSI-based vital signs monitoring

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Human respiration monitoring plays an important role in healthcare applications, such as sleep apnea detection and sleep-stage recognition. We have witnessed a diversity of approaches developed for respiration monitoring, ranging from contact-based pulse oximeter to contact-free camera and CW (Continuous Wave) radar solutions. Recently, WiFi CSI-based contact-free sensing solutions have attracted a tremendous amount of research attention due to the pervasive deployment of WiFi infrastructure. In this chapter, we first present an overview of WiFi based-human respiration monitoring techniques, covering both pattern-based and model-based approaches. By introducing the Fresnel reflection and diffraction models, we then show how human respiration sensing is achieved using WiFi signals and why “blind spots” occur sometimes using WiFi CSI amplitude. To address the “blind spots” and short sensing-range issues, we further develop a series of solutions for single-person respiration monitoring. Finally, we also present a state-of-the-art solution for multi-person respiration sensing.

Original languageEnglish
Title of host publicationContactless Vital Signs Monitoring
PublisherElsevier
Pages231-255
Number of pages25
ISBN (Electronic)9780128222812
ISBN (Print)9780128222829
DOIs
Publication statusPublished - 1 Jan 2021
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Channel state information (CSI)
  • Respiration monitoring
  • WiFi

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